This report presents a description, results and current progress on a new satellite rainfall and snowfall estimation system. The technique uses the Communication, Ocean and Meteorological Satellite (COMS) in the infrared (IR) band to compute real-time precipitation amounts based on a power-law regression algorithm. This regression is derived from a statistical analysis between TRMM/PR-derived rainfall estimates and TRMM/VIRS-derived black-body temperature, collocated in time and space. We examined the accuracy of the rainfall rate estimates daily for storm systems. Cloudsat satellite data is sensitive to snowfall and was collected during each month from Dec 2007 to Feb 2008. In this study, we attempt to develop a snowfall retrieval algorithm using a combination of radiometer and cloud radar data. We trained data on the relationship between brightness temperature measurements from the Advanced Microwave Scanning Radiometer for EOS(AMSR-E) and the radar reflectivity of the 2B-GEOPROF product from W-band (94 GHz) cloud radar onboard Cloudsat and applied it to the Korean peninsula. We used a principal components analysis to quantify the variations that are the result of the radiometric signatures of snowfall from those of the surface. Finally, we quantified the correlation between the higher principal component (orthogonal to surface variability) of the microwave radiances and the precipitation-sensitive CloudSat radar reflectivities. This study summarizes the results of applying this approach to observations over the East Sea during Feb. 2008. The retrieved data shows reasonable estimation skill for snowfall rate compared with Cloudsat vertical images.

1. 서론

2. 자료

2.1 천리안 위성(Communication, Ocean and Meteorological Satellite, COMS)

2.2 Cloudsat

2.3 AQUA AMSR-E

2.4 TRMM

3. 알고리즘 개발

3.1 강수 알고리즘

3.2 강설 알고리즘 개발

4. 결과 및 토론

4.1 수문모형 위성강수 입력자료

4.2 강설량 알고리즘 사례연구

5. 결론