diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json index 77f623ff8..70f69c227 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/collection.json @@ -8,11 +8,6 @@ ], "type": "Collection", "links": [ - { - "rel": "item", - "type": "application/json", - "href": "./models/tg_tbats.json" - }, { "rel": "item", "type": "application/json", @@ -33,6 +28,11 @@ "type": "application/json", "href": "./models/tg_ets.json" }, + { + "rel": "item", + "type": "application/json", + "href": "./models/tg_tbats.json" + }, { "rel": "parent", "type": "application/json", diff --git a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/climatology.json index cf4882ca5..bae81a219 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 d1cffa273..00935f2c2 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 721e7adf6..7b5e672d8 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 3e6b66e24..69736442c 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 bec5bc0d7..efcd80bec 100644 --- a/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json +++ b/catalog/scores/Aquatics/Daily_Chlorophyll_a/models/tg_tbats.json @@ -9,22 +9,22 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-82.0177, 29.6878], - [-88.1589, 31.8534], - [-149.6106, 68.6307], [-82.0084, 29.676], [-87.7982, 32.5415], [-89.4737, 46.2097], [-84.4374, 31.1854], [-89.7048, 45.9983], [-99.1139, 47.1591], - [-99.2531, 47.1298] + [-99.2531, 47.1298], + [-82.0177, 29.6878], + [-88.1589, 31.8534], + [-149.6106, 68.6307] ] }, "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: SUGG, TOMB, TOOK, BARC, BLWA, CRAM, FLNT, LIRO, PRLA, PRPO.\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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -55,16 +55,16 @@ "chla", "Daily", "P1D", - "SUGG", - "TOMB", - "TOOK", "BARC", "BLWA", "CRAM", "FLNT", "LIRO", "PRLA", - "PRPO" + "PRPO", + "SUGG", + "TOMB", + "TOOK" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/collection.json index bd15b767d..0e5676a1f 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/persistenceRW.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/hotdeck.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/AquaticEcosystemsOxygen.json" }, { "rel": "item", "type": "application/json", - "href": "./models/hotdeck.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/AquaticEcosystemsOxygen.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_arima.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 de7ed6b89..212fd8cd9 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 ea189842a..f21083c6e 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "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 418168568..dd818fc41 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/hotdeck.json @@ -9,8 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-82.0177, 29.6878], - [-111.5081, 33.751], [-82.0084, 29.676], [-119.2575, 37.0597], [-110.5871, 44.9501], @@ -22,13 +20,15 @@ [-122.1655, 44.2596], [-78.1473, 38.8943], [-97.7823, 33.3785], - [-111.7979, 40.7839] + [-111.7979, 40.7839], + [-82.0177, 29.6878], + [-111.5081, 33.751] ] }, "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": "2024-09-25T00:00:00Z", + "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: BARC, BIGC, BLDE, CRAM, KING, LEWI, LIRO, MAYF, MCRA, POSE, PRIN, REDB, SUGG, SYCA.\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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -59,8 +59,6 @@ "oxygen", "Daily", "P1D", - "SUGG", - "SYCA", "BARC", "BIGC", "BLDE", @@ -72,7 +70,9 @@ "MCRA", "POSE", "PRIN", - "REDB" + "REDB", + "SUGG", + "SYCA" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json index 559116d4d..49250e4dc 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/persistenceRW.json @@ -9,10 +9,6 @@ "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], @@ -42,13 +38,17 @@ [-111.7979, 40.7839], [-82.0177, 29.6878], [-111.5081, 33.751], - [-119.0274, 36.9559] + [-119.0274, 36.9559], + [-88.1589, 31.8534], + [-149.6106, 68.6307], + [-84.2793, 35.9574], + [-105.9154, 39.8914] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -79,10 +79,6 @@ "oxygen", "Daily", "P1D", - "TOMB", - "TOOK", - "WALK", - "WLOU", "ARIK", "BARC", "BIGC", @@ -112,7 +108,11 @@ "REDB", "SUGG", "SYCA", - "TECR" + "TECR", + "TOMB", + "TOOK", + "WALK", + "WLOU" ], "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 583ff0fc8..514af0103 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_arima.json @@ -48,7 +48,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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/tg_ets.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json index 6dac78798..7ec9fc527 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_ets.json @@ -48,7 +48,7 @@ "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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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/tg_tbats.json b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json index 3c0aa46b0..7032255b9 100644 --- a/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json +++ b/catalog/scores/Aquatics/Daily_Dissolved_oxygen/models/tg_tbats.json @@ -48,7 +48,7 @@ "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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json index 16af985e7..e73806b25 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/collection.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/collection.json @@ -11,22 +11,22 @@ { "rel": "item", "type": "application/json", - "href": "./models/fTSLM_lag.json" + "href": "./models/flareGLM_noDA.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGLM.json" + "href": "./models/hotdeck.json" }, { "rel": "item", "type": "application/json", - "href": "./models/flareGLM_noDA.json" + "href": "./models/fARIMA_clim_ensemble.json" }, { "rel": "item", "type": "application/json", - "href": "./models/fARIMA_clim_ensemble.json" + "href": "./models/GLEON_JRabaey_temp_physics.json" }, { "rel": "item", @@ -36,17 +36,17 @@ { "rel": "item", "type": "application/json", - "href": "./models/GLEON_JRabaey_temp_physics.json" + "href": "./models/lm_AT_WTL_WS.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/mkricheldorf_w_lag.json" }, { "rel": "item", "type": "application/json", - "href": "./models/hotdeck.json" + "href": "./models/mlp1_wtempforecast_LF.json" }, { "rel": "item", @@ -56,17 +56,17 @@ { "rel": "item", "type": "application/json", - "href": "./models/lm_AT_WTL_WS.json" + "href": "./models/fTSLM_lag.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mkricheldorf_w_lag.json" + "href": "./models/flareGLM.json" }, { "rel": "item", "type": "application/json", - "href": "./models/mlp1_wtempforecast_LF.json" + "href": "./models/GLEON_lm_lag_1day.json" }, { "rel": "item", @@ -81,22 +81,22 @@ { "rel": "item", "type": "application/json", - "href": "./models/GLEON_lm_lag_1day.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.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/tg_tbats.json" + "href": "./models/tg_arima.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 ce23567bb..f4752527f 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 7b479f476..633cfdfaf 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 @@ -48,7 +48,7 @@ "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: 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, PRLA, PRPO, 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-01-02T00:00:00Z", "end_datetime": "2024-03-12T00:00:00Z", "providers": [ 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 c68af8333..41613e413 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 3e6999fbb..ad24a2713 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/baseline_ensemble.json @@ -9,6 +9,15 @@ "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], @@ -33,22 +42,13 @@ [-88.1589, 31.8534], [-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], [-149.6106, 68.6307] ] }, "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: CUPE, FLNT, GUIL, HOPB, KING, LECO, 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, 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": "2024-09-25T00:00:00Z", + "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: 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, WALK, WLOU, 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-01T00:00:00Z", "providers": [ @@ -79,6 +79,15 @@ "temperature", "Daily", "P1D", + "ARIK", + "BARC", + "BIGC", + "BLDE", + "BLUE", + "BLWA", + "CARI", + "COMO", + "CRAM", "CUPE", "FLNT", "GUIL", @@ -103,15 +112,6 @@ "TOMB", "WALK", "WLOU", - "ARIK", - "BARC", - "BIGC", - "BLDE", - "BLUE", - "BLWA", - "CARI", - "COMO", - "CRAM", "TOOK" ], "table:columns": [ 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 166bdd629..4428cc425 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 605d35f25..822ef8f95 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: 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, ARIK, BARC, BIGC, BLDE.\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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 a9e68fade..759a7ae69 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 @@ -47,7 +47,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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/fTSLM_lag.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json index 0cd43105a..9ac296944 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/fTSLM_lag.json @@ -48,7 +48,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM.json index 87f2b51f8..0e8abfef4 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 5a65c56d7..bff7efdc1 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/flareGLM_noDA.json @@ -9,19 +9,19 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-82.0084, 29.676], - [-89.4737, 46.2097], - [-89.7048, 45.9983], [-99.1139, 47.1591], [-99.2531, 47.1298], [-82.0177, 29.6878], - [-149.6106, 68.6307] + [-149.6106, 68.6307], + [-82.0084, 29.676], + [-89.4737, 46.2097], + [-89.7048, 45.9983] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -52,13 +52,13 @@ "temperature", "Daily", "P1D", - "BARC", - "CRAM", - "LIRO", "PRLA", "PRPO", "SUGG", - "TOOK" + "TOOK", + "BARC", + "CRAM", + "LIRO" ], "table:columns": [ { diff --git a/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json b/catalog/scores/Aquatics/Daily_Water_temperature/models/hotdeck.json index fb448847a..5ff14e97d 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 d9db8bbd9..38e869d0f 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 d9c14c6f2..985aa7b3a 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 8b3134c74..e8070826c 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 a410e8ad5..77aa81b50 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "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 1fcd23a70..6b3dfacf7 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 3d821f15a..ed7bef4d7 100644 --- a/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json +++ b/catalog/scores/Aquatics/Daily_Water_temperature/models/tg_ets.json @@ -9,6 +9,16 @@ "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], @@ -32,23 +42,13 @@ [-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] + [-97.7823, 33.3785] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -79,6 +79,16 @@ "temperature", "Daily", "P1D", + "PRLA", + "PRPO", + "REDB", + "SUGG", + "SYCA", + "TECR", + "TOMB", + "TOOK", + "WALK", + "WLOU", "ARIK", "BARC", "BIGC", @@ -102,17 +112,7 @@ "MCRA", "OKSR", "POSE", - "PRIN", - "PRLA", - "PRPO", - "REDB", - "SUGG", - "SYCA", - "TECR", - "TOMB", - "TOOK", - "WALK", - "WLOU" + "PRIN" ], "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 2dbb2391b..bc98203d9 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 bf3e6d928..2898d2007 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 98000ee8a..2322ae5f8 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 @@ -9,6 +9,11 @@ "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], @@ -50,18 +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] + [-110.5391, 44.9535] ] }, "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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-17T00:00:00Z", "end_datetime": "2024-07-22T00:00:00Z", "providers": [ @@ -92,6 +92,11 @@ "abundance", "Weekly", "P1W", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", "CLBJ", "CPER", "DCFS", @@ -133,12 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA" + "YELL" ], "table:columns": [ { 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 5edd94c8a..9e567864d 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 a133f4882..e7622412c 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 2faa45607..3fa5c8c09 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 a897281d0..18f896f96 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 96cf78478..2efa98a35 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 5b27deabd..14fb0e9be 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_arima.json" + "href": "./models/ChlorophyllCrusaders.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "./models/ChlorophyllCrusaders.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.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 9c3aca5aa..b017e4154 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 5450d8951..6be4dd8d2 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/climatology.json @@ -61,7 +61,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ 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 e4d37fd25..042418dad 100644 --- a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json +++ b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/persistenceRW.json @@ -9,6 +9,21 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], @@ -40,28 +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], - [-149.2133, 63.8758] + [-110.5391, 44.9535] ] }, "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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ @@ -92,6 +92,21 @@ "gcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", "JERC", "JORN", "KONA", @@ -123,22 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL" + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_arima.json index 9ebeb87bf..bf529f7d8 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 @@ -9,29 +9,6 @@ "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], @@ -55,13 +32,36 @@ [-88.1612, 31.8539], [-80.5248, 37.3783], [-109.3883, 38.2483], - [-105.5824, 40.0543] + [-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] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ @@ -92,29 +92,6 @@ "gcc_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", @@ -138,7 +115,30 @@ "LENO", "MLBS", "MOAB", - "NIWO" + "NIWO", + "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/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json b/catalog/scores/Phenology/Daily_Green_chromatic_coordinate/models/tg_ets.json index d40fc1fba..43c7cee4b 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 @@ -9,6 +9,11 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-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], @@ -50,18 +55,13 @@ [-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] + [-89.5857, 45.4937] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ @@ -92,6 +92,11 @@ "gcc_90", "Daily", "P1D", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL", "ABBY", "BARR", "BART", @@ -133,12 +138,7 @@ "TALL", "TEAK", "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL" + "TREE" ], "table:columns": [ { 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 c0b67dc14..ecfd4ab3b 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 @@ -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_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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-07-28T00:00:00Z", "providers": [ @@ -92,6 +92,10 @@ "gcc_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/collection.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/collection.json index 753c6958a..b42759d45 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/tg_tbats.json" + "href": "./models/tg_arima.json" }, { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_arima.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/baseline_ensemble.json" }, { "rel": "item", "type": "application/json", - "href": "./models/baseline_ensemble.json" + "href": "./models/climatology.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 c56a213f5..8ec544a06 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 @@ -9,11 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-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], @@ -55,13 +50,18 @@ [-89.5857, 45.4937], [-95.1921, 39.0404], [-89.5373, 46.2339], - [-99.2413, 47.1282] + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535], + [-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: WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD.\n 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-01T00:00:00Z", "providers": [ @@ -92,11 +92,6 @@ "rcc_90", "Daily", "P1D", - "WREF", - "YELL", - "ABBY", - "BARR", - "BART", "BLAN", "BONA", "CLBJ", @@ -138,7 +133,12 @@ "TREE", "UKFS", "UNDE", - "WOOD" + "WOOD", + "WREF", + "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 554c5a6fa..48cd7711d 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 +9,21 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251], + [-83.5019, 35.689], + [-66.8687, 17.9696], + [-72.1727, 42.5369], + [-149.2133, 63.8758], [-84.4686, 31.1948], [-106.8425, 32.5907], [-96.6129, 39.1104], @@ -40,28 +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], - [-149.2133, 63.8758] + [-110.5391, 44.9535] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-07T00:00:00Z", "providers": [ @@ -92,6 +92,21 @@ "rcc_90", "Daily", "P1D", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV", + "HEAL", "JERC", "JORN", "KONA", @@ -123,22 +138,7 @@ "UNDE", "WOOD", "WREF", - "YELL", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", - "HEAL" + "YELL" ], "table:columns": [ { diff --git a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json index bec25dcc7..0e22b7fc4 100644 --- a/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json +++ b/catalog/scores/Phenology/Daily_Red_chromatic_coordinate/models/persistenceRW.json @@ -9,6 +9,20 @@ "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], @@ -41,27 +55,13 @@ [-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] + [-76.56, 38.8901] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-06T00:00:00Z", "providers": [ @@ -92,6 +92,20 @@ "rcc_90", "Daily", "P1D", + "SJER", + "SOAP", + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL", "ABBY", "BARR", "BART", @@ -124,21 +138,7 @@ "PUUM", "RMNP", "SCBI", - "SERC", - "SJER", - "SOAP", - "SRER", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL" + "SERC" ], "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 198bf4d12..f994f72ec 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 @@ -9,19 +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], @@ -55,13 +42,26 @@ [-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] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN.\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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,19 +92,6 @@ "rcc_90", "Daily", "P1D", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", "HARV", "HEAL", "JERC", @@ -138,7 +125,20 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN" ], "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 1d5933109..b958a3612 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 @@ -61,7 +61,7 @@ "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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ 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 f723aadd1..ad1954db8 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 @@ -61,7 +61,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ diff --git a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json index 56d7947ec..f4fd64ded 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/collection.json @@ -11,12 +11,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/climatology.json" + "href": "./models/tg_ets.json" }, { "rel": "item", "type": "application/json", - "href": "./models/persistenceRW.json" + "href": "./models/tg_tbats.json" }, { "rel": "item", @@ -26,12 +26,12 @@ { "rel": "item", "type": "application/json", - "href": "./models/tg_ets.json" + "href": "./models/persistenceRW.json" }, { "rel": "item", "type": "application/json", - "href": "./models/tg_tbats.json" + "href": "./models/climatology.json" }, { "rel": "item", 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 55c37c423..5d6c22b12 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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 5afa3ca27..6caf37c0f 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/climatology.json @@ -9,19 +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], [-78.0418, 39.0337], [-147.5026, 65.154], @@ -55,13 +42,26 @@ [-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], + [-122.3303, 45.7624], + [-156.6194, 71.2824] ] }, "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": "2024-09-25T00:00:00Z", + "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: 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, ABBY, BARR.\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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-03T00:00:00Z", "providers": [ @@ -92,19 +92,6 @@ "nee", "Daily", "P1D", - "STEI", - "STER", - "TALL", - "TEAK", - "TOOL", - "TREE", - "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL", - "ABBY", - "BARR", "BART", "BLAN", "BONA", @@ -138,7 +125,20 @@ "SERC", "SJER", "SOAP", - "SRER" + "SRER", + "STEI", + "STER", + "TALL", + "TEAK", + "TOOL", + "TREE", + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL", + "ABBY", + "BARR" ], "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 7d7ca38a5..9ab194b0c 100644 --- a/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json +++ b/catalog/scores/Terrestrial/Daily_Net_ecosystem_exchange/models/persistenceRW.json @@ -9,6 +9,9 @@ "geometry": { "type": "MultiPoint", "coordinates": [ + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -52,16 +55,13 @@ [-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] + [-89.5373, 46.2339] ] }, "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": "2024-09-25T00:00:00Z", + "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: WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE.\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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-03T00:00:00Z", "providers": [ @@ -92,6 +92,9 @@ "nee", "Daily", "P1D", + "WOOD", + "WREF", + "YELL", "ABBY", "BARR", "BART", @@ -135,10 +138,7 @@ "TOOL", "TREE", "UKFS", - "UNDE", - "WOOD", - "WREF", - "YELL" + "UNDE" ], "table:columns": [ { 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 e6ebe7bc5..33d405cff 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 @@ -61,7 +61,7 @@ "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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ 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 15c9bd004..8c1ef0396 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 @@ -9,6 +9,28 @@ "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], @@ -33,35 +55,13 @@ [-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] + [-100.9154, 46.7697] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,6 +92,28 @@ "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", @@ -116,29 +138,7 @@ "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" + "NOGP" ], "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 800bcf31f..98417328f 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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "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/climatology.json b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json index d38f09aff..6304a6834 100644 --- a/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json +++ b/catalog/scores/Terrestrial/Daily_latent_heat_flux/models/climatology.json @@ -9,17 +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], @@ -55,13 +44,24 @@ [-89.5373, 46.2339], [-99.2413, 47.1282], [-121.9519, 45.8205], - [-110.5391, 44.9535] + [-110.5391, 44.9535], + [-122.3303, 45.7624], + [-156.6194, 71.2824], + [-71.2874, 44.0639], + [-78.0418, 39.0337], + [-147.5026, 65.154], + [-97.57, 33.4012], + [-104.7456, 40.8155], + [-99.1066, 47.1617], + [-145.7514, 63.8811], + [-87.8039, 32.5417], + [-81.4362, 28.1251] ] }, "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": "2024-09-25T00:00:00Z", + "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: GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS, UNDE, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY.\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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-08T00:00:00Z", "providers": [ @@ -92,17 +92,6 @@ "le", "Daily", "P1D", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", "GRSM", "GUAN", "HARV", @@ -138,7 +127,18 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY" ], "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 6e9c92db6..a2dcbf3d7 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 @@ -9,10 +9,6 @@ "geometry": { "type": "MultiPoint", "coordinates": [ - [-89.5373, 46.2339], - [-99.2413, 47.1282], - [-121.9519, 45.8205], - [-110.5391, 44.9535], [-122.3303, 45.7624], [-156.6194, 71.2824], [-71.2874, 44.0639], @@ -55,13 +51,17 @@ [-119.006, 37.0058], [-149.3705, 68.6611], [-89.5857, 45.4937], - [-95.1921, 39.0404] + [-95.1921, 39.0404], + [-89.5373, 46.2339], + [-99.2413, 47.1282], + [-121.9519, 45.8205], + [-110.5391, 44.9535] ] }, "properties": { "title": "tg_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: UNDE, WOOD, WREF, YELL, ABBY, BARR, BART, BLAN, BONA, CLBJ, CPER, DCFS, DEJU, DELA, DSNY, GRSM, GUAN, HARV, HEAL, JERC, JORN, KONA, KONZ, LAJA, LENO, MLBS, MOAB, NIWO, NOGP, OAES, ONAQ, ORNL, OSBS, PUUM, RMNP, SCBI, SERC, SJER, SOAP, SRER, STEI, STER, TALL, TEAK, TOOL, TREE, UKFS.\n 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": "2024-09-25T00:00:00Z", + "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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,10 +92,6 @@ "le", "Daily", "P1D", - "UNDE", - "WOOD", - "WREF", - "YELL", "ABBY", "BARR", "BART", @@ -138,7 +134,11 @@ "TEAK", "TOOL", "TREE", - "UKFS" + "UKFS", + "UNDE", + "WOOD", + "WREF", + "YELL" ], "table:columns": [ { 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 5313f36da..9201af495 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 @@ -9,20 +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], @@ -55,13 +41,27 @@ [-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] ] }, "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: 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": "2024-09-25T00:00:00Z", + "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: 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": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [ @@ -92,20 +92,6 @@ "le", "Daily", "P1D", - "ABBY", - "BARR", - "BART", - "BLAN", - "BONA", - "CLBJ", - "CPER", - "DCFS", - "DEJU", - "DELA", - "DSNY", - "GRSM", - "GUAN", - "HARV", "HEAL", "JERC", "JORN", @@ -138,7 +124,21 @@ "UNDE", "WOOD", "WREF", - "YELL" + "YELL", + "ABBY", + "BARR", + "BART", + "BLAN", + "BONA", + "CLBJ", + "CPER", + "DCFS", + "DEJU", + "DELA", + "DSNY", + "GRSM", + "GUAN", + "HARV" ], "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 ad7a55a74..79cd21e58 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: 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": "2024-09-25T00:00:00Z", + "datetime": "2024-09-26T00:00:00Z", "start_datetime": "2024-06-13T00:00:00Z", "end_datetime": "2024-08-02T00:00:00Z", "providers": [