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Accuracy Comparison of Air Temperature Estimation using Spatial Interpolation Methods according to Application of Temperature Lapse Rate Effect

기온감률 효과 적용에 따른 공간내삽기법의 기온 추정 정확도 비교

  • Kim, Yong Seok (Climate Change & Agroecology Division, National Academy of Agricultural Science) ;
  • Shim, Kyo Moon (Climate Change & Agroecology Division, National Academy of Agricultural Science) ;
  • Jung, Myung Pyo (Climate Change & Agroecology Division, National Academy of Agricultural Science) ;
  • Choi, In Tae (Climate Change & Agroecology Division, National Academy of Agricultural Science)
  • 김용석 (국립농업과학원 농업환경부 기후변화생태과) ;
  • 심교문 (국립농업과학원 농업환경부 기후변화생태과) ;
  • 정명표 (국립농업과학원 농업환경부 기후변화생태과) ;
  • 최인태 (국립농업과학원 농업환경부 기후변화생태과)
  • Received : 2014.10.20
  • Accepted : 2014.12.10
  • Published : 2014.12.31

Abstract

Since the terrain of Korea is complex, micro- as well as meso-climate variability is extreme by locations in Korea. In particular, air temperature of agricultural fields is influenced by topographic features of the surroundings making accurate interpolation of regional meteorological data from point-measured data. This study was carried out to compare spatial interpolation methods to estimate air temperature in agricultural fields surrounded by rugged terrains in South Korea. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Ordinary Kriging (with the temperature lapse rate) and Cokriging were tested to estimate monthly air temperature of unobserved stations. Monthly measured data sets (minimum and maximum air temperature) from 588 automatic weather system(AWS) locations in South Korea were used to generate the gridded air temperature surface. As the result, temperature lapse rate improved accuracy of all of interpolation methods, especially, spline showed the lowest RMSE of spatial interpolation methods in both maximum and minimum air temperature estimation.

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Acknowledgement

Supported by : 국립농업과학원