연구보고서
- 저자
- 박경원 박사
- 작성일
- 2016.01.23
- 조회
- 363
- 요약
- 목차
Precipitation forecasting and rainfall retrieval algorithm at very short lead times is a difficult and important earth science goal and warning system and the implications of forecasting extend into aviation, flood forecasting and other areas. Using correlation analysis for the generation of motion vectors to advect a composite COMS rainfall field is the method of forecasting utilized in this work. The technique uses the GMS-5 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. the forecasting system is a correlation-based forecasting algorithm that utilizes spatial filtering to eliminate the potentially adverse effects of transient, small-scale rainfall features in the correlation step. We are used in this work to evaluate the benefits of COMS image filtering as compared to a situation where the filtering is absent. This system generates a spatially variable motion vector field for input rainfall field advection. Forecasts made using this enhancement are compared to forecasts made using a single motion value for all input pixels in order to determine the benefits of allowing for differential motion within the storm envelope. The results from three storm cases show that image filtering provides improvement in forecast accuracy however, we determine any benefits from using spatially variable motion vector requires more work.
This work the development and testing of a correlation-based forecasting algorithm for short term times. This system builds on advancements made to provide highly accurate precipitation forecasting prototype system. Initial testing shows that forecasts system are more accurate than persistence forecasts, and are approximately as accurate as forecasts generated by other system with a uniform advection method. This technique is more effective prototype system than the previous algorithm.