Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Evaluating the Predictability of Heat and Cold Damages of Soybean in South Korea using PNU CGCM -WRF Chain

PNU CGCM-WRF Chain을 이용한 우리나라 콩의 고온해 및 저온해에 대한 예측성 검증

  • Myeong-Ju, Choi (Department of Atmospheric Sciences, BK21 School of Earth and Environmental Systems, Pusan National University) ;
  • Joong-Bae, Ahn (Department of Atmospheric Sciences, Pusan National University) ;
  • Young-Hyun, Kim (Department of Atmospheric Sciences, Pusan National University) ;
  • Min-Kyung, Jung (Department of Atmospheric Sciences, BK21 School of Earth and Environmental Systems, Pusan National University) ;
  • Kyo-Moon, Shim (Climate Change Assessment Division, National Institute of Agricultural Sciences) ;
  • Jina, Hur (Climate Change Assessment Division, National Institute of Agricultural Sciences) ;
  • Sera, Jo (Climate Change Assessment Division, National Institute of Agricultural Sciences)
  • 최명주 (부산대학교 BK21 지구환경시스템 교육연구단 대기환경과학과) ;
  • 안중배 (부산대학교 대기환경과학과) ;
  • 김영현 (부산대학교 대기환경과학과) ;
  • 정민경 (부산대학교 BK21 지구환경시스템 교육연구단 대기환경과학과) ;
  • 심교문 (국립농업과학원 기후변화평가과) ;
  • 허지나 (국립농업과학원 기후변화평가과) ;
  • 조세라 (국립농업과학원 기후변화평가과)
  • Received : 2022.09.14
  • Accepted : 2022.11.17
  • Published : 2022.12.30
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Abstract

The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.

본 연구에서는 Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF)에서 생산된 hindcast 자료(1986~2020)를 이용하여 우리나라의 주요 곡물 중 하나인 콩의 생육단계별 고온해 및 저온해 발생일수의 예측성을 평가하였다. 예측성을 평가하는 방법으로는 Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), Heidke Skill Score (HSS)이다. 이를 위해 먼저 콩의 고온해 및 저온해를 정의하는 변수인 일 최고기온(Tmax) 및 일 최저기온(Tmin)의 모의성능을 검증하였다. 그 결과 1~5월(01RUN~05RUN)의 초기조건을 가지고 시작하는 월에 따라 다소 차이가 있지만, Variance Scaling 방법을 적용하여 보정한 결과가 보정전보다 관측과 유사하게 나타났으며, 보정한 3~10월의 Tmax 및 Tmin에 대한 모의성능은 전반적으로 01RUN~05RUN에 Simple Composite Method (SCM)을 적용하여 평균한 결과(ENS)에서 높게 나타났다. 또한, 콩의 생육시기별 고온해 및 저온해 발생일수의 지역적 패턴과 특성을 관측과 비교하였을 때 모형이 잘 모의하고 있다. ENS에서 콩의 고온해(저온해)에 대한 HR과 HSS는 생육시기 별로 0.45~0.75, 0.02~0.10(0.49~0.76, -0.04~0.11)의 범위를 가진다. 결론적으로, PNU CGCM-WRF chain의 01RUN~05RUN 및 ENS는 우리나라 콩의 생육시기별 고온해 및 저온해를 예측할 수 있는 성능을 가지고 있다.

Keywords

Acknowledgement

본 연구는 농촌진흥청 연구사업(세부과제번호: PJ01489102)의 지원으로 수행되었습니다.

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