A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS

DONG Hai-ping; LI Xing-wu; GUO Wei-dong; GAO Tai-chang

Abstract:

Based on the newly developed Weather Research and Forecasting model (WRF) and its three-dimensional variational data assimilation (3DVAR) system, this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi (2010) using a data assimilation cycle method. The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively. The average bias of the central sea level pressure (CSLP) drops to 18 hPa, compared to 42 hPa in the experiment without data assimilation. However, the influence due to different radiance data is not significant, which is less than 6 hPa on average, implying limited improvement from sole assimilation of ATOVS radiance. The track issue is studied in the following steps. First, the radiance from the same sensor of different satellites could produce different effect. For the AMSU-A, NOAA-15 and NOAA-18, they produce equivalent improvement, whereas NOAA-16 produces slightly poor effect. And for the AMSU-B, NOAA-15 and NOAA-16, they produce equivalent and more positive effect than that provided by the AMSU-A. Second, the assimilation radiance from different sensors of the identical satellites could also produce different effect. The assimilation of AMSU-B produces the largest improvement, while the ameliorating effect of HIRS/3 assimilation is inferior to that of AMSU-B assimilation, while the AMSU-A assimilation exhibits the poorest improvement. Moreover, the simultaneous assimilation of different radiance could not produce further improvement. Finally, the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system. Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites.

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DONG Hai-ping, LI Xing-wu, GUO Wei-dong, et al. A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS [J]. Journal of Tropical Meteorology, 2013, 19(3): 242-252.

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A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS

Air force Meteorological Center, Beijing 100843 China

Unit 95026 of the People's Liberation Army (PLA), Foshan 528227 China

Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101 China

Received Date: 2012-06-12

Rev Recd Date: 2013-05-31

Abstract: Based on the newly developed Weather Research and Forecasting model (WRF) and its three-dimensional variational data assimilation (3DVAR) system, this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi (2010) using a data assimilation cycle method. The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively. The average bias of the central sea level pressure (CSLP) drops to 18 hPa, compared to 42 hPa in the experiment without data assimilation. However, the influence due to different radiance data is not significant, which is less than 6 hPa on average, implying limited improvement from sole assimilation of ATOVS radiance. The track issue is studied in the following steps. First, the radiance from the same sensor of different satellites could produce different effect. For the AMSU-A, NOAA-15 and NOAA-18, they produce equivalent improvement, whereas NOAA-16 produces slightly poor effect. And for the AMSU-B, NOAA-15 and NOAA-16, they produce equivalent and more positive effect than that provided by the AMSU-A. Second, the assimilation radiance from different sensors of the identical satellites could also produce different effect. The assimilation of AMSU-B produces the largest improvement, while the ameliorating effect of HIRS/3 assimilation is inferior to that of AMSU-B assimilation, while the AMSU-A assimilation exhibits the poorest improvement. Moreover, the simultaneous assimilation of different radiance could not produce further improvement. Finally, the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system. Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites.

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A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS

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