From 3c0a07d7e9dd4c9f47d4c94f823414f345abafb1 Mon Sep 17 00:00:00 2001 From: github-actions Date: Fri, 1 Nov 2024 00:19:58 +0000 Subject: [PATCH] update catalog --- .../Daily_Chlorophyll_a/collection.json | 16 ++-- .../Daily_Chlorophyll_a/models/tg_tbats.json | 10 +-- .../Daily_Dissolved_oxygen/collection.json | 8 +- .../models/hotdeck.json | 6 +- .../models/persistenceRW.json | 90 +++++++++---------- .../Daily_Water_temperature/collection.json | 52 +++++------ .../models/air2waterSat_2.json | 18 ++-- .../models/baseline_ensemble.json | 14 +-- .../models/bee_bake_RFModel_2024.json | 14 +-- .../models/fARIMA_clim_ensemble.json | 6 +- .../models/hotdeck.json | 18 ++-- .../models/tg_temp_lm.json | 18 ++-- .../collection.json | 4 +- .../collection.json | 26 +++--- .../models/cb_prophet.json | 66 +++++++------- .../models/climatology.json | 10 +-- .../models/persistenceRW.json | 74 +++++++-------- .../models/tg_arima.json | 22 ++--- .../models/tg_humidity_lm.json | 70 +++++++-------- .../models/tg_tbats.json | 58 ++++++------ .../models/tg_temp_lm.json | 70 +++++++-------- .../collection.json | 18 ++-- .../models/climatology.json | 10 +-- .../models/tg_arima.json | 86 +++++++++--------- .../models/tg_ets.json | 86 +++++++++--------- .../models/tg_lasso.json | 18 ++-- .../models/tg_precip_lm.json | 66 +++++++------- .../models/tg_precip_lm_all_sites.json | 54 +++++------ .../models/tg_randfor.json | 70 +++++++-------- .../models/tg_tbats.json | 22 ++--- .../collection.json | 22 ++--- .../models/tg_humidity_lm_all_sites.json | 58 ++++++------ .../Daily_latent_heat_flux/collection.json | 8 +- .../models/cb_prophet.json | 22 ++--- .../models/tg_humidity_lm.json | 14 +-- .../models/tg_precip_lm.json | 66 +++++++------- 36 files changed, 645 insertions(+), 645 deletions(-) diff --git a/catalog/summaries/Aquatics/Daily_Chlorophyll_a/collection.json b/catalog/summaries/Aquatics/Daily_Chlorophyll_a/collection.json index 3302c7e036..aa97054c4d 100644 --- a/catalog/summaries/Aquatics/Daily_Chlorophyll_a/collection.json +++ b/catalog/summaries/Aquatics/Daily_Chlorophyll_a/collection.json @@ -76,42 +76,42 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_humidity_lm_all_sites.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_lasso.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm_all_sites.json" + "href": "./models/tg_humidity_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_randfor.json" + "href": "./models/tg_lasso.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/tg_precip_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/tg_precip_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/tg_randfor.json" }, { "rel": "parent", diff --git a/catalog/summaries/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json b/catalog/summaries/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json index 30fef4c75e..98878830fc 100644 --- a/catalog/summaries/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json +++ b/catalog/summaries/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json @@ -9,7 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-82.0084, 29.676], [-87.7982, 32.5415], [-89.4737, 46.2097], [-84.4374, 31.1854], @@ -18,12 +17,13 @@ [-99.2531, 47.1298], [-82.0177, 29.6878], [-88.1589, 31.8534], - [-149.6106, 68.6307] + [-149.6106, 68.6307], + [-82.0084, 29.676] ] }, "properties": { "title": "tg_tbats", - "description": "All summaries for the Daily_Chlorophyll_a variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Chlorophyll_a variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK, BARC.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-19", "updated": "2024-08-23", "start_datetime": "2023-01-01T00:00:00Z", @@ -56,7 +56,6 @@ "chla", "Daily", "P1D", - "BARC", "BLWA", "CRAM", "FLNT", @@ -65,7 +64,8 @@ "PRPO", "SUGG", "TOMB", - "TOOK" + "TOOK", + "BARC" ], "table:columns": [ { diff --git a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/collection.json b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/collection.json index 1ee7b0d1c1..419703ce46 100644 --- a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/collection.json +++ b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/collection.json @@ -71,22 +71,22 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "item", diff --git a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json index 63d3791233..d73bbdc648 100644 --- a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json +++ b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json @@ -12,12 +12,12 @@ [-82.0084, 29.676], [-82.0177, 29.6878], [-96.6038, 39.1051], + [-111.5081, 33.751], [-110.5871, 44.9501], [-119.2575, 37.0597], [-122.1655, 44.2596], [-111.7979, 40.7839], [-89.4737, 46.2097], - [-111.5081, 33.751], [-89.7048, 45.9983], [-97.7823, 33.3785], [-78.1473, 38.8943], @@ -27,7 +27,7 @@ }, "properties": { "title": "hotdeck", - "description": "All summaries for the Daily_Dissolved_oxygen variable for the hotdeck model. Information for the model is provided as follows: Uses a hot deck approach: - Take the latest observation/forecast. - Past observations from around the same window of the season are collected. - Values close to the latest observation/forecast are collected. - One of these is randomly sampled. - Its \"tomorrow\" observation is used as the forecast. - Repeat until forecast at step h..\n The model predicts this variable at the following sites: BARC, SUGG, KING, BLDE, BIGC, MCRA, REDB, CRAM, SYCA, LIRO, PRIN, POSE, MAYF, LEWI.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Dissolved_oxygen variable for the hotdeck model. Information for the model is provided as follows: Uses a hot deck approach: - Take the latest observation/forecast. - Past observations from around the same window of the season are collected. - Values close to the latest observation/forecast are collected. - One of these is randomly sampled. - Its \"tomorrow\" observation is used as the forecast. - Repeat until forecast at step h..\n The model predicts this variable at the following sites: BARC, SUGG, KING, SYCA, BLDE, BIGC, MCRA, REDB, CRAM, LIRO, PRIN, POSE, MAYF, LEWI.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-08-22", "updated": "2024-08-23", "start_datetime": "2024-04-05T00:00:00Z", @@ -63,12 +63,12 @@ "BARC", "SUGG", "KING", + "SYCA", "BLDE", "BIGC", "MCRA", "REDB", "CRAM", - "SYCA", "LIRO", "PRIN", "POSE", diff --git a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json index 741f13cfae..7ba6139f70 100644 --- a/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json +++ b/catalog/summaries/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json @@ -9,45 +9,45 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-87.4077, 32.9604], - [-96.443, 38.9459], - [-122.1655, 44.2596], - [-149.143, 68.6698], - [-78.1473, 38.8943], - [-97.7823, 33.3785], - [-96.6242, 34.4442], - [-87.7982, 32.5415], - [-147.504, 65.1532], - [-105.5442, 40.035], - [-89.4737, 46.2097], - [-66.9868, 18.1135], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-111.7979, 40.7839], - [-82.0177, 29.6878], - [-111.5081, 33.751], - [-105.9154, 39.8914], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], [-110.5871, 44.9501], + [-96.6242, 34.4442], + [-83.5038, 35.6904], + [-77.9832, 39.0956], + [-89.7048, 45.9983], + [-121.9338, 45.7908], + [-87.4077, 32.9604], + [-111.5081, 33.751], [-119.0274, 36.9559], [-88.1589, 31.8534], [-149.6106, 68.6307], [-84.2793, 35.9574], + [-87.7982, 32.5415], + [-147.504, 65.1532], + [-105.5442, 40.035], + [-89.4737, 46.2097], + [-66.9868, 18.1135], + [-105.9154, 39.8914], [-84.4374, 31.1854], [-66.7987, 18.1741], [-72.3295, 42.4719], [-96.6038, 39.1051], - [-83.5038, 35.6904], - [-77.9832, 39.0956], - [-89.7048, 45.9983], - [-121.9338, 45.7908] + [-97.7823, 33.3785], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-111.7979, 40.7839], + [-82.0177, 29.6878], + [-96.443, 38.9459], + [-122.1655, 44.2596], + [-149.143, 68.6698], + [-78.1473, 38.8943] ] }, "properties": { "title": "persistenceRW", - "description": "All summaries for the Daily_Dissolved_oxygen variable for the persistenceRW model. Information for the model is provided as follows: Random walk from the fable package with ensembles used to represent uncertainty.\n The model predicts this variable at the following sites: MAYF, MCDI, MCRA, OKSR, POSE, PRIN, BLUE, BLWA, CARI, COMO, CRAM, CUPE, PRLA, PRPO, REDB, SUGG, SYCA, WLOU, ARIK, BARC, BIGC, BLDE, TECR, TOMB, TOOK, WALK, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Dissolved_oxygen variable for the persistenceRW model. Information for the model is provided as follows: Random walk from the fable package with ensembles used to represent uncertainty.\n The model predicts this variable at the following sites: ARIK, BARC, BIGC, BLDE, BLUE, LECO, LEWI, LIRO, MART, MAYF, SYCA, TECR, TOMB, TOOK, WALK, BLWA, CARI, COMO, CRAM, CUPE, WLOU, FLNT, GUIL, HOPB, KING, PRIN, PRLA, PRPO, REDB, SUGG, MCDI, MCRA, OKSR, POSE.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-08-22", "updated": "2024-08-23", "start_datetime": "2023-11-15T00:00:00Z", @@ -80,40 +80,40 @@ "oxygen", "Daily", "P1D", - "MAYF", - "MCDI", - "MCRA", - "OKSR", - "POSE", - "PRIN", - "BLUE", - "BLWA", - "CARI", - "COMO", - "CRAM", - "CUPE", - "PRLA", - "PRPO", - "REDB", - "SUGG", - "SYCA", - "WLOU", "ARIK", "BARC", "BIGC", "BLDE", + "BLUE", + "LECO", + "LEWI", + "LIRO", + "MART", + "MAYF", + "SYCA", "TECR", "TOMB", "TOOK", "WALK", + "BLWA", + "CARI", + "COMO", + "CRAM", + "CUPE", + "WLOU", "FLNT", "GUIL", "HOPB", "KING", - "LECO", - "LEWI", - "LIRO", - "MART" + "PRIN", + "PRLA", + "PRPO", + "REDB", + "SUGG", + "MCDI", + "MCRA", + "OKSR", + "POSE" ], "table:columns": [ { diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/collection.json b/catalog/summaries/Aquatics/Daily_Water_temperature/collection.json index 2f48280152..3754ec4f35 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/collection.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/collection.json @@ -21,62 +21,62 @@ { "rel": "item", "type": "application/json", - "href": "./models/fTSLM_lag.json" + "href": "./models/tg_precip_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGLM.json" + "href": "./models/tg_precip_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGLM_noDA.json" + "href": "./models/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGOTM_noDA.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareSimstrat_noDA.json" + "href": "./models/fTSLM_lag.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flare_ler.json" + "href": "./models/flareGLM.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flare_ler_baselines.json" + "href": "./models/flareGLM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/flareGOTM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm.json" + "href": "./models/flareSimstrat_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm_all_sites.json" + "href": "./models/flare_ler.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_randfor.json" + "href": "./models/flare_ler_baselines.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", @@ -96,12 +96,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/climatology.json" }, { "rel": "item", @@ -111,12 +111,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/cb_prophet.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "item", @@ -131,17 +131,17 @@ { "rel": "item", "type": "application/json", - "href": "./models/air2waterSat_2.json" + "href": "./models/GLEON_physics.json" }, { "rel": "item", "type": "application/json", - "href": "./models/baseline_ensemble.json" + "href": "./models/air2waterSat_2.json" }, { "rel": "item", "type": "application/json", - "href": "./models/GLEON_physics.json" + "href": "./models/baseline_ensemble.json" }, { "rel": "item", @@ -156,37 +156,37 @@ { "rel": "item", "type": "application/json", - "href": "./models/lm_AT_WTL_WS.json" + "href": "./models/zimmerman_proj1.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mkricheldorf_w_lag.json" + "href": "./models/bee_bake_RFModel_2024.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mlp1_wtempforecast_LF.json" + "href": "./models/GAM_air_wind.json" }, { "rel": "item", "type": "application/json", - "href": "./models/zimmerman_proj1.json" + "href": "./models/TSLM_seasonal_JM.json" }, { "rel": "item", "type": "application/json", - "href": "./models/GAM_air_wind.json" + "href": "./models/lm_AT_WTL_WS.json" }, { "rel": "item", "type": "application/json", - "href": "./models/TSLM_seasonal_JM.json" + "href": "./models/mlp1_wtempforecast_LF.json" }, { "rel": "item", "type": "application/json", - "href": "./models/bee_bake_RFModel_2024.json" + "href": "./models/mkricheldorf_w_lag.json" }, { "rel": "item", diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/air2waterSat_2.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/air2waterSat_2.json index 2743630a8d..cae449c10b 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/air2waterSat_2.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/air2waterSat_2.json @@ -9,9 +9,7 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-149.6106, 68.6307], - [-84.2793, 35.9574], - [-105.9154, 39.8914], + [-77.9832, 39.0956], [-89.7048, 45.9983], [-121.9338, 45.7908], [-87.4077, 32.9604], @@ -42,12 +40,14 @@ [-72.3295, 42.4719], [-96.6038, 39.1051], [-83.5038, 35.6904], - [-77.9832, 39.0956] + [-149.6106, 68.6307], + [-84.2793, 35.9574], + [-105.9154, 39.8914] ] }, "properties": { "title": "air2waterSat_2", - "description": "All summaries for the Daily_Water_temperature variable for the air2waterSat_2 model. Information for the model is provided as follows: The air2water model is a linear model fit using the function lm() in R and uses air temperature as\na covariate.\n The model predicts this variable at the following sites: TOOK, WALK, WLOU, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the air2waterSat_2 model. Information for the model is provided as follows: The air2water model is a linear model fit using the function lm() in R and uses air temperature as\na covariate.\n The model predicts this variable at the following sites: LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, TOOK, WALK, WLOU.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-01", "updated": "2024-02-02", "start_datetime": "2023-11-14T00:00:00Z", @@ -80,9 +80,7 @@ "temperature", "Daily", "P1D", - "TOOK", - "WALK", - "WLOU", + "LEWI", "LIRO", "MART", "MAYF", @@ -113,7 +111,9 @@ "HOPB", "KING", "LECO", - "LEWI" + "TOOK", + "WALK", + "WLOU" ], "table:columns": [ { diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json index d87e98ca65..038e0ae87e 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json @@ -9,6 +9,9 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-96.443, 38.9459], + [-122.1655, 44.2596], + [-78.1473, 38.8943], [-87.7982, 32.5415], [-105.5442, 40.035], [-66.9868, 18.1135], @@ -26,9 +29,6 @@ [-77.9832, 39.0956], [-121.9338, 45.7908], [-87.4077, 32.9604], - [-96.443, 38.9459], - [-122.1655, 44.2596], - [-78.1473, 38.8943], [-97.7823, 33.3785], [-111.7979, 40.7839], [-102.4471, 39.7582], @@ -47,7 +47,7 @@ }, "properties": { "title": "baseline_ensemble", - "description": "All summaries for the Daily_Water_temperature variable for the baseline_ensemble model. Information for the model is provided as follows: The Baseline MME is a multi-model ensemble (MME) comprised of the two baseline models\n(day-of-year, persistence) submitted by Challenge organisers.\n The model predicts this variable at the following sites: BLWA, COMO, CUPE, FLNT, GUIL, HOPB, SUGG, SYCA, TECR, TOMB, WALK, WLOU, KING, LECO, LEWI, MART, MAYF, MCDI, MCRA, POSE, PRIN, REDB, ARIK, BARC, BIGC, BLDE, BLUE, CRAM, LIRO, PRLA, PRPO, CARI, OKSR, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the baseline_ensemble model. Information for the model is provided as follows: The Baseline MME is a multi-model ensemble (MME) comprised of the two baseline models\n(day-of-year, persistence) submitted by Challenge organisers.\n The model predicts this variable at the following sites: MCDI, MCRA, POSE, BLWA, COMO, CUPE, FLNT, GUIL, HOPB, SUGG, SYCA, TECR, TOMB, WALK, WLOU, KING, LECO, LEWI, MART, MAYF, PRIN, REDB, ARIK, BARC, BIGC, BLDE, BLUE, CRAM, LIRO, PRLA, PRPO, CARI, OKSR, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": null, "start_datetime": "2023-11-14T00:00:00Z", @@ -80,6 +80,9 @@ "temperature", "Daily", "P1D", + "MCDI", + "MCRA", + "POSE", "BLWA", "COMO", "CUPE", @@ -97,9 +100,6 @@ "LEWI", "MART", "MAYF", - "MCDI", - "MCRA", - "POSE", "PRIN", "REDB", "ARIK", diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json index b5989ae2db..ab74862299 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json @@ -10,17 +10,17 @@ "type": "MultiPoint", "coordinates": [ [-89.4737, 46.2097], - [-99.2531, 47.1298], - [-89.7048, 45.9983], - [-99.1139, 47.1591], [-82.0084, 29.676], + [-99.1139, 47.1591], [-82.0177, 29.6878], + [-99.2531, 47.1298], + [-89.7048, 45.9983], [-149.6106, 68.6307] ] }, "properties": { "title": "bee_bake_RFModel_2024", - "description": "All summaries for the Daily_Water_temperature variable for the bee_bake_RFModel_2024 model. Information for the model is provided as follows: Random Forest.\n The model predicts this variable at the following sites: CRAM, PRPO, LIRO, PRLA, BARC, SUGG, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the bee_bake_RFModel_2024 model. Information for the model is provided as follows: Random Forest.\n The model predicts this variable at the following sites: CRAM, BARC, PRLA, SUGG, PRPO, LIRO, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-08-22", "updated": "2024-08-23", "start_datetime": "2024-02-29T00:00:00Z", @@ -54,11 +54,11 @@ "Daily", "P1D", "CRAM", - "PRPO", - "LIRO", - "PRLA", "BARC", + "PRLA", "SUGG", + "PRPO", + "LIRO", "TOOK" ], "table:columns": [ diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json index 7a7524f23f..9a42c3157c 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json @@ -34,8 +34,8 @@ [-88.1589, 31.8534], [-119.2575, 37.0597], [-110.5871, 44.9501], - [-84.4374, 31.1854], [-89.4737, 46.2097], + [-84.4374, 31.1854], [-111.5081, 33.751], [-89.7048, 45.9983], [-99.1139, 47.1591], @@ -47,7 +47,7 @@ }, "properties": { "title": "fARIMA_clim_ensemble", - "description": "All summaries for the Daily_Water_temperature variable for the fARIMA_clim_ensemble model. Information for the model is provided as follows: The fAMIRA-DOY MME is a multi-model ensemble (MME) composed of two empirical\nmodels: an ARIMA model (fARIMA) and day-of-year model.\n The model predicts this variable at the following sites: LECO, LEWI, MART, MAYF, MCDI, MCRA, COMO, CUPE, GUIL, HOPB, KING, ARIK, BARC, BLUE, BLWA, WALK, WLOU, POSE, PRIN, REDB, SUGG, TECR, TOMB, BIGC, BLDE, FLNT, CRAM, SYCA, LIRO, PRLA, PRPO, CARI, OKSR, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the fARIMA_clim_ensemble model. Information for the model is provided as follows: The fAMIRA-DOY MME is a multi-model ensemble (MME) composed of two empirical\nmodels: an ARIMA model (fARIMA) and day-of-year model.\n The model predicts this variable at the following sites: LECO, LEWI, MART, MAYF, MCDI, MCRA, COMO, CUPE, GUIL, HOPB, KING, ARIK, BARC, BLUE, BLWA, WALK, WLOU, POSE, PRIN, REDB, SUGG, TECR, TOMB, BIGC, BLDE, CRAM, FLNT, SYCA, LIRO, PRLA, PRPO, CARI, OKSR, TOOK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": null, "start_datetime": "2023-11-10T00:00:00Z", @@ -105,8 +105,8 @@ "TOMB", "BIGC", "BLDE", - "FLNT", "CRAM", + "FLNT", "SYCA", "LIRO", "PRLA", diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/hotdeck.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/hotdeck.json index ac2cf0798c..6fedb4d081 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/hotdeck.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/hotdeck.json @@ -30,20 +30,20 @@ [-105.5442, 40.035], [-105.9154, 39.8914], [-89.4737, 46.2097], - [-89.7048, 45.9983], - [-99.1139, 47.1591], - [-99.2531, 47.1298], [-147.504, 65.1532], [-119.2575, 37.0597], [-96.6242, 34.4442], [-66.9868, 18.1135], [-66.7987, 18.1741], - [-84.2793, 35.9574] + [-84.2793, 35.9574], + [-89.7048, 45.9983], + [-99.1139, 47.1591], + [-99.2531, 47.1298] ] }, "properties": { "title": "hotdeck", - "description": "All summaries for the Daily_Water_temperature variable for the hotdeck model. Information for the model is provided as follows: Uses a hot deck approach: - Take the latest observation/forecast. - Past observations from around the same window of the season are collected. - Values close to the latest observation/forecast are collected. - One of these is randomly sampled. - Its \"tomorrow\" observation is used as the forecast. - Repeat until forecast at step h..\n The model predicts this variable at the following sites: BARC, SUGG, TOMB, BLWA, FLNT, MCRA, KING, SYCA, POSE, PRIN, MAYF, LEWI, LECO, ARIK, HOPB, REDB, TECR, BLDE, COMO, WLOU, CRAM, LIRO, PRLA, PRPO, CARI, BIGC, BLUE, CUPE, GUIL, WALK.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the hotdeck model. Information for the model is provided as follows: Uses a hot deck approach: - Take the latest observation/forecast. - Past observations from around the same window of the season are collected. - Values close to the latest observation/forecast are collected. - One of these is randomly sampled. - Its \"tomorrow\" observation is used as the forecast. - Repeat until forecast at step h..\n The model predicts this variable at the following sites: BARC, SUGG, TOMB, BLWA, FLNT, MCRA, KING, SYCA, POSE, PRIN, MAYF, LEWI, LECO, ARIK, HOPB, REDB, TECR, BLDE, COMO, WLOU, CRAM, CARI, BIGC, BLUE, CUPE, GUIL, WALK, LIRO, PRLA, PRPO.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-08-22", "updated": "2024-08-23", "start_datetime": "2024-02-28T00:00:00Z", @@ -97,15 +97,15 @@ "COMO", "WLOU", "CRAM", - "LIRO", - "PRLA", - "PRPO", "CARI", "BIGC", "BLUE", "CUPE", "GUIL", - "WALK" + "WALK", + "LIRO", + "PRLA", + "PRPO" ], "table:columns": [ { diff --git a/catalog/summaries/Aquatics/Daily_Water_temperature/models/tg_temp_lm.json b/catalog/summaries/Aquatics/Daily_Water_temperature/models/tg_temp_lm.json index d7bfd8c6df..059eb783f2 100644 --- a/catalog/summaries/Aquatics/Daily_Water_temperature/models/tg_temp_lm.json +++ b/catalog/summaries/Aquatics/Daily_Water_temperature/models/tg_temp_lm.json @@ -9,6 +9,9 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-149.6106, 68.6307], + [-84.2793, 35.9574], + [-105.9154, 39.8914], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -39,15 +42,12 @@ [-82.0177, 29.6878], [-111.5081, 33.751], [-119.0274, 36.9559], - [-88.1589, 31.8534], - [-149.6106, 68.6307], - [-84.2793, 35.9574], - [-105.9154, 39.8914] + [-88.1589, 31.8534] ] }, "properties": { "title": "tg_temp_lm", - "description": "All summaries for the Daily_Water_temperature variable for the tg_temp_lm model. Information for the model is provided as follows: The tg_temp_lm model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation..\n The model predicts this variable at the following sites: ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, TOOK, WALK, WLOU.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Water_temperature variable for the tg_temp_lm model. Information for the model is provided as follows: The tg_temp_lm model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation..\n The model predicts this variable at the following sites: TOOK, WALK, WLOU, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-02", "start_datetime": "2023-11-14T00:00:00Z", @@ -80,6 +80,9 @@ "temperature", "Daily", "P1D", + "TOOK", + "WALK", + "WLOU", "ARIK", "BARC", "BIGC", @@ -110,10 +113,7 @@ "SUGG", "SYCA", "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU" + "TOMB" ], "table:columns": [ { diff --git a/catalog/summaries/Beetles/Weekly_beetle_community_abundance/collection.json b/catalog/summaries/Beetles/Weekly_beetle_community_abundance/collection.json index 55db57408c..82ef8b026f 100644 --- a/catalog/summaries/Beetles/Weekly_beetle_community_abundance/collection.json +++ b/catalog/summaries/Beetles/Weekly_beetle_community_abundance/collection.json @@ -56,12 +56,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm_all_sites.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/tg_precip_lm_all_sites.json" }, { "rel": "parent", diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/collection.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/collection.json index dfa00b1325..aeb2189be5 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/collection.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/collection.json @@ -11,47 +11,42 @@ { "rel": "item", "type": "application/json", - "href": "./models/cb_prophet.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_humidity_lm.json" + "href": "./models/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/tg_humidity_lm.json" }, { "rel": "item", @@ -78,6 +73,11 @@ "type": "application/json", "href": "./models/tg_randfor.json" }, + { + "rel": "item", + "type": "application/json", + "href": "./models/tg_ets.json" + }, { "rel": "item", "type": "application/json", diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/cb_prophet.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/cb_prophet.json index d53ab2b048..cba5c2b0a0 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/cb_prophet.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/cb_prophet.json @@ -9,21 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-76.56, 38.8901], - [-119.7323, 37.1088], - [-119.2622, 37.0334], - [-110.8355, 31.9107], - [-89.5864, 45.5089], - [-103.0293, 40.4619], - [-87.3933, 32.9505], - [-119.006, 37.0058], - [-149.3705, 68.6611], - [-89.5857, 45.4937], - [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -55,12 +40,27 @@ [-81.9934, 29.6893], [-155.3173, 19.5531], [-105.546, 40.2759], - [-78.1395, 38.8929] + [-78.1395, 38.8929], + [-76.56, 38.8901], + [-119.7323, 37.1088], + [-119.2622, 37.0334], + [-110.8355, 31.9107], + [-89.5864, 45.5089], + [-103.0293, 40.4619], + [-87.3933, 32.9505], + [-119.006, 37.0058], + [-149.3705, 68.6611], + [-89.5857, 45.4937], + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535] ] }, "properties": { "title": "cb_prophet", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the cb_prophet model. Information for the model is provided as follows: The Prophet model is an empirical model, specifically a non-linear regression model that includes\nseasonality effects (Taylor & Letham, 2018). The model relies on Bayesian estimation with an additive\nwhite noise error term.\n The model predicts this variable at the following sites: SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the cb_prophet model. Information for the model is provided as follows: The Prophet model is an empirical model, specifically a non-linear regression model that includes\nseasonality effects (Taylor & Letham, 2018). The model relies on Bayesian estimation with an additive\nwhite noise error term.\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-06", "updated": "2024-02-07", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,21 +93,6 @@ "gcc_90", "Daily", "P1D", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -139,7 +124,22 @@ "OSBS", "PUUM", "RMNP", - "SCBI" + "SCBI", + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json index b5c8caf00b..f96f39aad9 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json @@ -54,13 +54,13 @@ [-147.5026, 65.154], [-145.7514, 63.8811], [-149.2133, 63.8758], - [-149.3705, 68.6611], - [-156.6194, 71.2824] + [-156.6194, 71.2824], + [-149.3705, 68.6611] ] }, "properties": { "title": "climatology", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the climatology model. Information for the model is provided as follows: Historical DOY mean and sd. Assumes normal distribution.\n The model predicts this variable at the following sites: ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, DSNY, GRSM, GUAN, HARV, 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, TREE, UKFS, UNDE, WOOD, WREF, YELL, BONA, DEJU, HEAL, TOOL, BARR.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the climatology model. Information for the model is provided as follows: Historical DOY mean and sd. Assumes normal distribution.\n The model predicts this variable at the following sites: ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, DSNY, GRSM, GUAN, HARV, 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, TREE, UKFS, UNDE, WOOD, WREF, YELL, BONA, DEJU, HEAL, BARR, TOOL.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-11-15T00:00:00Z", @@ -138,8 +138,8 @@ "BONA", "DEJU", "HEAL", - "TOOL", - "BARR" + "BARR", + "TOOL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json index c839d18b50..19d8e09d79 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json @@ -20,38 +20,38 @@ [-104.7456, 40.8155], [-99.1066, 47.1617], [-145.7514, 63.8811], + [-81.9934, 29.6893], + [-155.3173, 19.5531], + [-105.546, 40.2759], + [-78.1395, 38.8929], + [-76.56, 38.8901], [-119.7323, 37.1088], + [-67.0769, 18.0213], + [-88.1612, 31.8539], + [-80.5248, 37.3783], + [-109.3883, 38.2483], + [-105.5824, 40.0543], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535], + [-100.9154, 46.7697], [-119.2622, 37.0334], [-110.8355, 31.9107], [-89.5864, 45.5089], [-103.0293, 40.4619], [-87.3933, 32.9505], - [-100.9154, 46.7697], - [-99.0588, 35.4106], - [-112.4524, 40.1776], - [-84.2826, 35.9641], - [-81.9934, 29.6893], [-119.006, 37.0058], [-149.3705, 68.6611], [-89.5857, 45.4937], [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-67.0769, 18.0213], - [-88.1612, 31.8539], - [-80.5248, 37.3783], - [-109.3883, 38.2483], - [-105.5824, 40.0543], - [-155.3173, 19.5531], - [-105.546, 40.2759], - [-78.1395, 38.8929], - [-76.56, 38.8901], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], [-78.0418, 39.0337], + [-99.0588, 35.4106], + [-112.4524, 40.1776], + [-84.2826, 35.9641], [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], @@ -60,7 +60,7 @@ }, "properties": { "title": "persistenceRW", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the persistenceRW model. Information for the model is provided as follows: Random walk from the fable package with ensembles used to represent uncertainty.\n The model predicts this variable at the following sites: DELA, DSNY, GRSM, GUAN, HARV, HEAL, BONA, CLBJ, CPER, DCFS, DEJU, SJER, SOAP, SRER, STEI, STER, TALL, NOGP, OAES, ONAQ, ORNL, OSBS, TEAK, TOOL, TREE, UKFS, UNDE, LAJA, LENO, MLBS, MOAB, NIWO, PUUM, RMNP, SCBI, SERC, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, JERC, JORN, KONA, KONZ.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the persistenceRW model. Information for the model is provided as follows: Random walk from the fable package with ensembles used to represent uncertainty.\n The model predicts this variable at the following sites: DELA, DSNY, GRSM, GUAN, HARV, HEAL, BONA, CLBJ, CPER, DCFS, DEJU, OSBS, PUUM, RMNP, SCBI, SERC, SJER, LAJA, LENO, MLBS, MOAB, NIWO, UNDE, WOOD, WREF, YELL, NOGP, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, ABBY, BARR, BART, BLAN, OAES, ONAQ, ORNL, JERC, JORN, KONA, KONZ.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-11-15T00:00:00Z", @@ -104,38 +104,38 @@ "CPER", "DCFS", "DEJU", + "OSBS", + "PUUM", + "RMNP", + "SCBI", + "SERC", "SJER", + "LAJA", + "LENO", + "MLBS", + "MOAB", + "NIWO", + "UNDE", + "WOOD", + "WREF", + "YELL", + "NOGP", "SOAP", "SRER", "STEI", "STER", "TALL", - "NOGP", - "OAES", - "ONAQ", - "ORNL", - "OSBS", "TEAK", "TOOL", "TREE", "UKFS", - "UNDE", - "LAJA", - "LENO", - "MLBS", - "MOAB", - "NIWO", - "PUUM", - "RMNP", - "SCBI", - "SERC", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", "BLAN", + "OAES", + "ONAQ", + "ORNL", "JERC", "JORN", "KONA", diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json index 702dd10a34..cdb35d9166 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json @@ -9,6 +9,10 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -51,16 +55,12 @@ [-119.006, 37.0058], [-149.3705, 68.6611], [-89.5857, 45.4937], - [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535] + [-95.1921, 39.0404] ] }, "properties": { "title": "tg_arima", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_arima model. Information for the model is provided as follows: The tg_arima model is an AutoRegressive Integrated Moving Average (ARIMA) model fit using\nthe function auto.arima() from the forecast package in R (Hyndman et al. 2023; Hyndman et al., 2008).\nThis is an empirical time series model with no covariates.\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_arima model. Information for the model is provided as follows: The tg_arima model is an AutoRegressive Integrated Moving Average (ARIMA) model fit using\nthe function auto.arima() from the forecast package in R (Hyndman et al. 2023; Hyndman et al., 2008).\nThis is an empirical time series model with no covariates.\n The model predicts this variable at the following sites: UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-01-07T00:00:00Z", @@ -93,6 +93,10 @@ "gcc_90", "Daily", "P1D", + "UNDE", + "WOOD", + "WREF", + "YELL", "ABBY", "BARR", "BART", @@ -135,11 +139,7 @@ "TEAK", "TOOL", "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL" + "UKFS" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_humidity_lm.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_humidity_lm.json index 3980bc84a0..b6a326a544 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_humidity_lm.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_humidity_lm.json @@ -9,6 +9,23 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-149.2133, 63.8758], + [-84.4686, 31.1948], + [-106.8425, 32.5907], + [-96.6129, 39.1104], + [-96.5631, 39.1008], + [-67.0769, 18.0213], + [-88.1612, 31.8539], + [-80.5248, 37.3783], + [-109.3883, 38.2483], + [-105.5824, 40.0543], + [-100.9154, 46.7697], + [-99.0588, 35.4106], + [-112.4524, 40.1776], + [-84.2826, 35.9641], + [-81.9934, 29.6893], + [-155.3173, 19.5531], + [-105.546, 40.2759], [-78.1395, 38.8929], [-76.56, 38.8901], [-119.7323, 37.1088], @@ -34,23 +51,6 @@ [-104.7456, 40.8155], [-99.1066, 47.1617], [-145.7514, 63.8811], - [-149.2133, 63.8758], - [-84.4686, 31.1948], - [-106.8425, 32.5907], - [-96.6129, 39.1104], - [-96.5631, 39.1008], - [-67.0769, 18.0213], - [-88.1612, 31.8539], - [-80.5248, 37.3783], - [-109.3883, 38.2483], - [-105.5824, 40.0543], - [-100.9154, 46.7697], - [-99.0588, 35.4106], - [-112.4524, 40.1776], - [-84.2826, 35.9641], - [-81.9934, 29.6893], - [-155.3173, 19.5531], - [-105.546, 40.2759], [-87.8039, 32.5417], [-81.4362, 28.1251], [-83.5019, 35.689], @@ -60,7 +60,7 @@ }, "properties": { "title": "tg_humidity_lm", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_humidity_lm model. Information for the model is provided as follows: The tg_humidity_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity.\n The model predicts this variable at the following sites: SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, DELA, DSNY, GRSM, GUAN, HARV.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_humidity_lm model. Information for the model is provided as follows: The tg_humidity_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity.\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,23 @@ "gcc_90", "Daily", "P1D", + "HEAL", + "JERC", + "JORN", + "KONA", + "KONZ", + "LAJA", + "LENO", + "MLBS", + "MOAB", + "NIWO", + "NOGP", + "OAES", + "ONAQ", + "ORNL", + "OSBS", + "PUUM", + "RMNP", "SCBI", "SERC", "SJER", @@ -118,23 +135,6 @@ "CPER", "DCFS", "DEJU", - "HEAL", - "JERC", - "JORN", - "KONA", - "KONZ", - "LAJA", - "LENO", - "MLBS", - "MOAB", - "NIWO", - "NOGP", - "OAES", - "ONAQ", - "ORNL", - "OSBS", - "PUUM", - "RMNP", "DELA", "DSNY", "GRSM", diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json index 49eb2507d0..a2fd3c5592 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json @@ -9,19 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-76.56, 38.8901], - [-119.7323, 37.1088], - [-119.2622, 37.0334], - [-110.8355, 31.9107], - [-89.5864, 45.5089], - [-103.0293, 40.4619], - [-87.3933, 32.9505], - [-119.006, 37.0058], - [-149.3705, 68.6611], - [-89.5857, 45.4937], - [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-99.2413, 47.1282], [-121.9519, 45.8205], [-110.5391, 44.9535], [-122.3303, 45.7624], @@ -55,12 +42,25 @@ [-81.9934, 29.6893], [-155.3173, 19.5531], [-105.546, 40.2759], - [-78.1395, 38.8929] + [-78.1395, 38.8929], + [-76.56, 38.8901], + [-119.7323, 37.1088], + [-119.2622, 37.0334], + [-110.8355, 31.9107], + [-89.5864, 45.5089], + [-103.0293, 40.4619], + [-87.3933, 32.9505], + [-119.006, 37.0058], + [-149.3705, 68.6611], + [-89.5857, 45.4937], + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282] ] }, "properties": { "title": "tg_tbats", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: 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, WOOD.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-08-23", "start_datetime": "2023-01-01T00:00:00Z", @@ -93,19 +93,6 @@ "gcc_90", "Daily", "P1D", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", "WREF", "YELL", "ABBY", @@ -139,7 +126,20 @@ "OSBS", "PUUM", "RMNP", - "SCBI" + "SCBI", + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_temp_lm.json b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_temp_lm.json index a45a8253f5..6929bda8ca 100644 --- a/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_temp_lm.json +++ b/catalog/summaries/Phenology/Daily_Green_chromatic_coordinate/models/tg_temp_lm.json @@ -9,6 +9,22 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-78.1395, 38.8929], + [-76.56, 38.8901], + [-119.7323, 37.1088], + [-119.2622, 37.0334], + [-110.8355, 31.9107], + [-89.5864, 45.5089], + [-103.0293, 40.4619], + [-87.3933, 32.9505], + [-119.006, 37.0058], + [-149.3705, 68.6611], + [-89.5857, 45.4937], + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -39,28 +55,12 @@ [-84.2826, 35.9641], [-81.9934, 29.6893], [-155.3173, 19.5531], - [-105.546, 40.2759], - [-78.1395, 38.8929], - [-76.56, 38.8901], - [-119.7323, 37.1088], - [-119.2622, 37.0334], - [-110.8355, 31.9107], - [-89.5864, 45.5089], - [-103.0293, 40.4619], - [-87.3933, 32.9505], - [-119.006, 37.0058], - [-149.3705, 68.6611], - [-89.5857, 45.4937], - [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535] + [-105.546, 40.2759] ] }, "properties": { "title": "tg_temp_lm", - "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_temp_lm model. Information for the model is provided as follows: The tg_temp_lm model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Green_chromatic_coordinate variable for the tg_temp_lm model. Information for the model is provided as follows: The tg_temp_lm model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation..\n The model predicts this variable at the following sites: SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,22 @@ "gcc_90", "Daily", "P1D", + "SCBI", + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL", "ABBY", "BARR", "BART", @@ -123,23 +139,7 @@ "ORNL", "OSBS", "PUUM", - "RMNP", - "SCBI", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL" + "RMNP" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/collection.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/collection.json index ad59d2180b..49b16ce2de 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/collection.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/collection.json @@ -11,7 +11,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/baseline_ensemble.json" + "href": "./models/tg_arima.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "./models/tg_ets.json" }, { "rel": "item", @@ -21,7 +26,7 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/baseline_ensemble.json" }, { "rel": "item", @@ -46,7 +51,7 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", @@ -61,12 +66,7 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" - }, - { - "rel": "item", - "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json index 9de6a7ec63..d2d2cb888d 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json @@ -54,13 +54,13 @@ [-145.7514, 63.8811], [-149.2133, 63.8758], [-147.5026, 65.154], - [-149.3705, 68.6611], - [-156.6194, 71.2824] + [-156.6194, 71.2824], + [-149.3705, 68.6611] ] }, "properties": { "title": "climatology", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the climatology model. Information for the model is provided as follows: Historical DOY mean and sd. Assumes normal distribution.\n The model predicts this variable at the following sites: ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, DSNY, GRSM, GUAN, HARV, 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, TREE, UKFS, UNDE, WOOD, WREF, YELL, DEJU, HEAL, BONA, TOOL, BARR.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the climatology model. Information for the model is provided as follows: Historical DOY mean and sd. Assumes normal distribution.\n The model predicts this variable at the following sites: ABBY, BART, BLAN, CLBJ, CPER, DCFS, DELA, DSNY, GRSM, GUAN, HARV, 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, TREE, UKFS, UNDE, WOOD, WREF, YELL, DEJU, HEAL, BONA, BARR, TOOL.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-11-15T00:00:00Z", @@ -138,8 +138,8 @@ "DEJU", "HEAL", "BONA", - "TOOL", - "BARR" + "BARR", + "TOOL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json index 9f5775c7ad..a3800aa383 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json @@ -9,6 +9,26 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], + [-84.4686, 31.1948], + [-106.8425, 32.5907], + [-96.6129, 39.1104], + [-96.5631, 39.1008], + [-67.0769, 18.0213], + [-88.1612, 31.8539], + [-80.5248, 37.3783], + [-109.3883, 38.2483], + [-105.5824, 40.0543], + [-100.9154, 46.7697], + [-99.0588, 35.4106], + [-112.4524, 40.1776], + [-84.2826, 35.9641], + [-81.9934, 29.6893], [-155.3173, 19.5531], [-105.546, 40.2759], [-78.1395, 38.8929], @@ -35,32 +55,12 @@ [-97.57, 33.4012], [-104.7456, 40.8155], [-99.1066, 47.1617], - [-145.7514, 63.8811], - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], - [-66.8687, 17.9696], - [-72.1727, 42.5369], - [-149.2133, 63.8758], - [-84.4686, 31.1948], - [-106.8425, 32.5907], - [-96.6129, 39.1104], - [-96.5631, 39.1008], - [-67.0769, 18.0213], - [-88.1612, 31.8539], - [-80.5248, 37.3783], - [-109.3883, 38.2483], - [-105.5824, 40.0543], - [-100.9154, 46.7697], - [-99.0588, 35.4106], - [-112.4524, 40.1776], - [-84.2826, 35.9641], - [-81.9934, 29.6893] + [-145.7514, 63.8811] ] }, "properties": { "title": "tg_arima", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_arima model. Information for the model is provided as follows: The tg_arima model is an AutoRegressive Integrated Moving Average (ARIMA) model fit using\nthe function auto.arima() from the forecast package in R (Hyndman et al. 2023; Hyndman et al., 2008).\nThis is an empirical time series model with no covariates.\n The model predicts this variable at the following sites: PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_arima model. Information for the model is provided as follows: The tg_arima model is an AutoRegressive Integrated Moving Average (ARIMA) model fit using\nthe function auto.arima() from the forecast package in R (Hyndman et al. 2023; Hyndman et al., 2008).\nThis is an empirical time series model with no covariates.\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-01-07T00:00:00Z", @@ -93,6 +93,26 @@ "rcc_90", "Daily", "P1D", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", + "JERC", + "JORN", + "KONA", + "KONZ", + "LAJA", + "LENO", + "MLBS", + "MOAB", + "NIWO", + "NOGP", + "OAES", + "ONAQ", + "ORNL", + "OSBS", "PUUM", "RMNP", "SCBI", @@ -119,27 +139,7 @@ "CLBJ", "CPER", "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL", - "JERC", - "JORN", - "KONA", - "KONZ", - "LAJA", - "LENO", - "MLBS", - "MOAB", - "NIWO", - "NOGP", - "OAES", - "ONAQ", - "ORNL", - "OSBS" + "DEJU" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json index cd67350f18..630fb62435 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json @@ -9,26 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-84.2826, 35.9641], - [-81.9934, 29.6893], - [-155.3173, 19.5531], - [-105.546, 40.2759], - [-78.1395, 38.8929], - [-76.56, 38.8901], - [-119.7323, 37.1088], - [-119.2622, 37.0334], - [-110.8355, 31.9107], - [-89.5864, 45.5089], - [-103.0293, 40.4619], - [-87.3933, 32.9505], - [-119.006, 37.0058], - [-149.3705, 68.6611], - [-89.5857, 45.4937], - [-95.1921, 39.0404], - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -55,12 +35,32 @@ [-105.5824, 40.0543], [-100.9154, 46.7697], [-99.0588, 35.4106], - [-112.4524, 40.1776] + [-112.4524, 40.1776], + [-84.2826, 35.9641], + [-81.9934, 29.6893], + [-155.3173, 19.5531], + [-105.546, 40.2759], + [-78.1395, 38.8929], + [-76.56, 38.8901], + [-119.7323, 37.1088], + [-119.2622, 37.0334], + [-110.8355, 31.9107], + [-89.5864, 45.5089], + [-103.0293, 40.4619], + [-87.3933, 32.9505], + [-119.006, 37.0058], + [-149.3705, 68.6611], + [-89.5857, 45.4937], + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_ets", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_ets model. Information for the model is provided as follows: The tg_ets model is an Error, Trend, Seasonal (ETS) model fit using the function ets() from the\nforecast package in R (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series\nmodel with no covariates..\n The model predicts this variable at the following sites: ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_ets model. Information for the model is provided as follows: The tg_ets model is an Error, Trend, Seasonal (ETS) model fit using the function ets() from the\nforecast package in R (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series\nmodel with no covariates..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-07-04", "start_datetime": "2023-01-07T00:00:00Z", @@ -93,26 +93,6 @@ "rcc_90", "Daily", "P1D", - "ORNL", - "OSBS", - "PUUM", - "RMNP", - "SCBI", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -139,7 +119,27 @@ "NIWO", "NOGP", "OAES", - "ONAQ" + "ONAQ", + "ORNL", + "OSBS", + "PUUM", + "RMNP", + "SCBI", + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_lasso.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_lasso.json index 28087e2beb..42d6bd1a8b 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_lasso.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_lasso.json @@ -9,9 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], [-66.8687, 17.9696], [-72.1727, 42.5369], [-149.2133, 63.8758], @@ -55,12 +52,15 @@ [-97.57, 33.4012], [-104.7456, 40.8155], [-99.1066, 47.1617], - [-145.7514, 63.8811] + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689] ] }, "properties": { "title": "tg_lasso", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_lasso model. Information for the model is provided as follows: Lasso is a machine learning model implemented in the same workflow as tg_randfor, but with\ndifferent hyperparameter tuning. The model drivers are unlagged air temperature, air pressure, relative\nhumidity, surface downwelling longwave and shortwave radiation, precipitation, and northward and\neastward wind. Lasso regressions were fitted with the function glmnet() in\nthe package glmnet (Tay et al. 2023), where the regularization hyperparameter (lambda) is tuned and\nselected with 10-fold cross validation..\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_lasso model. Information for the model is provided as follows: Lasso is a machine learning model implemented in the same workflow as tg_randfor, but with\ndifferent hyperparameter tuning. The model drivers are unlagged air temperature, air pressure, relative\nhumidity, surface downwelling longwave and shortwave radiation, precipitation, and northward and\neastward wind. Lasso regressions were fitted with the function glmnet() in\nthe package glmnet (Tay et al. 2023), where the regularization hyperparameter (lambda) is tuned and\nselected with 10-fold cross validation..\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-01-31", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,9 +93,6 @@ "rcc_90", "Daily", "P1D", - "DELA", - "DSNY", - "GRSM", "GUAN", "HARV", "HEAL", @@ -139,7 +136,10 @@ "CLBJ", "CPER", "DCFS", - "DEJU" + "DEJU", + "DELA", + "DSNY", + "GRSM" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm.json index 889b4e7a42..8877238a17 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm.json @@ -9,6 +9,21 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], @@ -40,27 +55,12 @@ [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], - [-110.5391, 44.9535], - [-122.3303, 45.7624], - [-156.6194, 71.2824], - [-71.2874, 44.0639], - [-78.0418, 39.0337], - [-147.5026, 65.154], - [-97.57, 33.4012], - [-104.7456, 40.8155], - [-99.1066, 47.1617], - [-145.7514, 63.8811], - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], - [-66.8687, 17.9696], - [-72.1727, 42.5369], - [-149.2133, 63.8758] + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_precip_lm", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_precip_lm model. Information for the model is provided as follows: The tg_precip_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only total precipitation used as a model covariate..\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_precip_lm model. Information for the model is provided as follows: The tg_precip_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only total precipitation used as a model covariate..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,21 @@ "rcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", "JERC", "JORN", "KONA", @@ -124,22 +139,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL" + "YELL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm_all_sites.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm_all_sites.json index efb080feb8..ae50384cf4 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm_all_sites.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_precip_lm_all_sites.json @@ -9,18 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-122.3303, 45.7624], - [-156.6194, 71.2824], - [-71.2874, 44.0639], - [-78.0418, 39.0337], - [-147.5026, 65.154], - [-97.57, 33.4012], - [-104.7456, 40.8155], - [-99.1066, 47.1617], - [-145.7514, 63.8811], - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], [-66.8687, 17.9696], [-72.1727, 42.5369], [-149.2133, 63.8758], @@ -55,12 +43,24 @@ [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], - [-110.5391, 44.9535] + [-110.5391, 44.9535], + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689] ] }, "properties": { "title": "tg_precip_lm_all_sites", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_precip_lm_all_sites model. Information for the model is provided as follows: The tg_precip_lm_all_sites model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation. y. This model was used to forecast water temperature and dissolved oxygen\nconcentration at the seven lake sites, with the model fitted for all sites together..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_precip_lm_all_sites model. Information for the model is provided as follows: The tg_precip_lm_all_sites model is a linear model fit using the function lm() in R. This is a very\nsimple model with only one covariate: total precipitation. y. This model was used to forecast water temperature and dissolved oxygen\nconcentration at the seven lake sites, with the model fitted for all sites together..\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-01-31", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,18 +93,6 @@ "rcc_90", "Daily", "P1D", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", "GUAN", "HARV", "HEAL", @@ -139,7 +127,19 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_randfor.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_randfor.json index 94a1ac62e0..bed8d13cf5 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_randfor.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_randfor.json @@ -9,6 +9,22 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], + [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], [-96.5631, 39.1008], @@ -39,28 +55,12 @@ [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], - [-110.5391, 44.9535], - [-122.3303, 45.7624], - [-156.6194, 71.2824], - [-71.2874, 44.0639], - [-78.0418, 39.0337], - [-147.5026, 65.154], - [-97.57, 33.4012], - [-104.7456, 40.8155], - [-99.1066, 47.1617], - [-145.7514, 63.8811], - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], - [-66.8687, 17.9696], - [-72.1727, 42.5369], - [-149.2133, 63.8758], - [-84.4686, 31.1948] + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_randfor", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_randfor model. Information for the model is provided as follows: Random Forest is a machine learning model that is fitted with the ranger() function in the ranger\nR package (Wright & Ziegler 2017) within the tidymodels framework (Kuhn & Wickham 2020). The\nmodel drivers are unlagged air temperature, air pressure, relative humidity, surface downwelling\nlongwave and shortwave radiation, precipitation, and northward and eastward wind.\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_randfor model. Information for the model is provided as follows: Random Forest is a machine learning model that is fitted with the ranger() function in the ranger\nR package (Wright & Ziegler 2017) within the tidymodels framework (Kuhn & Wickham 2020). The\nmodel drivers are unlagged air temperature, air pressure, relative humidity, surface downwelling\nlongwave and shortwave radiation, precipitation, and northward and eastward wind.\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-01-31", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,22 @@ "rcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", + "JERC", "JORN", "KONA", "KONZ", @@ -123,23 +139,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL", - "JERC" + "YELL" ], "table:columns": [ { diff --git a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json index 6be88c472a..3d434d75d1 100644 --- a/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json +++ b/catalog/summaries/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json @@ -9,10 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -55,12 +51,16 @@ [-119.006, 37.0058], [-149.3705, 68.6611], [-89.5857, 45.4937], - [-95.1921, 39.0404] + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_tbats", - "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Red_chromatic_coordinate variable for the tg_tbats model. Information for the model is provided as follows: The tg_tbats model is a TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA\nerrors, Trend and Seasonal components) model fit using the function tbats() from the forecast package in\nR (Hyndman et al. 2023; Hyndman et al., 2008). This is an empirical time series model with no\ncovariates..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-07-03", "updated": "2024-08-23", "start_datetime": "2023-01-01T00:00:00Z", @@ -93,10 +93,6 @@ "rcc_90", "Daily", "P1D", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -139,7 +135,11 @@ "TEAK", "TOOL", "TREE", - "UKFS" + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { diff --git a/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/collection.json b/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/collection.json index d3b4ef6756..6085d1bbb4 100644 --- a/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/collection.json +++ b/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/collection.json @@ -21,57 +21,57 @@ { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_humidity_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_humidity_lm.json" + "href": "./models/tg_precip_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_humidity_lm_all_sites.json" + "href": "./models/tg_precip_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm.json" + "href": "./models/tg_randfor.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_precip_lm_all_sites.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_randfor.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/cb_prophet.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/tg_humidity_lm.json" }, { "rel": "item", diff --git a/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_humidity_lm_all_sites.json b/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_humidity_lm_all_sites.json index 1229cc6d87..4cff1cc664 100644 --- a/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_humidity_lm_all_sites.json +++ b/catalog/summaries/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_humidity_lm_all_sites.json @@ -9,6 +9,19 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-80.5248, 37.3783], + [-109.3883, 38.2483], + [-105.5824, 40.0543], + [-100.9154, 46.7697], + [-99.0588, 35.4106], + [-112.4524, 40.1776], + [-84.2826, 35.9641], + [-81.9934, 29.6893], + [-155.3173, 19.5531], + [-105.546, 40.2759], + [-78.1395, 38.8929], + [-76.56, 38.8901], + [-119.7323, 37.1088], [-119.2622, 37.0334], [-110.8355, 31.9107], [-89.5864, 45.5089], @@ -42,25 +55,12 @@ [-96.6129, 39.1104], [-96.5631, 39.1008], [-67.0769, 18.0213], - [-88.1612, 31.8539], - [-80.5248, 37.3783], - [-109.3883, 38.2483], - [-105.5824, 40.0543], - [-100.9154, 46.7697], - [-99.0588, 35.4106], - [-112.4524, 40.1776], - [-84.2826, 35.9641], - [-81.9934, 29.6893], - [-155.3173, 19.5531], - [-105.546, 40.2759], - [-78.1395, 38.8929], - [-76.56, 38.8901], - [-119.7323, 37.1088] + [-88.1612, 31.8539] ] }, "properties": { "title": "tg_humidity_lm_all_sites", - "description": "All summaries for the Daily_Net_ecosystem_exchange variable for the tg_humidity_lm_all_sites model. Information for the model is provided as follows: The tg_humidity_lm_all_sites model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity. This model was used to forecast water temperature and dissolved oxygen concentration at the\nseven lake sites, with the model fitted for all sites together.\n The model predicts this variable at the following sites: SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_Net_ecosystem_exchange variable for the tg_humidity_lm_all_sites model. Information for the model is provided as follows: The tg_humidity_lm_all_sites model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity. This model was used to forecast water temperature and dissolved oxygen concentration at the\nseven lake sites, with the model fitted for all sites together.\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-01-31", "updated": "2024-07-03", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,19 @@ "nee", "Daily", "P1D", + "MLBS", + "MOAB", + "NIWO", + "NOGP", + "OAES", + "ONAQ", + "ORNL", + "OSBS", + "PUUM", + "RMNP", + "SCBI", + "SERC", + "SJER", "SOAP", "SRER", "STEI", @@ -126,20 +139,7 @@ "KONA", "KONZ", "LAJA", - "LENO", - "MLBS", - "MOAB", - "NIWO", - "NOGP", - "OAES", - "ONAQ", - "ORNL", - "OSBS", - "PUUM", - "RMNP", - "SCBI", - "SERC", - "SJER" + "LENO" ], "table:columns": [ { diff --git a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/collection.json b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/collection.json index 7ad09ce729..ce5d82b65d 100644 --- a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/collection.json +++ b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/collection.json @@ -51,22 +51,22 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm.json" + "href": "./models/cb_prophet.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_temp_lm_all_sites.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/cb_prophet.json" + "href": "./models/tg_temp_lm.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_temp_lm_all_sites.json" }, { "rel": "parent", diff --git a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/cb_prophet.json b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/cb_prophet.json index b6783fc298..4e9deaa969 100644 --- a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/cb_prophet.json +++ b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/cb_prophet.json @@ -9,15 +9,11 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-97.57, 33.4012], - [-119.7323, 37.1088], - [-112.4524, 40.1776], [-81.4362, 28.1251], [-78.1395, 38.8929], [-109.3883, 38.2483], [-155.3173, 19.5531], [-66.8687, 17.9696], - [-81.9934, 29.6893], [-71.2874, 44.0639], [-104.7456, 40.8155], [-72.1727, 42.5369], @@ -54,12 +50,16 @@ [-121.9519, 45.8205], [-67.0769, 18.0213], [-119.006, 37.0058], - [-147.5026, 65.154] + [-97.57, 33.4012], + [-119.7323, 37.1088], + [-81.9934, 29.6893], + [-147.5026, 65.154], + [-112.4524, 40.1776] ] }, "properties": { "title": "cb_prophet", - "description": "All summaries for the Daily_latent_heat_flux variable for the cb_prophet model. Information for the model is provided as follows: The Prophet model is an empirical model, specifically a non-linear regression model that includes\nseasonality effects (Taylor & Letham, 2018). The model relies on Bayesian estimation with an additive\nwhite noise error term.\n The model predicts this variable at the following sites: CLBJ, SJER, ONAQ, DSNY, SCBI, MOAB, PUUM, GUAN, OSBS, BART, CPER, HARV, UNDE, STER, KONA, TREE, ABBY, LENO, UKFS, DEJU, KONZ, RMNP, BARR, JORN, SOAP, STEI, TALL, DCFS, TOOL, WOOD, OAES, HEAL, SERC, BLAN, GRSM, ORNL, SRER, NOGP, JERC, DELA, MLBS, NIWO, WREF, LAJA, TEAK, BONA.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_latent_heat_flux variable for the cb_prophet model. Information for the model is provided as follows: The Prophet model is an empirical model, specifically a non-linear regression model that includes\nseasonality effects (Taylor & Letham, 2018). The model relies on Bayesian estimation with an additive\nwhite noise error term.\n The model predicts this variable at the following sites: DSNY, SCBI, MOAB, PUUM, GUAN, BART, CPER, HARV, UNDE, STER, KONA, TREE, ABBY, LENO, UKFS, DEJU, KONZ, RMNP, BARR, JORN, SOAP, STEI, TALL, DCFS, TOOL, WOOD, OAES, HEAL, SERC, BLAN, GRSM, ORNL, SRER, NOGP, JERC, DELA, MLBS, NIWO, WREF, LAJA, TEAK, CLBJ, SJER, OSBS, BONA, ONAQ.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-06", "updated": "2024-02-07", "start_datetime": "2023-11-14T00:00:00Z", @@ -92,15 +92,11 @@ "le", "Daily", "P1D", - "CLBJ", - "SJER", - "ONAQ", "DSNY", "SCBI", "MOAB", "PUUM", "GUAN", - "OSBS", "BART", "CPER", "HARV", @@ -137,7 +133,11 @@ "WREF", "LAJA", "TEAK", - "BONA" + "CLBJ", + "SJER", + "OSBS", + "BONA", + "ONAQ" ], "table:columns": [ { diff --git a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_humidity_lm.json b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_humidity_lm.json index 440a057f33..a9b5cc44d1 100644 --- a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_humidity_lm.json +++ b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_humidity_lm.json @@ -9,6 +9,9 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-72.1727, 42.5369], + [-149.2133, 63.8758], + [-84.4686, 31.1948], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -22,9 +25,6 @@ [-81.4362, 28.1251], [-83.5019, 35.689], [-66.8687, 17.9696], - [-72.1727, 42.5369], - [-149.2133, 63.8758], - [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], [-96.5631, 39.1008], @@ -60,7 +60,7 @@ }, "properties": { "title": "tg_humidity_lm", - "description": "All summaries for the Daily_latent_heat_flux variable for the tg_humidity_lm model. Information for the model is provided as follows: The tg_humidity_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity.\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_latent_heat_flux variable for the tg_humidity_lm model. Information for the model is provided as follows: The tg_humidity_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only one covariate: relative humidity.\n The model predicts this variable at the following sites: HARV, HEAL, JERC, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-04", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,9 @@ "le", "Daily", "P1D", + "HARV", + "HEAL", + "JERC", "ABBY", "BARR", "BART", @@ -106,9 +109,6 @@ "DSNY", "GRSM", "GUAN", - "HARV", - "HEAL", - "JERC", "JORN", "KONA", "KONZ", diff --git a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_precip_lm.json b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_precip_lm.json index fe085bc28c..f2554fdcf7 100644 --- a/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_precip_lm.json +++ b/catalog/summaries/Terrestrial/Daily_latent_heat_flux/models/tg_precip_lm.json @@ -9,6 +9,21 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], @@ -40,27 +55,12 @@ [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], - [-110.5391, 44.9535], - [-122.3303, 45.7624], - [-156.6194, 71.2824], - [-71.2874, 44.0639], - [-78.0418, 39.0337], - [-147.5026, 65.154], - [-97.57, 33.4012], - [-104.7456, 40.8155], - [-99.1066, 47.1617], - [-145.7514, 63.8811], - [-87.8039, 32.5417], - [-81.4362, 28.1251], - [-83.5019, 35.689], - [-66.8687, 17.9696], - [-72.1727, 42.5369], - [-149.2133, 63.8758] + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_precip_lm", - "description": "All summaries for the Daily_latent_heat_flux variable for the tg_precip_lm model. Information for the model is provided as follows: The tg_precip_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only total precipitation used as a model covariate..\n The model predicts this variable at the following sites: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", + "description": "All summaries for the Daily_latent_heat_flux variable for the tg_precip_lm model. Information for the model is provided as follows: The tg_precip_lm model is a linear model fit using the function lm() in R. This is a very simple\nmodel with only total precipitation used as a model covariate..\n The model predicts this variable at the following sites: 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.\n Summaries are the forecasts statistics of the raw forecasts (i.e., mean, median, confidence intervals)", "datetime": "2024-02-03", "updated": "2024-07-04", "start_datetime": "2023-11-14T00:00:00Z", @@ -93,6 +93,21 @@ "le", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", "JERC", "JORN", "KONA", @@ -124,22 +139,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL" + "YELL" ], "table:columns": [ {