diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json index 5331a1f6cb..a608d7828d 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json @@ -24,7 +24,7 @@ "properties": { "title": "climatology", "description": "All scores for the Daily_Chlorophyll_a 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: BARC, BLWA, CRAM, FLNT, LIRO, PRPO, SUGG, TOMB, PRLA, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/persistenceRW.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/persistenceRW.json index 6ed2c0477c..56be592560 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/persistenceRW.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/persistenceRW.json @@ -24,7 +24,7 @@ "properties": { "title": "persistenceRW", "description": "All scores for the Daily_Chlorophyll_a 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: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_arima.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_arima.json index 4de863df9a..a089c6d29b 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_arima.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_arima.json @@ -24,7 +24,7 @@ "properties": { "title": "tg_arima", "description": "All scores for the Daily_Chlorophyll_a 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: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_ets.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_ets.json index d54707b47e..b6c9065735 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_ets.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_ets.json @@ -24,7 +24,7 @@ "properties": { "title": "tg_ets", "description": "All scores for the Daily_Chlorophyll_a 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: BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO, SUGG, TOMB, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json index 6b0fed501b..ca45b88651 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json @@ -24,7 +24,7 @@ "properties": { "title": "tg_tbats", "description": "All scores 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json index 6903c07047..298362071d 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json @@ -11,37 +11,37 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/hotdeck.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/hotdeck.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/AquaticEcosystemsOxygen.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/AquaticEcosystemsOxygen.json" }, { "rel": "parent", diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/AquaticEcosystemsOxygen.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/AquaticEcosystemsOxygen.json index f6d52a902a..86e1737286 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/AquaticEcosystemsOxygen.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/AquaticEcosystemsOxygen.json @@ -15,7 +15,7 @@ "properties": { "title": "AquaticEcosystemsOxygen", "description": "All scores for the Daily_Dissolved_oxygen variable for the AquaticEcosystemsOxygen model. Information for the model is provided as follows: Used a Bayesian Dynamic Linear Model using the fit_dlm function from the ecoforecastR package.\n The model predicts this variable at the following sites: WLOU.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-31T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/climatology.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/climatology.json index 60964605a0..ecc011f41d 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/climatology.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/climatology.json @@ -9,10 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-102.4471, 39.7582], - [-82.0084, 29.676], - [-119.2575, 37.0597], - [-110.5871, 44.9501], [-96.6242, 34.4442], [-87.7982, 32.5415], [-147.504, 65.1532], @@ -32,23 +28,27 @@ [-122.1655, 44.2596], [-78.1473, 38.8943], [-97.7823, 33.3785], + [-99.1139, 47.1591], [-99.2531, 47.1298], [-111.7979, 40.7839], [-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], - [-99.1139, 47.1591], - [-149.143, 68.6698], - [-149.6106, 68.6307] + [-102.4471, 39.7582], + [-82.0084, 29.676], + [-119.2575, 37.0597], + [-110.5871, 44.9501], + [-149.143, 68.6698] ] }, "properties": { "title": "climatology", - "description": "All scores for the Daily_Dissolved_oxygen 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: ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, POSE, PRIN, PRPO, REDB, SUGG, SYCA, TECR, TOMB, WALK, WLOU, PRLA, OKSR, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Dissolved_oxygen 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: BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, TOOK, WALK, WLOU, ARIK, BARC, BIGC, BLDE, OKSR.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ @@ -79,10 +79,6 @@ "oxygen", "Daily", "P1D", - "ARIK", - "BARC", - "BIGC", - "BLDE", "BLUE", "BLWA", "CARI", @@ -102,17 +98,21 @@ "MCRA", "POSE", "PRIN", + "PRLA", "PRPO", "REDB", "SUGG", "SYCA", "TECR", "TOMB", + "TOOK", "WALK", "WLOU", - "PRLA", - "OKSR", - "TOOK" + "ARIK", + "BARC", + "BIGC", + "BLDE", + "OKSR" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json index 2e9965a8b0..1d490ba832 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json @@ -28,7 +28,7 @@ "properties": { "title": "hotdeck", "description": "All scores 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: SUGG, SYCA, BARC, BIGC, BLDE, CRAM, KING, LEWI, LIRO, MAYF, MCRA, POSE, PRIN, REDB.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json index 3c0ffb44e5..af29aa05a2 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json @@ -9,6 +9,10 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-88.1589, 31.8534], + [-149.6106, 68.6307], + [-84.2793, 35.9574], + [-105.9154, 39.8914], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -38,17 +42,13 @@ [-111.7979, 40.7839], [-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] + [-119.0274, 36.9559] ] }, "properties": { "title": "persistenceRW", - "description": "All scores 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: TOMB, 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.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -79,6 +79,10 @@ "oxygen", "Daily", "P1D", + "TOMB", + "TOOK", + "WALK", + "WLOU", "ARIK", "BARC", "BIGC", @@ -108,11 +112,7 @@ "REDB", "SUGG", "SYCA", - "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU" + "TECR" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json index 0b252b7902..bb4da52490 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json @@ -9,18 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-78.1473, 38.8943], - [-97.7823, 33.3785], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-111.7979, 40.7839], - [-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], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -42,13 +30,25 @@ [-87.4077, 32.9604], [-96.443, 38.9459], [-122.1655, 44.2596], - [-149.143, 68.6698] + [-149.143, 68.6698], + [-78.1473, 38.8943], + [-97.7823, 33.3785], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-111.7979, 40.7839], + [-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] ] }, "properties": { "title": "tg_arima", - "description": "All scores for the Daily_Dissolved_oxygen 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: POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, 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.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Dissolved_oxygen 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -79,18 +79,6 @@ "oxygen", "Daily", "P1D", - "POSE", - "PRIN", - "PRLA", - "PRPO", - "REDB", - "SUGG", - "SYCA", - "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU", "ARIK", "BARC", "BIGC", @@ -112,7 +100,19 @@ "MAYF", "MCDI", "MCRA", - "OKSR" + "OKSR", + "POSE", + "PRIN", + "PRLA", + "PRPO", + "REDB", + "SUGG", + "SYCA", + "TECR", + "TOMB", + "TOOK", + "WALK", + "WLOU" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json index 10b6d260b1..22449955c2 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json @@ -9,6 +9,20 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-102.4471, 39.7582], + [-82.0084, 29.676], + [-119.2575, 37.0597], + [-110.5871, 44.9501], + [-96.6242, 34.4442], + [-87.7982, 32.5415], + [-147.504, 65.1532], + [-105.5442, 40.035], + [-89.4737, 46.2097], + [-66.9868, 18.1135], + [-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], @@ -28,27 +42,13 @@ [-88.1589, 31.8534], [-149.6106, 68.6307], [-84.2793, 35.9574], - [-105.9154, 39.8914], - [-102.4471, 39.7582], - [-82.0084, 29.676], - [-119.2575, 37.0597], - [-110.5871, 44.9501], - [-96.6242, 34.4442], - [-87.7982, 32.5415], - [-147.504, 65.1532], - [-105.5442, 40.035], - [-89.4737, 46.2097], - [-66.9868, 18.1135], - [-84.4374, 31.1854], - [-66.7987, 18.1741], - [-72.3295, 42.4719], - [-96.6038, 39.1051] + [-105.9154, 39.8914] ] }, "properties": { "title": "tg_ets", - "description": "All scores for the Daily_Dissolved_oxygen 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: LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, TOOK, WALK, WLOU, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Dissolved_oxygen 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -79,6 +79,20 @@ "oxygen", "Daily", "P1D", + "ARIK", + "BARC", + "BIGC", + "BLDE", + "BLUE", + "BLWA", + "CARI", + "COMO", + "CRAM", + "CUPE", + "FLNT", + "GUIL", + "HOPB", + "KING", "LECO", "LEWI", "LIRO", @@ -98,21 +112,7 @@ "TOMB", "TOOK", "WALK", - "WLOU", - "ARIK", - "BARC", - "BIGC", - "BLDE", - "BLUE", - "BLWA", - "CARI", - "COMO", - "CRAM", - "CUPE", - "FLNT", - "GUIL", - "HOPB", - "KING" + "WLOU" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json index 3bc70915f3..3a850232df 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json @@ -9,12 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-102.4471, 39.7582], - [-82.0084, 29.676], - [-119.2575, 37.0597], - [-110.5871, 44.9501], - [-96.6242, 34.4442], - [-87.7982, 32.5415], [-147.504, 65.1532], [-105.5442, 40.035], [-89.4737, 46.2097], @@ -42,13 +36,19 @@ [-88.1589, 31.8534], [-149.6106, 68.6307], [-84.2793, 35.9574], - [-105.9154, 39.8914] + [-105.9154, 39.8914], + [-102.4471, 39.7582], + [-82.0084, 29.676], + [-119.2575, 37.0597], + [-110.5871, 44.9501], + [-96.6242, 34.4442], + [-87.7982, 32.5415] ] }, "properties": { "title": "tg_tbats", - "description": "All scores for the Daily_Dissolved_oxygen 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Dissolved_oxygen 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: 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, ARIK, BARC, BIGC, BLDE, BLUE, BLWA.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -79,12 +79,6 @@ "oxygen", "Daily", "P1D", - "ARIK", - "BARC", - "BIGC", - "BLDE", - "BLUE", - "BLWA", "CARI", "COMO", "CRAM", @@ -112,7 +106,13 @@ "TOMB", "TOOK", "WALK", - "WLOU" + "WLOU", + "ARIK", + "BARC", + "BIGC", + "BLDE", + "BLUE", + "BLWA" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json index ffcfe2740d..e16efa4bd3 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json @@ -11,52 +11,52 @@ { "rel": "item", "type": "application/json", - "href": "./models/fARIMA_clim_ensemble.json" + "href": "./models/baseline_ensemble.json" }, { "rel": "item", "type": "application/json", - "href": "./models/fTSLM_lag.json" + "href": "./models/GLEON_JRabaey_temp_physics.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGLM_noDA.json" + "href": "./models/GLEON_lm_lag_1day.json" }, { "rel": "item", "type": "application/json", - "href": "./models/hotdeck.json" + "href": "./models/fARIMA_clim_ensemble.json" }, { "rel": "item", "type": "application/json", - "href": "./models/lm_AT_WTL_WS.json" + "href": "./models/flareGLM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mkricheldorf_w_lag.json" + "href": "./models/hotdeck.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mlp1_wtempforecast_LF.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/GAM_air_wind.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/GLEON_JRabaey_temp_physics.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/fTSLM_lag.json" }, { "rel": "item", @@ -66,27 +66,27 @@ { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/GAM_air_wind.json" }, { "rel": "item", "type": "application/json", - "href": "./models/baseline_ensemble.json" + "href": "./models/lm_AT_WTL_WS.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/mkricheldorf_w_lag.json" }, { "rel": "item", "type": "application/json", - "href": "./models/GLEON_lm_lag_1day.json" + "href": "./models/mlp1_wtempforecast_LF.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/climatology.json" }, { "rel": "item", @@ -96,7 +96,7 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/GAM_air_wind.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/GAM_air_wind.json index 1fbba979d9..ccd3ad41dc 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/GAM_air_wind.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/GAM_air_wind.json @@ -21,7 +21,7 @@ "properties": { "title": "GAM_air_wind", "description": "All scores for the Daily_Water_temperature variable for the GAM_air_wind model. Information for the model is provided as follows: I used a GAM (mgcv) with a linear relationship to air temperature and smoothing for eastward and northward winds..\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-03-01T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_JRabaey_temp_physics.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_JRabaey_temp_physics.json index 826ea50c57..6056666c1c 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_JRabaey_temp_physics.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_JRabaey_temp_physics.json @@ -9,6 +9,21 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-96.443, 38.9459], + [-122.1655, 44.2596], + [-149.143, 68.6698], + [-78.1473, 38.8943], + [-97.7823, 33.3785], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-111.7979, 40.7839], + [-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], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -27,28 +42,13 @@ [-77.9832, 39.0956], [-89.7048, 45.9983], [-121.9338, 45.7908], - [-87.4077, 32.9604], - [-96.443, 38.9459], - [-122.1655, 44.2596], - [-149.143, 68.6698], - [-78.1473, 38.8943], - [-97.7823, 33.3785], - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-111.7979, 40.7839], - [-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] + [-87.4077, 32.9604] ] }, "properties": { "title": "GLEON_JRabaey_temp_physics", - "description": "All scores for the Daily_Water_temperature variable for the GLEON_JRabaey_temp_physics model. Information for the model is provided as follows: The JR-physics model is a simple process model based on the assumption that surface water\ntemperature should trend towards equilibration with air temperature with a lag factor..\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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Water_temperature variable for the GLEON_JRabaey_temp_physics model. Information for the model is provided as follows: The JR-physics model is a simple process model based on the assumption that surface water\ntemperature should trend towards equilibration with air temperature with a lag factor..\n The model predicts this variable at the following sites: MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, TOOK, WALK, WLOU, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-01-02T00:00:00Z", "end_datetime": "2024-03-12T00:00:00Z", "providers": [ @@ -79,6 +79,21 @@ "temperature", "Daily", "P1D", + "MCDI", + "MCRA", + "OKSR", + "POSE", + "PRIN", + "PRLA", + "PRPO", + "REDB", + "SUGG", + "SYCA", + "TECR", + "TOMB", + "TOOK", + "WALK", + "WLOU", "ARIK", "BARC", "BIGC", @@ -97,22 +112,7 @@ "LEWI", "LIRO", "MART", - "MAYF", - "MCDI", - "MCRA", - "OKSR", - "POSE", - "PRIN", - "PRLA", - "PRPO", - "REDB", - "SUGG", - "SYCA", - "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU" + "MAYF" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_lm_lag_1day.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_lm_lag_1day.json index 2ab3e65b45..a5fb8c55d2 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_lm_lag_1day.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/GLEON_lm_lag_1day.json @@ -21,7 +21,7 @@ "properties": { "title": "GLEON_lm_lag_1day", "description": "All scores for the Daily_Water_temperature variable for the GLEON_lm_lag_1day model. Information for the model is provided as follows: NA.\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-01-02T00:00:00Z", "end_datetime": "2024-02-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json index 72cc10611a..28ed91a16d 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json @@ -48,7 +48,7 @@ "properties": { "title": "baseline_ensemble", "description": "All scores 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: LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, WALK, WLOU, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-01T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json index dfb1bfd4c4..c44b303b2e 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/bee_bake_RFModel_2024.json @@ -21,7 +21,7 @@ "properties": { "title": "bee_bake_RFModel_2024", "description": "All scores 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: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-05T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/climatology.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/climatology.json index b0201cde99..8f729edff3 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/climatology.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/climatology.json @@ -48,7 +48,7 @@ "properties": { "title": "climatology", "description": "All scores for the Daily_Water_temperature 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: TECR, TOMB, 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, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json index 662b31739d..5dafc9b109 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/fARIMA_clim_ensemble.json @@ -9,6 +9,8 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-102.4471, 39.7582], + [-82.0084, 29.676], [-110.5871, 44.9501], [-147.504, 65.1532], [-105.5442, 40.035], @@ -16,6 +18,7 @@ [-66.9868, 18.1135], [-84.4374, 31.1854], [-66.7987, 18.1741], + [-72.3295, 42.4719], [-96.6038, 39.1051], [-83.5038, 35.6904], [-77.9832, 39.0956], @@ -27,27 +30,24 @@ [-149.143, 68.6698], [-78.1473, 38.8943], [-97.7823, 33.3785], - [-99.1139, 47.1591], [-99.2531, 47.1298], [-111.7979, 40.7839], [-82.0177, 29.6878], [-111.5081, 33.751], + [-119.0274, 36.9559], [-88.1589, 31.8534], - [-84.2793, 35.9574], [-105.9154, 39.8914], - [-102.4471, 39.7582], - [-82.0084, 29.676], + [-84.2793, 35.9574], + [-87.7982, 32.5415], + [-99.1139, 47.1591], [-119.2575, 37.0597], - [-72.3295, 42.4719], - [-149.6106, 68.6307], - [-119.0274, 36.9559], - [-87.7982, 32.5415] + [-149.6106, 68.6307] ] }, "properties": { "title": "fARIMA_clim_ensemble", - "description": "All scores 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: BLDE, CARI, COMO, CRAM, CUPE, FLNT, GUIL, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TOMB, WALK, WLOU, ARIK, BARC, BIGC, HOPB, TOOK, TECR, BLWA.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: ARIK, BARC, BLDE, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRPO, REDB, SUGG, SYCA, TECR, TOMB, WLOU, WALK, BLWA, PRLA, BIGC, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-01T00:00:00Z", "providers": [ @@ -78,6 +78,8 @@ "temperature", "Daily", "P1D", + "ARIK", + "BARC", "BLDE", "CARI", "COMO", @@ -85,6 +87,7 @@ "CUPE", "FLNT", "GUIL", + "HOPB", "KING", "LECO", "LEWI", @@ -96,21 +99,18 @@ "OKSR", "POSE", "PRIN", - "PRLA", "PRPO", "REDB", "SUGG", "SYCA", + "TECR", "TOMB", - "WALK", "WLOU", - "ARIK", - "BARC", + "WALK", + "BLWA", + "PRLA", "BIGC", - "HOPB", - "TOOK", - "TECR", - "BLWA" + "TOOK" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json index abbbf39c6a..2e2a5fc1b4 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json @@ -9,15 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-102.4471, 39.7582], - [-82.0084, 29.676], - [-119.2575, 37.0597], - [-110.5871, 44.9501], - [-96.6242, 34.4442], - [-87.7982, 32.5415], - [-147.504, 65.1532], - [-105.5442, 40.035], - [-89.4737, 46.2097], [-66.9868, 18.1135], [-84.4374, 31.1854], [-66.7987, 18.1741], @@ -42,13 +33,22 @@ [-88.1589, 31.8534], [-149.6106, 68.6307], [-84.2793, 35.9574], - [-105.9154, 39.8914] + [-105.9154, 39.8914], + [-102.4471, 39.7582], + [-82.0084, 29.676], + [-119.2575, 37.0597], + [-110.5871, 44.9501], + [-96.6242, 34.4442], + [-87.7982, 32.5415], + [-147.504, 65.1532], + [-105.5442, 40.035], + [-89.4737, 46.2097] ] }, "properties": { "title": "fTSLM_lag", - "description": "All scores for the Daily_Water_temperature variable for the fTSLM_lag model. Information for the model is provided as follows: This is a simple time series linear model in which water temperature is a function of air\ntemperature of that day and the previous day’s air temperature.\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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Water_temperature variable for the fTSLM_lag model. Information for the model is provided as follows: This is a simple time series linear model in which water temperature is a function of air\ntemperature of that day and the previous day’s air temperature.\n The model predicts this variable at the following sites: 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, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -79,15 +79,6 @@ "temperature", "Daily", "P1D", - "ARIK", - "BARC", - "BIGC", - "BLDE", - "BLUE", - "BLWA", - "CARI", - "COMO", - "CRAM", "CUPE", "FLNT", "GUIL", @@ -112,7 +103,16 @@ "TOMB", "TOOK", "WALK", - "WLOU" + "WLOU", + "ARIK", + "BARC", + "BIGC", + "BLDE", + "BLUE", + "BLWA", + "CARI", + "COMO", + "CRAM" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM.json index dbac89c783..9a39fa0472 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM.json @@ -21,7 +21,7 @@ "properties": { "title": "flareGLM", "description": "All scores for the Daily_Water_temperature variable for the flareGLM model. Information for the model is provided as follows: The FLARE-GLM is a forecasting framework that integrates the General Lake Model\nhydrodynamic process model (GLM; Hipsey et al., 2019) and data assimilation algorithm to generate\nensemble forecasts of lake water temperature..\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json index 727b79dc38..18ee4fea9b 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json @@ -21,7 +21,7 @@ "properties": { "title": "flareGLM_noDA", "description": "All scores for the Daily_Water_temperature variable for the flareGLM_noDA model. Information for the model is provided as follows: The FLARE-GLM is a forecasting framework that integrates the General Lake Model\nhydrodynamic process model (GLM; Hipsey et al., 2019). This version does not incorportate data assimilation.\n The model predicts this variable at the following sites: PRLA, PRPO, SUGG, TOOK, BARC, CRAM, LIRO.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json index 5f537890e6..b8aa7f717e 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json @@ -44,7 +44,7 @@ "properties": { "title": "hotdeck", "description": "All scores 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: ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI, LIRO, MAYF, MCRA, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, WALK, WLOU.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/lm_AT_WTL_WS.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/lm_AT_WTL_WS.json index fde2b2369a..7b4fdafd4c 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/lm_AT_WTL_WS.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/lm_AT_WTL_WS.json @@ -21,7 +21,7 @@ "properties": { "title": "lm_AT_WTL_WS", "description": "All scores for the Daily_Water_temperature variable for the lm_AT_WTL_WS model. Information for the model is provided as follows: This forecast of water temperature at NEON Lake sites uses a linear model, incorporating air temperature, wind speed, and the previous day's forecasted water temperature as variables..\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/mkricheldorf_w_lag.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/mkricheldorf_w_lag.json index 8286c1d850..5ae30e1574 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/mkricheldorf_w_lag.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/mkricheldorf_w_lag.json @@ -21,7 +21,7 @@ "properties": { "title": "mkricheldorf_w_lag", "description": "All scores for the Daily_Water_temperature variable for the mkricheldorf_w_lag model. Information for the model is provided as follows: I used an autoregressive linear model using the lm() function.\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-26T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/mlp1_wtempforecast_LF.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/mlp1_wtempforecast_LF.json index 6afde16c06..3a3171b5fb 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/mlp1_wtempforecast_LF.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/mlp1_wtempforecast_LF.json @@ -21,7 +21,7 @@ "properties": { "title": "mlp1_wtempforecast_LF", "description": "All scores for the Daily_Water_temperature variable for the mlp1_wtempforecast_LF model. Information for the model is provided as follows: Modelling for water temperature using a single layer neural network (mlp() in tidymodels). Used relative humidity, precipitation flux and air temperature as drivers. Hypertuned parameters for models to be run with 100 epochs and penalty value of 0.01..\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-05T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/persistenceRW.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/persistenceRW.json index 6e650bbaa6..fba374c206 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/persistenceRW.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/persistenceRW.json @@ -9,12 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-102.4471, 39.7582], - [-82.0084, 29.676], - [-119.2575, 37.0597], - [-110.5871, 44.9501], - [-96.6242, 34.4442], - [-87.7982, 32.5415], [-147.504, 65.1532], [-105.5442, 40.035], [-89.4737, 46.2097], @@ -42,13 +36,19 @@ [-88.1589, 31.8534], [-149.6106, 68.6307], [-84.2793, 35.9574], - [-105.9154, 39.8914] + [-105.9154, 39.8914], + [-102.4471, 39.7582], + [-82.0084, 29.676], + [-119.2575, 37.0597], + [-110.5871, 44.9501], + [-96.6242, 34.4442], + [-87.7982, 32.5415] ] }, "properties": { "title": "persistenceRW", - "description": "All scores for the Daily_Water_temperature 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Water_temperature 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: 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, ARIK, BARC, BIGC, BLDE, BLUE, BLWA.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -79,12 +79,6 @@ "temperature", "Daily", "P1D", - "ARIK", - "BARC", - "BIGC", - "BLDE", - "BLUE", - "BLWA", "CARI", "COMO", "CRAM", @@ -112,7 +106,13 @@ "TOMB", "TOOK", "WALK", - "WLOU" + "WLOU", + "ARIK", + "BARC", + "BIGC", + "BLDE", + "BLUE", + "BLWA" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_arima.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_arima.json index bc05352d9a..6288adc761 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_arima.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_arima.json @@ -48,7 +48,7 @@ "properties": { "title": "tg_arima", "description": "All scores for the Daily_Water_temperature 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json index bba35be59e..1830011a8c 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json @@ -9,16 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-99.1139, 47.1591], - [-99.2531, 47.1298], - [-111.7979, 40.7839], - [-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], [-102.4471, 39.7582], [-82.0084, 29.676], [-119.2575, 37.0597], @@ -42,13 +32,23 @@ [-122.1655, 44.2596], [-149.143, 68.6698], [-78.1473, 38.8943], - [-97.7823, 33.3785] + [-97.7823, 33.3785], + [-99.1139, 47.1591], + [-99.2531, 47.1298], + [-111.7979, 40.7839], + [-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] ] }, "properties": { "title": "tg_ets", - "description": "All scores for the Daily_Water_temperature 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: PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, 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.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Water_temperature 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -79,16 +79,6 @@ "temperature", "Daily", "P1D", - "PRLA", - "PRPO", - "REDB", - "SUGG", - "SYCA", - "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU", "ARIK", "BARC", "BIGC", @@ -112,7 +102,17 @@ "MCRA", "OKSR", "POSE", - "PRIN" + "PRIN", + "PRLA", + "PRPO", + "REDB", + "SUGG", + "SYCA", + "TECR", + "TOMB", + "TOOK", + "WALK", + "WLOU" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_tbats.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_tbats.json index 7401ce0862..61c72b029f 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_tbats.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_tbats.json @@ -48,7 +48,7 @@ "properties": { "title": "tg_tbats", "description": "All scores for the Daily_Water_temperature 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: LIRO, MART, MAYF, MCDI, MCRA, OKSR, POSE, PRIN, PRLA, PRPO, REDB, SUGG, SYCA, TECR, TOMB, TOOK, WALK, WLOU, ARIK, BARC, BIGC, BLDE, BLUE, BLWA, CARI, COMO, CRAM, CUPE, FLNT, GUIL, HOPB, KING, LECO, LEWI.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/zimmerman_proj1.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/zimmerman_proj1.json index 11494ffc7c..2159974810 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/zimmerman_proj1.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/zimmerman_proj1.json @@ -21,7 +21,7 @@ "properties": { "title": "zimmerman_proj1", "description": "All scores for the Daily_Water_temperature variable for the zimmerman_proj1 model. Information for the model is provided as follows: I used an ARIMA model with one autoregressive term. I also included air pressure and air temperature.\n The model predicts this variable at the following sites: BARC, CRAM, LIRO, PRLA, PRPO, SUGG, TOOK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_arima.json b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_arima.json index 6f3855941b..97d22e0a53 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_arima.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_arima.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_arima", "description": "All scores for the Weekly_beetle_community_abundance 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: 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, ABBY, BARR, BART, BLAN, BONA.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-07-22T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_ets.json b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_ets.json index 9f9f00c5ad..5feaadf83a 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_ets.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_ets.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_ets", "description": "All scores for the Weekly_beetle_community_abundance 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-07-22T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_tbats.json b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_tbats.json index dbd3cc26d2..92b72ffa65 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_tbats.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_abundance/models/tg_tbats.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_tbats", "description": "All scores for the Weekly_beetle_community_abundance 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-07-22T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_arima.json b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_arima.json index 7880784c7e..3a5f08c3be 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_arima.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_arima.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_arima", "description": "All scores for the Weekly_beetle_community_richness 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-08-05T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_ets.json b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_ets.json index 8112616b65..877664dbeb 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_ets.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_ets.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_ets", "description": "All scores for the Weekly_beetle_community_richness 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: 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, SOAP, SRER, STEI, STER.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-08-05T00:00:00Z", "providers": [ diff --git a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_tbats.json b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_tbats.json index 9c41f61b16..2917d7d108 100644 --- a/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_tbats.json +++ b/catalog/scores/Beetles/Weekly_beetle_community_richness/models/tg_tbats.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_tbats", "description": "All scores for the Weekly_beetle_community_richness 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-08-05T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json index 27b0a684de..2c2f3a7e1d 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/collection.json @@ -11,32 +11,32 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/ChlorophyllCrusaders.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/ChlorophyllCrusaders.json" + "href": "./models/tg_arima.json" }, { "rel": "parent", diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/ChlorophyllCrusaders.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/ChlorophyllCrusaders.json index ca1db16d8e..a088324745 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/ChlorophyllCrusaders.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/ChlorophyllCrusaders.json @@ -15,7 +15,7 @@ "properties": { "title": "ChlorophyllCrusaders", "description": "All scores for the Daily_Green_chromatic_coordinate variable for the ChlorophyllCrusaders model. Information for the model is provided as follows: Our project utilizes a historical GCC data to fit a Dynamic Linear Model (DLM). After this DLM is trained, we utilize forecasted temperature data to predict future GCC data..\n The model predicts this variable at the following sites: HEAL.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-06-20T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json index 1a93ba5246..218bf54af7 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json @@ -9,6 +9,12 @@ "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], @@ -49,19 +55,13 @@ [-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] + [-110.5391, 44.9535] ] }, "properties": { "title": "climatology", - "description": "All scores 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: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ @@ -92,6 +92,12 @@ "gcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", "CPER", "DCFS", "DEJU", @@ -132,13 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ" + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json index 9bf430ffa4..4060fece21 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json @@ -61,7 +61,7 @@ "properties": { "title": "persistenceRW", "description": "All scores 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json index 7dfcb3745d..15396a79c4 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_arima", "description": "All scores 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json index 2dfe423d7e..59150cc2a1 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_ets", "description": "All scores for the Daily_Green_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: 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, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json index 0876616bd7..33f9021fdb 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_tbats.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_tbats", "description": "All scores 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: 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, ABBY, BARR, BART, BLAN.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json index 7aafd76769..753c6958a9 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json @@ -11,32 +11,32 @@ { "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/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/baseline_ensemble.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/baseline_ensemble.json" }, { "rel": "parent", diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/baseline_ensemble.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/baseline_ensemble.json index ab64fb5cfd..5de10cf8fb 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/baseline_ensemble.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/baseline_ensemble.json @@ -9,9 +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], @@ -55,13 +52,16 @@ [-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] ] }, "properties": { "title": "baseline_ensemble", - "description": "All scores for the Daily_Red_chromatic_coordinate 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Red_chromatic_coordinate 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: 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, ABBY, BARR, BART.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-01T00:00:00Z", "providers": [ @@ -92,9 +92,6 @@ "rcc_90", "Daily", "P1D", - "ABBY", - "BARR", - "BART", "BLAN", "BONA", "CLBJ", @@ -138,7 +135,10 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json index e5ed8b51ad..f486943542 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/climatology.json @@ -9,6 +9,29 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-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], + [-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], @@ -32,36 +55,13 @@ [-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], - [-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] + [-105.5824, 40.0543] ] }, "properties": { "title": "climatology", - "description": "All scores 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: 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, MLBS, MOAB, NIWO.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ @@ -92,6 +92,29 @@ "rcc_90", "Daily", "P1D", + "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", @@ -115,30 +138,7 @@ "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" + "NIWO" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json index 67583084ac..4da7084f42 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json @@ -9,20 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-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], @@ -55,13 +41,27 @@ [-155.3173, 19.5531], [-105.546, 40.2759], [-78.1395, 38.8929], - [-76.56, 38.8901] + [-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": "persistenceRW", - "description": "All scores for the Daily_Red_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: 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, SERC.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Red_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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -92,20 +92,6 @@ "rcc_90", "Daily", "P1D", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -138,7 +124,21 @@ "PUUM", "RMNP", "SCBI", - "SERC" + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json index 57f247fdf0..7e7b1111d5 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_arima.json @@ -9,6 +9,10 @@ "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], @@ -51,17 +55,13 @@ [-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] + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_arima", - "description": "All scores 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: 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, ABBY, BARR, BART, BLAN.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,6 +92,10 @@ "rcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", "BONA", "CLBJ", "CPER", @@ -134,11 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN" + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json index 6aff7c1d77..d58cc44609 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_ets.json @@ -9,28 +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], - [-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], @@ -55,13 +33,35 @@ [-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], + [-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] ] }, "properties": { "title": "tg_ets", - "description": "All scores 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: 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, MLBS.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,28 +92,6 @@ "rcc_90", "Daily", "P1D", - "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", @@ -138,7 +116,29 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", + "JERC", + "JORN", + "KONA", + "KONZ", + "LAJA", + "LENO", + "MLBS" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json index 6c525cb75c..17ce0fe4f1 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/tg_tbats.json @@ -9,6 +9,15 @@ "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], @@ -46,22 +55,13 @@ [-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] + [-105.546, 40.2759] ] }, "properties": { "title": "tg_tbats", - "description": "All scores 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: 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, SOAP, SRER, STEI, STER, TALL, TEAK.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,6 +92,15 @@ "rcc_90", "Daily", "P1D", + "SCBI", + "SERC", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", "TOOL", "TREE", "UKFS", @@ -129,16 +138,7 @@ "ORNL", "OSBS", "PUUM", - "RMNP", - "SCBI", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK" + "RMNP" ], "table:columns": [ { diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json index 1a3a77fde4..88633f9def 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json @@ -11,32 +11,32 @@ { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/bookcast_forest.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/bookcast_forest.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/tg_tbats.json" }, { "rel": "parent", diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/bookcast_forest.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/bookcast_forest.json index a8a3385e1b..a4df90a6db 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/bookcast_forest.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/bookcast_forest.json @@ -15,7 +15,7 @@ "properties": { "title": "bookcast_forest", "description": "All scores for the Daily_Net_ecosystem_exchange variable for the bookcast_forest model. Information for the model is provided as follows: A simple daily timestep process-based model of a terrestrial carbon cycle. It includes leaves, wood, and soil pools. It uses a light-use efficiency GPP model to convert PAR to carbon. The model is derived from https://github.com/mdietze/FluxCourseForecast..\n The model predicts this variable at the following sites: OSBS.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-12T00:00:00Z", "providers": [ diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json index 2b654103b9..9daaba6639 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json @@ -9,17 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-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], @@ -55,13 +44,24 @@ [-76.56, 38.8901], [-119.7323, 37.1088], [-119.2622, 37.0334], - [-110.8355, 31.9107] + [-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": "climatology", - "description": "All scores for the Daily_Net_ecosystem_exchange 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: 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, SOAP, SRER.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Net_ecosystem_exchange 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-03T00:00:00Z", "providers": [ @@ -92,17 +92,6 @@ "nee", "Daily", "P1D", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -138,7 +127,18 @@ "SERC", "SJER", "SOAP", - "SRER" + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json index faf3f52852..3b398f265a 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json @@ -61,7 +61,7 @@ "properties": { "title": "persistenceRW", "description": "All scores for the Daily_Net_ecosystem_exchange 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-03T00:00:00Z", "providers": [ diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_arima.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_arima.json index 0f0210ad92..5ce4855e5e 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_arima.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_arima.json @@ -9,6 +9,15 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-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], @@ -46,22 +55,13 @@ [-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] + [-104.7456, 40.8155] ] }, "properties": { "title": "tg_arima", - "description": "All scores for the Daily_Net_ecosystem_exchange 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Net_ecosystem_exchange 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: 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, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,6 +92,15 @@ "nee", "Daily", "P1D", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", + "JERC", "JORN", "KONA", "KONZ", @@ -129,16 +138,7 @@ "BLAN", "BONA", "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL", - "JERC" + "CPER" ], "table:columns": [ { diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_ets.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_ets.json index dd90f83592..cea5f01777 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_ets.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_ets.json @@ -9,28 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-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], - [-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], @@ -55,13 +33,35 @@ [-80.5248, 37.3783], [-109.3883, 38.2483], [-105.5824, 40.0543], - [-100.9154, 46.7697] + [-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], + [-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 scores for the Daily_Net_ecosystem_exchange 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: 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, MLBS, MOAB, NIWO, NOGP.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_Net_ecosystem_exchange 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,28 +92,6 @@ "nee", "Daily", "P1D", - "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", @@ -138,7 +116,29 @@ "MLBS", "MOAB", "NIWO", - "NOGP" + "NOGP", + "OAES", + "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/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_tbats.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_tbats.json index 575e0f35ec..e2aa613116 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_tbats.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/tg_tbats.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_tbats", "description": "All scores for the Daily_Net_ecosystem_exchange 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json index 2d02a359a0..69e786089f 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/collection.json @@ -21,12 +21,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/tg_tbats.json" }, { "rel": "parent", diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json index a7027a259f..edaed2d762 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json @@ -9,23 +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], - [-84.4686, 31.1948], - [-106.8425, 32.5907], [-96.6129, 39.1104], [-96.5631, 39.1008], [-67.0769, 18.0213], @@ -55,13 +38,30 @@ [-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], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], + [-84.4686, 31.1948], + [-106.8425, 32.5907] ] }, "properties": { "title": "climatology", - "description": "All scores for the Daily_latent_heat_flux 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, 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_latent_heat_flux 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: 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, JORN.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-08T00:00:00Z", "providers": [ @@ -92,23 +92,6 @@ "le", "Daily", "P1D", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL", - "JERC", - "JORN", "KONA", "KONZ", "LAJA", @@ -138,7 +121,24 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", + "JERC", + "JORN" ], "table:columns": [ { diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_arima.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_arima.json index 3736f8bb7f..e01635f3c1 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_arima.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_arima.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_arima", "description": "All scores for the Daily_latent_heat_flux 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_ets.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_ets.json index 1143b24fc3..6683e69cc9 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_ets.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_ets.json @@ -9,6 +9,20 @@ "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], @@ -41,27 +55,13 @@ [-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] + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_ets", - "description": "All scores for the Daily_latent_heat_flux 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: 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "description": "All scores for the Daily_latent_heat_flux 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 Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,6 +92,20 @@ "le", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", "HEAL", "JERC", "JORN", @@ -124,21 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV" + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_tbats.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_tbats.json index 89b6caab6e..0cac26c41e 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_tbats.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/tg_tbats.json @@ -61,7 +61,7 @@ "properties": { "title": "tg_tbats", "description": "All scores for the Daily_latent_heat_flux 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: 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, MLBS, MOAB.\n Scores are metrics that describe how well forecasts compare to observations. The scores catalog includes are summaries of the forecasts (i.e., mean, median, confidence intervals), matched observations (if available), and scores (metrics of how well the model distribution compares to observations)", - "datetime": "2024-09-22T00:00:00Z", + "datetime": "2024-09-23T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [