한국농림기상학회지 (Korean Journal of Agricultural and Forest Meteorology)

  • 제22권3호
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  • Pages.128-134
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  • 2020
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  • 1229-5671(pISSN)
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  • 2288-1859(eISSN)
한국농림기상학회 (Korean Society of Agricultural and Forest Meteorology)
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남한지역 기후변화량 평가를 위한 고해상도 농업기후 자료

A High-Resolution Agro-Climatic Dataset for Assessment of Climate Change over South Korea

  • 허지나 (국립농업과학원 기후변화평가과) ;
  • 박주현 (주식회사 에피넷) ;
  • 심교문 (국립농업과학원 기후변화평가과) ;
  • 김용석 (국립농업과학원 기후변화평가과) ;
  • 조세라 (국립농업과학원 기후변화평가과)
  • Hur, Jina (Climate Change Assessment Division, National Institute of Agricultural Sciences) ;
  • Park, Joo Hyeon (R&D Center, EPINET Co., Ltd) ;
  • Shim, Kyo Moon (Climate Change Assessment Division, National Institute of Agricultural Sciences) ;
  • Kim, Yong Seok (Climate Change Assessment Division, National Institute of Agricultural Sciences) ;
  • Jo, Sera (Climate Change Assessment Division, National Institute of Agricultural Sciences)
  • 투고 : 2020.09.07
  • 심사 : 2020.09.24
  • 발행 : 2020.09.30
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초록

국립농업과학원은 공동연구를 통해 기상청 소속 94개 종관기상관측소의 일별 기상자료를 기반으로 6가지 기상요소(최고·최저·평균 기온, 강수량, 일사량, 일조시간)에 대한 30m 및 270m 해상도의 격자형 일별 상세 기후 자료를 약 50년(1971-현재) 기간에 대해 생산하였고, 평년 기후값(1981-2010) 및 평년 대비 상세 기후 변화량 정보를 생산하였다. 이러한 일별 자료, 평년 자료 그리고 평년 대비 변화량 자료는 GeoTiff 형식으로 제공되며, 구글 크롬(Google Chrome) 에서 최적화된 https://agecoclim.agmet.kr 사이트에서 다운받을 수 있다. 본 연구 결과물은 현재 주식회사 에피넷과 국립농업과학원에서 공동으로 관리 중이며, 향후 기후·이상기상 변화량 분석 자동화 체계를 추가 보완을 통해 활용성을 제고하고, 기후 정보의 정확성을 향상시킬 예정이다.

The daily gridded meteorological information and climatology with high resolution (30m and 270m) was produced from 94 Automated Surface Observing System (ASOS) of Korea Meteorological Administration (KMA) for the past 50 years (1971-current) by different downscaling methods. In addition, the difference between daily meteorological data and the mean state of past 30 years (1981-2010) was calculated for the analysis of climate change. These datasets with GeoTiff format are available from the web interface (https://agecoclim. agmet.kr). The performance of the data is evaluated using 172 Automatic Weather S tation (AWS ) of Rural Development of Administration (RDA). The data have biases lower than 2.0, and root mean square errors (RMSE) lower than 3.8. This data may help to better understand the regional climatic change and its impact on agroecosystem in S outh Korea.

키워드

참고문헌

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