FY-3A MWHS资料同化对湿度场预报影响评价的试验研究

doi:10.3969/j.issn.1673-503X.2018.05.018

Journal of Meteorology and Environment ›› 2018, Vol. 34 ›› Issue (5): 142-148.doi: 10.3969/j.issn.1673-503X.2018.05.018

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Evaluating the effect of FY-3A MWHS data assimilation on atmospheric humidity field forecasting

TANG Shu-min¹, MA Jie-liang¹, YIN Jia-yan², LU Qi-feng³, GUAN Yuan-hong², CAI Xi², TANG Wei-yao², ZHU Liu-hua²

1. School of Electronic & Information Engineering, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, NUIST, Nanjing 210044, China;
2. Meteorological Disaster Forecast Warning and Evaluation of Collaborative Innovation Center, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, NUIST, Nanjing 210044, China;
3. Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

Received:2016-10-11 Revised:2017-08-16 Online:2018-10-31 Published:2018-10-31

Abstract

Abstract: Feng-Yun 3A is the first satellite with microwave humidity sensor (MWHS),which can provide data for numerical weather forecasting on global and regional scales.This paper focused on assessing the effects of FY-3A MWHS data assimilation on relative humidity analysis and forecasting by using a 3D-Var data assimilation system coupling WRF model.The results show that the MWHS data assimilation improves relative humidity analysis,and obtains better relative humidity analysis compared to the NOAA AMSU-B data assimilation.In general,the method using the MWHS data assimilation improves the relative humidity forecasting accuracy compared with the method using the AMSU-B data assimilation.For 18 hour forecasting results,the humidity forecasting accuracies at 400 hPa,600 hPa and 800 hPa levels using the MWHS data assimilation method are higher than those using the AMSU-B data assimilation method.These results indicate that the FY-3A MWHS has a wide application prospect in numerical weather forecasting.

Key words: Numerical weather forecasting, Data assimilation, Meteorological satellite, Microwave humidity sensor, Humidity field

CLC Number:

P457.3

TANG Shu-min, MA Jie-liang, YIN Jia-yan, LU Qi-feng, GUAN Yuan-hong, CAI Xi, TANG Wei-yao, ZHU Liu-hua. Evaluating the effect of FY-3A MWHS data assimilation on atmospheric humidity field forecasting[J]. Journal of Meteorology and Environment, 2018, 34(5): 142-148.

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Evaluating the effect of FY-3A MWHS data assimilation on atmospheric humidity field forecasting

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