| Autor: |
Xuanli Li, John R. Mecikalski, Jayanthi Srikishen, Bradley Zavodsky, Walter A. Petersen |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 5, Pp n/a-n/a (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1942-2466 |
| DOI: |
10.1029/2019MS001618 |
| Popis: |
Abstract The National Aeronautics and Space Administration‐Japan Aerospace Exploration Agency Global Precipitation Measurement (GPM) mission consists of a multisatellite constellation that provides real‐time or near‐real‐time global observations of rain and snow. In this study, GPM Level 3 Integrated Multi‐satellitE Retrievals for GPM (IMERG) and Level 2 GPM Microwave Imager Goddard Profiling rainfall products have been assimilated into the Weather Research and Forecasting model using the community Gridpoint Statistical Interpolation (GSI) data assimilation system. Experiments have been conducted and compared to demonstrate the impact of rain rate data assimilation on forecasts of heavy rainfall related to Hurricane Harvey (2017) and moderate to light rainfall observed during the GPM Integrated Precipitation and Hydrology Experiment field campaign. The results indicate that both GPM Microwave Imager Goddard Profiling and IMERG data could generate apparent increments in moisture, temperature, wind, and pressure fields for Hurricane Harvey, which led to significant improvement in the precipitation forecast. Frequent (every 3 hr) assimilation of IMERG data also positively impacted the short‐term precipitation forecast skill for the Integrated Precipitation and Hydrology Experiment moderate to light rain events. However, results also indicate that the impact of rain data assimilation was limited for a system that had a small horizontal dimension with low rain rates and within a relatively stable synoptic environment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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