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Assessing crop yield simulations driven by the NARCCAP regional climate models in the southeast United States

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Title
Assessing crop yield simulations driven by the NARCCAP regional climate models in the southeast United States
Other Titles
NARCCAP에 의해 주도되는 작물 생산량 시뮬레이션 평가미국 남동부의 지역 기후 모델
Authors
Shin, Dong Wook
Kim, Baek-Min
Oh, Ji-Hyun
Steve Cocke
Consuelo C. Romero
Guillermo A. Baigorria
Subject
Meteorology & Atmospheric Sciences
Keywords
A reanalysis-driven crop yield mightnot be good for a decision-makingprocess; Economically valuable cropproduction can be assessedbetter using a set of the regionalclimate models
Issue Date
2017
Citation
Shin, Dong Wook, et al. 2017. "Assessing crop yield simulations driven by the NARCCAP regional climate models in the southeast United States". JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 122(5): 2549-2558.
Abstract
A set of the North American Regional Climate Change Assessment Program (NARCCAP) regional climate models is used in crop modeling systems to assess economically valuable agricultural production in the southeast United States, where weather/climate exerts strong impact on agriculture. The maize/peanut/ cotton yield amounts for the period of 1981?2003 are obtained in a regularly gridded (~20km) southeast U.S. using (a) observed, (b) a reanalysis, and (c) the NARCCAP Phase I multimodel data set. It is shown that the regional-climate model-driven crop yield amounts are better simulated than the reanalysis-driven ones. Multimodel ensemble methods are then adopted to examine their usefulness in improving the simulation of regional crop yield amounts and are compared to each other. The bias-corrected or weighted composite methods combine the crop yield ensemble members better than the simple compositemethod. In general, the weighted ensemble crop yield simulations match marginally better with the observed-weather-driven yields compared to those of the other ensemble methods.
URI
http://repository.kopri.re.kr/handle/201206/5644
DOI
http://dx.doi.org/10.1002/2016JD025576
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