Four-Dimensional Variational Data Assimilation of Heterogeneous Mesoscale Observations for a Strong Convective Case
| Autor: | David B. Parsons, Ying-Hwa Kuo, Jimy Dudhia, C. Rocken, Yong-Run Guo |
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| Rok vydání: | 2000 |
| Předmět: | |
| Zdroj: | Monthly Weather Review. 128:619-643 |
| ISSN: | 1520-0493 0027-0644 |
| Popis: | On 19 September 1996, a squall line stretching from Nebraska to Texas with intense embedded convection moved eastward across the Kansas–Oklahoma area, where special observations were taken as part of a Water Vapor Intensive Observing Period sponsored by the Atmospheric Radiation Measurement program. This provided a unique opportunity to test mesoscale data assimilation strategies for a strong convective event. In this study, a series of real-data assimilation experiments is performed using the MM5 four-dimensional variational data assimilation (4DVAR) system with a full physics adjoint. With a grid size of 20 km and 15 vertical layers, the MM5-4DVAR system successfully assimilated wind profiler, hourly rainfall, surface dewpoint, and ground-based GPS precipitable water vapor data. The MM5-4DVAR system was able to reproduce the observed rainfall in terms of precipitation pattern and amount, and substantially reduced the model errors when verified against independent observations. Additional data a... |
| Databáze: | OpenAIRE |
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