Corrector Diffusion (CorrDiff) US GEFS-HRRR model down-scales several surface and atmospheric variables from 25-km resolution forecast data from the Global Ensemble Forecast System (GEFS) and predicts 3-km resolution High-Resolution Rapid Refresh (HRRR) data. CorrDiff US allows the prediction of high-fidelity stochastic weather phenomena over the CONUS from low-fidelity input data that would otherwise require expensive regional numerical simulations.
CorrDiff is a generative downscaling model trained over the contiguous United States (CONUS).
This model is ready for commercial use.
Architecture Type: Diffusion
Network Architecture: Patch-Based Corrector Diffusion
Input Type(s):
Input Format(s): NumPy
Input Parameters:
Other Properties Related to Input:
Output Type(s): Tensor (8 Surface & Atmospheric Variables)
Output Format: NumPy
Output Parameters: 5D (batch, samples, variable, latitude, longitude)
Other Properties Related to Output:
The output is on a cropped window of the grid used by HRRR.
Refer to the HRRR documentation for additional information on this grid.
The output coordinates can be obtained from the corrdiff_output_lat.npy
and corrdiff_output_lon.npy
files in the model package.
Runtime Engine(s): Not Applicable
Supported Hardware Microarchitecture Compatibility:
Supported Operating System(s):
Model version: v1
Link: GEFS
Data Collection Method by dataset
Labeling Method by dataset
Properties (Quantity, Dataset Descriptions, Sensor(s)):
GEFS data for the date range of 2020/12/02 to 2023/12/31. The Global Ensemble Forecast System (GEFS) is a weather model created by the National Centers for Environmental Prediction (NCEP) that generates 21 separate forecasts (ensemble members) to address underlying uncertainties in the input data such limited coverage, instruments or observing systems biases, and the limitations of the model itself.
Link: HRRR
Data Collection Method by dataset
Labeling Method by dataset
Properties (Quantity, Dataset Descriptions, Sensor(s)):
HRRR data for the date range of 2020/12/02 to 2023/12/31. The 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.
Link: GEFS
Data Collection Method by dataset
Labeling Method by dataset
Properties (Quantity, Dataset Descriptions, Sensor(s)):
GEFS data for the date range of 2024/01/01 to 2024/07/31. The Global Ensemble Forecast System (GEFS) is a weather model created by the National Centers for Environmental Prediction (NCEP) that generates 21 separate forecasts (ensemble members) to address underlying uncertainties in the input data such limited coverage, instruments or observing systems biases, and the limitations of the model itself.
Link: HRRR
Data Collection Method by dataset
Labeling Method by dataset
Properties (Quantity, Dataset Descriptions, Sensor(s)):
HRRR data for the date range of 2024/01/01 to 2024/07/31. The 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.
Engine: Triton
Test Hardware:
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