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Evaluation of NU-WRF rainfall forecasts for IFloodS
Di Wu1,2, Christa Peters-Lidard3, Wei-Kuo Tao1
1Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland.
Journal of Hydrometeorology
|August 5, 2020
Summary
The NASA-Unified Weather Research and Forecasting (NU-WRF) model showed good precipitation forecasts during the Iowa Flood Studies. High-resolution modeling improved rainfall prediction, though land surface initialization had minimal impact.
Area of Science:
- Atmospheric Science
- Hydrology
- Meteorology
Background:
- The Iowa Flood Studies (IFloodS) campaign (May 1-June 15, 2013) aimed to improve precipitation forecasting.
- Real-time weather forecasts were generated using the NASA-Unified Weather Research and Forecasting (NU-WRF) model.
Purpose of the Study:
- Evaluate NU-WRF rainfall forecasts against Stage IV and Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation (QPE).
- Assess the impact of land surface initialization on NU-WRF precipitation predictions.
- Compare NU-WRF performance with the North American Mesoscale Forecast System (NAM) model.
Main Methods:
- Utilized the NU-WRF model for rainfall forecasting during the IFloodS campaign.
- Validated NU-WRF forecasts using Stage IV and MRMS QPE data.
- Conducted sensitivity tests on model resolution and land surface initialization.
Main Results:
- NU-WRF accurately captured individual precipitation events and showed improved spatial rainfall distribution compared to NAM.
- Higher model resolution positively impacted rainfall forecast accuracy.
- Land surface initialization did not significantly affect short-term rainfall forecasts due to prevailing soil conditions.
Conclusions:
- NU-WRF is a capable tool for precipitation forecasting, outperforming NAM in spatial distribution.
- High-resolution modeling is crucial for enhancing rainfall forecast accuracy.
- Land surface initialization's impact on short-term forecasts may be limited under specific soil moisture conditions.
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