Retrieval of rainfall by combining rain gauge, ground-based radar and satellite measurements over Phimai, Thailand

Parichat Wetchayont, Tadahiro Hayasaka, Takehiko Satomura, Shuichiro Katagiri, Somchai Baimoung

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A classification system for rain clouds was developed using ground-based radar reflectivity and infrared brightness temperature (TBB) data from multifunctional transport satellites (MTSAT) and applied to the Phimai radar station, Thailand. The proposed method can classify cloud types into convective rain, stratiform rain and non-rain for areas covered with cumulus and/or cirrus clouds by applying a statistical integration analysis of rain gauges, ground-based radar, and MTSAT data. The classified precipitation areas were used to estimate quantitative precipitation amounts over Phimai. To merge different rainfall data sets derived from these three sources, the bias among the data must be removed. A combined correction method was developed to estimate the spatially varying multiplicative biases in hourly rainfall obtained from the radar and MTSAT using the rain gauges. This consecutive analysis was applied to the rainy season (July to September) in 2009 to obtain the multiplicative bias correction and to combine the data sets. The correlation coefficient, root mean square error, and mean bias were used as indicators to evaluate the performance of our bias-correction method. The combined method is simple and useful. The combined rainfall data were more useful than the data of TRMM 3B42 V7 and ground-based radar estimates.

Original languageEnglish
Pages (from-to)166-169
Number of pages4
JournalScientific Online Letters on the Atmosphere
Volume9
Issue number1
DOIs
Publication statusPublished - 2013

ASJC Scopus subject areas

  • Atmospheric Science

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