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Poster Session 2
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The Study of Precipitation Effects on AMSU and Application of AMSU on Typhoon Monotorning
4. Monitoring Typhoon by AMSU
When typhoon is severe, there is almost not problem to identify the center of typhoon. When typhoon or tropical cyclone is weak, or the eye of typhoon is masked by cirrus cloud, it is very difficult to identify the center of cyclone. Traditionally base on the cloud bands of the cyclone to track the eye of typhoon, such as Dvorak (1982). This identification skill strongly depends on the experience of the weather analyst. When center of typhoon is unclear, the forecast of moving direction of typhoon could be missed. Identify center of typhoon is a very important issue in tropical and subtropical area weather services.
Viewing from vertical distribution of AMSU weighting function, each channel of AMSU-A can present vertical structure of temperature at specific level. It is shows in Fig. 4. Viewing the vertical structure over a cross line that passes through center of typhoon. The surface warm core of typhoon and cold core at high altitude is significant. Weak typhoon is shows on Fig. 4. The low-level warm core still is very easy to be identified. Not only center of typhoon, but also the strength of typhoon could be defined also. Further more researches are keep on going.
5. Conclusion
A developed forward model is presented that could be used in real data simulation and widely used in research. Not only clear sky but also cloudy or rain could be a simulation tool also. Using AMSU data on weather analysis was mentioned in this research, such as using AMSU may provide total water vapor or low level water vapor and typhoon tracking successfully. The relation between AMSU and wind speed is an interesting and useful article in weather forecast, and it will be next research object. The original design purpose of AMSU is not used for precipitation retrieval. Actually, the correlation between rain rate and AMSU observed TB is poor, but rains still affect upward radiance of AMSU surface channel. Removing rain effects on AMSU data utilization, or getting more precise surface emissivity to retrieval rainfall information from AMSU is another task in the near future.
Since AMSU data was available two years passed, and NOAA-16 was lunched also. AMSU is not a new instrument any more, and other new microwave instruments are in progressing, which means microwave remote sensing may create a new window for satellite weather service.
Reference
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Dvorak, V.F., 1982: A technique for the analysis and forecasting of tropical cyclone intensities from satellite pictures. NOAA Tech. Memo. NESS 36, Dept of Comm.
- Goodrum, Geoffrey, Katherine B. Kidwell, Wayne Winston, 1997, NOAA KLM USER's GUIDE, NOAA/NESDIS
- Grody, Norman, Fuzhong Weng and Ralph Ferraro, 1999, Technical Proceedings of The Tenth International ATOVS Study Conference, Boulder CO
- Kummerow, C. L. Giglo,1994: A passive microwave technique for estimating rainfall and vertical structure information from space, Part I: algorithm description, J. of Appl. Meteo. , 33, 3-18.
- Liebe, H. J. , 1985, An updated model for millimeter wave propagation in moist air, Radio Science, 20, 1069-1089.
- Rosenkranz, P. W., 1998, Improved rapid transmittance algorithm for microwave sounding channels, International Geoscience and Remote Sensing Symposium (IGARSS'98), Seattle, WA
Figure 1. Scattering diagram of estimated TB and satellite observed TB. Data are almost linear distribute along a line. Some points disperse from central line are caused by unknown precipitaion and surface emissivity.
Figure 2. Scatter diagram of two result of Grody's and Wang's TWV with RAOB's TWV. Lower graphic is the
difference between these two algorithm and RAOB's results
Figure 3. Histogram of two results of Grody's and Wang's TWV algoritms
Figure 4. Upper left are sever Typhoon Bilis (0010), announced eye of typhoon is located on 22.2N, 122.2E. Upper right is structure of typhoon center. Lower left is weak typhoon Kaitak(0004), announced eye of typhoon is located on 18.7N, 120.7E
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