update catalog

LTREB-reservoirs · Nov 2, 2023 · fbf6fdb · fbf6fdb
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diff --git a/catalog/forecasts/Biological/Bloom_binary_mean_daily/collection.json b/catalog/forecasts/Biological/Bloom_binary_mean_daily/collection.json
@@ -78,7 +78,7 @@
       "interval": [
         [
           "2023-10-18T00:00:00Z",
-          "2023-12-05T00:00:00Z"
+          "2023-12-06T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/forecasts/Biological/Chla_ugL_mean_daily/collection.json b/catalog/forecasts/Biological/Chla_ugL_mean_daily/collection.json
@@ -93,7 +93,7 @@
       "interval": [
         [
           "2023-10-01T00:00:00Z",
-          "2023-12-06T00:00:00Z"
+          "2023-12-07T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/forecasts/Physical/Temp_C_mean_daily/collection.json b/catalog/forecasts/Physical/Temp_C_mean_daily/collection.json
@@ -93,7 +93,7 @@
       "interval": [
         [
           "2023-09-21T00:00:00Z",
-          "2023-12-06T00:00:00Z"
+          "2023-12-07T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/forecasts/models/model_items/climatology.json b/catalog/forecasts/models/model_items/climatology.json
@@ -24,7 +24,7 @@
   "properties": {
     "description": "\nmodel info: Historical DOY mean and sd.  Assumes normal distribution\n\nSites: bvre, fcre, tubr\n\nVariables: Chla_ugL_mean, Temp_C_mean, Flow_cms_mean, AirTemp_C_mean",
     "start_datetime": "2023-09-21",
-    "end_datetime": "2023-12-06",
+    "end_datetime": "2023-12-07",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/ecmwf_ifs04.json b/catalog/forecasts/models/model_items/ecmwf_ifs04.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: ECMWF IFS Ensemble weather model downloaded from open-meteo.com.  Since ECMWF IFS Ensemble does output solar radiation on open-meteo.com,  the solar radiation from GFS seamless is used.\n\nSites: fcre\n\nVariables: AirTemp_C_mean, RH_percent_mean, Rain_mm_sum, BP_kPa_mean, WindSpeed_ms_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-11-09",
+    "end_datetime": "2023-11-10",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/fableARIMA.json b/catalog/forecasts/models/model_items/fableARIMA.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: ARIMA fit using the ARIMA() function in the fable R package\n\nSites: fcre, bvre\n\nVariables: Chla_ugL_mean, Bloom_binary_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/fableETS.json b/catalog/forecasts/models/model_items/fableETS.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: fable package exponential smoothing model fable::ETS()\n\nSites: bvre, fcre\n\nVariables: Chla_ugL_mean, Bloom_binary_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/fableNNETAR.json b/catalog/forecasts/models/model_items/fableNNETAR.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: autoregressive neural net fit using the NNETAR() function in the fable R package\n\nSites: bvre, fcre\n\nVariables: Bloom_binary_mean, Chla_ugL_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/gem_global.json b/catalog/forecasts/models/model_items/gem_global.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: Candian GEM Global Ensemble model downloaded from open-meteo.com\n\nSites: fcre\n\nVariables: Rain_mm_sum, ShortwaveRadiationUp_Wm2_mean, BP_kPa_mean, WindSpeed_ms_mean, AirTemp_C_mean, RH_percent_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-12-01",
+    "end_datetime": "2023-12-02",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/gfs_seamless.json b/catalog/forecasts/models/model_items/gfs_seamless.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: NOAA Global Ensemble Forecasting Model downloaded using the https://open-meteo.com.  The seamless model combines the 0.25 and 0.5 degree resolution products to get a full 35-day ahead forecast\n\nSites: fcre\n\nVariables: RH_percent_mean, Rain_mm_sum, ShortwaveRadiationUp_Wm2_mean, BP_kPa_mean, AirTemp_C_mean, WindSpeed_ms_mean",
     "start_datetime": "2023-10-13",
-    "end_datetime": "2023-12-04",
+    "end_datetime": "2023-12-05",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/icon_seamless.json b/catalog/forecasts/models/model_items/icon_seamless.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: The DWD Icon EPS Seamless model downloaded from open-meteo.com\n\nSites: fcre\n\nVariables: BP_kPa_mean, RH_percent_mean, Rain_mm_sum, AirTemp_C_mean, WindSpeed_ms_mean, ShortwaveRadiationUp_Wm2_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-11-06",
+    "end_datetime": "2023-11-07",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/inflow_gefsClimAED.json b/catalog/forecasts/models/model_items/inflow_gefsClimAED.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: flow is forecasted as using a linear relationship between historical flow, month, and 5-day sum of precipitation.  Temperature is forecasted using a linear relationship between historical water temperature, month, and 5-day mean air temperature.  NOAA GEFS is then used to get the future values of 5-day sum precipitation and mean temperature.  Nutrients are forecasting using the DOY climatology.  The DOY climatology was developed using a linear interpolation of the historical samples.\n\nSites: tubr\n\nVariables: DIC_mgL_sample, DRSI_mgL_sample, Flow_cms_mean, Temp_C_mean, CH4_umolL_sample, DOC_mgL_sample, TN_ugL_sample, NH4_ugL_sample, TP_ugL_sample, NO3NO2_ugL_sample, SRP_ugL_sample",
     "start_datetime": "2023-10-13",
-    "end_datetime": "2023-12-04",
+    "end_datetime": "2023-12-05",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/forecasts/models/model_items/persistenceRW.json b/catalog/forecasts/models/model_items/persistenceRW.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: bvre, fcre\n\nVariables: Chla_ugL_mean, Temp_C_mean",
     "start_datetime": "2023-09-21",
-    "end_datetime": "2023-12-06",
+    "end_datetime": "2023-12-07",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/Biological/Bloom_binary_mean_daily/collection.json b/catalog/scores/Biological/Bloom_binary_mean_daily/collection.json
@@ -78,7 +78,7 @@
       "interval": [
         [
           "2023-10-18T00:00:00Z",
-          "2023-12-05T00:00:00Z"
+          "2023-12-06T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/scores/Biological/Chla_ugL_mean_daily/collection.json b/catalog/scores/Biological/Chla_ugL_mean_daily/collection.json
@@ -93,7 +93,7 @@
       "interval": [
         [
           "2023-10-01T00:00:00Z",
-          "2023-12-06T00:00:00Z"
+          "2023-12-07T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/scores/Physical/Temp_C_mean_daily/collection.json b/catalog/scores/Physical/Temp_C_mean_daily/collection.json
@@ -93,7 +93,7 @@
       "interval": [
         [
           "2023-09-21T00:00:00Z",
-          "2023-12-06T00:00:00Z"
+          "2023-12-07T00:00:00Z"
         ]
       ]
     }

diff --git a/catalog/scores/models/model_items/climatology.json b/catalog/scores/models/model_items/climatology.json
@@ -24,7 +24,7 @@
   "properties": {
     "description": "\nmodel info: Historical DOY mean and sd.  Assumes normal distribution\n\nSites: bvre, fcre, tubr\n\nVariables: Chla_ugL_mean, Temp_C_mean, Flow_cms_mean, AirTemp_C_mean",
     "start_datetime": "2023-09-21",
-    "end_datetime": "2023-12-06",
+    "end_datetime": "2023-12-07",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/ecmwf_ifs04.json b/catalog/scores/models/model_items/ecmwf_ifs04.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: ECMWF IFS Ensemble weather model downloaded from open-meteo.com.  Since ECMWF IFS Ensemble does output solar radiation on open-meteo.com,  the solar radiation from GFS seamless is used.\n\nSites: fcre\n\nVariables: AirTemp_C_mean, RH_percent_mean, Rain_mm_sum, BP_kPa_mean, WindSpeed_ms_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-11-09",
+    "end_datetime": "2023-11-10",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/fableARIMA.json b/catalog/scores/models/model_items/fableARIMA.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: ARIMA fit using the ARIMA() function in the fable R package\n\nSites: fcre, bvre\n\nVariables: Chla_ugL_mean, Bloom_binary_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/fableETS.json b/catalog/scores/models/model_items/fableETS.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: fable package exponential smoothing model fable::ETS()\n\nSites: bvre, fcre\n\nVariables: Chla_ugL_mean, Bloom_binary_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/fableNNETAR.json b/catalog/scores/models/model_items/fableNNETAR.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: autoregressive neural net fit using the NNETAR() function in the fable R package\n\nSites: bvre, fcre\n\nVariables: Bloom_binary_mean, Chla_ugL_mean",
     "start_datetime": "2023-10-12",
-    "end_datetime": "2023-12-05",
+    "end_datetime": "2023-12-06",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/gem_global.json b/catalog/scores/models/model_items/gem_global.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: Candian GEM Global Ensemble model downloaded from open-meteo.com\n\nSites: fcre\n\nVariables: Rain_mm_sum, ShortwaveRadiationUp_Wm2_mean, BP_kPa_mean, WindSpeed_ms_mean, AirTemp_C_mean, RH_percent_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-12-01",
+    "end_datetime": "2023-12-02",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/gfs_seamless.json b/catalog/scores/models/model_items/gfs_seamless.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: NOAA Global Ensemble Forecasting Model downloaded using the https://open-meteo.com.  The seamless model combines the 0.25 and 0.5 degree resolution products to get a full 35-day ahead forecast\n\nSites: fcre\n\nVariables: RH_percent_mean, Rain_mm_sum, ShortwaveRadiationUp_Wm2_mean, BP_kPa_mean, AirTemp_C_mean, WindSpeed_ms_mean",
     "start_datetime": "2023-10-13",
-    "end_datetime": "2023-12-04",
+    "end_datetime": "2023-12-05",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/icon_seamless.json b/catalog/scores/models/model_items/icon_seamless.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: The DWD Icon EPS Seamless model downloaded from open-meteo.com\n\nSites: fcre\n\nVariables: BP_kPa_mean, RH_percent_mean, Rain_mm_sum, AirTemp_C_mean, WindSpeed_ms_mean, ShortwaveRadiationUp_Wm2_mean",
     "start_datetime": "2023-10-14",
-    "end_datetime": "2023-11-06",
+    "end_datetime": "2023-11-07",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/inflow_gefsClimAED.json b/catalog/scores/models/model_items/inflow_gefsClimAED.json
@@ -22,7 +22,7 @@
   "properties": {
     "description": "\nmodel info: flow is forecasted as using a linear relationship between historical flow, month, and 5-day sum of precipitation.  Temperature is forecasted using a linear relationship between historical water temperature, month, and 5-day mean air temperature.  NOAA GEFS is then used to get the future values of 5-day sum precipitation and mean temperature.  Nutrients are forecasting using the DOY climatology.  The DOY climatology was developed using a linear interpolation of the historical samples.\n\nSites: tubr\n\nVariables: DIC_mgL_sample, DRSI_mgL_sample, Flow_cms_mean, Temp_C_mean, CH4_umolL_sample, DOC_mgL_sample, TN_ugL_sample, NH4_ugL_sample, TP_ugL_sample, NO3NO2_ugL_sample, SRP_ugL_sample",
     "start_datetime": "2023-10-13",
-    "end_datetime": "2023-12-04",
+    "end_datetime": "2023-12-05",
     "providers": [
       {
         "url": "pending",

diff --git a/catalog/scores/models/model_items/persistenceRW.json b/catalog/scores/models/model_items/persistenceRW.json
@@ -23,7 +23,7 @@
   "properties": {
     "description": "\nmodel info: Random walk from the fable package with ensembles used to represent uncertainty\n\nSites: bvre, fcre\n\nVariables: Chla_ugL_mean, Temp_C_mean",
     "start_datetime": "2023-09-21",
-    "end_datetime": "2023-12-06",
+    "end_datetime": "2023-12-07",
     "providers": [
       {
         "url": "pending",