Validating infrared-based rainfall retrieval algorithms with 1-minute spatially dense raingage measurements over Korean peninsula |
| |
| Authors: | H-J Oh B-J Sohn E A Smith F J Turk Ae-suk Seo H-S Chung |
| |
| Institution: | (1) School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea, KR;(2) NASA/Goddard Space Flight Center, Greenbelt, MD, USA, US;(3) Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, USA, US;(4) Meteorological Research Institute, Korean Meteorological Administration, Seoul, Korea, KR |
| |
| Abstract: | Summary ?This study compares and contrasts six infrared-based satellite rain estimation techniques and their validation during a 2-month
period from June 20–August 20, 1998 over the Korean peninsula. Two probability matching techniques (PMM1, PMM2), a look-up
table technique (LUT), a convective-stratiform technique (CST), the Negri-Adler-Wetzel technique (NAWT), and the Arkin technique
(ARKT) are applied to hourly infrared GMS imagery. Retrieved rainrates are compared against one-minute reporting raingage
observations from the dense Automated Weather Station (AWS) network of Korea. The high spatial resolution and fine temporal
resolution of the AWS measurements provide a unique and effective means to validate rain estimates derived from instantaneous
space measurements, which is a main scientific focus of this study.
Validation results indicate that all techniques exhibit better performance for more evenly spread rain events while exhibiting
lesser performance for weak and sporadic rains for which validation sampling becomes more of a problem. Validation statistics
show that climatologically-local techniques such as the PMM and LUT algorithms perform better than techniques developed in
climatologically different regimes, indicating the well-known dependence of rain physics on the immediate environment. Nevertheless,
the validation results suggest how the rain determination parameters including attributed rain and threshold brightness temperature
could be optimized locally before application. As others have found, the most difficult problem with satellite infrared techniques
is in the detection and quantification of heavy rainfall events arising from uncertainties in discriminating non-precipitating
anvil clouds from convective clouds. However, for the set of algorithms under examination here, given the sharp resolution
of the validation measurements, it is evident that the CST algorithm exhibits superior performance in differentiating between
non-precipitating anvil and heavy rain.
Received January 4, 2002; revised March 11, 2002 |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
