본문 바로가기
KERD
논문KCI 등재

PNU CGCM-WRF Chain을 이용한 남한지역 벼의 생육단계별 고온해 및 저온해 발생일수에 대한 예측성 연구

A Study on the Predictability of the Number of Days of Heat and Cold Damages by Growth Stages of Rice Using PNU CGCM-WRF Chain in South Korea

조세라|최명주|허지나|심교문|안중배|김영현
한국기상학회 (Korean Meteorological Society)|2021.12|대기 (Atmosphere)|제31권 제5호|pp. 577-592|DOI 10.14191/Atmos.2021.31.5.577

1

조회

0

다운로드

3

인용

0

참고문헌

키워드

ricepredictabilitycold damageWRFheat damagePNU CGCM
주제분류대기과학

초록

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6oC and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and lowtemperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and 0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

Abstract

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6oC and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and lowtemperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and 0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

참고문헌 (46)

  1. Ahn, J. -B., "Numerical study on the role of sea-ice using ocean general circulation model", J. Korean Soc. Oceanogr, 6, pp.225~233 (2001)
  2. 안중배, "접합대순환모형의 초기조건 생산방법에 따른 북반구 겨울철 기온과 해수면 온도의 계절 예측성 비교 연구", 대기, 25(2), pp.353~366 (2015), 한국기상학회
  3. 안중배, "PNU CGCM V1.1을 이용한 12개월 앙상블 예측 시스템의 개발", 대기, 22(4), pp.455~464 (2012), 한국기상학회
  4. 안중배, "Changes of Precipitation Extremes over South Korea Projected by the 5 RCMs under RCP Scenarios", Asia-Pacific Journal of Atmospheric Sciences, 52(2), pp.223~236 (2016), 한국기상학회
  5. 안중배, "PNU CGCM 앙상블 예보 시스템의 겨울철 남한 기온 예측 성능 평가", 대기, 28(4), pp.509~520 (2018), 한국기상학회[DOI]
  6. 안중배, "PNU CGCM과 WRF를 이용한 남한 지역 기온 예측성 검증", 대기, 28(4), pp.479~490 (2018), 한국기상학회[DOI]
  7. Ahn, J. -B., "Climatic yield potential of Japonica-type rice in the Korean Peninsula under RCP scenarios using the ensemble of multi-GCM and multi-RCM chains", Int. J. Climatol, 41, pp.E1287~E1302 (2021)[DOI]
  8. Bonan, G. B., "The land surface climatology of the NCAR land surface model coupled to the NCAR community climate model", J. Climate, 11, pp.1307~1326 (1998)
  9. Chen, F., "Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity", Mon. Wea. Rev., 129, pp.569~585 (2001)[DOI]
  10. Chung, S. -O., "Simulating evapotranspiration and yield responses of rice to climate change using FAOAquaCrop", J. Korean Soc. Agric. Eng, 52, pp.57~64 (2010)[DOI]
  11. Dudhia, J., "Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model", J. Atmos. Sci., 46, pp.3077~3107 (1989)[DOI]
  12. The State of Food Security and Nutrition in the World 2021. Transforming food systems for food security, improved nutrition and affordable healthy diets for all, "FAO", Food and Agriculture Organization of the United Nations, 240~ (2021)
  13. 허인혜, "한국의 지역별 이상기온의 분포 특성과 그 지역구분", 한국지역지리학회지, 12(4), pp.461~474 (2006), 한국지역지리학회
  14. Hong, S. -Y., "A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation", Mon. Wea. Rev, 132, pp.103~120 (2004)[DOI]
  15. Hong, S. -Y., "A new vertical diffusion package with an explicit treatment of entrainment processes", Mon. Wea. Rev, 134, pp.2318~2341 (2006)[DOI]
  16. Hunke, E. C., "An Elastic-Viscous-Plastic model for sea ice dynamics", J. Phys. Oceanogr, 27, pp.1849~1867 (1997)[DOI]
  17. Jeong, H. -K., "Impacts of abnormal weather factors on rice production", J. Climate Change Res, 4, pp.317~330 (2013)
  18. Kain, J. S., "The Kain-Fritsch convective parameterization : An update", J. Appl. Meteor. Climatol, 43, pp.170~181 (2004)[DOI]
  19. Description of the NCAR Community Climate Model (CCM3), "Kiehl, J. T.", NCAR, 152~, pp.NCAR (1996), TN-420+STR
  20. Impacts and countermeasures of climate change on food supply in Kor, "Kim, C.-K.", Korea Rural Economic Institute, 176~ (2013)
  21. 김대준, "기후변화 시나리오에 근거한 과수 개화기 변화 및 개화 후 저온 발생 전망", 한국농림기상학회지, 20(4), pp.313~320 (2018), 한국농림기상학회
  22. Kim, G. -H, "Development of an agrophotovoltaic system and analysis of the agronomic characteristic of crops under agrophotovoltaic system", Bull. Korea Photovoltaic Soc, 6, pp.15~24 (2020)
  23. Kim, M. -R, "The Status of Korea’s rice industry and the rice processing industry", Food Indust. Nutr, 16, pp.22~26 (2011)
  24. 김선영, "한국에서 기온상승이 사과 재배지역의 변화에 미치는 영향", 한국지역지리학회지, 16(3), pp.201~215 (2010), 한국지역지리학회
  25. 김영현, "PNU CGCM-WRF Chain을 이용한 남한 지역 폭염 장기 계절 예측성 평가", 대기, 29(5), pp.671~687 (2019), 한국기상학회[DOI]
  26. Lee, D., "Thermodynamic and dynamic contributions to future changes in summer precipitation over Northeast Asia and Korea: a multi-RCM study", Climate Dyn, 49, pp.4121~4139 (2017)[DOI]
  27. Lee, M. -H., "Mechanisms of cold injury and cultural practices for reducing damage of rice", Korean J. Crop Sci, 34, pp.34~44 (1989)[DOI]
  28. 이인혜, "강우처리 및 수확 지연에 따른 콩 종실 특성 및 수량성 변화", 한국작물학회지, 65(4), pp.353~364 (2020), 한국작물학회
  29. Lee, S. -H., "Impacts of climate change on phonology and growth of crops : In the case of Naju", J. Korean Geograph. Soc, 43, pp.20~35 (2008)[DOI]
  30. Lesk, C., "Influence of extreme weather disasters on global crop production", Nature, 529, pp.84~87 (2016)[DOI]
  31. Mlawer, E. J., "Radiative transfer for inhomogeneous atmospheres : RRTM, a validated correlated-k model for the longwave", J. Geophys. Res. Atmos, 102, pp.16663~16682 (1997)[DOI]
  32. 명수정, "기후변화 관련 자연재해가 우리나라의 쌀 생산에 미치는 영향", 한국방재학회논문집, 18(7), pp.53~60 (2018), 한국방재학회[DOI]
  33. "MOM 3.0 manual" (1998)[URL]
  34. Park, C., "Evaluation of multiple regional climate models for summer climate extremes over East Asia", Climate Dyn, 46, pp.2469~2486 (2016)[DOI]
  35. Park, C., "Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models", Int. J. Climatol, 40, pp.2270~2284 (2020)[DOI]
  36. Paulson, C. A., "The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer", J. Appl. Meteor. Climatol, 9, pp.857~861 (1970)[DOI]
  37. Development of production prospects and risk assessment evaluation technology for decreasing climate disaster on upland crops, "RDA", National Institute of Crop Science, Rural Development Administration, 159~ (2018)
  38. 심교문, "한국의 농업기후지대별 이상일조 출현 특성 평가", 한국농림기상학회지, 16(1), pp.83~91 (2014), 한국농림기상학회[DOI]
  39. A description of the advanced research WRF version 3, "Skamarock, W. C.", NCAR, 113~, pp.NCAR (2008), TN475+STR
  40. 손인창, "고랭지 여름배추 주산지의 기온을 기준으로 한 수준별 온도가 배추 ‘춘광’의 생육 및 생리반응에 미치는 영향", 한국농림기상학회지, 17(3), pp.254~260 (2015), 한국농림기상학회[DOI]
  41. Sun, J., "A GCM-based forecasting model for the landfall of tropical cyclones in China", Adv. Atmos. Sci, 28, pp.1049~1055 (2011)[DOI]
  42. Sun, J., "Dynamical seasonal predictability of the Arctic Oscillation using a CGCM", Int. J. Climatol, 35, pp.1342~1353 (2015)[DOI]
  43. Teutschbein, C., "Bias correction of regional climate model simulations for hydrological climate-change impact studies : Review and evaluation of different methods", J. Hydrol, 456, pp.12~29 (2012)
  44. World Population Prospects 2019. Highlights, "UN", United Nations, Department of Economic and Social Affairs, Population Division, 39~, pp.ST (2019), ESA[DOI]
  45. Yun, J. I., "Agricultural meteorology", pp.337~ (1999), Arche Inc.
  46. Wilks, D. S., "Statistical Methods in the Atmospheric Sciences", pp.467~ (1995), Academic Press

관련 논문AI추천

PNU CGCM-WRF Chain을 이용한 남한 지역 폭염 장기 계절 예측성 평가김영현, 김응섭, 심교문, 안중배, 최명주한국기상학회 · 대기2019 · 제29권 제5호PNU CGCM과 WRF를 이용한 남한 지역 기온 예측성 검증김영현, 김응섭, 심교문, 안중배, 정명표, 정하규한국기상학회 · 대기2018 · 제28권 제4호PNU CGCM 앙상블 예보 시스템의 겨울철 남한 기온 예측 성능 평가안중배, 이준리, 조세라한국기상학회 · 대기2018 · 제28권 제4호기후변화 시나리오를 이용한 남한에서의 서리일수(첫/마지막 서리일)의 시공간 변동특성 연구배철호, 서명석, 오석근기후연구소 · 기후연구2017 · 제12권 제1호현 기후예측시스템에서의 기온과 강수 계절 확률 예측 신뢰도 평가김윤재, 박진경, 이상민, 이조한, 임소민, 지희숙, 함현준, 허솔잎, 현유경한국기상학회 · 대기2020 · 제30권 제2호경험적 분위사상법을 이용한 지역기후모형 기반 미국 강수 및 가뭄의 계절 예측 성능 개선김소희, 송찬영, 안중배한국기상학회 · 대기2021 · 제31권 제5호

이 간행물의 다른 논문 (11건)

고해상도 지상 기온 상세화 모델 개발이상현, 김연희, 정형세, 이두일pp. 473-488국지성 집중호우 감시를 위한 천리안위성 2A호 대류운 전조 탐지 알고리즘 개발문재인, 박기홍, 박혜인, 정성래pp. 489-510기상청 기후예측시스템(GloSea5)의 과거기후장 앙상블 확대에 따른 예측성능 평가지희숙, 현유경, 박연희, 허솔잎pp. 511-523도로기상차량으로 관측한 노면온도자료를 이용한 도로살얼음 취약 구간 산정박문수, 장성빈, 강민수, 류성현, 김상헌, 유동길, 정현채pp. 525-537이순신장군의 난중일기에 기록된 기상자료의 분석차소영, 서명석pp. 539-551
원문 보기