Modelling global impacts of climate variability and trend on maize yield during 1980-2010

doi:10.1002/joc.6792

	Modelling global impacts of climate variability and trend on maize yield during 1980-2010
	Yin, Xiaomeng 1,2; Leng, Guoyong 2,3
刊名	INTERNATIONAL JOURNAL OF CLIMATOLOGY
	2020-09-01
页码	14
关键词	climate change climate impact crop yield global trend variability
ISSN号	0899-8418
DOI	10.1002/joc.6792
通讯作者	Leng, Guoyong(lenggy@igsnrr.ac.cn)
英文摘要	Enhanced understanding of historical climate impacts on crop yield is critical for adaptation and mitigations within the context of global warming. Previous impact assessments rely on statistical or process-based models, each with its own strength and weakness. To date, a global-scale comparison between process-based and statistical models in assessing climate impacts on yield variability and trends is lacking. Here, we leverage both statistical and process models to estimate global impacts of climate variability and trend on maize yield between 1980 and 2010. To allow for reasonable comparability, we develop a novel emulator to mimic each of eight global process-based maize models, based on which the common set of climate scenarios are used for driving both statistical and process models. Results show that climate variability controls 42% of global maize yield variations in statistical model, while large discrepancy is found in process-based models withR(2)ranging from 0.22 to 0.61, especially at the country scale. Both statistical and most process models suggest that historical climate trend has led to a yield loss by 1.51-3.80% during the period 1980-1990. As for the period 1991-2000, however, the observed negative climate impacts are only captured by two process models. In contrast to the positive climate impact in statistical model, most of process-based models simulated negative climate effects for the period 2001-2010, due to large yield sensitivity to maximum temperature in process models. This study highlights the large discrepancies not only among the eight process-based models but also between statistical and process-based models in simulating yield response to climate variation and trends, which has great implications for projecting future crop yields under climate change.
资助项目	Chinese Academy of Sciences[YJRCPT2019-001]
WOS关键词	CROP YIELD ; STATISTICAL-MODELS ; UNITED-STATES ; WHEAT YIELDS ; SIMULATION ; PATTERNS ; NORTHERN ; CEREAL ; DSSAT
WOS研究方向	Meteorology & Atmospheric Sciences
语种	英语
出版者	WILEY
WOS记录号	WOS:000564554800001
资助机构	Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/157964]
专题	中国科学院地理科学与资源研究所
通讯作者	Leng, Guoyong
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 3.Univ Oxford, Environm Change Inst, Oxford, England
推荐引用方式 GB/T 7714	Yin, Xiaomeng,Leng, Guoyong. Modelling global impacts of climate variability and trend on maize yield during 1980-2010[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2020:14.
APA	Yin, Xiaomeng,&Leng, Guoyong.(2020).Modelling global impacts of climate variability and trend on maize yield during 1980-2010.INTERNATIONAL JOURNAL OF CLIMATOLOGY,14.
MLA	Yin, Xiaomeng,et al."Modelling global impacts of climate variability and trend on maize yield during 1980-2010".INTERNATIONAL JOURNAL OF CLIMATOLOGY (2020):14.