diff --git a/datasets/dynamical-ecmwf-ifs-ens.yaml b/datasets/dynamical-ecmwf-ifs-ens.yaml
new file mode 100644
index 000000000..793c975a5
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+++ b/datasets/dynamical-ecmwf-ifs-ens.yaml
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+Name: ECMWF IFS ENS
+Description: |
+
+
+ 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.
+
+
+ These datasets have been translated to cloud-optimized Icechunk Zarr format by dynamical.org.
+
+Documentation: https://dynamical.org/catalog/ifs-ens/'
+Contact: feedback@dynamical.org
+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
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diff --git a/datasets/dynamical-noaa-gfs.yaml b/datasets/dynamical-noaa-gfs.yaml
new file mode 100644
index 000000000..81745a7a7
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+++ b/datasets/dynamical-noaa-gfs.yaml
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+Name: NOAA GFS
+Description: |
+
+
+ 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.
+
+
+ These datasets have been translated to cloud-optimized Icechunk Zarr format by dynamical.org.
+
+
+ - NOAA GFS forecast - Weather forecasts from the Global Forecast System (GFS) operated by NOAA NWS NCEP.
+
+
+Documentation: https://dynamical.org/catalog/gfs/'
+Contact: feedback@dynamical.org
+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
\ No newline at end of file
diff --git a/datasets/dynamical-noaa-hrrr.yaml b/datasets/dynamical-noaa-hrrr.yaml
new file mode 100644
index 000000000..9712c012a
--- /dev/null
+++ b/datasets/dynamical-noaa-hrrr.yaml
@@ -0,0 +1,45 @@
+Name: NOAA HRRR
+Description: |
+
+
+ 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.
+
+
+ These datasets have been translated to cloud-optimized Icechunk Zarr format by dynamical.org.
+
+Documentation: https://dynamical.org/catalog/hrrr/'
+Contact: feedback@dynamical.org
+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
\ No newline at end of file