[논문]경험적 분위사상법을 이용한 미국 지표 기온 기반 농업기후지수의 지역 규모 계절 예측성 개선

송찬영; 안중배; 이경도

doi:10.5532/kjafm.2022.24.4.201

[국내논문] 경험적 분위사상법을 이용한 미국 지표 기온 기반 농업기후지수의 지역 규모 계절 예측성 개선
Improvement in Regional-Scale Seasonal Prediction of Agro-Climatic Indices Based on Surface Air Temperature over the United States Using Empirical Quantile Mapping 원문보기

한국농림기상학회지 = Korean Journal of Agricultural and Forest Meteorology, v.24 no.4, 2022년, pp.201 - 217

송찬영 (부산대학교 BK21 지구환경시스템 교육연구단 대기환경과학과) , 안중배 (부산대학교 대기환경과학과) , 이경도 (국립농업과학원 기후변화평가과)

초록
AI-Helper

미국은 전 세계 주요 곡물(밀, 옥수수, 콩 등)의 생산 및 수출 국가로 알려져 있다. 따라서 신뢰할 만한 기상 예측 정보를 바탕으로 해당 지역에 대한 작황을 추정하는 것은 우리나라의 곡물 수급을 안정적으로 계획하기 위해서 중요하다. 본 연구에서는 지역 규모의 일 기온 및 이를 기반으로 산출되는 농업기후지수의 계절 예측성을 향상시키는 데 목적을 두었다. 이를 위해 먼저 역학적 규모축소법을 위한 지역기후모형으로 WRF가 사용되었으며, 해당 모형의 초기 및 측면 경계조건으로 PNU CGCM에서 생산된 시간 별 전지구 예측자료가 활용되었다. WRF의 적분은 22년(2000~2021년) 동안 매년 하반기를 포함하는 기간(6~12월)에 대해 수행되었다. 본 연구에서는 WRF에 의해 모의된 일 평균⋅최저⋅최고기온에 대해 EQM을 적용하여 모형이 갖는 편의를 보정하였다. EQM을 이용하여 보정된(보정되지 않은) 자료들은 WRF_C (WRF_UC)로 명명하였다. WRF_UC는 미국 내 대부분의 지역에서 일 최저기온(최고기온)을 과대(과소) 모의했는데, 이는 저온(고온) 범위를 과소 모의한 특징에서 비롯되었다. WRF_C는 WRF_UC에 나타난 일 평균⋅최저⋅최고기온의 편의가 감소하고 공간분포에 대한 예측성이 향상되었기 때문에 결과적으로 일 기온을 기반으로 산출되는 농업기후지수의 예측성 향상을 유도했다.

Abstract ▼ AI-Helper

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

주제어

표/그림 (13)

그림 Fig. 1. (a) Topography (Unit: m) and (b) WRF domain (gray shading). The numbers in the (a) indicate the six sub-regions over the United States.
표 Table 1. Configuration of the WRF
그림 Fig. 2. Spatial distribution of the daily mean temperature (Unit: ℃) during the 22 years of 2000-2021 (June to December) derived from (a) OBS, (b) WRF_UC, and (c) WRF_C, and the bias of (d) WRF_UC and (e) WRF_C. (f-j) and (k- o) are same as (a-e), but for daily minimum and maximum temperature, respectively.
표 Table 2. Climatology of the daily mean, minimum, and maximum temperature (Unit: ℃) for the United States and their sub-regions during the 22 years of 2000-2021 (June to December) derived from OBS, WRF_UC, and WRF_C
그림 Fig. 3. Root mean square temporal error (RMSTE) of daily mean temperature (Unit: ℃) during the 22 years of 2000-2021 (June to December) derived from (a) WRF_UC and (b) WRF_C. (c-d) and (e-f) are same as (a-b), but for daily minimum and maximum temperature, respectively.
표 Table 3. Root mean square temporal error (RMSTE) of the daily mean, minimum, and maximum temperature (Unit: ℃) for the United States and their sub-regions during the 22 years of 2000-2021 (June to December) derived from OBS, WRF_UC, and WRF_C
그림 Fig. 4. Timeseries of (a) spatial correlation coefficient (SCC) and (b) root mean square spatial error (RMSSE, Unit: ℃) of the daily mean temperature during the 22 years of 2000-2021 (June to December) derived from WRF_UC and WRF_C. (c-d) and (e-f) are same as (a-b), but for daily minimum and maximum temperature, respectively.
그림 Fig. 5. Frequency distribution of area-averaged daily (a) mean, (b) minimum, and (c) maximum temperature (Unit: ℃) over the United States.
그림 Fig. 6. Spatial distribution of the Growing Degree Days (GDD, Unit: ℃ days) during the 22 years of 2000-2021 derived from (a) OBS, (b) WRF_UC, and (c) WRF_C, and the bias of (d) WRF_UC and (e) WRF_C. (f-j), (k-o), and (p-t) are same as (a-e), but for the Growing Season Length (GSL, Unit: days), Number of frost days (FD, Unit: days), and Plant heat stress (PHS, Unit: days), respectively.
표 Table 4. Climatology of the Growing Degree Days (GDD, Unit: ℃ days), Growing Season Length (GSL, Unit: days), Number of frost days (FD, Unit: days), and Plant heat stress (PHS, Unit: days) for the United States and their sub-regions during the 22 years of 2000-2021 derived from OBS, WRF_UC, and WRF_C
그림 Fig. 7. Root mean square temporal error (RMSTE) of the Growing Degree Days (GDD, Unit: ℃ days) during the 22 years of 2000-2021 derived from (a) WRF_UC and (b) WRF_C. (c-d), (e-f), and (g-h) are same as (a-b), but for the Growing Season Length (GSL, Unit: days), Number of frost days (FD, Unit: days), and Plant heat stress (PHS, Unit: days), respectively.
표 Table 5. Root mean square temporal error (RMSTE) of the Growing Degree Days (GDD, Unit: ℃ days), Growing Season Length (GSL, Unit: days), Number of frost days (FD, Unit: days), and Plant heat stress (PHS, Unit: days) for the United States and their sub-regions during the 22 years of 2000-2021 derived from OBS, WRF_UC, and WRF_C
그림 Fig. 8. Timeseries of (a) spatial correlation coefficient (SCC) and (b) root mean square spatial error (RMSSE, Unit: ℃ days) of the Growing Degree Days (GDD) during the 22 years of 2000-2021 derived from WRF_UC and WRF_C. (c-d), (e-f), and (g-h) are same as (a-b), but for the Growing Season Length (GSL, Unit: days), Number of frost days (FD, Unit: days), and Plant heat stress (PHS, Unit: days), respectively.

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Themessl, M. J., A. Gobiet, and A. Leuprecht, 2011:？Empirical-statistical downscaling and error？correction of daily precipitation from regional？climate models. International Journal of Climatology？31(10), 1530-1544. https://doi.org/10.1002/joc.2168

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Themessl, M. J., A. Gobiet, and G. Heinrich, 2012:？Empirical-statistical downscaling and error？correction of regional climate models and its？impact on the climate change signal. Climatic？Change 112(2), 449-468. https://doi.org/10.1007/s10584-011-0224-4？

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저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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