Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Generation of daily temperature data using monthly mean temperature and precipitation data

월 평균 기온과 강우 자료를 이용한 일 기온 자료의 생성

  • Moon, Kyung Hwan (National Institute of Horticulture and Herbal Science Rural Development Administration) ;
  • Song, Eun Young (National Institute of Horticulture and Herbal Science Rural Development Administration) ;
  • Wi, Seung Hwan (National Institute of Horticulture and Herbal Science Rural Development Administration) ;
  • Seo, Hyung Ho (National Institute of Horticulture and Herbal Science Rural Development Administration) ;
  • Hyun, Hae Nam (Major of plant resources and environment Jeju National University)
  • 문경환 (국립원예특작과학원 농촌진흥청) ;
  • 송은영 (국립원예특작과학원 농촌진흥청) ;
  • 위승환 (국립원예특작과학원 농촌진흥청) ;
  • 서형호 (국립원예특작과학원 농촌진흥청) ;
  • 현해남 (식물자원환경전공 제주대학교)
  • Received : 2018.02.13
  • Accepted : 2018.09.13
  • Published : 2018.09.30
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Abstract

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

이 연구는 월평균 기상자료를 이용하여 일 최고기온, 일 최저기온을 생성하는 방법을 개발하기 위하여 진행되었다. 전국 23개 기상관서의 과거 30년간의 일기상자료를 분석하여 일 최고기온 및 일 최저기온의 연간 변동 경향을 나타내는 모수(중심값($\hat{U}$), 진폭(C), 편이(T))와 일간 변동을 반영하는 모수(A, B)를 탐색하였다. 그 중 중심값은 지점간의 연 평균자료로부터 도출하였고, 중심값을 제외한 모수들은 전국 평균을 기상생성과정에 적용하였다. 먼저 강우발생 유무에 따라 일 기상자료를 생성한 후 월 자료를 이용하여 보정하고 마지막으로 일 최고기온 및 일 최저기온을 생성하였다. 이 방법으로 전체 23개 지역에 대하여 월별로 생성하였을 때 전체 월별 분포의 95% 이상 관측된 분포와 유사한 일 자료를 생성할 수 있었다. 또 이 방법에 의해 과거 자료와 유사한 생장도일(Growing Degree Day)를 생성할 수 있었고, 조사대상이 아닌 지역에도 충분히 적용할 수 있었다. 이 방법은 기후변화시나리오 등 월 자료가 확보되어 있는 경우에 일기상자료를 생성하는데 유용할 것으로 판단되었다.

Keywords

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