TY - GEN
T1 - Categorizing precipitating clouds by using Radar and Geostationary satellite
AU - Wetchayont, P.
AU - Hayasaka, Tadahiro
AU - Katagiri, S.
AU - Satomura, T.
PY - 2012/12/1
Y1 - 2012/12/1
N2 - The classification of precipitating cloud systems over Thailand was attempted by using radar reflectivity and Multifunctional Transport Satellites (MTSAT) infrared brightness temperature (TBB) data. The proposed method can classify the convective rain (CR) area, stratiform rain (SR) area and non-precipitation area such as cumulus and cirrus cloud by applying an integrating analysis of rain gauge, ground-based radar and geostationary satellite data. Since the present study focuses on precipitation, the classified results of precipitation area are used to estimate quantitative precipitation amount. To merge different rainfall products, the bias between the products should be removed. The bias correction method is used to estimate spatially varying multiplicative biases in hourly radar and satellite rainfall using a gauge and radar rainfall product, respectively. An extreme rain event was selected to obtain the multiplicative bias correction and to merge data set. Correlation coefficient (CC), root mean square error (RMSE) and mean bias are used to evaluate the performance of bias correction method. The combined radar-MTSAT method is a simple and useful method. This method has been successfully applied to merge radar and gauge rainfall for hydrological purpose.
AB - The classification of precipitating cloud systems over Thailand was attempted by using radar reflectivity and Multifunctional Transport Satellites (MTSAT) infrared brightness temperature (TBB) data. The proposed method can classify the convective rain (CR) area, stratiform rain (SR) area and non-precipitation area such as cumulus and cirrus cloud by applying an integrating analysis of rain gauge, ground-based radar and geostationary satellite data. Since the present study focuses on precipitation, the classified results of precipitation area are used to estimate quantitative precipitation amount. To merge different rainfall products, the bias between the products should be removed. The bias correction method is used to estimate spatially varying multiplicative biases in hourly radar and satellite rainfall using a gauge and radar rainfall product, respectively. An extreme rain event was selected to obtain the multiplicative bias correction and to merge data set. Correlation coefficient (CC), root mean square error (RMSE) and mean bias are used to evaluate the performance of bias correction method. The combined radar-MTSAT method is a simple and useful method. This method has been successfully applied to merge radar and gauge rainfall for hydrological purpose.
KW - MTSAT
KW - cloud classification
KW - precipitation
KW - radar
UR - http://www.scopus.com/inward/record.url?scp=84880048240&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880048240&partnerID=8YFLogxK
U2 - 10.1117/12.976833
DO - 10.1117/12.976833
M3 - Conference contribution
AN - SCOPUS:84880048240
SN - 9780819492623
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Remote Sensing of the Atmosphere, Clouds, and Precipitation IV
T2 - Remote Sensing of the Atmosphere, Clouds, and Precipitation IV
Y2 - 29 October 2012 through 31 October 2012
ER -