한국농림기상학회지 (Korean Journal of Agricultural and Forest Meteorology)

  • 제21권3호
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  • Pages.146-157
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  • 2019
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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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농장맞춤형 농업기상정보 생산을 위한 소기후 모형 구축

Establishment of Geospatial Schemes Based on Topo-Climatology for Farm-Specific Agrometeorological Information

  • Kim, Dae-Jun (National Center for Agro-Meteorology, Seoul National University) ;
  • Kim, Soo-Ock (National Center for Agro-Meteorology, Seoul National University) ;
  • Kim, Jin-Hee (National Center for Agro-Meteorology, Seoul National University) ;
  • Yun, Eun-Jeong (National Center for Agro-Meteorology, Seoul National University)
  • 투고 : 2019.09.17
  • 심사 : 2019.09.25
  • 발행 : 2019.09.30
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초록

우리나라 농산촌 환경의 가장 큰 특징 중 하나는 지형이 복잡하여 좁은 지역 내에서도 기상/기후 분포변이가 크다는 점이다. 이를 효과적으로 모의하기 위하여 '소기후 모형'이 개발되었고 현재까지 지속적으로 개선 연구가 진행되고 있다. 소기후 모형은 우리나라 전역에 대해 농장필지 단위까지 공간적으로 정밀한 농업기상/기후 정보를 표현할 수 있는 모형으로 기후요소별로 독자적으로 개발되었다. 소기후모형을 이용하여 2000년대에는 국지규모의 현재평년 및 미래 시나리오 기반 기후정보를 산출하였다. 평년 전자기후도는 과거 30년 기간의 월별 최저기온, 최고기온, 강수량, 일사량을 30 m 격자해상도로 상세화 한 분포도이며, 이 전자기후도를 기반으로 미래 기후변화 시나리오를 고해상도로 상세화하여 제작하였다. 이 들 전자기후도는 농업분야 기후변화 영향평가에 다양한 형태로 재가공 되어 이용되었다. 2010년대에는 농장맞춤형 기상 실황 및 예보자료를 국지규모로 생성하고 있다. 소기후 모형은 지속적인 개선 과정을 통해 일별 관측기상자료를 기반으로 실황정보를 상세화하는 기술로 발전하고 있으며, 기상청 동네예보 및 중기예보를 30 m 격자해상도로 상세 모의하여 농업분야 종사자에게 예측 정보를 실시간 제공할 수 있는 '농업기상 재해 조기경보 서비스' 기반의 핵심기술로 인정 받고 있다. 현재 상세 기상 실황 및 예보정보로는 일 최저 및 최고기온과 강수량, 일사량, 일조시간 등이 산출되고 있으며, 과거-현재-미래의 농장규모 기상정보를 토대로 각종 농작물의 생육정보와 기상재해 예측정보를 생산하고 있다.

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.

키워드

참고문헌

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