Development and testing of ensemble-variational data assimilation capabilities for radar data within JEDI coupled with FV3-LAM model

Park, Jun; Liu, Chengsi; Xue, Ming

doi:10.5194/gmd-19-8213-2026

Articles | Volume 19, issue 17

https://doi.org/10.5194/gmd-19-8213-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

The application of JEDI (Joint Effort for Data assimilation...

https://doi.org/10.5194/gmd-19-8213-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 17

Development and technical paper

|

07 Sep 2026

Development and technical paper |

| 07 Sep 2026

Development and testing of ensemble-variational data assimilation capabilities for radar data within JEDI coupled with FV3-LAM model

Jun Park, Chengsi Liu, and Ming Xue

Data sets

Processed radar observations and configuration files for JEDI–FV3 v1.0.0 (v1.0.0) Jun Park and Chengsi Liu https://doi.org/10.5281/zenodo.18272368

Global Ensemble Forecast System (GEFS) NOAA https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast

Model code and software

JEDI–FV3 v1.0.0 with radar data assimilation implementation (v1.0.0) Jun Park and Chengsi Liu https://doi.org/10.5281/zenodo.18272913

Short summary

This study develops and tests new methods to improve weather forecasts by using radar observations within a modern data assimilation system called the Joint Effort for Data Assimilation Integration. The approach combines information from radar measurements and computer models to better describe storms. Tests with a major U.S. storm show improved prediction of rainfall and storm structure.