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An Observing System Simulation Experiment for the Impact of MTG Candidate Infrared Sounding Mission on Regional Forecasts: System Development and Preliminary Results
Author(s) -
Hongli Wang,
Huang Xiangyu,
Yongsheng Chen
Publication year - 2013
Publication title -
isrn meteorology
Language(s) - English
Resource type - Journals
eISSN - 2090-7524
pISSN - 2090-7516
DOI - 10.1155/2013/971501
Subject(s) - mm5 , environmental science , meteorology , weather research and forecasting model , depth sounding , data assimilation , quantitative precipitation forecast , climatology , geostationary orbit , precipitation , forecast skill , satellite , atmospheric sciences , geography , geology , cartography , aerospace engineering , engineering
An Observing System Simulation Experiment (OSSE) was designed and developed to assess the potential benefit of the Infrared Sounding on the Meteosat Third Generation (MTG-IRS) geostationary meteorological satellite system to regional forecasts. In the proposed OSSE framework, two different models, namely, the MM5 and WRF models, were used in a nature run and data assimilation experiments, respectively, to reduce the identical twin problem. The 5-day nature run, which included three convective storms that occurred during the period from 11 to 16 June 2002 over US Great Plains, was generated using MM5 with a 4 km. The simulated “conventional” observations and MTG-IRS retrieved temperature and humidity profiles, produced from the nature run, were then assimilated into the WRF model. Calibration experiments showed that assimilating real or simulated “conventional” observations yielded similar error statistics in analyses and forecasts, indicating that the developed OSSE system worked well. On average, the MTG-IRS retrieved profiles had positive impact on the analyses and forecasts. The analyses reduced the errors not only in the temperature and the humidity fields but in the horizontal wind fields as well. The forecast skills of these variables were improved up to 12 hours. The 18 h precipitation forecast accuracy was also increased.

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