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A two-season impact study of radiative forced tropospheric response to stratospheric initial conditions inferred from satellite radiance assimilation

Shao Min, Bao Yansong, Zhang Hongfang, Petropoulos Georgios

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URI: http://purl.tuc.gr/dl/dias/BE6A0F25-FE3F-4070-B996-C1C6C0394CC0
Έτος 2019
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
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Βιβλιογραφική Αναφορά M. Shao, Y. Bao, G.P. Petropoulos and H. Zhang, "A two-season impact study of radiative forced tropospheric response to stratospheric initial conditions inferred from satellite radiance assimilation," Climate, vol. 7, no. 9, Sep. 2019. doi: 10.3390/cli7090114 https://doi.org/10.3390/cli7090114
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This study investigated the impacts of stratospheric temperatures and their variations on tropospheric short-term weather forecasting using the Advanced Research Weather Research and Forecasting (WRF-ARW) system with real satellite data assimilation. Satellite-borne microwave stratospheric temperature measurements up to 1 mb, from the Advanced Microwave Sounding Unit-A (AMSU-A), the Advanced Technology Microwave Sounder (ATMS), and the Special Sensor microwave Imager/Sounder (SSMI/S), were assimilated into the WRF model over the continental U.S. during winter and summer 2015 using the community Gridpoint Statistical Interpolation (GSI) system. Adjusted stratospheric temperature related to upper stratospheric ozone absorption of short-wave (SW) radiation further lead to vibration in downward SW radiation in winter predictions and overall reduced with a maximum of 5.5% reduction of downward SW radiation in summer predictions. Stratospheric signals in winter need 48- to 72-h to propagate to the lower troposphere while near-instant tropospheric response to the stratospheric initial conditions are observed in summer predictions. A schematic plot illustrated the physical processes of the coupled stratosphere and troposphere related to radiative processes. Our results suggest that the inclusion of the entire stratosphere and better representation of the upper stratosphere are important in regional NWP systems in short-term forecasts.

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