diff --git a/catalog/forecasts/aquatics/Daily_Chlorophyll_a/collection.json b/catalog/forecasts/aquatics/Daily_Chlorophyll_a/collection.json new file mode 100644 index 0000000000..aa84613658 --- /dev/null +++ b/catalog/forecasts/aquatics/Daily_Chlorophyll_a/collection.json @@ -0,0 +1,152 @@ +{ + "id": "Daily_Chlorophyll_a", + "description": "This page includes all models for the Daily_Chlorophyll_a variable.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/climatology.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/persistenceRW.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "Daily_Chlorophyll_a", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-03-17T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified for probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.”For summary statistics: “summary.”" + }, + { + "name": "parameter", + "type": "string", + "description": "ensemble member or distribution parameter" + }, + { + "name": "prediction", + "type": "double", + "description": "predicted value for variable" + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "project_id", + "type": "string", + "description": "unique identifier for the forecast project" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly, daily, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "reference_date", + "type": "string", + "description": "date that the forecast was initiated" + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "pending", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "pending" + } + } +} diff --git a/catalog/forecasts/aquatics/collection.json b/catalog/forecasts/aquatics/collection.json new file mode 100644 index 0000000000..1c278d639f --- /dev/null +++ b/catalog/forecasts/aquatics/collection.json @@ -0,0 +1,147 @@ +{ + "id": "aquatics", + "description": "This page includes variables for the aquatics group.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "child", + "type": "application/json", + "href": "Daily_Chlorophyll_a/collection.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "aquatics", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-03-17T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified for probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.”For summary statistics: “summary.”" + }, + { + "name": "parameter", + "type": "string", + "description": "ensemble member or distribution parameter" + }, + { + "name": "prediction", + "type": "double", + "description": "predicted value for variable" + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "project_id", + "type": "string", + "description": "unique identifier for the forecast project" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly, daily, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "reference_date", + "type": "string", + "description": "date that the forecast was initiated" + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"chla\")) |>\n dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/Back-b.jpg", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "USGS Streamgage" + } + } +} diff --git a/catalog/forecasts/collection.json b/catalog/forecasts/collection.json index 4dc66e61a6..689e89835b 100644 --- a/catalog/forecasts/collection.json +++ b/catalog/forecasts/collection.json @@ -70,7 +70,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-03-14T00:00:00Z" + "2024-03-17T00:00:00Z" ] ] } diff --git a/catalog/forecasts/models/collection.json b/catalog/forecasts/models/collection.json index 61c0eac9f7..8f38db70c6 100644 --- a/catalog/forecasts/models/collection.json +++ b/catalog/forecasts/models/collection.json @@ -63,7 +63,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-03-14T00:00:00Z" + "2024-03-17T00:00:00Z" ] ] } diff --git a/catalog/forecasts/models/model_items/climatology.json b/catalog/forecasts/models/model_items/climatology.json index 1dfb280dc3..56366817ea 100644 --- a/catalog/forecasts/models/model_items/climatology.json +++ b/catalog/forecasts/models/model_items/climatology.json @@ -30,7 +30,7 @@ "properties": { "description": "\nmodel info: Forecasts stream chlorophyll-a based on the historic average and standard deviation for that given site and day-of-year.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-03-14", + "end_datetime": "2024-03-17", "providers": [ { "url": "pending", diff --git a/catalog/forecasts/models/model_items/persistenceRW.json b/catalog/forecasts/models/model_items/persistenceRW.json index 8374faa30a..0f2a7aeecf 100644 --- a/catalog/forecasts/models/model_items/persistenceRW.json +++ b/catalog/forecasts/models/model_items/persistenceRW.json @@ -31,7 +31,7 @@ "properties": { "description": "\nmodel info: Random walk model based on most recent stream chl-a observations using the fable::RW() model.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-03-13", + "end_datetime": "2024-03-15", "providers": [ { "url": "pending", diff --git a/catalog/inventory/collection.json b/catalog/inventory/collection.json index e5fb725599..2c6de1f42e 100644 --- a/catalog/inventory/collection.json +++ b/catalog/inventory/collection.json @@ -1,166 +1,166 @@ -{ - "id": "inventory", - "description": "The catalog contains forecasts for the EFI-USGS River Chlorophyll Forecasting Challenge. The forecasts are the raw forecasts that include all ensemble members (if a forecast represents uncertainty using an ensemble). Due to the size of the raw forecasts, we recommend accessing the scores (summaries of the forecasts) to analyze forecasts (unless you need the individual ensemble members). You can access the forecasts at the top level of the dataset where all models, variables, and dates that forecasts were produced (reference_datetime) are available. The code to access the entire dataset is provided as an asset. Given the size of the forecast catalog, it can be time-consuming to access the data at the full dataset level. For quicker access to the forecasts for a particular model (model_id), we also provide the code to access the data at the model_id level as an asset for each model.", - "stac_version": "1.0.0", - "license": "CC0-1.0", - "stac_extensions": [ - "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", - "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", - "https://stac-extensions.github.io/table/v1.2.0/schema.json" - ], - "type": "Collection", - "links": [ - { - "rel": "parent", - "type": "application/json", - "href": "../catalog.json" - }, - { - "rel": "root", - "type": "application/json", - "href": "../catalog.json" - }, - { - "rel": "self", - "type": "application/json", - "href": "collection.json" - }, - { - "rel": "cite-as", - "href": "https://doi.org/10.1002/fee.2616" - }, - { - "rel": "about", - "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", - "type": "text/html", - "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" - }, - { - "rel": "describedby", - "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", - "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", - "type": "text/html" - } - ], - "title": "Inventory", - "extent": { - "spatial": { - "bbox": [ - [ - -122.6692, - 39.6327, - -74.7781, - 45.5175 - ] - ] - }, - "temporal": { - "interval": [ - [ - "2024-02-07T00:00:00Z", - "2024-03-17T00:00:00Z" - ] - ] - } - }, - "table:columns": [ - { - "name": "duration", - "type": "string", - "description": "sample duration code for variable" - }, - { - "name": "model_id", - "type": "string", - "description": "unique model identifier" - }, - { - "name": "site_id", - "type": "string", - "description": "unique site identifier" - }, - { - "name": "reference_date", - "type": "date32[day]", - "description": "date that the forecast was initiated (horizon = 0)" - }, - { - "name": "variable", - "type": "string", - "description": "forecast variable" - }, - { - "name": "date", - "type": "date32[day]", - "description": "date of the predicted value" - }, - { - "name": "project_id", - "type": "string", - "description": "unique project identifier" - }, - { - "name": "pub_date", - "type": "date32[day]", - "description": {} - }, - { - "name": "path", - "type": null, - "description": "storage path for forecast data" - }, - { - "name": "path_full", - "type": null, - "description": {} - }, - { - "name": "path_summaries", - "type": null, - "description": {} - }, - { - "name": "endpoint", - "type": "string", - "description": "storage location for forecast data" - }, - { - "name": "latitude", - "type": "double", - "description": {} - }, - { - "name": "longitude", - "type": "double", - "description": {} - } - ], - "assets": { - "data": { - "href": "s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/forecasts/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org", - "type": "application/x-parquet", - "title": "Forecast Inventory Access", - "roles": [ - "data" - ], - "description": "Use `arrow` for remote access to the database. This R code will return results for the forecast challenge inventory bucket.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/forecasts/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "data.1": { - "href": "s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/scores/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org", - "type": "application/x-parquet", - "title": "Scores Inventory Access", - "roles": [ - "data" - ], - "description": "Use `arrow` for remote access to the database. This R code will return results for the forecast challenge inventory bucket.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/scores/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" - }, - "thumbnail": { - "href": "https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/Streamgaging%20Basics%20photo%20showing%20Acoustic%20Doppler%20Current%20Profiler2.jpg", - "type": "image/JPEG", - "roles": [ - "thumbnail" - ], - "title": "USGS Image" - } - } -} +{ + "id": "inventory", + "description": "The catalog contains forecasts for the EFI-USGS River Chlorophyll Forecasting Challenge. The forecasts are the raw forecasts that include all ensemble members (if a forecast represents uncertainty using an ensemble). Due to the size of the raw forecasts, we recommend accessing the scores (summaries of the forecasts) to analyze forecasts (unless you need the individual ensemble members). You can access the forecasts at the top level of the dataset where all models, variables, and dates that forecasts were produced (reference_datetime) are available. The code to access the entire dataset is provided as an asset. Given the size of the forecast catalog, it can be time-consuming to access the data at the full dataset level. For quicker access to the forecasts for a particular model (model_id), we also provide the code to access the data at the model_id level as an asset for each model.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "parent", + "type": "application/json", + "href": "../catalog.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../catalog.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "Inventory", + "extent": { + "spatial": { + "bbox": [ + [ + -122.6692, + 39.6327, + -74.7781, + 45.5175 + ] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-03-17T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "duration", + "type": "string", + "description": "sample duration code for variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "site_id", + "type": "string", + "description": "unique site identifier" + }, + { + "name": "reference_date", + "type": "date32[day]", + "description": "date that the forecast was initiated (horizon = 0)" + }, + { + "name": "variable", + "type": "string", + "description": "forecast variable" + }, + { + "name": "date", + "type": "date32[day]", + "description": "date of the predicted value" + }, + { + "name": "project_id", + "type": "string", + "description": "unique project identifier" + }, + { + "name": "pub_date", + "type": "date32[day]", + "description": {} + }, + { + "name": "path", + "type": null, + "description": "storage path for forecast data" + }, + { + "name": "path_full", + "type": null, + "description": {} + }, + { + "name": "path_summaries", + "type": null, + "description": {} + }, + { + "name": "endpoint", + "type": "string", + "description": "storage location for forecast data" + }, + { + "name": "latitude", + "type": "double", + "description": {} + }, + { + "name": "longitude", + "type": "double", + "description": {} + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/forecasts/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Forecast Inventory Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for the forecast challenge inventory bucket.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/forecasts/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "data.1": { + "href": "s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/scores/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Scores Inventory Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for the forecast challenge inventory bucket.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/inventory/catalog/scores/project_id=usgsrc4cast?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/Streamgaging%20Basics%20photo%20showing%20Acoustic%20Doppler%20Current%20Profiler2.jpg", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "USGS Image" + } + } +} diff --git a/catalog/noaa_forecasts/Pseudo/collection.json b/catalog/noaa_forecasts/Pseudo/collection.json index c96b7a837e..ae8db5062c 100644 --- a/catalog/noaa_forecasts/Pseudo/collection.json +++ b/catalog/noaa_forecasts/Pseudo/collection.json @@ -53,7 +53,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/noaa_forecasts/Stage1-stats/collection.json b/catalog/noaa_forecasts/Stage1-stats/collection.json index 957d2aa360..a9c31e6792 100644 --- a/catalog/noaa_forecasts/Stage1-stats/collection.json +++ b/catalog/noaa_forecasts/Stage1-stats/collection.json @@ -53,7 +53,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/noaa_forecasts/Stage1/collection.json b/catalog/noaa_forecasts/Stage1/collection.json index f7d612e3f2..7b680bb0ee 100644 --- a/catalog/noaa_forecasts/Stage1/collection.json +++ b/catalog/noaa_forecasts/Stage1/collection.json @@ -53,7 +53,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/noaa_forecasts/Stage2/collection.json b/catalog/noaa_forecasts/Stage2/collection.json index 0557c9890d..94d8fd52bc 100644 --- a/catalog/noaa_forecasts/Stage2/collection.json +++ b/catalog/noaa_forecasts/Stage2/collection.json @@ -53,7 +53,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/noaa_forecasts/Stage3/collection.json b/catalog/noaa_forecasts/Stage3/collection.json index 9946239a4c..2c15a2f7bb 100644 --- a/catalog/noaa_forecasts/Stage3/collection.json +++ b/catalog/noaa_forecasts/Stage3/collection.json @@ -53,7 +53,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/noaa_forecasts/collection.json b/catalog/noaa_forecasts/collection.json index cb74bce851..d7c8e6e122 100644 --- a/catalog/noaa_forecasts/collection.json +++ b/catalog/noaa_forecasts/collection.json @@ -88,7 +88,7 @@ "interval": [ [ "2024-01-29T00:00:00Z", - "2024-03-13T00:00:00Z" + "2024-03-16T00:00:00Z" ] ] } diff --git a/catalog/scores/aquatics/Daily_Chlorophyll_a/collection.json b/catalog/scores/aquatics/Daily_Chlorophyll_a/collection.json new file mode 100644 index 0000000000..4f1a92c11f --- /dev/null +++ b/catalog/scores/aquatics/Daily_Chlorophyll_a/collection.json @@ -0,0 +1,192 @@ +{ + "id": "Daily_Chlorophyll_a", + "description": "This page includes all models for the Daily_Chlorophyll_a variable.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/climatology.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/persistenceRW.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "Daily_Chlorophyll_a", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-02-12T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat); however in netCDF this could be handled by the CF Discrete Sampling Geometry data model." + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified For probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.” For summary statistics: “summary.”If this dimension does not vary, it is permissible to specify family as a variable attribute if the file format being used supports this (e.g.,netCDF)." + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "observation", + "type": "double", + "description": "observed value for variable" + }, + { + "name": "crps", + "type": "double", + "description": "crps forecast score" + }, + { + "name": "logs", + "type": "double", + "description": "logs forecast score" + }, + { + "name": "mean", + "type": "double", + "description": "mean forecast prediction" + }, + { + "name": "median", + "type": "double", + "description": "median forecast prediction" + }, + { + "name": "sd", + "type": "double", + "description": "standard deviation forecasts" + }, + { + "name": "quantile97.5", + "type": "double", + "description": "upper 97.5 percentile value of forecast" + }, + { + "name": "quantile02.5", + "type": "double", + "description": "upper 2.5 percentile value of forecast" + }, + { + "name": "quantile90", + "type": "double", + "description": "upper 90 percentile value of forecast" + }, + { + "name": "quantile10", + "type": "double", + "description": "upper 10 percentile value of forecast" + }, + { + "name": "project_id", + "type": "string", + "description": "unique project identifier" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly = PT1H, daily = P1D, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "date", + "type": "string", + "description": "ISO 8601 (ISO 2019) date of the predicted value; follows CF convention http://cfconventions.org/cf-conventions/cf-conventions.html#time-coordinate. This variable was called time before v0.5of the EFI convention. For time-integrated variables (e.g., cumulative net primary productivity), one should specify the start_datetime and end_datetime as two variables, instead of the single datetime. If this is not provided the datetime is assumed to be the MIDPOINT of the integration period." + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/scores/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "pending", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "pending" + } + } +} diff --git a/catalog/scores/aquatics/collection.json b/catalog/scores/aquatics/collection.json new file mode 100644 index 0000000000..d8dbe012be --- /dev/null +++ b/catalog/scores/aquatics/collection.json @@ -0,0 +1,187 @@ +{ + "id": "aquatics", + "description": "This page includes variables for the aquatics group.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "child", + "type": "application/json", + "href": "Daily_Chlorophyll_a/collection.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "aquatics", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-02-12T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat); however in netCDF this could be handled by the CF Discrete Sampling Geometry data model." + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified For probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.” For summary statistics: “summary.”If this dimension does not vary, it is permissible to specify family as a variable attribute if the file format being used supports this (e.g.,netCDF)." + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "observation", + "type": "double", + "description": "observed value for variable" + }, + { + "name": "crps", + "type": "double", + "description": "crps forecast score" + }, + { + "name": "logs", + "type": "double", + "description": "logs forecast score" + }, + { + "name": "mean", + "type": "double", + "description": "mean forecast prediction" + }, + { + "name": "median", + "type": "double", + "description": "median forecast prediction" + }, + { + "name": "sd", + "type": "double", + "description": "standard deviation forecasts" + }, + { + "name": "quantile97.5", + "type": "double", + "description": "upper 97.5 percentile value of forecast" + }, + { + "name": "quantile02.5", + "type": "double", + "description": "upper 2.5 percentile value of forecast" + }, + { + "name": "quantile90", + "type": "double", + "description": "upper 90 percentile value of forecast" + }, + { + "name": "quantile10", + "type": "double", + "description": "upper 10 percentile value of forecast" + }, + { + "name": "project_id", + "type": "string", + "description": "unique project identifier" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly = PT1H, daily = P1D, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "date", + "type": "string", + "description": "ISO 8601 (ISO 2019) date of the predicted value; follows CF convention http://cfconventions.org/cf-conventions/cf-conventions.html#time-coordinate. This variable was called time before v0.5of the EFI convention. For time-integrated variables (e.g., cumulative net primary productivity), one should specify the start_datetime and end_datetime as two variables, instead of the single datetime. If this is not provided the datetime is assumed to be the MIDPOINT of the integration period." + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/scores/parquet/?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/scores/parquet/?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"chla\")) |>\n dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/Back-b.jpg", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "USGS Streamgage" + } + } +} diff --git a/catalog/scores/collection.json b/catalog/scores/collection.json index ca551f7e4b..8d0608e102 100644 --- a/catalog/scores/collection.json +++ b/catalog/scores/collection.json @@ -70,7 +70,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-02-09T00:00:00Z" + "2024-02-12T00:00:00Z" ] ] } diff --git a/catalog/scores/models/collection.json b/catalog/scores/models/collection.json index 7cda4dea03..dfe9d1a961 100644 --- a/catalog/scores/models/collection.json +++ b/catalog/scores/models/collection.json @@ -13,12 +13,12 @@ { "rel": "item", "type": "application/json", - "href": "model_items/persistenceRW.json" + "href": "model_items/climatology.json" }, { "rel": "item", "type": "application/json", - "href": "model_items/climatology.json" + "href": "model_items/persistenceRW.json" }, { "rel": "parent", @@ -63,7 +63,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-02-09T00:00:00Z" + "2024-02-12T00:00:00Z" ] ] } diff --git a/catalog/scores/models/model_items/climatology.json b/catalog/scores/models/model_items/climatology.json index df69da2ac9..be1bf9601f 100644 --- a/catalog/scores/models/model_items/climatology.json +++ b/catalog/scores/models/model_items/climatology.json @@ -30,7 +30,7 @@ "properties": { "description": "\nmodel info: Forecasts stream chlorophyll-a based on the historic average and standard deviation for that given site and day-of-year.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-02-09", + "end_datetime": "2024-02-12", "providers": [ { "url": "pending", diff --git a/catalog/scores/models/model_items/persistenceRW.json b/catalog/scores/models/model_items/persistenceRW.json index de73b6f9b6..091dc00a8e 100644 --- a/catalog/scores/models/model_items/persistenceRW.json +++ b/catalog/scores/models/model_items/persistenceRW.json @@ -31,7 +31,7 @@ "properties": { "description": "\nmodel info: Random walk model based on most recent stream chl-a observations using the fable::RW() model.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-02-09", + "end_datetime": "2024-02-12", "providers": [ { "url": "pending", diff --git a/catalog/summaries/aquatics/Daily_Chlorophyll_a/collection.json b/catalog/summaries/aquatics/Daily_Chlorophyll_a/collection.json new file mode 100644 index 0000000000..e27ebad3d7 --- /dev/null +++ b/catalog/summaries/aquatics/Daily_Chlorophyll_a/collection.json @@ -0,0 +1,177 @@ +{ + "id": "Daily_Chlorophyll_a", + "description": "This page includes all models for the Daily_Chlorophyll_a variable.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/climatology.json" + }, + { + "rel": "item", + "type": "application/json", + "href": "../../models/model_items/persistenceRW.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "Daily_Chlorophyll_a", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-03-17T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat)" + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified for probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.”For summary statistics: “summary.”" + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "mean", + "type": "double", + "description": "mean forecast prediction" + }, + { + "name": "median", + "type": "double", + "description": "median forecast prediction" + }, + { + "name": "sd", + "type": "double", + "description": "standard deviation forecasts" + }, + { + "name": "quantile97.5", + "type": "double", + "description": "upper 97.5 percentile value of forecast" + }, + { + "name": "quantile02.5", + "type": "double", + "description": "upper 2.5 percentile value of forecast" + }, + { + "name": "quantile90", + "type": "double", + "description": "upper 90 percentile value of forecast" + }, + { + "name": "quantile10", + "type": "double", + "description": "upper 10 percentile value of forecast" + }, + { + "name": "project_id", + "type": "string", + "description": "unique identifier for the forecast project" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly, daily, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "reference_date", + "type": "string", + "description": "date that the forecast was initiated" + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=usgsrc4cast/duration=P1D/variable=chla?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "pending", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "pending" + } + } +} diff --git a/catalog/summaries/aquatics/collection.json b/catalog/summaries/aquatics/collection.json new file mode 100644 index 0000000000..4d19ee6257 --- /dev/null +++ b/catalog/summaries/aquatics/collection.json @@ -0,0 +1,172 @@ +{ + "id": "aquatics", + "description": "This page includes variables for the aquatics group.", + "stac_version": "1.0.0", + "license": "CC0-1.0", + "stac_extensions": [ + "https://stac-extensions.github.io/scientific/v1.0.0/schema.json", + "https://stac-extensions.github.io/item-assets/v1.0.0/schema.json", + "https://stac-extensions.github.io/table/v1.2.0/schema.json" + ], + "type": "Collection", + "links": [ + { + "rel": "child", + "type": "application/json", + "href": "Daily_Chlorophyll_a/collection.json" + }, + { + "rel": "parent", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "root", + "type": "application/json", + "href": "../collection.json" + }, + { + "rel": "self", + "type": "application/json", + "href": "collection.json" + }, + { + "rel": "cite-as", + "href": "https://doi.org/10.1002/fee.2616" + }, + { + "rel": "about", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "type": "text/html", + "title": "EFI-USGS River Chlorophyll Forecasting Challenge Documentation" + }, + { + "rel": "describedby", + "href": "https://projects.ecoforecast.org/usgsrc4cast-docs/", + "title": "EFI-USGS River Chlorophyll Forecast Challenge Dashboard", + "type": "text/html" + } + ], + "title": "aquatics", + "extent": { + "spatial": { + "bbox": [ + ["Inf", "Inf", "-Inf", "-Inf"] + ] + }, + "temporal": { + "interval": [ + [ + "2024-02-07T00:00:00Z", + "2024-03-17T00:00:00Z" + ] + ] + } + }, + "table:columns": [ + { + "name": "reference_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that the forecast was initiated (horizon = 0)" + }, + { + "name": "site_id", + "type": "string", + "description": "For forecasts that are not on a spatial grid, use of a site dimension that maps to a more detailed geometry (points, polygons, etc.) is allowable. In general this would be documented in the external metadata (e.g., alook-up table that provides lon and lat)" + }, + { + "name": "datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime of the forecasted value (ISO 8601)" + }, + { + "name": "family", + "type": "string", + "description": "For ensembles: “ensemble.” Default value if unspecified for probability distributions: Name of the statistical distribution associated with the reported statistics. The “sample” distribution is synonymous with “ensemble.”For summary statistics: “summary.”" + }, + { + "name": "pub_datetime", + "type": "timestamp[us, tz=UTC]", + "description": "datetime that forecast was submitted" + }, + { + "name": "mean", + "type": "double", + "description": "mean forecast prediction" + }, + { + "name": "median", + "type": "double", + "description": "median forecast prediction" + }, + { + "name": "sd", + "type": "double", + "description": "standard deviation forecasts" + }, + { + "name": "quantile97.5", + "type": "double", + "description": "upper 97.5 percentile value of forecast" + }, + { + "name": "quantile02.5", + "type": "double", + "description": "upper 2.5 percentile value of forecast" + }, + { + "name": "quantile90", + "type": "double", + "description": "upper 90 percentile value of forecast" + }, + { + "name": "quantile10", + "type": "double", + "description": "upper 10 percentile value of forecast" + }, + { + "name": "project_id", + "type": "string", + "description": "unique identifier for the forecast project" + }, + { + "name": "duration", + "type": "string", + "description": "temporal duration of forecast (hourly, daily, etc.); follows ISO 8601 duration convention" + }, + { + "name": "variable", + "type": "string", + "description": "name of forecasted variable" + }, + { + "name": "model_id", + "type": "string", + "description": "unique model identifier" + }, + { + "name": "reference_date", + "type": "string", + "description": "date that the forecast was initiated" + } + ], + "assets": { + "data": { + "href": "s3://anonymous@bio230014-bucket01/vera4cast/forecasts/summaries/parquet/?endpoint_override=sdsc.osn.xsede.org", + "type": "application/x-parquet", + "title": "Database Access", + "roles": [ + "data" + ], + "description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/vera4cast/forecasts/summaries/parquet/?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |>\n dplyr::filter(variable %in% c(\"chla\")) |>\n dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n" + }, + "thumbnail": { + "href": "https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/Back-b.jpg", + "type": "image/JPEG", + "roles": [ + "thumbnail" + ], + "title": "USGS Streamgage" + } + } +} diff --git a/catalog/summaries/collection.json b/catalog/summaries/collection.json index 332caa159a..25ac4b7bdd 100644 --- a/catalog/summaries/collection.json +++ b/catalog/summaries/collection.json @@ -70,7 +70,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-03-14T00:00:00Z" + "2024-03-17T00:00:00Z" ] ] } diff --git a/catalog/summaries/models/collection.json b/catalog/summaries/models/collection.json index a601aa832b..3d7a48c53b 100644 --- a/catalog/summaries/models/collection.json +++ b/catalog/summaries/models/collection.json @@ -63,7 +63,7 @@ "interval": [ [ "2024-02-07T00:00:00Z", - "2024-03-14T00:00:00Z" + "2024-03-17T00:00:00Z" ] ] } diff --git a/catalog/summaries/models/model_items/climatology.json b/catalog/summaries/models/model_items/climatology.json index beb7f88ca8..5114c3b22e 100644 --- a/catalog/summaries/models/model_items/climatology.json +++ b/catalog/summaries/models/model_items/climatology.json @@ -30,7 +30,7 @@ "properties": { "description": "\nmodel info: Forecasts stream chlorophyll-a based on the historic average and standard deviation for that given site and day-of-year.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-03-14", + "end_datetime": "2024-03-17", "providers": [ { "url": "pending", diff --git a/catalog/summaries/models/model_items/persistenceRW.json b/catalog/summaries/models/model_items/persistenceRW.json index be7a7ce474..300c435d6c 100644 --- a/catalog/summaries/models/model_items/persistenceRW.json +++ b/catalog/summaries/models/model_items/persistenceRW.json @@ -31,7 +31,7 @@ "properties": { "description": "\nmodel info: Random walk model based on most recent stream chl-a observations using the fable::RW() model.\n\nSites: USGS-01427510, USGS-01463500, USGS-05543010, USGS-05549500, USGS-05553700, USGS-05558300, USGS-05586300, USGS-14181500, USGS-14211010, USGS-14211720\n\nVariables: Daily Chlorophyll_a", "start_datetime": "2024-02-07", - "end_datetime": "2024-03-13", + "end_datetime": "2024-03-15", "providers": [ { "url": "pending", diff --git a/catalog/targets/collection.json b/catalog/targets/collection.json index 4ae1766854..ca449d8b9c 100644 --- a/catalog/targets/collection.json +++ b/catalog/targets/collection.json @@ -58,7 +58,7 @@ "interval": [ [ "2009-01-22T00:00:00Z", - "2024-02-09T00:00:00Z" + "2024-02-12T00:00:00Z" ] ] }