diff --git a/catalog/forecasts/Phenology/Daily_Green_chromatic_coordinate/collection.json b/catalog/forecasts/Phenology/Daily_Green_chromatic_coordinate/collection.json index 55cc65d63b..653ab662d3 100644 --- a/catalog/forecasts/Phenology/Daily_Green_chromatic_coordinate/collection.json +++ b/catalog/forecasts/Phenology/Daily_Green_chromatic_coordinate/collection.json @@ -13,32 +13,32 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/persistenceRW.json" + "href": "../../models/model_items/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_arima.json" + "href": "../../models/model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_auto_adam.json" + "href": "../../models/model_items/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" + "href": "../../models/model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/cb_prophet.json" + "href": "../../models/model_items/tg_auto_adam.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/climatology.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", diff --git a/catalog/forecasts/Terrestrial/Daily_Net_ecosystem_exchange/collection.json b/catalog/forecasts/Terrestrial/Daily_Net_ecosystem_exchange/collection.json index 902314f07f..8c9f0a0479 100644 --- a/catalog/forecasts/Terrestrial/Daily_Net_ecosystem_exchange/collection.json +++ b/catalog/forecasts/Terrestrial/Daily_Net_ecosystem_exchange/collection.json @@ -13,62 +13,62 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_arima.json" + "href": "../../models/model_items/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_auto_adam.json" + "href": "../../models/model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" + "href": "../../models/model_items/lasso.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_ets.json" + "href": "../../models/model_items/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_precip_lm.json" + "href": "../../models/model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_precip_lm_all_sites.json" + "href": "../../models/model_items/tg_precip_lm.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_randfor.json" + "href": "../../models/model_items/tg_precip_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_tbats.json" + "href": "../../models/model_items/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/cb_prophet.json" + "href": "../../models/model_items/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/climatology.json" + "href": "../../models/model_items/tg_auto_adam.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/lasso.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/persistenceRW.json" + "href": "../../models/model_items/tg_ets.json" }, { "rel": "item", diff --git a/catalog/forecasts/Terrestrial/Daily_latent_heat_flux/collection.json b/catalog/forecasts/Terrestrial/Daily_latent_heat_flux/collection.json index 2c7da14669..85eafbc878 100644 --- a/catalog/forecasts/Terrestrial/Daily_latent_heat_flux/collection.json +++ b/catalog/forecasts/Terrestrial/Daily_latent_heat_flux/collection.json @@ -38,42 +38,42 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_ets.json" + "href": "../../models/model_items/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_humidity_lm_all_sites.json" + "href": "../../models/model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_precip_lm.json" + "href": "../../models/model_items/lasso.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/cb_prophet.json" + "href": "../../models/model_items/randfor.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/climatology.json" + "href": "../../models/model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/lasso.json" + "href": "../../models/model_items/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/randfor.json" + "href": "../../models/model_items/tg_humidity_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_arima.json" + "href": "../../models/model_items/tg_precip_lm.json" }, { "rel": "item", diff --git a/catalog/forecasts/models/collection.json b/catalog/forecasts/models/collection.json index c5436956c5..2bb7ad0199 100644 --- a/catalog/forecasts/models/collection.json +++ b/catalog/forecasts/models/collection.json @@ -13,72 +13,67 @@ { "rel": "item", "type": "application/json", - "href": "model_items/persistenceRW.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "model_items/tg_arima.json" + "href": "model_items/USGSHABs1.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/tg_auto_adam.json" + "href": "model_items/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/tg_bag_mlp.json" + "href": "model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/USGSHABs1.json" + "href": "model_items/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/cb_prophet.json" + "href": "model_items/procBlanchardMonod.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/climatology.json" + "href": "model_items/procBlanchardSteele.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procBlanchardMonod.json" + "href": "model_items/procCTMIMonod.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procBlanchardSteele.json" + "href": "model_items/procCTMISteele.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procCTMIMonod.json" + "href": "model_items/procEppleyNorbergMonod.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procCTMISteele.json" + "href": "model_items/procEppleyNorbergSteele.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procEppleyNorbergMonod.json" + "href": "model_items/procHinshelwoodSteele.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procEppleyNorbergSteele.json" + "href": "model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/procHinshelwoodSteele.json" + "href": "model_items/tg_bag_mlp.json" }, { "rel": "item", @@ -125,6 +120,11 @@ "type": "application/json", "href": "model_items/tg_temp_lm_all_sites.json" }, + { + "rel": "item", + "type": "application/json", + "href": "model_items/tg_auto_adam.json" + }, { "rel": "item", "type": "application/json", @@ -263,17 +263,17 @@ { "rel": "item", "type": "application/json", - "href": "model_items/precip_mod.json" + "href": "model_items/PEG.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/neon4cast_example.json" + "href": "model_items/precip_mod.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/PEG.json" + "href": "model_items/neon4cast_example.json" }, { "rel": "parent", diff --git a/catalog/forecasts/models/model_items/persistenceRW.json b/catalog/forecasts/models/model_items/persistenceRW.json index 624192d9ec..e909361e91 100644 --- a/catalog/forecasts/models/model_items/persistenceRW.json +++ b/catalog/forecasts/models/model_items/persistenceRW.json @@ -16,6 +16,18 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-149.6106, 68.6307], + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-119.7323, 37.1088], + [-119.2622, 37.0334], + [-110.8355, 31.9107], + [-89.5864, 45.5089], + [-103.0293, 40.4619], + [-87.3933, 32.9505], [-67.0769, 18.0213], [-88.1612, 31.8539], [-80.5248, 37.3783], @@ -27,12 +39,6 @@ [-106.8425, 32.5907], [-96.6129, 39.1104], [-96.5631, 39.1008], - [-119.7323, 37.1088], - [-119.2622, 37.0334], - [-110.8355, 31.9107], - [-89.5864, 45.5089], - [-103.0293, 40.4619], - [-87.3933, 32.9505], [-81.9934, 29.6893], [-155.3173, 19.5531], [-105.546, 40.2759], @@ -51,12 +57,6 @@ [-99.0588, 35.4106], [-112.4524, 40.1776], [-84.2826, 35.9641], - [-149.6106, 68.6307], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], @@ -100,7 +100,7 @@ ] }, "properties": { - "description": ["\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: LAJA, LENO, MLBS, MOAB, NIWO, NOGP, HEAL, JERC, JORN, KONA, KONZ, SJER, SOAP, SRER, STEI, STER, TALL, OSBS, PUUM, RMNP, SCBI, SERC, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, OAES, ONAQ, ORNL, TOOK, BARC, BLWA, CRAM, FLNT, LIRO, UNDE, WOOD, WREF, YELL, TEAK, TOOL, TREE, UKFS, DSNY, GRSM, GUAN, HARV, TECR, TOMB, WALK, WLOU, SYCA, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, LECO, LEWI, MART, PRLA, PRPO, REDB, SUGG, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, KING, GUIL, HOPB\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily Net_ecosystem_exchange, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Daily Water_temperature", "\nmodel info: NA\n\nSites: LAJA, LENO, MLBS, MOAB, NIWO, NOGP, HEAL, JERC, JORN, KONA, KONZ, SJER, SOAP, SRER, STEI, STER, TALL, OSBS, PUUM, RMNP, SCBI, SERC, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, OAES, ONAQ, ORNL, TOOK, BARC, BLWA, CRAM, FLNT, LIRO, UNDE, WOOD, WREF, YELL, TEAK, TOOL, TREE, UKFS, DSNY, GRSM, GUAN, HARV, TECR, TOMB, WALK, WLOU, SYCA, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, LECO, LEWI, MART, PRLA, PRPO, REDB, SUGG, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, KING, GUIL, HOPB\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily Net_ecosystem_exchange, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Daily Water_temperature"], + "description": ["\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: TOOK, BARC, BLWA, CRAM, FLNT, LIRO, SJER, SOAP, SRER, STEI, STER, TALL, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, HEAL, JERC, JORN, KONA, KONZ, OSBS, PUUM, RMNP, SCBI, SERC, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, OAES, ONAQ, ORNL, UNDE, WOOD, WREF, YELL, TEAK, TOOL, TREE, UKFS, DSNY, GRSM, GUAN, HARV, TECR, TOMB, WALK, WLOU, SYCA, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, LECO, LEWI, MART, PRLA, PRPO, REDB, SUGG, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, KING, GUIL, HOPB\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Daily Water_temperature", "\nmodel info: NA\n\nSites: TOOK, BARC, BLWA, CRAM, FLNT, LIRO, SJER, SOAP, SRER, STEI, STER, TALL, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, HEAL, JERC, JORN, KONA, KONZ, OSBS, PUUM, RMNP, SCBI, SERC, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, OAES, ONAQ, ORNL, UNDE, WOOD, WREF, YELL, TEAK, TOOL, TREE, UKFS, DSNY, GRSM, GUAN, HARV, TECR, TOMB, WALK, WLOU, SYCA, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, LECO, LEWI, MART, PRLA, PRPO, REDB, SUGG, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, KING, GUIL, HOPB\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Daily Water_temperature"], "start_datetime": "2023-11-15", "end_datetime": "2024-02-04", "providers": [ @@ -125,8 +125,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily Net_ecosystem_exchange", "Daily Red_chromatic_coordinate", "Daily Dissolved_oxygen", @@ -242,17 +242,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily Net_ecosystem_exchange", diff --git a/catalog/forecasts/models/model_items/tg_arima.json b/catalog/forecasts/models/model_items/tg_arima.json index 188fabcf44..f19a12dcd6 100644 --- a/catalog/forecasts/models/model_items/tg_arima.json +++ b/catalog/forecasts/models/model_items/tg_arima.json @@ -16,6 +16,16 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -63,16 +73,6 @@ [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], [-102.4471, 39.7582], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -100,7 +100,7 @@ ] }, "properties": { - "description": "\nmodel info: NA\n\nSites: ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily Net_ecosystem_exchange, Daily latent_heat_flux, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Daily Water_temperature, Weekly beetle_community_richness, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", + "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily latent_heat_flux, Daily Red_chromatic_coordinate, Daily Dissolved_oxygen, Weekly beetle_community_richness, Daily Water_temperature, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", "start_datetime": "2023-01-01", "end_datetime": "2024-12-23", "providers": [ @@ -125,14 +125,14 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily Net_ecosystem_exchange", "Daily latent_heat_flux", "Daily Red_chromatic_coordinate", "Daily Dissolved_oxygen", - "Daily Water_temperature", "Weekly beetle_community_richness", + "Daily Water_temperature", "Weekly beetle_community_abundance", "Weekly Amblyomma_americanum_population" ], @@ -246,17 +246,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily Net_ecosystem_exchange", @@ -282,17 +282,17 @@ "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=oxygen/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, "9": { - "type": "application/x-parquet", - "title": "Database Access for Daily Water_temperature", - "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "10": { "type": "application/x-parquet", "title": "Database Access for Weekly beetle_community_richness", "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1W/variable=richness/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1W/variable=richness/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "10": { + "type": "application/x-parquet", + "title": "Database Access for Daily Water_temperature", + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "11": { "type": "application/x-parquet", "title": "Database Access for Weekly beetle_community_abundance", diff --git a/catalog/forecasts/models/model_items/tg_bag_mlp.json b/catalog/forecasts/models/model_items/tg_bag_mlp.json index ecfe54eaf4..2c44a66750 100644 --- a/catalog/forecasts/models/model_items/tg_bag_mlp.json +++ b/catalog/forecasts/models/model_items/tg_bag_mlp.json @@ -16,6 +16,16 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307], [-78.1395, 38.8929], [-76.56, 38.8901], [-119.7323, 37.1088], @@ -32,16 +42,6 @@ [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -125,8 +125,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily Net_ecosystem_exchange", "Daily latent_heat_flux", "Daily Red_chromatic_coordinate", @@ -243,17 +243,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=chla/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=gcc_90/model_id=tg_bag_mlp?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily Net_ecosystem_exchange", diff --git a/catalog/forecasts/models/model_items/tg_ets.json b/catalog/forecasts/models/model_items/tg_ets.json index 100e6c7acd..7988b5ce0b 100644 --- a/catalog/forecasts/models/model_items/tg_ets.json +++ b/catalog/forecasts/models/model_items/tg_ets.json @@ -100,7 +100,7 @@ ] }, "properties": { - "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily latent_heat_flux, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature, Weekly beetle_community_richness, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", + "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily latent_heat_flux, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Weekly beetle_community_richness, Daily Water_temperature, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", "start_datetime": "2023-01-01", "end_datetime": "2024-12-23", "providers": [ @@ -131,8 +131,8 @@ "Daily latent_heat_flux", "Daily Dissolved_oxygen", "Daily Red_chromatic_coordinate", - "Daily Water_temperature", "Weekly beetle_community_richness", + "Daily Water_temperature", "Weekly beetle_community_abundance", "Weekly Amblyomma_americanum_population" ], @@ -282,17 +282,17 @@ "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=rcc_90/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, "9": { - "type": "application/x-parquet", - "title": "Database Access for Daily Water_temperature", - "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "10": { "type": "application/x-parquet", "title": "Database Access for Weekly beetle_community_richness", "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1W/variable=richness/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1W/variable=richness/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "10": { + "type": "application/x-parquet", + "title": "Database Access for Daily Water_temperature", + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/duration=P1D/variable=temperature/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "11": { "type": "application/x-parquet", "title": "Database Access for Weekly beetle_community_abundance", diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json index 938b320428..be29055f8c 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json @@ -55,16 +55,6 @@ "type": "application/json", "href": "../../models/model_items/tg_tbats.json" }, - { - "rel": "item", - "type": "application/json", - "href": "../../models/model_items/tg_temp_lm.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "../../models/model_items/tg_temp_lm_all_sites.json" - }, { "rel": "item", "type": "application/json", @@ -140,6 +130,16 @@ "type": "application/json", "href": "../../models/model_items/tg_bag_mlp.json" }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/tg_temp_lm.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/tg_temp_lm_all_sites.json" + }, { "rel": "parent", "type": "application/json", diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json index cd2cf0fbce..c45f30f258 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json @@ -10,6 +10,16 @@ ], "type": "Collection", "links": [ + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/GLEON_lm_lag_1day.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/air2waterSat_2.json" + }, { "rel": "item", "type": "application/json", @@ -43,12 +53,12 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/GLEON_lm_lag_1day.json" + "href": "../../models/model_items/tg_auto_adam.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/air2waterSat_2.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", @@ -100,16 +110,6 @@ "type": "application/json", "href": "../../models/model_items/tg_tbats.json" }, - { - "rel": "item", - "type": "application/json", - "href": "../../models/model_items/tg_auto_adam.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" - }, { "rel": "item", "type": "application/json", diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json index 50d9a04466..2a2f712acf 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json @@ -68,72 +68,72 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareGLM.json" + "href": "../../models/model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareGLM_noDA.json" + "href": "../../models/model_items/tg_auto_adam.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareGOTM.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareGOTM_noDA.json" + "href": "../../models/model_items/flareGLM.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareSimstrat.json" + "href": "../../models/model_items/flareGLM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flareSimstrat_noDA.json" + "href": "../../models/model_items/flareGOTM.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flare_ler.json" + "href": "../../models/model_items/flareGOTM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/flare_ler_baselines.json" + "href": "../../models/model_items/flareSimstrat.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/null.json" + "href": "../../models/model_items/flareSimstrat_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/persistenceRW.json" + "href": "../../models/model_items/flare_ler.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/precip_mod.json" + "href": "../../models/model_items/flare_ler_baselines.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_arima.json" + "href": "../../models/model_items/null.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_auto_adam.json" + "href": "../../models/model_items/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" + "href": "../../models/model_items/precip_mod.json" }, { "rel": "item", diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json index 8cee1fe29a..c9ab94cd29 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json @@ -58,27 +58,27 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_randfor.json" + "href": "../../models/model_items/tg_humidity_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_tbats.json" + "href": "../../models/model_items/tg_lasso.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_humidity_lm_all_sites.json" + "href": "../../models/model_items/tg_lasso_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_lasso.json" + "href": "../../models/model_items/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_lasso_all_sites.json" + "href": "../../models/model_items/tg_tbats.json" }, { "rel": "item", diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json index a1288cd6e7..1df6e38f10 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json @@ -88,17 +88,17 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_randfor_all_sites.json" + "href": "../../models/model_items/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_tbats.json" + "href": "../../models/model_items/tg_randfor_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_randfor.json" + "href": "../../models/model_items/tg_tbats.json" }, { "rel": "item", diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json index 7e96776c25..f920fa6b93 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json @@ -10,11 +10,6 @@ ], "type": "Collection", "links": [ - { - "rel": "item", - "type": "application/json", - "href": "../../models/model_items/USUNEEDAILY.json" - }, { "rel": "item", "type": "application/json", @@ -38,27 +33,27 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_arima.json" + "href": "../../models/model_items/USUNEEDAILY.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_auto_adam.json" + "href": "../../models/model_items/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" + "href": "../../models/model_items/tg_auto_adam.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_ets.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_humidity_lm.json" + "href": "../../models/model_items/tg_ets.json" }, { "rel": "item", @@ -80,6 +75,11 @@ "type": "application/json", "href": "../../models/model_items/tg_randfor.json" }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/tg_humidity_lm.json" + }, { "rel": "item", "type": "application/json", diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json index 70b723b9c4..c9e93853fb 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json @@ -38,12 +38,12 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_bag_mlp.json" + "href": "../../models/model_items/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_ets.json" + "href": "../../models/model_items/tg_bag_mlp.json" }, { "rel": "item", @@ -58,7 +58,7 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_humidity_lm_all_sites.json" + "href": "../../models/model_items/tg_tbats.json" }, { "rel": "item", @@ -68,17 +68,17 @@ { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_tbats.json" + "href": "../../models/model_items/tg_precip_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_precip_lm_all_sites.json" + "href": "../../models/model_items/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "../../models/model_items/tg_randfor.json" + "href": "../../models/model_items/tg_humidity_lm_all_sites.json" }, { "rel": "item", diff --git a/catalog/scores/models/collection.json b/catalog/scores/models/collection.json index e8d1b8edea..9091a25363 100644 --- a/catalog/scores/models/collection.json +++ b/catalog/scores/models/collection.json @@ -15,21 +15,6 @@ "type": "application/json", "href": "model_items/tg_ets.json" }, - { - "rel": "item", - "type": "application/json", - "href": "model_items/climatology.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "model_items/persistenceRW.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "model_items/tg_arima.json" - }, { "rel": "item", "type": "application/json", @@ -73,27 +58,22 @@ { "rel": "item", "type": "application/json", - "href": "model_items/tg_temp_lm.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "model_items/tg_temp_lm_all_sites.json" + "href": "model_items/USGSHABs1.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/PEG.json" + "href": "model_items/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/cb_prophet.json" + "href": "model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/USGSHABs1.json" + "href": "model_items/persistenceRW.json" }, { "rel": "item", @@ -135,6 +115,11 @@ "type": "application/json", "href": "model_items/procHinshelwoodSteele.json" }, + { + "rel": "item", + "type": "application/json", + "href": "model_items/tg_arima.json" + }, { "rel": "item", "type": "application/json", @@ -145,6 +130,21 @@ "type": "application/json", "href": "model_items/tg_bag_mlp.json" }, + { + "rel": "item", + "type": "application/json", + "href": "model_items/tg_temp_lm.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "model_items/tg_temp_lm_all_sites.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "model_items/PEG.json" + }, { "rel": "item", "type": "application/json", @@ -163,22 +163,22 @@ { "rel": "item", "type": "application/json", - "href": "model_items/cb_f1.json" + "href": "model_items/GLEON_lm_lag_1day.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/null.json" + "href": "model_items/air2waterSat_2.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/GLEON_lm_lag_1day.json" + "href": "model_items/cb_f1.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/air2waterSat_2.json" + "href": "model_items/null.json" }, { "rel": "item", diff --git a/catalog/scores/models/model_items/cb_f1.json b/catalog/scores/models/model_items/cb_f1.json index 7b7effedda..f297f719cd 100644 --- a/catalog/scores/models/model_items/cb_f1.json +++ b/catalog/scores/models/model_items/cb_f1.json @@ -16,7 +16,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-105.9154, 39.8914], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -49,7 +48,8 @@ [-119.0274, 36.9559], [-88.1589, 31.8534], [-149.6106, 68.6307], - [-84.2793, 35.9574] + [-84.2793, 35.9574], + [-105.9154, 39.8914] ] }, "properties": { diff --git a/catalog/scores/models/model_items/cb_prophet.json b/catalog/scores/models/model_items/cb_prophet.json index daba7b96c8..d1467d11b2 100644 --- a/catalog/scores/models/model_items/cb_prophet.json +++ b/catalog/scores/models/model_items/cb_prophet.json @@ -16,6 +16,15 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -63,15 +72,6 @@ [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], [-102.4471, 39.7582], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -98,7 +98,7 @@ ] }, "properties": { - "description": "\nmodel info: NA\n\nSites: ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", + "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", "start_datetime": "2023-11-14", "end_datetime": "2023-12-31", "providers": [ @@ -123,8 +123,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily latent_heat_flux", "Daily Net_ecosystem_exchange", "Daily Dissolved_oxygen", @@ -281,17 +281,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=cb_prophet?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily latent_heat_flux", diff --git a/catalog/scores/models/model_items/climatology.json b/catalog/scores/models/model_items/climatology.json index c4669404b6..80ce755a0e 100644 --- a/catalog/scores/models/model_items/climatology.json +++ b/catalog/scores/models/model_items/climatology.json @@ -16,6 +16,11 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-84.4374, 31.1854], + [-82.0177, 29.6878], + [-88.1589, 31.8534], [-81.4362, 28.1251], [-83.5019, 35.689], [-66.8687, 17.9696], @@ -58,11 +63,6 @@ [-104.7456, 40.8155], [-99.1066, 47.1617], [-87.8039, 32.5417], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-84.4374, 31.1854], - [-82.0177, 29.6878], - [-88.1589, 31.8534], [-156.6194, 71.2824], [-147.5026, 65.154], [-145.7514, 63.8811], @@ -93,7 +93,7 @@ ] }, "properties": { - "description": ["\nmodel info: Historical DOY mean and sd. Assumes normal distribution\n\n\nSites: DSNY, GRSM, GUAN, HARV, JERC, JORN, KONA, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TREE, UKFS, UNDE, WOOD, WREF, YELL, KONZ, ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, BARC, BLWA, FLNT, SUGG, TOMB, BARR, BONA, DEJU, HEAL, TOOL, ARIK, BIGC, BLDE, BLUE, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily latent_heat_flux, 30min latent_heat_flux, Daily Net_ecosystem_exchange, 30min Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", "\nmodel info: NA\n\nSites: DSNY, GRSM, GUAN, HARV, JERC, JORN, KONA, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TREE, UKFS, UNDE, WOOD, WREF, YELL, KONZ, ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, BARC, BLWA, FLNT, SUGG, TOMB, BARR, BONA, DEJU, HEAL, TOOL, ARIK, BIGC, BLDE, BLUE, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily latent_heat_flux, 30min latent_heat_flux, Daily Net_ecosystem_exchange, 30min Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature"], + "description": ["\nmodel info: Historical DOY mean and sd. Assumes normal distribution\n\n\nSites: BARC, BLWA, FLNT, SUGG, TOMB, DSNY, GRSM, GUAN, HARV, JERC, JORN, KONA, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TREE, UKFS, UNDE, WOOD, WREF, YELL, KONZ, ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, BARR, BONA, DEJU, HEAL, TOOL, ARIK, BIGC, BLDE, BLUE, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily latent_heat_flux, 30min latent_heat_flux, Daily Net_ecosystem_exchange, 30min Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", "\nmodel info: NA\n\nSites: BARC, BLWA, FLNT, SUGG, TOMB, DSNY, GRSM, GUAN, HARV, JERC, JORN, KONA, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TREE, UKFS, UNDE, WOOD, WREF, YELL, KONZ, ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, BARR, BONA, DEJU, HEAL, TOOL, ARIK, BIGC, BLDE, BLUE, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily latent_heat_flux, 30min latent_heat_flux, Daily Net_ecosystem_exchange, 30min Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature"], "start_datetime": "2023-11-14", "end_datetime": "2023-12-31", "providers": [ @@ -118,8 +118,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily latent_heat_flux", "30min latent_heat_flux", "Daily Net_ecosystem_exchange", @@ -278,17 +278,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=climatology?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=climatology?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=climatology?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=climatology?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=climatology?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=climatology?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily latent_heat_flux", diff --git a/catalog/scores/models/model_items/persistenceRW.json b/catalog/scores/models/model_items/persistenceRW.json index ac9681d84c..ac9ca34090 100644 --- a/catalog/scores/models/model_items/persistenceRW.json +++ b/catalog/scores/models/model_items/persistenceRW.json @@ -16,6 +16,16 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -63,16 +73,6 @@ [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], [-102.4471, 39.7582], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -100,7 +100,7 @@ ] }, "properties": { - "description": ["\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", "\nmodel info: NA\n\nSites: ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature"], + "description": ["\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature", "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature"], "start_datetime": "2023-11-15", "end_datetime": "2023-12-31", "providers": [ @@ -125,8 +125,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily Net_ecosystem_exchange", "Daily Dissolved_oxygen", "Daily Red_chromatic_coordinate", @@ -282,17 +282,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=persistenceRW?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily Net_ecosystem_exchange", diff --git a/catalog/scores/models/model_items/tg_arima.json b/catalog/scores/models/model_items/tg_arima.json index 8081d89531..d2071eee08 100644 --- a/catalog/scores/models/model_items/tg_arima.json +++ b/catalog/scores/models/model_items/tg_arima.json @@ -16,6 +16,16 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -63,16 +73,6 @@ [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], [-102.4471, 39.7582], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -100,7 +100,7 @@ ] }, "properties": { - "description": "\nmodel info: NA\n\nSites: ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population, Weekly beetle_community_richness", + "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population, Weekly beetle_community_richness", "start_datetime": "2023-01-01", "end_datetime": "2023-12-31", "providers": [ @@ -125,8 +125,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily latent_heat_flux", "Daily Net_ecosystem_exchange", "Daily Dissolved_oxygen", @@ -286,17 +286,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_arima?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily latent_heat_flux", diff --git a/catalog/scores/models/model_items/tg_ets.json b/catalog/scores/models/model_items/tg_ets.json index 9e0e68a8d6..7ebf70f1d7 100644 --- a/catalog/scores/models/model_items/tg_ets.json +++ b/catalog/scores/models/model_items/tg_ets.json @@ -16,6 +16,16 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-82.0084, 29.676], + [-87.7982, 32.5415], + [-89.4737, 46.2097], + [-84.4374, 31.1854], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307], [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], @@ -63,23 +73,6 @@ [-89.5857, 45.4937], [-95.1921, 39.0404], [-89.5373, 46.2339], - [-82.0084, 29.676], - [-87.7982, 32.5415], - [-89.4737, 46.2097], - [-84.4374, 31.1854], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], - [-78.1473, 38.8943], - [-97.7823, 33.3785], - [-111.7979, 40.7839], - [-111.5081, 33.751], - [-119.0274, 36.9559], - [-84.2793, 35.9574], - [-105.9154, 39.8914], [-102.4471, 39.7582], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -96,11 +89,18 @@ [-87.4077, 32.9604], [-96.443, 38.9459], [-122.1655, 44.2596], - [-149.143, 68.6698] + [-149.143, 68.6698], + [-78.1473, 38.8943], + [-97.7823, 33.3785], + [-111.7979, 40.7839], + [-111.5081, 33.751], + [-119.0274, 36.9559], + [-84.2793, 35.9574], + [-105.9154, 39.8914] ] }, "properties": { - "description": "\nmodel info: NA\n\nSites: WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR\n\nVariables: Daily Green_chromatic_coordinate, Daily Chlorophyll_a, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature, Weekly beetle_community_richness, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", + "description": "\nmodel info: NA\n\nSites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, ARIK, BIGC, BLDE, BLUE, CARI, COMO, CUPE, GUIL, HOPB, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, REDB, SYCA, TECR, WALK, WLOU\n\nVariables: Daily Chlorophyll_a, Daily Green_chromatic_coordinate, Daily latent_heat_flux, Daily Net_ecosystem_exchange, Daily Dissolved_oxygen, Daily Red_chromatic_coordinate, Daily Water_temperature, Weekly beetle_community_richness, Weekly beetle_community_abundance, Weekly Amblyomma_americanum_population", "start_datetime": "2023-01-01", "end_datetime": "2023-12-31", "providers": [ @@ -125,8 +125,8 @@ "keywords": [ "Forecasting", "neon4cast", - "Daily Green_chromatic_coordinate", "Daily Chlorophyll_a", + "Daily Green_chromatic_coordinate", "Daily latent_heat_flux", "Daily Net_ecosystem_exchange", "Daily Dissolved_oxygen", @@ -286,17 +286,17 @@ "description": "The link to the model code provided by the model submission team" }, "3": { - "type": "application/x-parquet", - "title": "Database Access for Daily Green_chromatic_coordinate", - "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", - "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "4": { "type": "application/x-parquet", "title": "Database Access for Daily Chlorophyll_a", "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=chla/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" }, + "4": { + "type": "application/x-parquet", + "title": "Database Access for Daily Green_chromatic_coordinate", + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org", + "description": "Use `arrow` for remote access to the database. This R code will return results for this variable and model combination.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/scores/parquet/duration=P1D/variable=gcc_90/model_id=tg_ets?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, "5": { "type": "application/x-parquet", "title": "Database Access for Daily latent_heat_flux", diff --git a/catalog/scores/models/model_items/tg_randfor_all_sites.json b/catalog/scores/models/model_items/tg_randfor_all_sites.json index b4b8992772..47f5deef36 100644 --- a/catalog/scores/models/model_items/tg_randfor_all_sites.json +++ b/catalog/scores/models/model_items/tg_randfor_all_sites.json @@ -50,8 +50,6 @@ [-149.6106, 68.6307], [-84.2793, 35.9574], [-105.9154, 39.8914], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -96,7 +94,9 @@ [-89.5857, 45.4937], [-95.1921, 39.0404], [-89.5373, 46.2339], - [-99.2413, 47.1282] + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535] ] }, "properties": {