한국지구과학회지 제40권 제4호 (p.406-413)

Convective Cloud RGB Product and Its Application to Tropical Cyclone Analysis Using Geostationary Satellite Observation

키워드 :
RGB composite image,convective clouds,Typhoon,GEO,satellite remote sensing

목차

Abstract
1. Introduction
2. Data and Methods
   2.1. RGB color model
   2.2. RGB products for convective clouds
   2.3. Center location analysis of TyphoonsDanas and Francisco in 2013: a case study
3. Results
   3.1. RGB product analysis
   3.2. Center location analysis of TyphoonsDanas and Francisco in 2013: a case study
4. Discussion and ConcludingRemarks
References

초록

Red-Green-Blue (RGB) imagery techniques are useful for both forecasters and public users because they are intuitively understood, have advantageous visualization, and do not lose observational information. This study presents a novel RGB convective cloud product and its application to tropical cyclone analysis using Communication, Oceanography, and Meteorology (COMS) satellite observations. The RGB convective cloud product was developed using the brightness temperature differences between WV (6.75 μm) and IR1 (10.8 μm), and IR2 (12.0 μm) and IR1 (10.8 μm) as well as the brightness temperature in the IR1 bands of the COMS, with the threshold values estimated from the Korea Meteorological Administration (KMA) radar observations and the EUMETSAT RGB recipe. To verify the accuracy of the convective cloud RGB product, the product was applied to the center positions analysis of two typhoons in 2013. Thus, the convective cloud RGB product threshold values were estimated for WV-IR1 (−20 K to 15 K), IR1 (210 K to 300 K), and IR1-IR2 (−4 K to 2 K). The product application in typhoon analysis shows relatively low bias and root mean square errors (RMSE)s of 23 and 28 km for DANAS in 2013, and 17 and 22 km for FRANCISCO in 2013, as compared to the best tracks data from the Regional Specialized Meteorological Center (RSMC) in Tokyo. Consequently, our proposed RGB convective cloud product has the advantages of high accuracy and excellent visualization for a variety of meteorological applications.