Preliminary Investigation of Assimilating Global Synthetic Weather Radar
Abstract
Global Synthetic Weather Radar (GSWR) is a promising dataset to assimilate for improving short-term weather forecasts because it provides near-global coverage of certain fields normally obtained via radar. This report documents what appears to be the first attempt to assimilate GSWR data in a numerical weather prediction model. Derived from sources including satellite-based instrumentation, the GSWR column maximum reflectivity is used to create an estimated vertical profile of reflectivity, which is then converted to a heating term and assimilated using methods demonstrated in previous work with radar data. The assimilation technique is modified to better assimilate the GSWR data; these modifications include allowing the GSWR data to directly modify precipitation hydrometeors, cloud water, and water vapor. The assimilation of the GSWR data shows improvement in short-term forecasts of the placement of moist convection for the two cases studied. Further work is needed to expand to additional cases, continue to improve the assimilation method, and evaluate GSWR data and model forecasts assimilating GSWR against radar observations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2020
- Accession Number
- AD1111072
Entities
People
- Brian P. Reen
- Huaqing Cai
- John W. Raby
Organizations
- United States Army Combat Capabilities Development Command