Add dynamical.org NOAA HRRR, NOAA GFS, and ECMWF IFS ENS datasets

datasets/dynamical-ecmwf-ifs-ens.yaml

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+Name: ECMWF IFS ENS
+Description: |
+
+      <p>
+       The Integrated Forecasting System (IFS) is a global forecast model developed 
+       by ECMWF. ENS is an ensemble configuration of IFS, containing 51 ensemble members.
+       IFS consists of a numerical model of the Earth system, which includes
+       an atmospheric model at its heart, coupled with models of other Earth system 
+       components such as the ocean. The data assimilation system combines 
+       the latest weather observations with a recent forecast to obtain the best 
+       possible estimate of the current state of the Earth system.
+      </p>
+
+  These datasets have been translated to cloud-optimized Icechunk Zarr format by <a href="https://dynamical.org">dynamical.org</a>.
+  <ul>
+
+  <li><a href="https://dynamical.org/catalog/ecmwf-ifs-ens-forecast-15-day-0-25-degree/">ECMWF IFS ENS Forecast, 15 day, 0.25 degree</a> - Ensemble weather forecasts from the ECMWF Integrated Forecasting System (IFS).</li>
+
+  </ul>
+Documentation: https://dynamical.org/catalog/ifs-ens/'
+Contact: [email protected]
+ManagedBy: "[dynamical.org](https://dynamical.org)"
+UpdateFrequency: ECMWF IFS ENS Forecast, 15 day, 0.25 degree: Forecasts initialized every 24 hours
+Tags:
+  - weather
+  - atmosphere
+  - meteorological
+  - climate
+  - forecast
+  - zarr
+License: "[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)"
+Resources:
+  - Description: ECMWF IFS ENS Icechunk Zarr data
+    ARN: arn:aws:s3:::dynamical-ecmwf-ifs-ens
+    Region: us-west-2
+    Type: S3 Bucket
+    Explore:
+      - "[Browse Bucket](https://dynamical-ecmwf-ifs-ens.s3.amazonaws.com/index.html)"
+DataAtWork:
+  Tutorials:
+  - Title: ECMWF IFS ENS Forecast, 15 day, 0.25 degree python quickstart notebook
+      NotebookURL: https://github.com/dynamical-org/notebooks/blob/main/ecmwf-ifs-ens-forecast-15-day-0-25-degree-icechunk.ipynb
+      AuthorName: dynamical.org
+      AuthorURL: https://dynamical.org
+ADXCategories:
+  - Environmental Data

datasets/dynamical-noaa-gfs.yaml

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+Name: NOAA GFS
+Description: |
+
+      <p>
+      The Global Forecast System (GFS) is a National Oceanic and Atmospheric
+      Administration (NOAA) National Centers for Environmental Prediction
+      (NCEP) weather forecast model that generates data for dozens of
+      atmospheric and land-soil variables, including temperatures, winds,
+      precipitation, soil moisture, and atmospheric ozone concentration. The
+      system couples four separate models (atmosphere, ocean model, land/soil
+      model, and sea ice) that work together to depict weather conditions.
+      </p>
+
+  These datasets have been translated to cloud-optimized Icechunk Zarr format by <a href="https://dynamical.org">dynamical.org</a>.
+  <ul>
+
+  <li><a href="https://dynamical.org/catalog/noaa-gfs-forecast/">NOAA GFS forecast</a> - Weather forecasts from the Global Forecast System (GFS) operated by NOAA NWS NCEP.</li>
+
+  </ul>
+Documentation: https://dynamical.org/catalog/gfs/'
+Contact: [email protected]
+ManagedBy: "[dynamical.org](https://dynamical.org)"
+UpdateFrequency: NOAA GFS forecast: Forecasts initialized every 6 hours
+Tags:
+  - weather
+  - atmosphere
+  - meteorological
+  - climate
+  - forecast
+  - zarr
+License: "[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)"
+Resources:
+  - Description: NOAA GFS Icechunk Zarr data
+    ARN: arn:aws:s3:::dynamical-noaa-gfs
+    Region: us-west-2
+    Type: S3 Bucket
+    Explore:
+      - "[Browse Bucket](https://dynamical-noaa-gfs.s3.amazonaws.com/index.html)"
+DataAtWork:
+  Tutorials:
+  - Title: NOAA GFS forecast python quickstart notebook
+      NotebookURL: https://github.com/dynamical-org/notebooks/blob/main/noaa-gfs-forecast-icechunk.ipynb
+      AuthorName: dynamical.org
+      AuthorURL: https://dynamical.org
+ADXCategories:
+  - Environmental Data

datasets/dynamical-noaa-hrrr.yaml

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+Name: NOAA HRRR
+Description: |
+
+      <p>
+      The High-Resolution Rapid Refresh (HRRR) is a NOAA real-time 3-km resolution,
+      hourly updated, cloud-resolving, convection-allowing atmospheric model,
+      initialized by 3km grids with 3km radar assimilation. Radar data is
+      assimilated in the HRRR every 15 min over a 1-h period adding further
+      detail to that provided by the hourly data assimilation from the 13km
+      radar-enhanced Rapid Refresh.
+      </p>
+
+  These datasets have been translated to cloud-optimized Icechunk Zarr format by <a href="https://dynamical.org">dynamical.org</a>.
+  <ul>
+
+  <li><a href="https://dynamical.org/catalog/noaa-hrrr-forecast-48-hour/">NOAA HRRR forecast, 48 hour</a> - Weather forecasts from the High Resolution Rapid Refresh (HRRR) model operated by NOAA NWS NCEP.</li>
+
+  </ul>
+Documentation: https://dynamical.org/catalog/hrrr/'
+Contact: [email protected]
+ManagedBy: "[dynamical.org](https://dynamical.org)"
+UpdateFrequency: NOAA HRRR forecast, 48 hour: Forecasts initialized every 6 hours.
+Tags:
+  - weather
+  - atmosphere
+  - meteorological
+  - climate
+  - forecast
+  - zarr
+License: "[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)"
+Resources:
+  - Description: NOAA HRRR Icechunk Zarr data
+    ARN: arn:aws:s3:::dynamical-noaa-hrrr
+    Region: us-west-2
+    Type: S3 Bucket
+    Explore:
+      - "[Browse Bucket](https://dynamical-noaa-hrrr.s3.amazonaws.com/index.html)"
+DataAtWork:
+  Tutorials:
+  - Title: NOAA HRRR forecast, 48 hour python quickstart notebook
+      NotebookURL: https://github.com/dynamical-org/notebooks/blob/main/noaa-hrrr-forecast-48-hour-icechunk.ipynb
+      AuthorName: dynamical.org
+      AuthorURL: https://dynamical.org
+ADXCategories:
+  - Environmental Data