한국지구과학회지 (Journal of the Korean earth science society)

  • 제31권5호
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  • Pages.465-474
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  • 2010
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  • 1225-6692(pISSN)
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  • 2287-4518(eISSN)
한국지구과학회 (The Korean Earth Science Society)
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Half-hourly Rainfall Monitoring over the Indochina Area from MTSAT Infrared Measurements: Development of Rain Estimation Algorithm using an Artificial Neural Network

  • 투고 : 2010.07.22
  • 심사 : 2010.09.18
  • 발행 : 2010.09.30
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초록

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and $12-{\mu}m$ channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.

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참고문헌

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