From 82b5cc0b46f1db07d4334182c5aa6a2912ecbf7f Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 14:13:35 +0000 Subject: [PATCH 01/22] Try codecov --- .github/workflows/test-coverage.yaml | 35 +++++++++++++++++++++++++ {.circleci => .old_circleci}/config.yml | 0 2 files changed, 35 insertions(+) create mode 100644 .github/workflows/test-coverage.yaml rename {.circleci => .old_circleci}/config.yml (100%) diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml new file mode 100644 index 00000000..d0b83edc --- /dev/null +++ b/.github/workflows/test-coverage.yaml @@ -0,0 +1,35 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master, rcheck] + pull_request: + branches: [main, master] + +name: test-coverage + +jobs: + test-coverage: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + + steps: + - uses: actions/checkout@v2 + + - uses: r-lib/actions/setup-pandoc@v2 +# with: +# pandoc-version: '2.17.1' + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::covr + needs: coverage + + - name: Test coverage + run: covr::codecov(type="all") + shell: Rscript {0} diff --git a/.circleci/config.yml b/.old_circleci/config.yml similarity index 100% rename from .circleci/config.yml rename to .old_circleci/config.yml From 68ac19aa969717609ddebaf334c71c1e0921e8c2 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 14:25:19 +0000 Subject: [PATCH 02/22] remove token --- .github/workflows/test-coverage.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml index d0b83edc..625c7876 100644 --- a/.github/workflows/test-coverage.yaml +++ b/.github/workflows/test-coverage.yaml @@ -11,11 +11,11 @@ name: test-coverage jobs: test-coverage: runs-on: ubuntu-latest - env: - GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} +# env: +# GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - uses: r-lib/actions/setup-pandoc@v2 # with: From a8ccb9a641a93e7944844115d73a64613d9db2de Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 16:34:44 +0000 Subject: [PATCH 03/22] Use checkoutv3 but also a token --- .github/workflows/test-coverage.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml index 625c7876..1e4bbc70 100644 --- a/.github/workflows/test-coverage.yaml +++ b/.github/workflows/test-coverage.yaml @@ -11,8 +11,8 @@ name: test-coverage jobs: test-coverage: runs-on: ubuntu-latest -# env: -# GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - uses: actions/checkout@v3 From c2ef7090e6d87208f38b14f773c6bd2ce0f86328 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 16:59:06 +0000 Subject: [PATCH 04/22] re-enable circle ci but without codecov So that we can test on our custom Docker. --- {.old_circleci => .circleci}/config.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename {.old_circleci => .circleci}/config.yml (99%) diff --git a/.old_circleci/config.yml b/.circleci/config.yml similarity index 99% rename from .old_circleci/config.yml rename to .circleci/config.yml index f6ec96ab..e120021f 100644 --- a/.old_circleci/config.yml +++ b/.circleci/config.yml @@ -179,7 +179,7 @@ jobs: - run: rm deps_checksum # Delete the temp file with the dir checksum - *devtools-check # (includes vignettes) - - *code-cov +# - *code-cov ################################### From 7d74389bd2a2d023ae57ae86f6da9686443ee493 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 17:19:13 +0000 Subject: [PATCH 05/22] Add yml for codecov --- codecov.yml | 14 ++++++++++++++ 1 file changed, 14 insertions(+) create mode 100644 codecov.yml diff --git a/codecov.yml b/codecov.yml new file mode 100644 index 00000000..a467aa25 --- /dev/null +++ b/codecov.yml @@ -0,0 +1,14 @@ +coverage: + status: + project: + default: + # basic + target: 80% + threshold: 1% + base: auto + patch: + default: + # basic + target: 80% + threshold: 2% + base: auto From 4694f8cd2006f9ccbf3dd5d29bf170e7d72adc79 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 17:27:12 +0000 Subject: [PATCH 06/22] Add codecov.yml to Rbuildignore --- .Rbuildignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.Rbuildignore b/.Rbuildignore index 89a8a3a8..155dccb1 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -10,3 +10,4 @@ ci_dependencies ^cran-comments.md ^cran-comments\.md$ ^CRAN-SUBMISSION$ +^codecov.yml \ No newline at end of file From e7318bf86360bb2d93c2e60d8925e06c768757f1 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 17:47:58 +0000 Subject: [PATCH 07/22] Clean up badges --- README.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b42bb685..41535e3a 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,16 @@ # pastclim -[![CircleCI](https://circleci.com/gh/EvolEcolGroup/pastclim/tree/master.svg?style=shield&circle-token=928bdbe8f065e17b22642f66a8b9c13f29f2e3fb)](https://app.circleci.com/pipelines/github/EvolEcolGroup/pastclim?branch=master) -[![R-CMD-check dev](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml/badge.svg?branch=dev)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) +[![R-CMD-check master](https://img.shields.io/github/checks-status/EvolEcolGroup/pastclim/dev?label=master&logo=GitHub)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) +[![R-CMD-check dev](https://img.shields.io/github/checks-status/EvolEcolGroup/pastclim/dev?label=dev&logo=GitHub)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) [![codecov](https://codecov.io/gh/EvolEcolGroup/pastclim/branch/master/graph/badge.svg?token=NflUsWlnQR)](https://app.codecov.io/gh/EvolEcolGroup/pastclim) + This `R` library is designed to provide an easy way to extract and manipulate palaeoclimate From a3d15b6942d0561083e1a5ab9475d5708e76c85d Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 17:53:32 +0000 Subject: [PATCH 08/22] Switch off codecov failing checks --- codecov.yml | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/codecov.yml b/codecov.yml index a467aa25..edbacf5a 100644 --- a/codecov.yml +++ b/codecov.yml @@ -3,12 +3,12 @@ coverage: project: default: # basic - target: 80% - threshold: 1% + target: 10% + threshold: 20% base: auto patch: default: # basic - target: 80% - threshold: 2% - base: auto + target: 10% + threshold: 20% + base: auto From 5d4641866017cf7971aa639a059830aba4eab993 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Wed, 30 Nov 2022 18:03:57 +0000 Subject: [PATCH 09/22] Fix badge typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 41ea365d..13b24262 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # pastclim -[![R-CMD-check master](https://img.shields.io/github/checks-status/EvolEcolGroup/pastclim/dev?label=master&logo=GitHub)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) +[![R-CMD-check master](https://img.shields.io/github/checks-status/EvolEcolGroup/pastclim/master?label=master&logo=GitHub)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) [![R-CMD-check dev](https://img.shields.io/github/checks-status/EvolEcolGroup/pastclim/dev?label=dev&logo=GitHub)](https://github.com/EvolEcolGroup/pastclim/actions/workflows/R-CMD-check.yaml) [![codecov](https://codecov.io/gh/EvolEcolGroup/pastclim/branch/master/graph/badge.svg?token=NflUsWlnQR)](https://app.codecov.io/gh/EvolEcolGroup/pastclim) From 9d2134e143d73dce74263aaabfc62a1c57fb5c83 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 08:10:54 +0000 Subject: [PATCH 10/22] Update datasets [skip ci] --- R/sysdata.rda | Bin 3064 -> 3046 bytes R/zzz.R | 1 - .../data_files/variable_table.csv | 334 +++++++++--------- .../downsample_CHELSA_TraCE21k_tiff.R | 6 + .../update_meta_data_of_vars_in_nc.R | 42 +++ .../rawdata_scripts/verify_files_by_dataset.R | 13 + 6 files changed, 228 insertions(+), 168 deletions(-) create mode 100644 inst/rawdata_scripts/downsample_CHELSA_TraCE21k_tiff.R create mode 100644 inst/rawdata_scripts/update_meta_data_of_vars_in_nc.R create mode 100644 inst/rawdata_scripts/verify_files_by_dataset.R diff --git a/R/sysdata.rda b/R/sysdata.rda index 88523f60aa532941446f8399dbece038b89a456a..cc08c8c613b247cdb65194fdc25bc6172012dfd4 100644 GIT binary patch delta 3002 zcmZY9dpr|r9{_MG)#lPM*FtKHF>+lSl3QE3&23XI<>WRd*X0t$q78G|+!?vdWmrJguH-UZ4mss9I%oGX`0#ur7*g$=SXmkA>;zA$K zB=faMEP|O$WRI;S6%p9Q=uzGUyI76RgqljYf-Z}mP6!oxmsQ>Vbns!g_?zOYaX4tr zxAxaTxL|6;a-9FPY;7y%-3os@inI*PDFFDJnL&bo#QZ8Dvn&FyuL79|ZfrAp|d zSMDuXoiuVg?=`-^)9yH=R+efEuy8#FNZ65>gUX7p-YQ1Rc4NK?md-_w#(OLf`gnu3 z29AXkGF-Dcxam!B(~V@AV7=CD#N@3ve^~DH zBVo`vs%lfWR^z}<5TDet_Fym=vb~%rl{*~`;YF3y5bt!~|BM$bd^aK3$}@#nC!)F?CPc^Ya>YE$kx@Hsx`=CHvZwDSx>uihLO!p$?QvhxOtvM z{Q#24Rwt&m+6bTRl5og2P*?65Gin zMuOl*&Q9-gnrv=fJ!#zLU>~0m{!rYszHt;7K zKk`(|=3cHV>forQ)2XX>C3#w%jmZE_fEG)uVqQ@FWUW!FE}K9w3=vG*GPRN=`beRM 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100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -8,7 +8,6 @@ if (any(toset)) options(op.pastclim[toset]) # check that gdal was compiled with netcdf support - d <- gdal(drivers=TRUE) if (!"netCDF" %in% terra::gdal(drivers=TRUE)$name){ stop("The installed version of terra lacks support for reading netcdf files.\n", "pastclim needs netcdf support: you will need to reinstall terra,\n", diff --git a/inst/rawdata_scripts/data_files/variable_table.csv b/inst/rawdata_scripts/data_files/variable_table.csv index 01540a44..194db58c 100644 --- a/inst/rawdata_scripts/data_files/variable_table.csv +++ b/inst/rawdata_scripts/data_files/variable_table.csv @@ -1,168 +1,168 @@ variable,ncvar,dataset,monthly,file_name,download_path,file_name_orig,download_path_orig,version,long_name,abbreviated_name,time_frame,units,units_exp -bio01,BIO1,Example,FALSE,example_climate_v2.nc,,,,1.1.0,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio10,BIO10,Example,FALSE,example_climate_v2.nc,,,,1.1.0,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio12,BIO12,Example,FALSE,example_climate_v2.nc,,,,1.1.0,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -biome,biome,Example,FALSE,example_climate_v2.nc,,,,1.1.0,biome (from BIOME4),biome,year,, -bio01,bio01,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio04,bio04,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,temperature seasonality,T season.,year,degrees Celsius,*degree*C* -bio05,bio05,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,maximum temperature of warmest month,max. T of warmest mo.,year,degrees Celsius,*degree*C* -bio06,bio06,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,minimum temperature of coldest month,min. T of coldest mo.,year,degrees Celsius,*degree*C* -bio07,bio07,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,temperature annual range (bio05-bio06),T ann. Range,year,degrees Celsius,*degree*C* -bio08,bio08,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C* -bio09,bio09,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C* -bio10,bio10,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio11,bio11,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C* -bio12,bio12,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -bio13,bio13,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of wettest month,P of wettest mo.,year,mm per month,*mm~mo^-1* -bio14,bio14,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of driest month,P of driest mo.,year,mm per month,*mm~mo^-1* -bio15,bio15,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation seasonality (coeff var),P season.,year,, -bio16,bio16,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of wettest quarter,P of wettest qtr,year,mm per quarter,*mm~qtr^-1* -bio17,bio17,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of driest quarter,P of driest qtr,year,mm per quarter,*mm~qtr^-1* -bio18,bio18,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of warmest quarter,P of warmest qtr,year,mm per quarter,*mm~qtr^-1* -bio19,bio19,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation of coldest quarter,P of coldest qtr,year,mm per quarter,*mm~qtr^-1* -npp,npp,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity,NPP,year,gC per m^2 per year,*gC~m^-2~yr^-1* -lai,lai,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,leaf area index,LAI,year,gC per m^2,*gC~m^-2* -biome,biome,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,biome (from BIOME4),biome,year,, -altitude,altitude,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,,,1.1.0,altitude over the sea level,altitude,year,meters,*m* -rugosity,rugosity,Beyer2020,FALSE,Beyer2020_annual_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_annual_vars_v1.1.0.nc?download=1,,,1.1.0,rugosity (st. dev. altitude at 1 min),rugosity,year,, -temperature_01,temperature_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Jan,mean T Jan,january,degrees Celsius,*degree*C* -temperature_02,temperature_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Feb,mean T Feb,february,degrees Celsius,*degree*C* -temperature_03,temperature_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Mar,mean T Mar,march,degrees Celsius,*degree*C* -temperature_04,temperature_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Apr,mean T Apr,april,degrees Celsius,*degree*C* -temperature_05,temperature_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature May,mean T May,may,degrees Celsius,*degree*C* -temperature_06,temperature_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Jun,mean T Jun,june,degrees Celsius,*degree*C* -temperature_07,temperature_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Jul,mean T Jul,july,degrees Celsius,*degree*C* -temperature_08,temperature_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Aug,mean T Aug,august,degrees Celsius,*degree*C* -temperature_09,temperature_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Sep,mean T Sep,september,degrees Celsius,*degree*C* -temperature_10,temperature_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Oct,mean T Oct,october,degrees Celsius,*degree*C* -temperature_11,temperature_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Nov,mean T Nov,november,degrees Celsius,*degree*C* -temperature_12,temperature_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,mean temperature Dec,mean T Dec,december,degrees Celsius,*degree*C* -precipitation_01,precipitation_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Jan,P Jan,january,mm per month,*mm~mo^-1* -precipitation_02,precipitation_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Feb,P Feb,february,mm per month,*mm~mo^-1* -precipitation_03,precipitation_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Mar,P Mar,march,mm per month,*mm~mo^-1* -precipitation_04,precipitation_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Apr,P Apr,april,mm per month,*mm~mo^-1* -precipitation_05,precipitation_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation May,P May,may,mm per month,*mm~mo^-1* -precipitation_06,precipitation_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Jun,P Jun,june,mm per month,*mm~mo^-1* -precipitation_07,precipitation_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Jul,P Jul,july,mm per month,*mm~mo^-1* -precipitation_08,precipitation_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Aug,P Aug,august,mm per month,*mm~mo^-1* -precipitation_09,precipitation_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Sep,P Sep,september,mm per month,*mm~mo^-1* -precipitation_10,precipitation_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Oct,P Oct,october,mm per month,*mm~mo^-1* -precipitation_11,precipitation_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Nov,P Nov,november,mm per month,*mm~mo^-1* -precipitation_12,precipitation_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1* -cloudiness_01,cloudiness_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Jan,cloudiness Jan,january,%,*'%'* -cloudiness_02,cloudiness_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Feb,cloudiness Feb,february,%,*'%'* -cloudiness_03,cloudiness_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Mar,cloudiness Mar,march,%,*'%'* -cloudiness_04,cloudiness_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Apr,cloudiness Apr,april,%,*'%'* -cloudiness_05,cloudiness_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness May,cloudiness May,may,%,*'%'* -cloudiness_06,cloudiness_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Jun,cloudiness Jun,june,%,*'%'* -cloudiness_07,cloudiness_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Jul,cloudiness Jul,july,%,*'%'* -cloudiness_08,cloudiness_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Aug,cloudiness Aug,august,%,*'%'* -cloudiness_09,cloudiness_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Sep,cloudiness Sep,september,%,*'%'* -cloudiness_10,cloudiness_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Oct,cloudiness Oct,october,%,*'%'* -cloudiness_11,cloudiness_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Nov,cloudiness Nov,november,%,*'%'* -cloudiness_12,cloudiness_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,cloudiness Dec,cloudiness Dec,december,%,*'%'* -relative_humidity_01,relative_humidity_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Jan,RH Jan,january,%,*'%'* -relative_humidity_02,relative_humidity_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Feb,RH Feb,february,%,*'%'* -relative_humidity_03,relative_humidity_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Mar,RH Mar,march,%,*'%'* -relative_humidity_04,relative_humidity_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Apr,RH Apr,april,%,*'%'* -relative_humidity_05,relative_humidity_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity May,RH May,may,%,*'%'* -relative_humidity_06,relative_humidity_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Jun,RH Jun,june,%,*'%'* -relative_humidity_07,relative_humidity_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Jul,RH Jul,july,%,*'%'* -relative_humidity_08,relative_humidity_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Aug,RH Aug,august,%,*'%'* -relative_humidity_09,relative_humidity_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Sep,RH Sep,september,%,*'%'* -relative_humidity_10,relative_humidity_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Oct,RH Oct,october,%,*'%'* -relative_humidity_11,relative_humidity_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Nov,RH Nov,november,%,*'%'* -relative_humidity_12,relative_humidity_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,relative humidity Dec,RH Dec,december,%,*'%'* -wind_speed_01,wind_speed_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Jan,WS Jan,january,m per second,*m~s^-1* -wind_speed_02,wind_speed_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Feb,WS Feb,february,m per second,*m~s^-1* -wind_speed_03,wind_speed_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Mar,WS Mar,march,m per second,*m~s^-1* -wind_speed_04,wind_speed_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Apr,WS Apr,april,m per second,*m~s^-1* -wind_speed_05,wind_speed_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed May,WS May,may,m per second,*m~s^-1* -wind_speed_06,wind_speed_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Jun,WS Jun,june,m per second,*m~s^-1* -wind_speed_07,wind_speed_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Jul,WS Jul,july,m per second,*m~s^-1* -wind_speed_08,wind_speed_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Aug,WS Aug,august,m per second,*m~s^-1* -wind_speed_09,wind_speed_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Sep,WS Sep,september,m per second,*m~s^-1* -wind_speed_10,wind_speed_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Oct,WS Oct,october,m per second,*m~s^-1* -wind_speed_11,wind_speed_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Nov,WS Nov,november,m per second,*m~s^-1* -wind_speed_12,wind_speed_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,wind speed Dec,WS Dec,december,m per second,*m~s^-1* -mo_npp_01,mo_npp_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_02,mo_npp_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_03,mo_npp_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_04,mo_npp_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_05,mo_npp_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_06,mo_npp_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_07,mo_npp_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_08,mo_npp_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_09,mo_npp_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_10,mo_npp_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_11,mo_npp_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_12,mo_npp_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.1.0.nc,https://zenodo.org/record/7062281/files/Beyer2020_monthly_vars_v1.1.0.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.1.0,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1* -bio01,bio01,Krapp2021,FALSE,Krapp2021_bio01_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio01_v1.0.0.nc?download=1,bio01_800ka.nc,https://osf.io/a39gh/?action=download,1.1.0,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio04,bio04,Krapp2021,FALSE,Krapp2021_bio04_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio04_v1.0.0.nc?download=1,bio04_800ka.nc,https://osf.io/p82ue/?action=download,1.1.0,temperature seasonality,T season.,year,degrees Celsius,*degree*C* -bio05,bio05,Krapp2021,FALSE,Krapp2021_bio05_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio05_v1.0.0.nc?download=1,bio05_800ka.nc,https://osf.io/emhp9/?action=download,1.1.0,maximum temperature of warmest month,maximum T of warmest mo.,year,degrees Celsius,*degree*C* -bio06,bio06,Krapp2021,FALSE,Krapp2021_bio06_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio06_v1.0.0.nc?download=1,bio06_800ka.nc,https://osf.io/cm923/?action=download,1.1.0,minimum temperature of coldest month,minimum T of coldest mo.,year,degrees Celsius,*degree*C* -bio07,bio07,Krapp2021,FALSE,Krapp2021_bio07_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio07_v1.0.0.nc?download=1,bio07_800ka.nc,https://osf.io/prq8n/?action=download,1.1.0,temperature annual range (bio05-bio06),T ann. range (bio05-bio06),year,degrees Celsius,*degree*C* -bio08,bio08,Krapp2021,FALSE,Krapp2021_bio08_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio08_v1.0.0.nc?download=1,bio08_800ka.nc,https://osf.io/7jsa8/?action=download,1.1.0,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C* -bio09,bio09,Krapp2021,FALSE,Krapp2021_bio09_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio09_v1.0.0.nc?download=1,bio09_800ka.nc,https://osf.io/zaxku/?action=download,1.1.0,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C* -bio10,bio10,Krapp2021,FALSE,Krapp2021_bio10_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio10_v1.0.0.nc?download=1,bio10_800ka.nc,https://osf.io/b3kx8/?action=download,1.1.0,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio11,bio11,Krapp2021,FALSE,Krapp2021_bio11_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio11_v1.0.0.nc?download=1,bio11_800ka.nc,https://osf.io/vaune/?action=download,1.1.0,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C* -bio12,bio12,Krapp2021,FALSE,Krapp2021_bio12_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio12_v1.0.0.nc?download=1,bio12_800ka.nc,https://osf.io/kg9v6/?action=download,1.1.0,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -bio13,bio13,Krapp2021,FALSE,Krapp2021_bio13_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio13_v1.0.0.nc?download=1,bio13_800ka.nc,https://osf.io/2u5c6/?action=download,1.1.0,precipitation of wettest month,P of wettest mo.,year,mm per month,*mm~mo^-1* -bio14,bio14,Krapp2021,FALSE,Krapp2021_bio14_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio14_v1.0.0.nc?download=1,bio14_800ka.nc,https://osf.io/z2ewu/?action=download,1.1.0,precipitation of driest month,P of driest mo.,year,mm per month,*mm~mo^-1* -bio15,bio15,Krapp2021,FALSE,Krapp2021_bio15_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio15_v1.0.0.nc?download=1,bio15_800ka.nc,https://osf.io/z52xr/?action=download,1.1.0,precipitation seasonality (coefficient of variation),P season. (coefficient of variation),year,, -bio16,bio16,Krapp2021,FALSE,Krapp2021_bio16_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio16_v1.0.0.nc?download=1,bio16_800ka.nc,https://osf.io/kn8ma/?action=download,1.1.0,precipitation of wettest quarter,P of wettest qtr,year,mm per quarter,*mm~qtr^-1* -bio17,bio17,Krapp2021,FALSE,Krapp2021_bio17_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio17_v1.0.0.nc?download=1,bio17_800ka.nc,https://osf.io/2z8ej/?action=download,1.1.0,precipitation of driest quarter,P of driest qtr,year,mm per quarter,*mm~qtr^-1* -bio18,bio18,Krapp2021,FALSE,Krapp2021_bio18_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio18_v1.0.0.nc?download=1,bio18_800ka.nc,https://osf.io/a2uhm/?action=download,1.1.0,precipitation of warmest quarter,P of warmest qtr,year,mm per quarter,*mm~qtr^-1* -bio19,bio19,Krapp2021,FALSE,Krapp2021_bio19_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_bio19_v1.0.0.nc?download=1,bio19_800ka.nc,https://osf.io/3mbd9/?action=download,1.1.0,precipitation of coldest quarter,P of coldest qtr,year,mm per quarter,*mm~qtr^-1* -npp,npp,Krapp2021,FALSE,Krapp2021_npp_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_biome_v1.0.0.nc?download=1,biome4output_800ka.nc,https://osf.io/cf5zp/?action=download,1.1.0,net primary productivity,NPP,year,gC per m^2 per year,*gC~m^-2~yr^-1* -biome,biome,Krapp2021,FALSE,Krapp2021_biome_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_biome_v1.0.0.nc?download=1,biome4output_800ka.nc,https://osf.io/cf5zp/?action=download,1.1.0,biome (from BIOME4),biome (from BIOME4),year,, -altitude,altitude,Krapp2021,FALSE,Krapp2021_topography_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_topography_v1.0.0.nc?download=1,,,1.1.0,altitude over the sea level,altitude over the sea level,year,m,*m* -rugosity,rugosity,Krapp2021,FALSE,Krapp2021_topography_v1.0.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_topography_v1.0.0.nc?download=1,,,1.1.0,rugosity,rugosity,year,, -temperature_01,temp_01,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Jan,mean T Jan,january,degrees Celsius,*degree*C* -temperature_02,temp_02,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Feb,mean T Feb,february,degrees Celsius,*degree*C* -temperature_03,temp_03,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Mar,mean T Mar,march,degrees Celsius,*degree*C* -temperature_04,temp_04,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Apr,mean T Apr,april,degrees Celsius,*degree*C* -temperature_05,temp_05,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature May,mean T May,may,degrees Celsius,*degree*C* -temperature_06,temp_06,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Jun,mean T Jun,june,degrees Celsius,*degree*C* -temperature_07,temp_07,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Jul,mean T Jul,july,degrees Celsius,*degree*C* -temperature_08,temp_08,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Aug,mean T Aug,august,degrees Celsius,*degree*C* -temperature_09,temp_09,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Sep,mean T Sep,september,degrees Celsius,*degree*C* -temperature_10,temp_10,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Oct,mean T Oct,october,degrees Celsius,*degree*C* -temperature_11,temp_11,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Nov,mean T Nov,november,degrees Celsius,*degree*C* -temperature_12,temp_12,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_temp_monthly_v1.1.0.nc?download=1,,,1.1.0,mean temperature Dec,mean T Dec,december,degrees Celsius,*degree*C* -precipitation_01,prec_01,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Jan,P Jan,january,mm per month,*mm~mo^-1* -precipitation_02,prec_02,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Feb,P Feb,february,mm per month,*mm~mo^-1* -precipitation_03,prec_03,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Mar,P Mar,march,mm per month,*mm~mo^-1* -precipitation_04,prec_04,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Apr,P Apr,april,mm per month,*mm~mo^-1* -precipitation_05,prec_05,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation May,P May,may,mm per month,*mm~mo^-1* -precipitation_06,prec_06,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Jun,P Jun,june,mm per month,*mm~mo^-1* -precipitation_07,prec_07,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Jul,P Jul,july,mm per month,*mm~mo^-1* -precipitation_08,prec_08,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Aug,P Aug,august,mm per month,*mm~mo^-1* -precipitation_09,prec_09,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Sep,P Sep,september,mm per month,*mm~mo^-1* -precipitation_10,prec_10,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Oct,P Oct,october,mm per month,*mm~mo^-1* -precipitation_11,prec_11,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Nov,P Nov,november,mm per month,*mm~mo^-1* -precipitation_12,prec_12,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_prec_monthly_v1.1.0.nc?download=1,,,1.1.0,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1* -mo_npp_01,mo_npp_01,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_02,mo_npp_02,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_03,mo_npp_03,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_04,mo_npp_04,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_05,mo_npp_05,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_06,mo_npp_06,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_07,mo_npp_07,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_08,mo_npp_08,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_09,mo_npp_09,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_10,mo_npp_10,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_11,mo_npp_11,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_12,mo_npp_12,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_npp_v1.0.0.nc?download=1,,,1.1.0,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1* -cloudiness_01,tcc_01,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Jan,cloudiness Jan,january,%,*'%'* -cloudiness_02,tcc_02,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Feb,cloudiness Feb,february,%,*'%'* -cloudiness_03,tcc_03,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Mar,cloudiness Mar,march,%,*'%'* -cloudiness_04,tcc_04,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Apr,cloudiness Apr,april,%,*'%'* -cloudiness_05,tcc_05,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness May,cloudiness May,may,%,*'%'* -cloudiness_06,tcc_06,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Jun,cloudiness Jun,june,%,*'%'* -cloudiness_07,tcc_07,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Jul,cloudiness Jul,july,%,*'%'* -cloudiness_08,tcc_08,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Aug,cloudiness Aug,august,%,*'%'* -cloudiness_09,tcc_09,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Sep,cloudiness Sep,september,%,*'%'* -cloudiness_10,tcc_10,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Oct,cloudiness Oct,october,%,*'%'* -cloudiness_11,tcc_11,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Nov,cloudiness Nov,november,%,*'%'* -cloudiness_12,tcc_12,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.1.0.nc,https://zenodo.org/record/7065055/files/Krapp2021_tcc_monthly_v1.1.0.nc?download=1,,,1.1.0,cloudiness Dec,cloudiness Dec,december,%,*'%'* +bio01,BIO1,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* +bio10,BIO10,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* +bio12,BIO12,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* +biome,biome,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,biome (from BIOME4),biome,year,, +bio01,bio01,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* +bio04,bio04,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,temperature seasonality,T season.,year,degrees Celsius,*degree*C* +bio05,bio05,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,maximum temperature of warmest month,max. T of warmest mo.,year,degrees Celsius,*degree*C* +bio06,bio06,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,minimum temperature of coldest month,min. T of coldest mo.,year,degrees Celsius,*degree*C* +bio07,bio07,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,temperature annual range (bio05-bio06),T ann. Range,year,degrees Celsius,*degree*C* +bio08,bio08,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C* +bio09,bio09,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C* +bio10,bio10,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* +bio11,bio11,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C* +bio12,bio12,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* +bio13,bio13,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of wettest month,P of wettest mo.,year,mm per month,*mm~mo^-1* +bio14,bio14,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of driest month,P of driest mo.,year,mm per month,*mm~mo^-1* +bio15,bio15,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation seasonality (coeff var),P season.,year,, 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+precipitation_12,prec_12,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1* +mo_npp_01,mo_npp_01,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_02,mo_npp_02,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_03,mo_npp_03,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_04,mo_npp_04,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_05,mo_npp_05,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_06,mo_npp_06,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_07,mo_npp_07,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_08,mo_npp_08,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_09,mo_npp_09,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_10,mo_npp_10,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_11,mo_npp_11,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1* +mo_npp_12,mo_npp_12,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1* +cloudiness_01,tcc_01,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jan,cloudiness Jan,january,%,*'%'* +cloudiness_02,tcc_02,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Feb,cloudiness Feb,february,%,*'%'* +cloudiness_03,tcc_03,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Mar,cloudiness Mar,march,%,*'%'* +cloudiness_04,tcc_04,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Apr,cloudiness Apr,april,%,*'%'* +cloudiness_05,tcc_05,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness May,cloudiness May,may,%,*'%'* +cloudiness_06,tcc_06,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jun,cloudiness Jun,june,%,*'%'* +cloudiness_07,tcc_07,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jul,cloudiness Jul,july,%,*'%'* +cloudiness_08,tcc_08,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Aug,cloudiness Aug,august,%,*'%'* +cloudiness_09,tcc_09,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Sep,cloudiness Sep,september,%,*'%'* +cloudiness_10,tcc_10,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Oct,cloudiness Oct,october,%,*'%'* +cloudiness_11,tcc_11,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Nov,cloudiness Nov,november,%,*'%'* +cloudiness_12,tcc_12,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Dec,cloudiness Dec,december,%,*'%'* diff --git a/inst/rawdata_scripts/downsample_CHELSA_TraCE21k_tiff.R b/inst/rawdata_scripts/downsample_CHELSA_TraCE21k_tiff.R new file mode 100644 index 00000000..d22f8ce3 --- /dev/null +++ b/inst/rawdata_scripts/downsample_CHELSA_TraCE21k_tiff.R @@ -0,0 +1,6 @@ +# ran in bash +# this takes 3 files downloaded at high resolution and downsamples so that they can be +# used as example files +gdalwarp -tr 1 1 -r average CHELSA_TraCE21k_bio01_-1_V1.0.tif CHELSA_TraCE21k_bio01_-1_V1.0.small.tif +gdalwarp -tr 1 1 -r average CHELSA_TraCE21k_bio01_-2_V1.0.tif CHELSA_TraCE21k_bio01_-2_V1.0.small.tif +gdalwarp -tr 1 1 -r average CHELSA_TraCE21k_bio01_-3_V1.0.tif CHELSA_TraCE21k_bio01_-3_V1.0.small.tif diff --git a/inst/rawdata_scripts/update_meta_data_of_vars_in_nc.R b/inst/rawdata_scripts/update_meta_data_of_vars_in_nc.R new file mode 100644 index 00000000..b75755cf --- /dev/null +++ b/inst/rawdata_scripts/update_meta_data_of_vars_in_nc.R @@ -0,0 +1,42 @@ +#read.csv(system.file("rawdata_scripts/data_files/variable_table_complete_meta.csv", +# library="pastclim")) +library(ClimateOperators) +rm(list=ls()) +dataset <- "Krapp2021" +version_number <- "1.2.2" +out_dir <- "../../project_temp/past_climate/new_meta" +full_meta <- read.csv("./inst/rawdata_scripts/data_files/variable_table_complete_meta.csv") +data_path <- get_data_path() +sub_meta <- full_meta[full_meta$dataset == dataset,] +target_files <- unique(sub_meta$file_name) + +for (i in target_files){ + name_components<-unlist(strsplit(i,"_",fixed=TRUE)) + # replace the last component with new version 1.2.2 + name_components<-name_components[-length(name_components)] + new_name <- paste(paste(name_components, collapse="_"),paste0("v", version_number,".nc"),sep="_") + new_target_path <- file.path(out_dir, new_name) + old_target_path <- file.path(get_data_path(),i) + file.copy(old_target_path,new_target_path) + nc_in <- ncdf4::nc_open(new_target_path, write = TRUE) + # update time units + ncdf4::ncatt_put(nc_in, varid="time", attname = "units", attval = "years since 1950-01-01 00:00:00.0") + ncdf4::ncatt_put(nc_in,varid="time", attname = "long_name",attval = "years BP") + # update meta units + this_var_names <- names(nc_in$var) + for (x in this_var_names){ + ncdf4::ncatt_put(nc_in, varid=x, attname = "long_name", + attval = sub_meta$long_name[sub_meta$ncvar==x]) + ncdf4::ncatt_put(nc_in, varid=x, attname = "units", + attval = sub_meta$units[sub_meta$ncvar==x]) + } + ncdf4::ncatt_put(nc_in, varid = 0, attname = "pastclim_version", + attval=version_number) + + ncdf4::nc_close(nc_in) + # now remove the attribute unit if present (it should be units) + for (x in this_var_names){ + ncatted(paste0('-a unit,',x,',d,, -h ',new_target_path)) + } + +} diff --git a/inst/rawdata_scripts/verify_files_by_dataset.R b/inst/rawdata_scripts/verify_files_by_dataset.R new file mode 100644 index 00000000..cbf753b1 --- /dev/null +++ b/inst/rawdata_scripts/verify_files_by_dataset.R @@ -0,0 +1,13 @@ +# verify that all the variables in the tables are actually found in the files +# this requires all data to have been downloaded +full_meta <- read.csv("./inst/rawdata_scripts/data_files/variable_table.csv") +in_dir <- get_data_path() +in_dir <- "~/project_temp/past_climate/new_meta" +for (i in 1:nrow(full_meta)){ + nc_in <- ncdf4::nc_open(file.path(in_dir, full_meta$file_name[i])) + if (!full_meta$ncvar[i] %in% names(nc_in$var)){ + ncdf4::nc_close(nc_in) + stop("problem with ",full_meta$ncvar[i]," in ", full_meta$file_name[i]) + } + ncdf4::nc_close(nc_in) +} From a6a5546298e37cf55b02b726c55dbfe4fe917e9a Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 09:03:07 +0000 Subject: [PATCH 11/22] Update to latest datasets --- R/download_dataset.R | 24 +++++++++++------- R/set_data_path.R | 7 ++--- ...limate_v2.nc => example_climate_v1.2.2.nc} | Bin tests/testthat/test_check_dataset_path.R | 3 ++- tests/testthat/test_download_dataset.R | 3 ++- tests/testthat/test_get_mis_time_steps.R | 3 ++- tests/testthat/test_get_set_data_path.R | 8 +++++- tests/testthat/test_get_time_steps.R | 5 ++-- tests/testthat/test_get_vars_for_dataset.R | 5 ++-- tests/testthat/test_location_series.R | 5 ++-- tests/testthat/test_location_slice.R | 5 ++-- tests/testthat/test_region_series.R | 6 +++-- tests/testthat/test_region_slice.R | 6 +++-- 13 files changed, 52 insertions(+), 28 deletions(-) rename inst/extdata/{example_climate_v2.nc => example_climate_v1.2.2.nc} (100%) diff --git a/R/download_dataset.R b/R/download_dataset.R index f01b8216..c6e149a5 100644 --- a/R/download_dataset.R +++ b/R/download_dataset.R @@ -50,15 +50,21 @@ download_dataset <- function(dataset, bio_variables = NULL) { } - # download the dataset - for (this_var in bio_variables) { - file_details <- get_file_for_dataset(this_var, dataset) - # only download the file if it is needed - if (!file.exists(file.path(get_data_path(), file_details$file_name))) { - curl::curl_download(file_details$download_path, - destfile = file.path(get_data_path(), file_details$file_name), - quiet = FALSE - ) + # special case for the example dataset + # as we have a copy on the package + if (dataset == "Example"){ + copy_example_data() + } else { + # download the file for each variable + for (this_var in bio_variables) { + file_details <- get_file_for_dataset(this_var, dataset) + # only download the file if it is needed + if (!file.exists(file.path(get_data_path(), file_details$file_name))) { + curl::curl_download(file_details$download_path, + destfile = file.path(get_data_path(), file_details$file_name), + quiet = FALSE + ) + } } } return(TRUE) diff --git a/R/set_data_path.R b/R/set_data_path.R index 0a5309f9..9f51e28f 100644 --- a/R/set_data_path.R +++ b/R/set_data_path.R @@ -92,12 +92,13 @@ set_data_path <- function(path_to_nc = NULL, ask = TRUE, write_config = TRUE, #' @keywords internal copy_example_data <- function() { - if (!file.exists(file.path(get_data_path(), "example_climate_v2.nc"))) { + example_filename <- unique(files_by_dataset$file_name[files_by_dataset$dataset == "Example"]) + if (!file.exists(file.path(get_data_path(), example_filename))) { file.copy( - from = system.file("/extdata/example_climate_v2.nc", + from = system.file(file.path("/extdata",example_filename), package = "pastclim" ), - to = file.path(get_data_path(), "example_climate_v2.nc") + to = file.path(get_data_path(), example_filename) ) } return(TRUE) diff --git a/inst/extdata/example_climate_v2.nc b/inst/extdata/example_climate_v1.2.2.nc similarity index 100% rename from inst/extdata/example_climate_v2.nc rename to inst/extdata/example_climate_v1.2.2.nc diff --git a/tests/testthat/test_check_dataset_path.R b/tests/testthat/test_check_dataset_path.R index 3e212861..65c38fe2 100644 --- a/tests/testthat/test_check_dataset_path.R +++ b/tests/testthat/test_check_dataset_path.R @@ -18,11 +18,12 @@ test_that("check_dataset_path errors", { check_dataset_path("custom", NULL), "you need to set path_to_nc if dataset='custom'" ) + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] expect_true(check_dataset_path( "custom", file.path( get_data_path(), - "example_climate_v2.nc" + example_filename ) )) expect_error( diff --git a/tests/testthat/test_download_dataset.R b/tests/testthat/test_download_dataset.R index e13d31cf..ad7fed55 100644 --- a/tests/testthat/test_download_dataset.R +++ b/tests/testthat/test_download_dataset.R @@ -20,7 +20,8 @@ test_that("download_dataset", { "^foo not available " ) # check that only the example climate is in the data directory - expect_true("example_climate_v2.nc" %in% list.files(get_data_path())) + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + expect_true(example_filename %in% list.files(get_data_path())) # expect no error as the dataset exists expect_error(download_dataset("Example"), NA) }) diff --git a/tests/testthat/test_get_mis_time_steps.R b/tests/testthat/test_get_mis_time_steps.R index c4500f2f..95f8a648 100644 --- a/tests/testthat/test_get_mis_time_steps.R +++ b/tests/testthat/test_get_mis_time_steps.R @@ -16,7 +16,8 @@ test_that("get_mis_time_steps for standard dataset", { }) test_that("get_mis_time_steps for local file", { - path_to_example_nc <- system.file("/extdata/", "example_climate_v2.nc", + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) expect_equal(get_mis_time_steps( diff --git a/tests/testthat/test_get_set_data_path.R b/tests/testthat/test_get_set_data_path.R index df4b934f..c8ae92be 100644 --- a/tests/testthat/test_get_set_data_path.R +++ b/tests/testthat/test_get_set_data_path.R @@ -1,14 +1,20 @@ # start with a clean slate in case other tests set up the path options(pastclim.data_path = NULL) # reset the option -test_that("set and get data path", { +test_that("get data path when config not present", { + skip_if((file.exists(file.path( + tools::R_user_dir("pastclim", "config"), + "pastclim_data.txt" + ))),"config file already exists on this system") # try to get path when none is set expect_message(null_data_path <- get_data_path()) expect_null(null_data_path) # now do the same in silent mode expect_no_message(null_data_path <- get_data_path(silent = TRUE)) expect_null(null_data_path) +}) +test_that("set and get data path", { # now set the path in a subdirectory of tempdir data_path <- file.path(tempdir(),"pastclim_data") unlink(data_path, recursive = TRUE) # it should not exist, but remove it just in case diff --git a/tests/testthat/test_get_time_steps.R b/tests/testthat/test_get_time_steps.R index c3ea551e..13d63d56 100644 --- a/tests/testthat/test_get_time_steps.R +++ b/tests/testthat/test_get_time_steps.R @@ -27,8 +27,9 @@ test_that("get_time_steps for standard dataset", { }) test_that("get_time_steps for local file", { - path_to_example_nc <- system.file("/extdata/", "example_climate_v2.nc", - package = "pastclim" + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" ) expect_equal(get_time_steps( dataset = "custom", diff --git a/tests/testthat/test_get_vars_for_dataset.R b/tests/testthat/test_get_vars_for_dataset.R index ea0f38a1..7213da84 100644 --- a/tests/testthat/test_get_vars_for_dataset.R +++ b/tests/testthat/test_get_vars_for_dataset.R @@ -33,8 +33,9 @@ test_that("get_vars_for_dataset returns appropriate object", { test_that("get_vars_for_dataset for local file", { - path_to_example_nc <- system.file("/extdata/", "example_climate_v2.nc", - package = "pastclim" + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" ) vars <- get_vars_for_dataset(dataset = "custom", path_to_nc = path_to_example_nc) expect_true(inherits(vars,"character")) diff --git a/tests/testthat/test_location_series.R b/tests/testthat/test_location_series.R index d6fd188c..1b8bcbf1 100644 --- a/tests/testthat/test_location_series.R +++ b/tests/testthat/test_location_series.R @@ -92,8 +92,9 @@ test_that("time_series_for_location", { # now use a custom dataset - path_to_example_nc <- system.file("/extdata/example_climate_v2.nc", - package = "pastclim" + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" ) locations_ts <- location_series( x = locations[, c("longitude", "latitude")], diff --git a/tests/testthat/test_location_slice.R b/tests/testthat/test_location_slice.R index 27bbd7ef..6ef3a309 100644 --- a/tests/testthat/test_location_slice.R +++ b/tests/testthat/test_location_slice.R @@ -91,8 +91,9 @@ test_that("location_slice", { ) # now test a custom dataset - path_to_example_nc <- system.file("/extdata/example_climate_v2.nc", - package = "pastclim" + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" ) this_climate <- location_slice( x = locations[, c("longitude", "latitude")], diff --git a/tests/testthat/test_region_series.R b/tests/testthat/test_region_series.R index 19755eb2..a4782b05 100644 --- a/tests/testthat/test_region_series.R +++ b/tests/testthat/test_region_series.R @@ -19,8 +19,10 @@ test_that("region series", { expect_true(all(terra::nlyr(climate_region) == c(2, 2))) # do the same for a custom dataset - path_to_example_nc <- system.file("/extdata/example_climate_v2.nc", - package = "pastclim") + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" + ) climate_region <- region_series(c(-20000, -10000), c("BIO1", "BIO10"), "custom", path_to_nc = path_to_example_nc diff --git a/tests/testthat/test_region_slice.R b/tests/testthat/test_region_slice.R index 48b2a297..e8731a06 100644 --- a/tests/testthat/test_region_slice.R +++ b/tests/testthat/test_region_slice.R @@ -19,8 +19,10 @@ test_that("region slice", { expect_true(terra::nlyr(climate_slice) == c(2)) # do the same for a custom dataset - path_to_example_nc <- system.file("/extdata/example_climate_v2.nc", - package = "pastclim") + example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + path_to_example_nc <- system.file("/extdata/", example_filename, + package = "pastclim" + ) climate_slice <- region_slice(c(-10000), c("BIO1", "BIO10"), "custom", path_to_nc = path_to_example_nc From 54f7711b0b9787f00c2a667db3ba4dd036687567 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 11:27:37 +0000 Subject: [PATCH 12/22] Fix for Lucy --- inst/temp/_delta_downscale_3.R | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/inst/temp/_delta_downscale_3.R b/inst/temp/_delta_downscale_3.R index d0bdce40..f4d8a54c 100644 --- a/inst/temp/_delta_downscale_3.R +++ b/inst/temp/_delta_downscale_3.R @@ -182,6 +182,10 @@ idw_interp <- function(x, y, ...){ x_gap[x_gap==0]<-NA x_df <- terra::as.data.frame(x,xy=TRUE,na.rm=TRUE) x_gap_df <- terra::as.data.frame(x_gap, xy=TRUE, na.rm=TRUE) + # if there is not gap between the values and the mask, just return the values + if (nrow(x_gap_df)==0){ + return(x) + } names(x_df)[3] <-"this_var" names(x_gap_df)[3] <-"this_var" # interpolate those gaps with idw (time consuming...) From 4dfb019c66c39b8160a6dfedbfb8c9bfa8a54f41 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 12:13:18 +0000 Subject: [PATCH 13/22] Bug in delta_compute [skip ci] --- inst/temp/_delta_downscale_3.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/inst/temp/_delta_downscale_3.R b/inst/temp/_delta_downscale_3.R index f4d8a54c..61a0e1f2 100644 --- a/inst/temp/_delta_downscale_3.R +++ b/inst/temp/_delta_downscale_3.R @@ -33,7 +33,7 @@ delta_compute <- function(x, ref_time, obs) { x_modern_high<-disagg(x_modern, fact = terra::res( x_modern)/terra::res(obs), method="bilinear") # compute anomalies against the modern - delta <- x_modern_high - obs + delta <- obs - x_modern_high # mask for maximum land extent max_land <- max(x,na.rm=TRUE) max_land <- disagg(max_land, fact = terra::res( x)/terra::res(obs), From 149fd4fb191ff221bb52c7e20250c5e15b1e8f8c Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 15:59:05 +0000 Subject: [PATCH 14/22] Clean up data path --- NAMESPACE | 1 + R/clean_data_path.R | 35 +++++++++++++++++++++++++++ R/get_time_steps.R | 13 ++++++---- R/location_series.R | 2 +- man/clean_data_path.Rd | 19 +++++++++++++++ man/get_time_steps.Rd | 2 +- tests/testthat/test_clean_data_path.R | 31 ++++++++++++++++++++++++ vignettes/a0_pastclim_overview.Rmd | 6 +++++ vignettes/a2_custom_datasets.Rmd | 3 ++- 9 files changed, 104 insertions(+), 8 deletions(-) create mode 100644 R/clean_data_path.R create mode 100644 man/clean_data_path.Rd create mode 100644 tests/testthat/test_clean_data_path.R diff --git a/NAMESPACE b/NAMESPACE index 35ffae82..e4f3e447 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,6 +1,7 @@ # Generated by roxygen2: do not edit by hand export(check_dataset_path) +export(clean_data_path) export(climate_for_locations) export(climate_for_time_slice) export(df_from_region_series) diff --git a/R/clean_data_path.R b/R/clean_data_path.R new file mode 100644 index 00000000..de2d54c7 --- /dev/null +++ b/R/clean_data_path.R @@ -0,0 +1,35 @@ +#' Clean the data path +#' +#' This function deletes old reconstructions that have been superseded in the +#' data_path. It assumes that the only files in data_path are part of pastclim +#' (i.e. there are no custom datasets stored in that directory). +#' +#' @param ask boolean on whether the user should be asked before deleting +#' @returns TRUE if files are deleted successfully +#' @export + +clean_data_path <- function(ask=TRUE) { + if (is.null(get_data_path(silent=TRUE))){ + message("The data path has not been set yet; use set_data_path() first!") + return(FALSE) + } + files_now <- list.files(get_data_path()) + possible_files <- unique(files_by_dataset$file_name) + files_to_remove <- files_now[!files_now %in% possible_files] + if (length(files_to_remove)>0){ + if (ask){ + this_answer <- utils::menu(choices = c("yes","no"), + title = paste("The following files are obsolete:\n", + paste(files_to_remove,collapse = ", "), + "\n Do you want to delete them?")) + } else { # default to delete if we are not asking + this_answer <- 1 + } + if (this_answer==1){ + file.remove(file.path(get_data_path(),files_to_remove)) + } + } else { + message("Everything is up-to-date; no files need removing.") + } + return(TRUE) +} diff --git a/R/get_time_steps.R b/R/get_time_steps.R index 54e620fe..f130b975 100644 --- a/R/get_time_steps.R +++ b/R/get_time_steps.R @@ -1,6 +1,6 @@ #' Get time steps for a given dataset #' -#' Get the time steps available in a given dataset. +#' Get the time steps (in time_bp) available in a given dataset. #' #' @param dataset string defining dataset to be downloaded (a list of possible #' values can be obtained with \code{get_available_datasets}). If set to @@ -21,8 +21,11 @@ get_time_steps <- function(dataset, path_to_nc = NULL) { path_to_nc <- file.path(get_data_path(), this_file) } - climate_nc <- ncdf4::nc_open(path_to_nc) - time_steps <- (climate_nc$dim$time$vals) - ncdf4::nc_close(climate_nc) - return(time_steps) + climate_nc <- terra::rast(path_to_nc, subds=1) + return(time_bp(climate_nc)) + + # climate_nc <- ncdf4::nc_open(path_to_nc) + # time_steps <- (climate_nc$dim$time$vals) + # ncdf4::nc_close(climate_nc) + # return(time_steps) } diff --git a/R/location_series.R b/R/location_series.R index cb43879e..82c62064 100644 --- a/R/location_series.R +++ b/R/location_series.R @@ -116,7 +116,7 @@ location_series <- #' @export time_series_for_locations <- function(...) { - warning("DEPRECATED: use 'location_slice' instead") + warning("DEPRECATED: use 'location_series' instead") # if (!is.null(path_to_nc)) { # stop( # "the use of pastclimData is now deprecated", diff --git a/man/clean_data_path.Rd b/man/clean_data_path.Rd new file mode 100644 index 00000000..b526dd01 --- /dev/null +++ b/man/clean_data_path.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/clean_data_path.R +\name{clean_data_path} +\alias{clean_data_path} +\title{Clean the data path} +\usage{ +clean_data_path(ask = TRUE) +} +\arguments{ +\item{ask}{boolean on whether the user should be asked before deleting} +} +\value{ +TRUE if files are deleted successfully +} +\description{ +This function deletes old reconstructions that have been superseded in the +data_path. It assumes that the only files in data_path are part of pastclim +(i.e. there are no custom datasets stored in that directory). +} diff --git a/man/get_time_steps.Rd b/man/get_time_steps.Rd index 01cd6256..5620b304 100644 --- a/man/get_time_steps.Rd +++ b/man/get_time_steps.Rd @@ -16,5 +16,5 @@ reconstructions. All the variables of interest need to be included in this file.} } \description{ -Get the time steps available in a given dataset. +Get the time steps (in time_bp) available in a given dataset. } diff --git a/tests/testthat/test_clean_data_path.R b/tests/testthat/test_clean_data_path.R new file mode 100644 index 00000000..78b81ff8 --- /dev/null +++ b/tests/testthat/test_clean_data_path.R @@ -0,0 +1,31 @@ +# set up data path for this test +data_path <- file.path(tempdir(),"pastclim_data") +unlink(data_path, recursive = TRUE) # it should not exist, but remove it just in case +# set data path +set_data_path(path_to_nc = data_path, + ask = FALSE, + write_config = FALSE, + copy_example = TRUE) +################################################################################ + +test_that("clean data path", { + files_in_data_path <- list.files(get_data_path()) + expect_message(clean_data_path(ask = FALSE), + "Everything is") + # the files should not be touched + expect_equal(files_in_data_path,list.files(get_data_path())) + # now create a spurious file + file_to_add <- "example_climate_v0.0.1.nc" + write.csv("blash",file.path(get_data_path(),file_to_add)) + # now the extra file is there + expect_true(file_to_add %in% list.files(get_data_path())) + expect_true(clean_data_path(ask = FALSE)) + # now it's gone + expect_false(file_to_add %in% list.files(get_data_path())) + +}) + +################################################################################ +# clean up for the next test +unlink(data_path, recursive = TRUE) + diff --git a/vignettes/a0_pastclim_overview.Rmd b/vignettes/a0_pastclim_overview.Rmd index 9c265d94..27703c46 100644 --- a/vignettes/a0_pastclim_overview.Rmd +++ b/vignettes/a0_pastclim_overview.Rmd @@ -174,6 +174,12 @@ download_dataset(dataset = "Beyer2020", bio_variables = c("bio01", "bio05")) Note that multiple variables can be packed together into a single file, so `get_downloaded_datasets()` might list more variables than the ones that we chose to download (it depends on the dataset). +When upgrading `pastclim`, new version of various datasets might become available. +This will make the previously downloaded datasets obsolete, and you might suddenly +be told by `pastclim` that some variables have to be re-downloaded. This can lead +to the accumulation of old datasets in your data path. The function `clean_data_path()` +can be used to delete old files that are no longer needed. + # Get climate for locations Often we want to get the climate for specific locations. We can do so by using diff --git a/vignettes/a2_custom_datasets.Rmd b/vignettes/a2_custom_datasets.Rmd index 1a0afcdd..a643e882 100644 --- a/vignettes/a2_custom_datasets.Rmd +++ b/vignettes/a2_custom_datasets.Rmd @@ -40,12 +40,13 @@ Now we need to set the time axis of the raster (in this case, reconstructions ar ```{r} terra::time(bio01)<-c(0,-100,-200) names(bio01)<-paste("bio01",terra::time(bio01),sep="_") +bio01_sds<-sds(bio01) ``` Now we save the data as a *nc* file (we will use the temporary directory) ```{r} nc_name <- file.path(tempdir(),"CHELSA_TraCE21k_bio01.nc") -terra::writeCDF(bio01, filename = nc_name, varname = "bio01") +terra::writeCDF(bio01, filename = nc_name, varname = "bio01", overwrite=TRUE) ``` We also need to make sure that the *time* dimension has units and is labelled From 52c6d7fecb8a2e912b47022c39e6aacaaa802dae Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 17:21:53 +0000 Subject: [PATCH 15/22] Small fixes to work around some issues in terra --- NEWS.md | 5 +++++ R/time_bp.R | 3 ++- inst/temp/_delta_downscale_3.R | 6 ++++-- inst/temp/a4_delta_downscale.Rmd | 10 +++++----- 4 files changed, 16 insertions(+), 8 deletions(-) diff --git a/NEWS.md b/NEWS.md index d76bf47a..8c3fb41c 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,8 @@ +# pastclim 1.2.2 (under development) +* Update of Krapp2021 files to make them compatible with how terra now handles + time. Users will have to redownload datasets. Old files can be removed with + 'clean_data_path()' + # pastclim 1.2.1 * Small updates for CRAN submission. diff --git a/R/time_bp.R b/R/time_bp.R index 79e0f755..fa93ccee 100644 --- a/R/time_bp.R +++ b/R/time_bp.R @@ -13,7 +13,8 @@ time_bp <- function(x){ stop("x is not a SpatRaster") } if (x@ptr$timestep!="years"){ - stop("the time units of SpatRaster are not 'years'", + # this should be escalated to an error once terra can properly set times in years (it's in dev) + warning("the time units of SpatRaster are not 'years'", " it might be a problem with the time units not being properly set in the original nc file") } time_yr<-terra::time(x) diff --git a/inst/temp/_delta_downscale_3.R b/inst/temp/_delta_downscale_3.R index 61a0e1f2..27d501d3 100644 --- a/inst/temp/_delta_downscale_3.R +++ b/inst/temp/_delta_downscale_3.R @@ -14,7 +14,7 @@ #' #' @param x a \code{terra::SpatRaster} for the variable of interest, with all #' time steps of interest -#' @param ref_time the time of the slice that is used to compute the delta +#' @param ref_time the time (BP) of the slice that is used to compute the delta #' @param obs the observations #' #' @export @@ -143,7 +143,9 @@ make_land_mask <- function(topo_rast, time_bp, sea_level = NULL) { add(land_mask)<-sea_patches } } - terra::time(land_mask) <- (time_bp+1950) + # TODO work around problem in terra (fixed in dev) + #terra::time(land_mask, tstep="years") <- (time_bp+1950) + terra::time(land_mask, tstep="") <- (time_bp+1950) return(land_mask) } diff --git a/inst/temp/a4_delta_downscale.Rmd b/inst/temp/a4_delta_downscale.Rmd index 7b53b300..c25c8200 100644 --- a/inst/temp/a4_delta_downscale.Rmd +++ b/inst/temp/a4_delta_downscale.Rmd @@ -49,7 +49,7 @@ model_rast ``` And we can now plot it: ```{r, fig.width=6, fig.height=5} -plot(model_rast) +plot(model_rast, main=time_bp(model_rast)) ``` We can see how that the reconstructions are rather coarse (the Example dataset @@ -97,7 +97,7 @@ for `make_land_mask` for details): ```{r, fig.width=6, fig.height=5} high_res_mask <- make_land_mask(topo_rast = topo_rast, time_bp = time_bp(model_rast)) -plot(high_res_mask) +plot(high_res_mask, main=time_bp(high_res_mask)) ``` We can now compute a delta raster and use it to downscale the model reconstructions: @@ -110,11 +110,11 @@ model_downscaled Let's inspect the resulting data: ```{r, fig.width=6, fig.height=5} -plot(model_downscaled) +plot(model_downscaled, main=time_bp(model_downscaled)) ``` And, as a reminder, the original reconstructions (note that the colour scales are not -the same! The interpolated data have a wider temperature range): +the same! `terra` chooses a scale for each time step based on the time specific range): ```{r, fig.width=6, fig.height=5} -plot(model_rast) +plot(model_rast, main=time_bp(model_rast)) ``` From 0f0f0ed2762d2eba76fc921e917a04346034a72e Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 17:25:39 +0000 Subject: [PATCH 16/22] clean up old file [skip ci] --- inst/temp/notes_on_saving_nc_files.R | 39 ---------------------------- 1 file changed, 39 deletions(-) delete mode 100644 inst/temp/notes_on_saving_nc_files.R diff --git a/inst/temp/notes_on_saving_nc_files.R b/inst/temp/notes_on_saving_nc_files.R deleted file mode 100644 index 67c848a3..00000000 --- a/inst/temp/notes_on_saving_nc_files.R +++ /dev/null @@ -1,39 +0,0 @@ -# testing times - -s <- rast(system.file("ex/logo.tif", package="terra")) - -# Date" -#d <- as.Date("2001-05-04") + 0:2 -d <- c(0,-1000,-2000) -d <- c(0, 1000, 2000) -time_bp(s) <- d - -time_bp(s) - -setwd(tempdir()) -rr <- writeCDF(s, "test.nc", overwrite=TRUE) -foo<-rast("test.nc", drivers="NETCDF") - -foo<-rast("test.nc", drivers="blah") - -nc_in <- ncdf4::nc_open("test.nc", write=TRUE) -ncdf4::ncatt_put(nc_in, varid="time", attname="axis", attval = "T") -ncdf4::ncatt_put(nc_in, varid="easting", attname="axis", attval = "X") -ncdf4::ncatt_put(nc_in, varid="northing", attname="axis", attval = "Y") -ncdf4::ncatt_put(nc_in, varid="time", attname="units", attval = "years since present") -ncdf4::nc_close(nc_in) - -## time not recognised unless it is both axis=T and a unit that is NOT unknown -## is that a terra problem, or a gdal? -foo<-rast("test.nc", drivers="NETCDF") - -# but years in terra does not allow for negative values - -rr <- writeCDF(f, "test2.nc", overwrite=TRUE, varname="alt", - longname="elevation in m above sea level", unit="m") - - -f <- system.file("ex/elev.tif", package="terra") -f <-rast(f) -writeCDF(f) -g <- rast("test2.nc") From 05928c854440fa910f742d2ce60ea6ec1df0f6c7 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 21:24:05 +0000 Subject: [PATCH 17/22] Allow to update list of files --- R/clean_data_path.R | 2 +- R/download_dataset.R | 4 +- R/get_available_datasets.R | 2 +- R/get_downloaded_datasets.R | 2 +- R/get_file_for_dataset.R | 4 +- R/get_vars_for_dataset.R | 8 +- R/load_dataset_list.R | 38 ++ R/set_data_path.R | 2 +- R/sysdata.rda | Bin 3046 -> 3074 bytes R/var_labels.R | 4 +- R/zzz.R | 3 +- .../create_dataset_list_included.R | 6 + .../rawdata_scripts/create_files_by_dataset.R | 6 - ...le_table.csv => dataset_list_included.csv} | 336 +++++++++--------- inst/rawdata_scripts/readme.md | 2 +- man/load_dataset_list.Rd | 24 ++ tests/testthat/test_check_dataset_path.R | 2 +- tests/testthat/test_download_dataset.R | 2 +- tests/testthat/test_get_mis_time_steps.R | 4 +- tests/testthat/test_get_time_steps.R | 2 +- tests/testthat/test_get_vars_for_dataset.R | 4 +- tests/testthat/test_load_dataset_list.R | 31 ++ tests/testthat/test_location_series.R | 4 +- tests/testthat/test_location_slice.R | 4 +- tests/testthat/test_region_series.R | 2 +- tests/testthat/test_region_slice.R | 2 +- vignettes/a2_custom_datasets.Rmd | 6 +- 27 files changed, 300 insertions(+), 206 deletions(-) create mode 100644 R/load_dataset_list.R create mode 100644 inst/rawdata_scripts/create_dataset_list_included.R delete mode 100644 inst/rawdata_scripts/create_files_by_dataset.R rename inst/rawdata_scripts/data_files/{variable_table.csv => dataset_list_included.csv} (85%) create mode 100644 man/load_dataset_list.Rd create mode 100644 tests/testthat/test_load_dataset_list.R diff --git a/R/clean_data_path.R b/R/clean_data_path.R index de2d54c7..4cdc67e9 100644 --- a/R/clean_data_path.R +++ b/R/clean_data_path.R @@ -14,7 +14,7 @@ clean_data_path <- function(ask=TRUE) { return(FALSE) } files_now <- list.files(get_data_path()) - possible_files <- unique(files_by_dataset$file_name) + possible_files <- unique(getOption("pastclim.dataset_list")$file_name) files_to_remove <- files_now[!files_now %in% possible_files] if (length(files_to_remove)>0){ if (ask){ diff --git a/R/download_dataset.R b/R/download_dataset.R index c6e149a5..bcb95890 100644 --- a/R/download_dataset.R +++ b/R/download_dataset.R @@ -16,7 +16,7 @@ download_dataset <- function(dataset, bio_variables = NULL) { # check the dataset exists - available_datasets <- unique(files_by_dataset$dataset) + available_datasets <- unique(getOption("pastclim.dataset_list")$dataset) if (!dataset %in% available_datasets) { stop( "'dataset' must be one of ", @@ -26,7 +26,7 @@ download_dataset <- function(dataset, bio_variables = NULL) { # check that the variable is available for this dataset available_variables <- - files_by_dataset$variable[files_by_dataset$dataset == dataset] + getOption("pastclim.dataset_list")$variable[getOption("pastclim.dataset_list")$dataset == dataset] # if variable is null, donwload all possible variables if (is.null(bio_variables)) { bio_variables <- available_variables diff --git a/R/get_available_datasets.R b/R/get_available_datasets.R index 7daf7660..2bd65b0e 100644 --- a/R/get_available_datasets.R +++ b/R/get_available_datasets.R @@ -7,5 +7,5 @@ #' @export get_available_datasets <- function() { - return(unique(as.character(files_by_dataset$dataset))) + return(unique(as.character(getOption("pastclim.dataset_list")$dataset))) } diff --git a/R/get_downloaded_datasets.R b/R/get_downloaded_datasets.R index aa788bda..dcd1c7e2 100644 --- a/R/get_downloaded_datasets.R +++ b/R/get_downloaded_datasets.R @@ -12,7 +12,7 @@ get_downloaded_datasets <- function(data_path = NULL) { data_path <- get_data_path() } all_nc_files <- list.files(data_path) - files_subset <- files_by_dataset[files_by_dataset$file_name %in% + files_subset <- getOption("pastclim.dataset_list")[getOption("pastclim.dataset_list")$file_name %in% all_nc_files, ] downloaded_vars <- list() for (dataset in unique(files_subset$dataset)) { diff --git a/R/get_file_for_dataset.R b/R/get_file_for_dataset.R index fc749b9a..dff4b1fc 100644 --- a/R/get_file_for_dataset.R +++ b/R/get_file_for_dataset.R @@ -9,6 +9,6 @@ get_file_for_dataset <- function(variable, dataset) { check_available_variable(variable, dataset) - return(files_by_dataset[files_by_dataset$variable %in% variable & - files_by_dataset$dataset == dataset, ]) + return(getOption("pastclim.dataset_list")[getOption("pastclim.dataset_list")$variable %in% variable & + getOption("pastclim.dataset_list")$dataset == dataset, ]) } diff --git a/R/get_vars_for_dataset.R b/R/get_vars_for_dataset.R index c2a84a8e..e10fe81f 100644 --- a/R/get_vars_for_dataset.R +++ b/R/get_vars_for_dataset.R @@ -21,9 +21,9 @@ get_vars_for_dataset <- function(dataset, path_to_nc = NULL, details=FALSE) { } check_available_dataset(dataset) if (!details){ - return(files_by_dataset$variable[files_by_dataset$dataset == dataset]) + return(getOption("pastclim.dataset_list")$variable[getOption("pastclim.dataset_list")$dataset == dataset]) } else { - return(files_by_dataset[files_by_dataset$dataset == dataset, + return(getOption("pastclim.dataset_list")[getOption("pastclim.dataset_list")$dataset == dataset, c("variable","long_name", "units")]) } } else { @@ -80,6 +80,6 @@ check_available_variable <- function(variable, dataset) { #' get_varname <- function(variable, dataset) { - return(files_by_dataset$ncvar[files_by_dataset$variable == variable & - files_by_dataset$dataset == dataset]) + return(getOption("pastclim.dataset_list")$ncvar[getOption("pastclim.dataset_list")$variable == variable & + getOption("pastclim.dataset_list")$dataset == dataset]) } diff --git a/R/load_dataset_list.R b/R/load_dataset_list.R new file mode 100644 index 00000000..3c17c04f --- /dev/null +++ b/R/load_dataset_list.R @@ -0,0 +1,38 @@ +#' Load the dataset list +#' +#' This function returns a dataframe with the details for each variable +#' available in every dataset. It defaults to the copy stored within the +#' package, but it checks in case there is an udpated version stored as +#' 'data_list.csv' in +#' `tools::R_user_dir("pastclim","config")`. If the latter is present, the last +#' column, named 'dataset_list_v', provides the version of this table, and the +#' most advanced table is used. +#' +#' @param on_cran boolean to make this function run on ci tests using tempdir +#' @returns the dataset list +#' @keywords internal + +load_dataset_list <- function(on_cran=FALSE) { + if (!on_cran){ + config_dir <- tools::R_user_dir("pastclim", "config") + } else { + config_dir <- tempdir() + } + if (file.exists(file.path( + config_dir, + "dataset_list_included.csv" + ))) { + table_in_config <- utils::read.csv(file.path( + config_dir, + "dataset_list_included.csv" + )) + table_in_config$dataset <- as.factor(table_in_config$dataset) + # we should check that the new table includes all the columns in the original file + if (utils::compareVersion(table_in_config$dataset_list_v[1], + dataset_list_included$dataset_list_v[1])==1){ + # need to update + return(table_in_config) + } + } + return(dataset_list_included) +} diff --git a/R/set_data_path.R b/R/set_data_path.R index 9f51e28f..5c4b0049 100644 --- a/R/set_data_path.R +++ b/R/set_data_path.R @@ -92,7 +92,7 @@ set_data_path <- function(path_to_nc = NULL, ask = TRUE, write_config = TRUE, #' @keywords internal copy_example_data <- function() { - example_filename <- unique(files_by_dataset$file_name[files_by_dataset$dataset == "Example"]) + example_filename <- unique(getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset == "Example"]) if (!file.exists(file.path(get_data_path(), example_filename))) { file.copy( from = system.file(file.path("/extdata",example_filename), diff --git a/R/sysdata.rda b/R/sysdata.rda index cc08c8c613b247cdb65194fdc25bc6172012dfd4..6c07e06b16d7fee238fe284abf688699d15aa5df 100644 GIT binary patch literal 3074 zcmZ|RS6CAW5(n@Q%94OeLg>9i6zK>nD1^{LLQ7Do(h`ak0TnSSNXMlKp+tH~Lsn5i zX;MQAy$L8qP^zmU0!tH)-P`-_*(|=|j=4}v8zWN%*j*3{vTJUoQz@YzV=;-M1 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function(x, dataset, with_units=TRUE, } # get variable details for this dataset - sub_table <- files_by_dataset[files_by_dataset$dataset==dataset,] + sub_table <- getOption("pastclim.dataset_list")[getOption("pastclim.dataset_list")$dataset==dataset,] indeces <- match(variables, sub_table$variable) if (any(is.na(indeces))){ @@ -69,4 +69,4 @@ var_labels <- function(x, dataset, with_units=TRUE, pretty_names <- c(pretty_names,this_name) } return(parse(text = pretty_names)) -} \ No newline at end of file +} diff --git a/R/zzz.R b/R/zzz.R index d353da82..ee3bd9c3 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -2,7 +2,8 @@ # store the data path as an option for easy retrieval op <- options() op.pastclim <- list( - pastclim.data_path = get_data_path(silent=TRUE) + pastclim.data_path = get_data_path(silent=TRUE), + pastclim.dataset_list = load_dataset_list() ) toset <- !(names(op.pastclim) %in% names(op)) if (any(toset)) options(op.pastclim[toset]) diff --git a/inst/rawdata_scripts/create_dataset_list_included.R b/inst/rawdata_scripts/create_dataset_list_included.R new file mode 100644 index 00000000..b7c97150 --- /dev/null +++ b/inst/rawdata_scripts/create_dataset_list_included.R @@ -0,0 +1,6 @@ +# Run this script from the package root to update the internal dataset +# of filenames for each variable, based on the dataset_list_included.csv +dataset_list_included <- + read.csv("./inst/rawdata_scripts/data_files/dataset_list_included.csv") +dataset_list_included$dataset <- as.factor(dataset_list_included$dataset) +usethis::use_data(dataset_list_included, internal = TRUE, overwrite = TRUE) diff --git a/inst/rawdata_scripts/create_files_by_dataset.R b/inst/rawdata_scripts/create_files_by_dataset.R deleted file mode 100644 index d8a294d4..00000000 --- a/inst/rawdata_scripts/create_files_by_dataset.R +++ /dev/null @@ -1,6 +0,0 @@ -# Run this script from the package root to update the internal dataset -# of filenames for each variable, based on the variable_table.csv -files_by_dataset <- - read.csv("./inst/rawdata_scripts/data_files/variable_table.csv") -files_by_dataset$dataset <- as.factor(files_by_dataset$dataset) -usethis::use_data(files_by_dataset, internal = TRUE, overwrite = TRUE) diff --git a/inst/rawdata_scripts/data_files/variable_table.csv b/inst/rawdata_scripts/data_files/dataset_list_included.csv similarity index 85% rename from inst/rawdata_scripts/data_files/variable_table.csv rename to inst/rawdata_scripts/data_files/dataset_list_included.csv index 194db58c..8fb0c014 100644 --- a/inst/rawdata_scripts/data_files/variable_table.csv +++ b/inst/rawdata_scripts/data_files/dataset_list_included.csv @@ -1,168 +1,168 @@ -variable,ncvar,dataset,monthly,file_name,download_path,file_name_orig,download_path_orig,version,long_name,abbreviated_name,time_frame,units,units_exp -bio01,BIO1,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio10,BIO10,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio12,BIO12,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -biome,biome,Example,FALSE,example_climate_v1.2.2.nc,,,,1.2.2,biome (from BIOME4),biome,year,, -bio01,bio01,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio04,bio04,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,temperature seasonality,T season.,year,degrees Celsius,*degree*C* -bio05,bio05,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,maximum temperature of warmest month,max. T of warmest mo.,year,degrees Celsius,*degree*C* -bio06,bio06,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,minimum temperature of coldest month,min. T of coldest mo.,year,degrees Celsius,*degree*C* -bio07,bio07,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,temperature annual range (bio05-bio06),T ann. Range,year,degrees Celsius,*degree*C* -bio08,bio08,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C* -bio09,bio09,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C* -bio10,bio10,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio11,bio11,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C* -bio12,bio12,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -bio13,bio13,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of wettest month,P of wettest mo.,year,mm per month,*mm~mo^-1* -bio14,bio14,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of driest month,P of driest mo.,year,mm per month,*mm~mo^-1* -bio15,bio15,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation seasonality (coeff var),P season.,year,, -bio16,bio16,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of wettest quarter,P of wettest qtr,year,mm per quarter,*mm~qtr^-1* -bio17,bio17,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of driest quarter,P of driest qtr,year,mm per quarter,*mm~qtr^-1* -bio18,bio18,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of warmest quarter,P of warmest qtr,year,mm per quarter,*mm~qtr^-1* -bio19,bio19,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation of coldest quarter,P of coldest qtr,year,mm per quarter,*mm~qtr^-1* -npp,npp,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity,NPP,year,gC per m^2 per year,*gC~m^-2~yr^-1* -lai,lai,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,leaf area index,LAI,year,gC per m^2,*gC~m^-2* -biome,biome,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,biome (from BIOME4),biome,year,, -altitude,altitude,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,,,1.2.2,altitude over the sea level,altitude,year,meters,*m* -rugosity,rugosity,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,,,1.2.2,rugosity (st. dev. altitude at 1 min),rugosity,year,, -temperature_01,temperature_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Jan,mean T Jan,january,degrees Celsius,*degree*C* -temperature_02,temperature_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Feb,mean T Feb,february,degrees Celsius,*degree*C* -temperature_03,temperature_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Mar,mean T Mar,march,degrees Celsius,*degree*C* -temperature_04,temperature_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Apr,mean T Apr,april,degrees Celsius,*degree*C* -temperature_05,temperature_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature May,mean T May,may,degrees Celsius,*degree*C* -temperature_06,temperature_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Jun,mean T Jun,june,degrees Celsius,*degree*C* -temperature_07,temperature_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Jul,mean T Jul,july,degrees Celsius,*degree*C* -temperature_08,temperature_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Aug,mean T Aug,august,degrees Celsius,*degree*C* -temperature_09,temperature_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Sep,mean T Sep,september,degrees Celsius,*degree*C* -temperature_10,temperature_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Oct,mean T Oct,october,degrees Celsius,*degree*C* -temperature_11,temperature_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Nov,mean T Nov,november,degrees Celsius,*degree*C* -temperature_12,temperature_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature Dec,mean T Dec,december,degrees Celsius,*degree*C* -precipitation_01,precipitation_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Jan,P Jan,january,mm per month,*mm~mo^-1* -precipitation_02,precipitation_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Feb,P Feb,february,mm per month,*mm~mo^-1* -precipitation_03,precipitation_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Mar,P Mar,march,mm per month,*mm~mo^-1* -precipitation_04,precipitation_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Apr,P Apr,april,mm per month,*mm~mo^-1* -precipitation_05,precipitation_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation May,P May,may,mm per month,*mm~mo^-1* -precipitation_06,precipitation_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Jun,P Jun,june,mm per month,*mm~mo^-1* -precipitation_07,precipitation_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Jul,P Jul,july,mm per month,*mm~mo^-1* -precipitation_08,precipitation_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Aug,P Aug,august,mm per month,*mm~mo^-1* -precipitation_09,precipitation_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Sep,P Sep,september,mm per month,*mm~mo^-1* -precipitation_10,precipitation_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Oct,P Oct,october,mm per month,*mm~mo^-1* -precipitation_11,precipitation_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Nov,P Nov,november,mm per month,*mm~mo^-1* -precipitation_12,precipitation_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1* -cloudiness_01,cloudiness_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Jan,cloudiness Jan,january,%,*'%'* -cloudiness_02,cloudiness_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Feb,cloudiness Feb,february,%,*'%'* -cloudiness_03,cloudiness_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Mar,cloudiness Mar,march,%,*'%'* -cloudiness_04,cloudiness_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Apr,cloudiness Apr,april,%,*'%'* -cloudiness_05,cloudiness_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness May,cloudiness May,may,%,*'%'* -cloudiness_06,cloudiness_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Jun,cloudiness Jun,june,%,*'%'* -cloudiness_07,cloudiness_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Jul,cloudiness Jul,july,%,*'%'* -cloudiness_08,cloudiness_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Aug,cloudiness Aug,august,%,*'%'* -cloudiness_09,cloudiness_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Sep,cloudiness Sep,september,%,*'%'* -cloudiness_10,cloudiness_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Oct,cloudiness Oct,october,%,*'%'* -cloudiness_11,cloudiness_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Nov,cloudiness Nov,november,%,*'%'* -cloudiness_12,cloudiness_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,cloudiness Dec,cloudiness Dec,december,%,*'%'* -relative_humidity_01,relative_humidity_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Jan,RH Jan,january,%,*'%'* -relative_humidity_02,relative_humidity_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Feb,RH Feb,february,%,*'%'* -relative_humidity_03,relative_humidity_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Mar,RH Mar,march,%,*'%'* -relative_humidity_04,relative_humidity_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Apr,RH Apr,april,%,*'%'* -relative_humidity_05,relative_humidity_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity May,RH May,may,%,*'%'* -relative_humidity_06,relative_humidity_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Jun,RH Jun,june,%,*'%'* -relative_humidity_07,relative_humidity_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Jul,RH Jul,july,%,*'%'* -relative_humidity_08,relative_humidity_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Aug,RH Aug,august,%,*'%'* -relative_humidity_09,relative_humidity_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Sep,RH Sep,september,%,*'%'* -relative_humidity_10,relative_humidity_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Oct,RH Oct,october,%,*'%'* -relative_humidity_11,relative_humidity_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Nov,RH Nov,november,%,*'%'* -relative_humidity_12,relative_humidity_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,relative humidity Dec,RH Dec,december,%,*'%'* -wind_speed_01,wind_speed_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Jan,WS Jan,january,m per second,*m~s^-1* -wind_speed_02,wind_speed_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Feb,WS Feb,february,m per second,*m~s^-1* -wind_speed_03,wind_speed_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Mar,WS Mar,march,m per second,*m~s^-1* -wind_speed_04,wind_speed_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Apr,WS Apr,april,m per second,*m~s^-1* -wind_speed_05,wind_speed_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed May,WS May,may,m per second,*m~s^-1* -wind_speed_06,wind_speed_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Jun,WS Jun,june,m per second,*m~s^-1* -wind_speed_07,wind_speed_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Jul,WS Jul,july,m per second,*m~s^-1* -wind_speed_08,wind_speed_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Aug,WS Aug,august,m per second,*m~s^-1* -wind_speed_09,wind_speed_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Sep,WS Sep,september,m per second,*m~s^-1* -wind_speed_10,wind_speed_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Oct,WS Oct,october,m per second,*m~s^-1* -wind_speed_11,wind_speed_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Nov,WS Nov,november,m per second,*m~s^-1* -wind_speed_12,wind_speed_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,wind speed Dec,WS Dec,december,m per second,*m~s^-1* -mo_npp_01,mo_npp_01,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_02,mo_npp_02,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_03,mo_npp_03,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_04,mo_npp_04,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_05,mo_npp_05,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_06,mo_npp_06,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_07,mo_npp_07,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_08,mo_npp_08,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_09,mo_npp_09,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_10,mo_npp_10,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_11,mo_npp_11,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_12,mo_npp_12,Beyer2020,TRUE,Beyer2020_monthly_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_monthly_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1* -bio01,bio01,Krapp2021,FALSE,Krapp2021_bio01_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio01_v1.2.2.nc?download=1,bio01_800ka.nc,https://osf.io/a39gh/?action=download,1.2.2,annual mean temperature,ann. mean T,year,degrees Celsius,*degree*C* -bio04,bio04,Krapp2021,FALSE,Krapp2021_bio04_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio04_v1.2.2.nc?download=1,bio04_800ka.nc,https://osf.io/p82ue/?action=download,1.2.2,temperature seasonality,T season.,year,degrees Celsius,*degree*C* -bio05,bio05,Krapp2021,FALSE,Krapp2021_bio05_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio05_v1.2.2.nc?download=1,bio05_800ka.nc,https://osf.io/emhp9/?action=download,1.2.2,maximum temperature of warmest month,maximum T of warmest mo.,year,degrees Celsius,*degree*C* -bio06,bio06,Krapp2021,FALSE,Krapp2021_bio06_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio06_v1.2.2.nc?download=1,bio06_800ka.nc,https://osf.io/cm923/?action=download,1.2.2,minimum temperature of coldest month,minimum T of coldest mo.,year,degrees Celsius,*degree*C* -bio07,bio07,Krapp2021,FALSE,Krapp2021_bio07_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio07_v1.2.2.nc?download=1,bio07_800ka.nc,https://osf.io/prq8n/?action=download,1.2.2,temperature annual range (bio05-bio06),T ann. range (bio05-bio06),year,degrees Celsius,*degree*C* -bio08,bio08,Krapp2021,FALSE,Krapp2021_bio08_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio08_v1.2.2.nc?download=1,bio08_800ka.nc,https://osf.io/7jsa8/?action=download,1.2.2,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C* -bio09,bio09,Krapp2021,FALSE,Krapp2021_bio09_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio09_v1.2.2.nc?download=1,bio09_800ka.nc,https://osf.io/zaxku/?action=download,1.2.2,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C* -bio10,bio10,Krapp2021,FALSE,Krapp2021_bio10_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio10_v1.2.2.nc?download=1,bio10_800ka.nc,https://osf.io/b3kx8/?action=download,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C* -bio11,bio11,Krapp2021,FALSE,Krapp2021_bio11_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio11_v1.2.2.nc?download=1,bio11_800ka.nc,https://osf.io/vaune/?action=download,1.2.2,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C* -bio12,bio12,Krapp2021,FALSE,Krapp2021_bio12_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio12_v1.2.2.nc?download=1,bio12_800ka.nc,https://osf.io/kg9v6/?action=download,1.2.2,annual precipitation,ann. P,year,mm per year,*mm~yr^-1* -bio13,bio13,Krapp2021,FALSE,Krapp2021_bio13_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio13_v1.2.2.nc?download=1,bio13_800ka.nc,https://osf.io/2u5c6/?action=download,1.2.2,precipitation of wettest month,P of wettest mo.,year,mm per month,*mm~mo^-1* -bio14,bio14,Krapp2021,FALSE,Krapp2021_bio14_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio14_v1.2.2.nc?download=1,bio14_800ka.nc,https://osf.io/z2ewu/?action=download,1.2.2,precipitation of driest month,P of driest mo.,year,mm per month,*mm~mo^-1* -bio15,bio15,Krapp2021,FALSE,Krapp2021_bio15_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio15_v1.2.2.nc?download=1,bio15_800ka.nc,https://osf.io/z52xr/?action=download,1.2.2,precipitation seasonality (coefficient of variation),P season. (coefficient of variation),year,, -bio16,bio16,Krapp2021,FALSE,Krapp2021_bio16_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio16_v1.2.2.nc?download=1,bio16_800ka.nc,https://osf.io/kn8ma/?action=download,1.2.2,precipitation of wettest quarter,P of wettest qtr,year,mm per quarter,*mm~qtr^-1* -bio17,bio17,Krapp2021,FALSE,Krapp2021_bio17_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio17_v1.2.2.nc?download=1,bio17_800ka.nc,https://osf.io/2z8ej/?action=download,1.2.2,precipitation of driest quarter,P of driest qtr,year,mm per quarter,*mm~qtr^-1* -bio18,bio18,Krapp2021,FALSE,Krapp2021_bio18_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio18_v1.2.2.nc?download=1,bio18_800ka.nc,https://osf.io/a2uhm/?action=download,1.2.2,precipitation of warmest quarter,P of warmest qtr,year,mm per quarter,*mm~qtr^-1* -bio19,bio19,Krapp2021,FALSE,Krapp2021_bio19_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_bio19_v1.2.2.nc?download=1,bio19_800ka.nc,https://osf.io/3mbd9/?action=download,1.2.2,precipitation of coldest quarter,P of coldest qtr,year,mm per quarter,*mm~qtr^-1* -npp,npp,Krapp2021,FALSE,Krapp2021_npp_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_v1.2.2.nc?download=1,biome4output_800ka.nc,https://osf.io/cf5zp/?action=download,1.2.2,net primary productivity,NPP,year,gC per m^2 per year,*gC~m^-2~yr^-1* -biome,biome,Krapp2021,FALSE,Krapp2021_biome_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_biome_v1.2.2.nc?download=1,biome4output_800ka.nc,https://osf.io/cf5zp/?action=download,1.2.2,biome (from BIOME4),biome (from BIOME4),year,, -altitude,altitude,Krapp2021,FALSE,Krapp2021_topography_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_topography_v1.2.2.nc?download=1,,,1.2.2,altitude over the sea level,altitude over the sea level,year,m,*m* -rugosity,rugosity,Krapp2021,FALSE,Krapp2021_topography_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_topography_v1.2.2.nc?download=1,,,1.2.2,rugosity,rugosity,year,, -temperature_01,temp_01,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Jan,mean T Jan,january,degrees Celsius,*degree*C* -temperature_02,temp_02,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Feb,mean T Feb,february,degrees Celsius,*degree*C* -temperature_03,temp_03,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Mar,mean T Mar,march,degrees Celsius,*degree*C* -temperature_04,temp_04,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Apr,mean T Apr,april,degrees Celsius,*degree*C* -temperature_05,temp_05,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature May,mean T May,may,degrees Celsius,*degree*C* -temperature_06,temp_06,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Jun,mean T Jun,june,degrees Celsius,*degree*C* -temperature_07,temp_07,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Jul,mean T Jul,july,degrees Celsius,*degree*C* -temperature_08,temp_08,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Aug,mean T Aug,august,degrees Celsius,*degree*C* -temperature_09,temp_09,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Sep,mean T Sep,september,degrees Celsius,*degree*C* -temperature_10,temp_10,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Oct,mean T Oct,october,degrees Celsius,*degree*C* -temperature_11,temp_11,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Nov,mean T Nov,november,degrees Celsius,*degree*C* -temperature_12,temp_12,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Dec,mean T Dec,december,degrees Celsius,*degree*C* -precipitation_01,prec_01,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jan,P Jan,january,mm per month,*mm~mo^-1* -precipitation_02,prec_02,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Feb,P Feb,february,mm per month,*mm~mo^-1* -precipitation_03,prec_03,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Mar,P Mar,march,mm per month,*mm~mo^-1* -precipitation_04,prec_04,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Apr,P Apr,april,mm per month,*mm~mo^-1* -precipitation_05,prec_05,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation May,P May,may,mm per month,*mm~mo^-1* -precipitation_06,prec_06,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jun,P Jun,june,mm per month,*mm~mo^-1* -precipitation_07,prec_07,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jul,P Jul,july,mm per month,*mm~mo^-1* -precipitation_08,prec_08,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Aug,P Aug,august,mm per month,*mm~mo^-1* -precipitation_09,prec_09,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Sep,P Sep,september,mm per month,*mm~mo^-1* -precipitation_10,prec_10,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Oct,P Oct,october,mm per month,*mm~mo^-1* -precipitation_11,prec_11,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Nov,P Nov,november,mm per month,*mm~mo^-1* -precipitation_12,prec_12,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1* -mo_npp_01,mo_npp_01,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_02,mo_npp_02,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_03,mo_npp_03,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_04,mo_npp_04,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_05,mo_npp_05,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_06,mo_npp_06,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_07,mo_npp_07,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_08,mo_npp_08,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_09,mo_npp_09,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_10,mo_npp_10,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_11,mo_npp_11,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1* -mo_npp_12,mo_npp_12,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1* -cloudiness_01,tcc_01,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jan,cloudiness Jan,january,%,*'%'* -cloudiness_02,tcc_02,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Feb,cloudiness Feb,february,%,*'%'* -cloudiness_03,tcc_03,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Mar,cloudiness Mar,march,%,*'%'* -cloudiness_04,tcc_04,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Apr,cloudiness Apr,april,%,*'%'* -cloudiness_05,tcc_05,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness May,cloudiness May,may,%,*'%'* -cloudiness_06,tcc_06,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jun,cloudiness Jun,june,%,*'%'* -cloudiness_07,tcc_07,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jul,cloudiness Jul,july,%,*'%'* -cloudiness_08,tcc_08,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Aug,cloudiness Aug,august,%,*'%'* -cloudiness_09,tcc_09,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Sep,cloudiness Sep,september,%,*'%'* -cloudiness_10,tcc_10,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Oct,cloudiness Oct,october,%,*'%'* -cloudiness_11,tcc_11,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Nov,cloudiness Nov,november,%,*'%'* -cloudiness_12,tcc_12,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Dec,cloudiness Dec,december,%,*'%'* 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T of warmest mo.,year,degrees Celsius,*degree*C*, +bio06,bio06,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,minimum temperature of coldest month,min. T of coldest mo.,year,degrees Celsius,*degree*C*, +bio07,bio07,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,temperature annual range (bio05-bio06),T ann. Range,year,degrees Celsius,*degree*C*, +bio08,bio08,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of wettest quarter,mean T of wettest qtr,year,degrees Celsius,*degree*C*, +bio09,bio09,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of driest quarter,mean T of driest qtr,year,degrees Celsius,*degree*C*, +bio10,bio10,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of warmest quarter,mean T of warmest qtr,year,degrees Celsius,*degree*C*, +bio11,bio11,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,mean temperature of coldest quarter,mean T of coldest qtr,year,degrees Celsius,*degree*C*, +bio12,bio12,Beyer2020,FALSE,Beyer2020_annual_vars_v1.2.2.nc,https://zenodo.org/record/7388091/files/Beyer2020_annual_vars_v1.2.2.nc?download=1,LateQuaternary_Environment.nc,https://ndownloader.figshare.com/files/22659026,1.2.2,annual precipitation,ann. 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+temperature_12,temp_12,Krapp2021,TRUE,Krapp2021_temp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_temp_monthly_v1.2.2.nc?download=1,,,1.2.2,mean temperature Dec,mean T Dec,december,degrees Celsius,*degree*C*, +precipitation_01,prec_01,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jan,P Jan,january,mm per month,*mm~mo^-1*, +precipitation_02,prec_02,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Feb,P Feb,february,mm per month,*mm~mo^-1*, +precipitation_03,prec_03,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Mar,P Mar,march,mm per month,*mm~mo^-1*, +precipitation_04,prec_04,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Apr,P Apr,april,mm per month,*mm~mo^-1*, +precipitation_05,prec_05,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation May,P May,may,mm per month,*mm~mo^-1*, +precipitation_06,prec_06,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jun,P Jun,june,mm per month,*mm~mo^-1*, +precipitation_07,prec_07,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Jul,P Jul,july,mm per month,*mm~mo^-1*, +precipitation_08,prec_08,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Aug,P Aug,august,mm per month,*mm~mo^-1*, +precipitation_09,prec_09,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Sep,P Sep,september,mm per month,*mm~mo^-1*, +precipitation_10,prec_10,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Oct,P Oct,october,mm per month,*mm~mo^-1*, +precipitation_11,prec_11,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Nov,P Nov,november,mm per month,*mm~mo^-1*, +precipitation_12,prec_12,Krapp2021,TRUE,Krapp2021_prec_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_prec_monthly_v1.2.2.nc?download=1,,,1.2.2,precipitation Dec,P Dec,december,mm per month,*mm~mo^-1*, +mo_npp_01,mo_npp_01,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jan,NPP Jan,january,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_02,mo_npp_02,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Feb,NPP Feb,february,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_03,mo_npp_03,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Mar,NPP Mar,march,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_04,mo_npp_04,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Apr,NPP Apr,april,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_05,mo_npp_05,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity May,NPP May,may,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_06,mo_npp_06,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jun,NPP Jun,june,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_07,mo_npp_07,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Jul,NPP Jul,july,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_08,mo_npp_08,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Aug,NPP Aug,august,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_09,mo_npp_09,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Sep,NPP Sep,september,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_10,mo_npp_10,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Oct,NPP Oct,october,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_11,mo_npp_11,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Nov,NPP Nov,november,gC per m^2 per month,*gC~m^-2~mo^-1*, +mo_npp_12,mo_npp_12,Krapp2021,TRUE,Krapp2021_npp_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_npp_monthly_v1.2.2.nc?download=1,,,1.2.2,net primary productivity Dec,NPP Dec,december,gC per m^2 per month,*gC~m^-2~mo^-1*, +cloudiness_01,tcc_01,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jan,cloudiness Jan,january,%,*'%'*, +cloudiness_02,tcc_02,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Feb,cloudiness Feb,february,%,*'%'*, +cloudiness_03,tcc_03,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Mar,cloudiness Mar,march,%,*'%'*, +cloudiness_04,tcc_04,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Apr,cloudiness Apr,april,%,*'%'*, +cloudiness_05,tcc_05,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness May,cloudiness May,may,%,*'%'*, +cloudiness_06,tcc_06,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jun,cloudiness Jun,june,%,*'%'*, +cloudiness_07,tcc_07,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Jul,cloudiness Jul,july,%,*'%'*, +cloudiness_08,tcc_08,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Aug,cloudiness Aug,august,%,*'%'*, +cloudiness_09,tcc_09,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Sep,cloudiness Sep,september,%,*'%'*, +cloudiness_10,tcc_10,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Oct,cloudiness Oct,october,%,*'%'*, +cloudiness_11,tcc_11,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Nov,cloudiness Nov,november,%,*'%'*, +cloudiness_12,tcc_12,Krapp2021,TRUE,Krapp2021_tcc_monthly_v1.2.2.nc,https://zenodo.org/record/7388149/files/Krapp2021_tcc_monthly_v1.2.2.nc?download=1,,,1.2.2,cloudiness Dec,cloudiness Dec,december,%,*'%'*, diff --git a/inst/rawdata_scripts/readme.md b/inst/rawdata_scripts/readme.md index d02f4bad..d8695532 100644 --- a/inst/rawdata_scripts/readme.md +++ b/inst/rawdata_scripts/readme.md @@ -22,7 +22,7 @@ variables into two separate files. ## scripts to create internal variables for pastclim -1. `create_files_by_dataset.R` is a script to update the internal dataframe which stores the link between variable names and file names and locations. It is based on `variable_table.csv`. +1. `create_getOption("pastclim.dataset_list").R` is a script to update the internal dataframe which stores the link between variable names and file names and locations. It is based on `variable_table.csv`. 2. `creat_mis_boundaries.R` create internal dataset of mis boundaries. diff --git a/man/load_dataset_list.Rd b/man/load_dataset_list.Rd new file mode 100644 index 00000000..3c9a69cd --- /dev/null +++ b/man/load_dataset_list.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/load_dataset_list.R +\name{load_dataset_list} +\alias{load_dataset_list} +\title{Load the dataset list} +\usage{ +load_dataset_list(on_cran = FALSE) +} +\arguments{ +\item{on_cran}{boolean to make this function run on ci tests using tempdir} +} +\value{ +the dataset list +} +\description{ +This function returns a dataframe with the details for each variable +available in every dataset. It defaults to the copy stored within the +package, but it checks in case there is an udpated version stored as +'data_list.csv' in +`tools::R_user_dir("pastclim","config")`. If the latter is present, the last +column, named 'dataset_list_v', provides the version of this table, and the +most advanced table is used. +} +\keyword{internal} diff --git a/tests/testthat/test_check_dataset_path.R b/tests/testthat/test_check_dataset_path.R index 65c38fe2..e308a10e 100644 --- a/tests/testthat/test_check_dataset_path.R +++ b/tests/testthat/test_check_dataset_path.R @@ -18,7 +18,7 @@ test_that("check_dataset_path errors", { check_dataset_path("custom", NULL), "you need to set path_to_nc if dataset='custom'" ) - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] expect_true(check_dataset_path( "custom", file.path( diff --git a/tests/testthat/test_download_dataset.R b/tests/testthat/test_download_dataset.R index ad7fed55..6646ffb2 100644 --- a/tests/testthat/test_download_dataset.R +++ b/tests/testthat/test_download_dataset.R @@ -20,7 +20,7 @@ test_that("download_dataset", { "^foo not available " ) # check that only the example climate is in the data directory - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] expect_true(example_filename %in% list.files(get_data_path())) # expect no error as the dataset exists expect_error(download_dataset("Example"), NA) diff --git a/tests/testthat/test_get_mis_time_steps.R b/tests/testthat/test_get_mis_time_steps.R index 95f8a648..3f219dd3 100644 --- a/tests/testthat/test_get_mis_time_steps.R +++ b/tests/testthat/test_get_mis_time_steps.R @@ -16,7 +16,7 @@ test_that("get_mis_time_steps for standard dataset", { }) test_that("get_mis_time_steps for local file", { - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) @@ -41,4 +41,4 @@ test_that("get_mis_time_steps requires correct variables", { ################################################################################ # clean up for the next test -unlink(data_path, recursive = TRUE) \ No newline at end of file +unlink(data_path, recursive = TRUE) diff --git a/tests/testthat/test_get_time_steps.R b/tests/testthat/test_get_time_steps.R index 13d63d56..d9c18d14 100644 --- a/tests/testthat/test_get_time_steps.R +++ b/tests/testthat/test_get_time_steps.R @@ -27,7 +27,7 @@ test_that("get_time_steps for standard dataset", { }) test_that("get_time_steps for local file", { - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) diff --git a/tests/testthat/test_get_vars_for_dataset.R b/tests/testthat/test_get_vars_for_dataset.R index 7213da84..11638447 100644 --- a/tests/testthat/test_get_vars_for_dataset.R +++ b/tests/testthat/test_get_vars_for_dataset.R @@ -33,7 +33,7 @@ test_that("get_vars_for_dataset returns appropriate object", { test_that("get_vars_for_dataset for local file", { - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) @@ -46,4 +46,4 @@ test_that("get_vars_for_dataset for local file", { ################################################################################ # clean up for the next test -unlink(data_path, recursive = TRUE) \ No newline at end of file +unlink(data_path, recursive = TRUE) diff --git a/tests/testthat/test_load_dataset_list.R b/tests/testthat/test_load_dataset_list.R new file mode 100644 index 00000000..b8d88bef --- /dev/null +++ b/tests/testthat/test_load_dataset_list.R @@ -0,0 +1,31 @@ +# set up data path for this test +data_path <- file.path(tempdir(),"pastclim_data") +unlink(data_path, recursive = TRUE) # it should not exist, but remove it just in case +# set data path +set_data_path(path_to_nc = data_path, + ask = FALSE, + write_config = FALSE, + copy_example = TRUE) +################################################################################ + +test_that("load_dataset_list", { + # check that the version returned by load_dataset is the default on + expect_identical(load_dataset_list(on_cran=TRUE)$dataset_list_v[1], + utils::read.csv(system.file("rawdata_scripts/data_files/dataset_list_included.csv", + package="pastclim"))$dataset_list_v[1]) + # now create a file in the tempdir + new_table <- utils::read.csv(system.file("rawdata_scripts/data_files/dataset_list_included.csv", + package="pastclim")) + # now update to the version + new_table$dataset_list_v[1]<-"99.0.0" + + write.csv(new_table, + file.path(tempdir(),"dataset_list_included.csv"),row.names = FALSE) + # now check the version + expect_true(load_dataset_list(on_cran=TRUE)$dataset_list_v[1]=="99.0.0") +}) + +################################################################################ +# clean up for the next test +unlink(data_path, recursive = TRUE) + diff --git a/tests/testthat/test_location_series.R b/tests/testthat/test_location_series.R index 1b8bcbf1..17d1dd62 100644 --- a/tests/testthat/test_location_series.R +++ b/tests/testthat/test_location_series.R @@ -92,7 +92,7 @@ test_that("time_series_for_location", { # now use a custom dataset - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) @@ -124,4 +124,4 @@ test_that("time_series_for_location", { ################################################################################ # clean up for the next test -unlink(data_path, recursive = TRUE) \ No newline at end of file +unlink(data_path, recursive = TRUE) diff --git a/tests/testthat/test_location_slice.R b/tests/testthat/test_location_slice.R index 6ef3a309..a5a62527 100644 --- a/tests/testthat/test_location_slice.R +++ b/tests/testthat/test_location_slice.R @@ -91,7 +91,7 @@ test_that("location_slice", { ) # now test a custom dataset - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) @@ -144,4 +144,4 @@ test_that("location_slice", { ################################################################################ # clean up for the next test -unlink(data_path, recursive = TRUE) \ No newline at end of file +unlink(data_path, recursive = TRUE) diff --git a/tests/testthat/test_region_series.R b/tests/testthat/test_region_series.R index a4782b05..192b3dda 100644 --- a/tests/testthat/test_region_series.R +++ b/tests/testthat/test_region_series.R @@ -19,7 +19,7 @@ test_that("region series", { expect_true(all(terra::nlyr(climate_region) == c(2, 2))) # do the same for a custom dataset - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) diff --git a/tests/testthat/test_region_slice.R b/tests/testthat/test_region_slice.R index e8731a06..0c187069 100644 --- a/tests/testthat/test_region_slice.R +++ b/tests/testthat/test_region_slice.R @@ -19,7 +19,7 @@ test_that("region slice", { expect_true(terra::nlyr(climate_slice) == c(2)) # do the same for a custom dataset - example_filename <- files_by_dataset$file_name[files_by_dataset$dataset=="Example"][1] + example_filename <- getOption("pastclim.dataset_list")$file_name[getOption("pastclim.dataset_list")$dataset=="Example"][1] path_to_example_nc <- system.file("/extdata/", example_filename, package = "pastclim" ) diff --git a/vignettes/a2_custom_datasets.Rmd b/vignettes/a2_custom_datasets.Rmd index a643e882..30d531b9 100644 --- a/vignettes/a2_custom_datasets.Rmd +++ b/vignettes/a2_custom_datasets.Rmd @@ -118,7 +118,7 @@ store information about available datasets. This table is found in "./inst/rawdata_scripts/data_files/variable_table.csv". ```{r} -head(read.csv(system.file("rawdata_scripts/data_files/variable_table.csv", +head(read.csv(system.file("rawdata_scripts/data_files/dataset_list_included.csv", package="pastclim")), n=2) ``` @@ -154,9 +154,9 @@ the *nc* dataset. `units_exp`: units formatted to be included in `expression` when creating plot labels -3) Once you have added lines detailing the variables in your dataset, run the script "./inst/rawdata_scripts/create_files_by_dataset.R" to store +3) Once you have added lines detailing the variables in your dataset, run the script "./inst/rawdata_scripts/create_getOption("pastclim.dataset_list").R" to store that information into the appropriate dataset in `pastclim`. 4) Provide information on the new dataset in the file "./R/dataset_docs", using `roxygen2` syntax. Make sure that you provide an appropriate reference for the original data, as it is important that users can refer back to the original source. -4) Make a Pull Request on GitHub. \ No newline at end of file +4) Make a Pull Request on GitHub. From 534766fbfaaa1b6945e3ed7bd7db969219dc52ce Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 21:25:19 +0000 Subject: [PATCH 18/22] Update version number --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 2062b6c4..02253597 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: pastclim Type: Package Title: Manipulate Time Series of Palaeoclimate Reconstructions -Version: 1.2.1 +Version: 1.2.1.9000 Authors@R: c( person("Michela", "Leonardi", role = "aut"), person(c("Emily","Y."), "Hallet", role = "ctb"), From 09e9887b22a8ecaf71e35044215e1d7deb6b3715 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 21:35:46 +0000 Subject: [PATCH 19/22] Start implementing update dataset list --- R/update_dataset_list.R | 40 ++++++++++++++++++++++++++++++++++++++ man/update_dataset_list.Rd | 23 ++++++++++++++++++++++ 2 files changed, 63 insertions(+) create mode 100644 R/update_dataset_list.R create mode 100644 man/update_dataset_list.Rd diff --git a/R/update_dataset_list.R b/R/update_dataset_list.R new file mode 100644 index 00000000..ad65b6ab --- /dev/null +++ b/R/update_dataset_list.R @@ -0,0 +1,40 @@ +#' Update the dataset list +#' +#' If a newer dataset list (which includes all the information about the files +#' storing the data for pastclim), download it and start using it as +#' 'dataset_list_included.csv' in +#' `tools::R_user_dir("pastclim","config")`. If the latter is present, the last +#' column, named 'dataset_list_v', provides the version of this table, and the +#' most advanced table is used. +#' +#' @param on_cran boolean to make this function run on ci tests using tempdir +#' @returns the dataset list +#' @keywords internal + +update_dataset_list <- function(on_cran=FALSE) { + warning("this function is incomplete and non-functional yet") + if (!on_cran){ + config_dir <- tools::R_user_dir("pastclim", "config") + } else { + config_dir <- tempdir() + } + # this is incomplete + + if (file.exists(file.path( + config_dir, + "dataset_list_included.csv" + ))) { + table_in_config <- utils::read.csv(file.path( + config_dir, + "dataset_list_included.csv" + )) + table_in_config$dataset <- as.factor(table_in_config$dataset) + # we should check that the new table includes all the columns in the original file + if (utils::compareVersion(table_in_config$dataset_list_v[1], + dataset_list_included$dataset_list_v[1])==1){ + # need to update + return(table_in_config) + } + } + return(dataset_list_included) +} diff --git a/man/update_dataset_list.Rd b/man/update_dataset_list.Rd new file mode 100644 index 00000000..b816f9fb --- /dev/null +++ b/man/update_dataset_list.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/update_dataset_list.R +\name{update_dataset_list} +\alias{update_dataset_list} +\title{Update the dataset list} +\usage{ +update_dataset_list(on_cran = FALSE) +} +\arguments{ +\item{on_cran}{boolean to make this function run on ci tests using tempdir} +} +\value{ +the dataset list +} +\description{ +If a newer dataset list (which includes all the information about the files +storing the data for pastclim), download it and start using it as +'dataset_list_included.csv' in +`tools::R_user_dir("pastclim","config")`. If the latter is present, the last +column, named 'dataset_list_v', provides the version of this table, and the +most advanced table is used. +} +\keyword{internal} From b4fc185fd99454c98c7b310a7acf43cbe8681326 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 21:52:59 +0000 Subject: [PATCH 20/22] add ability to update the datasets --- NAMESPACE | 1 + R/update_dataset_list.R | 40 +++++++++++++++----------------------- man/update_dataset_list.Rd | 3 +-- 3 files changed, 18 insertions(+), 26 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index e4f3e447..c3f7feeb 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -28,5 +28,6 @@ export(set_data_path_for_CRAN) export(slice_region_series) export(time_bp) export(time_series_for_locations) +export(update_dataset_list) export(var_labels) import(terra) diff --git a/R/update_dataset_list.R b/R/update_dataset_list.R index ad65b6ab..b5010d5b 100644 --- a/R/update_dataset_list.R +++ b/R/update_dataset_list.R @@ -8,33 +8,25 @@ #' most advanced table is used. #' #' @param on_cran boolean to make this function run on ci tests using tempdir -#' @returns the dataset list -#' @keywords internal +#' @returns TRUE if the dataset was updated +#' @export update_dataset_list <- function(on_cran=FALSE) { - warning("this function is incomplete and non-functional yet") - if (!on_cran){ - config_dir <- tools::R_user_dir("pastclim", "config") + curl::curl_download("https://raw.githubusercontent.com/EvolEcolGroup/pastclim/dataset_list/dataset_list_included.csv", + destfile = file.path(tempdir(), "dataset_list_included.csv"), + quiet = FALSE) + new_table_github <- utils::read.csv(file.path(tempdir(), "dataset_list_included.csv")) + # if the github version is more recent, copy it into config + if (utils::compareVersion(new_table_github$dataset_list_v[1], + getOption("pastclim.dataset_list")$dataset_list_v[1])==1){ + file.copy(utils::read.csv(file.path(tempdir(), "dataset_list_included.csv")), + to= file.path(tools::R_user_dir("pastclim", "config"),"dataset_list_included.csv")) + load_dataset_list() + message("The dataset list was updated.") + return(TRUE) } else { - config_dir <- tempdir() + message("The dataset list currently installed is already the latest version.") + return(FALSE) } - # this is incomplete - if (file.exists(file.path( - config_dir, - "dataset_list_included.csv" - ))) { - table_in_config <- utils::read.csv(file.path( - config_dir, - "dataset_list_included.csv" - )) - table_in_config$dataset <- as.factor(table_in_config$dataset) - # we should check that the new table includes all the columns in the original file - if (utils::compareVersion(table_in_config$dataset_list_v[1], - dataset_list_included$dataset_list_v[1])==1){ - # need to update - return(table_in_config) - } - } - return(dataset_list_included) } diff --git a/man/update_dataset_list.Rd b/man/update_dataset_list.Rd index b816f9fb..6d0c8354 100644 --- a/man/update_dataset_list.Rd +++ b/man/update_dataset_list.Rd @@ -10,7 +10,7 @@ update_dataset_list(on_cran = FALSE) \item{on_cran}{boolean to make this function run on ci tests using tempdir} } \value{ -the dataset list +TRUE if the dataset was updated } \description{ If a newer dataset list (which includes all the information about the files @@ -20,4 +20,3 @@ storing the data for pastclim), download it and start using it as column, named 'dataset_list_v', provides the version of this table, and the most advanced table is used. } -\keyword{internal} From 60bc7ed8ad2fe02ad62a224b348a0b29746b268e Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Fri, 2 Dec 2022 22:00:02 +0000 Subject: [PATCH 21/22] fix type in vignette --- vignettes/a2_custom_datasets.Rmd | 1 - 1 file changed, 1 deletion(-) diff --git a/vignettes/a2_custom_datasets.Rmd b/vignettes/a2_custom_datasets.Rmd index 30d531b9..12da2295 100644 --- a/vignettes/a2_custom_datasets.Rmd +++ b/vignettes/a2_custom_datasets.Rmd @@ -40,7 +40,6 @@ Now we need to set the time axis of the raster (in this case, reconstructions ar ```{r} terra::time(bio01)<-c(0,-100,-200) names(bio01)<-paste("bio01",terra::time(bio01),sep="_") -bio01_sds<-sds(bio01) ``` Now we save the data as a *nc* file (we will use the temporary directory) From 16c20679b244f5de6457be79a32cda495844fef4 Mon Sep 17 00:00:00 2001 From: Andrea Manica Date: Sat, 3 Dec 2022 12:53:25 +0000 Subject: [PATCH 22/22] Bump to 1.2.2 --- DESCRIPTION | 2 +- NEWS.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 02253597..d5253577 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: pastclim Type: Package Title: Manipulate Time Series of Palaeoclimate Reconstructions -Version: 1.2.1.9000 +Version: 1.2.2 Authors@R: c( person("Michela", "Leonardi", role = "aut"), person(c("Emily","Y."), "Hallet", role = "ctb"), diff --git a/NEWS.md b/NEWS.md index 8c3fb41c..a3399a21 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# pastclim 1.2.2 (under development) +# pastclim 1.2.2 * Update of Krapp2021 files to make them compatible with how terra now handles time. Users will have to redownload datasets. Old files can be removed with 'clean_data_path()'