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update catalog
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github-actions committed Dec 12, 2024
1 parent a146d32 commit f436cf5
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Showing 7 changed files with 24 additions and 24 deletions.
2 changes: 1 addition & 1 deletion catalog/forecasts/aquatics/Daily_Chlorophyll_a/collection.json
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"interval": [
[
"2024-02-07T00:00:00Z",
"2025-01-14T00:00:00Z"
"2025-01-15T00:00:00Z"
]
]
}
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6 changes: 3 additions & 3 deletions catalog/forecasts/aquatics/Daily_Chlorophyll_a/models/USGSHABs1.json
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"properties": {
"title": "USGSHABs1",
"description": "All forecasts for the Daily_Chlorophyll_a variable for the USGSHABs1 model. Information for the model is provided as follows: Uses the randomForest::randomForest() R package model to train site-specific models for predicting river chl-a. Uses ensemble Kalman filter to adjust predicted chl-a states..\n The model predicts this variable at the following sites: USGS-14211720, USGS-14181500, USGS-05586300, USGS-05558300, USGS-05553700, USGS-05543010, USGS-05549500, USGS-01427510, USGS-14211010, USGS-01463500.\n Forecasts are the raw forecasts that includes all ensemble members or distribution parameters. Due to the size of the raw forecasts, we recommend accessing the forecast summaries or scores to analyze forecasts (unless you need the individual ensemble members)",
"datetime": "2024-12-10",
"updated": "2024-12-11",
"datetime": "2024-12-11",
"updated": "2024-12-12",
"start_datetime": "2024-02-13T00:00:00Z",
"end_datetime": "2025-01-12T00:00:00Z",
"end_datetime": "2025-01-13T00:00:00Z",
"providers": [
{
"url": "https://code.usgs.gov/wma/proxies/habs/habs-forecast-chl-usgsrc4cast/-/blob/main/2_model/src/chla_models.R?ref_type=heads",
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6 changes: 3 additions & 3 deletions catalog/forecasts/aquatics/Daily_Chlorophyll_a/models/USGSHABsDL1.json
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"properties": {
"title": "USGSHABsDL1",
"description": "All forecasts for the Daily_Chlorophyll_a variable for the USGSHABsDL1 model. Information for the model is provided as follows: We train a long-short term memory neural network to predict the Gaussian distribution of river chl-a and update the model states with ensemble Kalman filter. Written in PyTorch.\n The model predicts this variable at the following sites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720.\n Forecasts are the raw forecasts that includes all ensemble members or distribution parameters. Due to the size of the raw forecasts, we recommend accessing the forecast summaries or scores to analyze forecasts (unless you need the individual ensemble members)",
"datetime": "2024-12-10",
"updated": "2024-12-11",
"datetime": "2024-12-11",
"updated": "2024-12-12",
"start_datetime": "2024-09-26T00:00:00Z",
"end_datetime": "2025-01-08T00:00:00Z",
"end_datetime": "2025-01-09T00:00:00Z",
"providers": [
{
"url": "https://projects.ecoforecast.org/neon4cast-ci/",
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24 changes: 12 additions & 12 deletions catalog/forecasts/aquatics/Daily_Chlorophyll_a/models/climatology.json
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"geometry": {
"type": "MultiPoint",
"coordinates": [
[-88.2515, 42.31],
[-75.0574, 41.7567],
[-74.7781, 40.2217],
[-88.6142, 41.2999],
[-88.984, 41.3248],
[-89.3562, 41.1073],
[-90.6077, 39.6328],
[-122.2974, 44.7538],
[-122.5773, 45.3793],
[-122.6692, 45.5175],
[-75.0574, 41.7567],
[-74.7781, 40.2217],
[-88.6142, 41.2999]
[-88.2515, 42.31]
]
},
"properties": {
"title": "climatology",
"description": "All forecasts for the Daily_Chlorophyll_a variable for the climatology model. Information for the model is provided as follows: Forecasts stream chlorophyll-a based on the historic average and standard deviation for that given site and day-of-year..\n The model predicts this variable at the following sites: USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720, USGS-01427510, USGS-01463500, USGS-05543010.\n Forecasts are the raw forecasts that includes all ensemble members or distribution parameters. Due to the size of the raw forecasts, we recommend accessing the forecast summaries or scores to analyze forecasts (unless you need the individual ensemble members)",
"datetime": "2024-12-10",
"updated": "2024-12-11",
"description": "All forecasts for the Daily_Chlorophyll_a variable for the climatology model. Information for the model is provided as follows: Forecasts stream chlorophyll-a based on the historic average and standard deviation for that given site and day-of-year..\n The model predicts this variable at the following sites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720, USGS-05549500.\n Forecasts are the raw forecasts that includes all ensemble members or distribution parameters. Due to the size of the raw forecasts, we recommend accessing the forecast summaries or scores to analyze forecasts (unless you need the individual ensemble members)",
"datetime": "2024-12-11",
"updated": "2024-12-12",
"start_datetime": "2024-02-07T00:00:00Z",
"end_datetime": "2025-01-14T00:00:00Z",
"end_datetime": "2025-01-15T00:00:00Z",
"providers": [
{
"url": "https://github.com/eco4cast/usgsrc4cast-ci/blob/main/baseline_models/models/aquatics_climatology.R",
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"chla",
"Daily",
"P1D",
"USGS-05549500",
"USGS-01427510",
"USGS-01463500",
"USGS-05543010",
"USGS-05553700",
"USGS-05558300",
"USGS-05586300",
"USGS-14181500",
"USGS-14211010",
"USGS-14211720",
"USGS-01427510",
"USGS-01463500",
"USGS-05543010"
"USGS-05549500"
],
"table:columns": [
{
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6 changes: 3 additions & 3 deletions catalog/forecasts/aquatics/Daily_Chlorophyll_a/models/persistenceRW.json
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"properties": {
"title": "persistenceRW",
"description": "All forecasts for the Daily_Chlorophyll_a variable for the persistenceRW model. Information for the model is provided as follows: Random walk model based on most recent stream chl-a observations using the fable::RW() model..\n The model predicts this variable at the following sites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720.\n Forecasts are the raw forecasts that includes all ensemble members or distribution parameters. Due to the size of the raw forecasts, we recommend accessing the forecast summaries or scores to analyze forecasts (unless you need the individual ensemble members)",
"datetime": "2024-12-10",
"updated": "2024-12-11",
"datetime": "2024-12-11",
"updated": "2024-12-12",
"start_datetime": "2024-02-07T00:00:00Z",
"end_datetime": "2025-01-13T00:00:00Z",
"end_datetime": "2025-01-14T00:00:00Z",
"providers": [
{
"url": "https://github.com/eco4cast/usgsrc4cast-ci/blob/main/baseline_models/models/aquatics_persistenceRW.R",
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2 changes: 1 addition & 1 deletion catalog/forecasts/aquatics/collection.json
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Expand Up @@ -59,7 +59,7 @@
"interval": [
[
"2024-02-07T00:00:00Z",
"2025-01-14T00:00:00Z"
"2025-01-15T00:00:00Z"
]
]
}
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2 changes: 1 addition & 1 deletion catalog/forecasts/collection.json
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Expand Up @@ -57,7 +57,7 @@
"interval": [
[
"2024-02-07T00:00:00Z",
"2025-01-14T00:00:00Z"
"2025-01-15T00:00:00Z"
]
]
}
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