干旱区生态环境知识资源中心(Arid): Interannual variability and climatic sensitivity of global wildfire activity

Arid

	Interannual variability and climatic sensitivity of global wildfire activity
	Tang Rongyun; Mao Jiafu; Jin Mingzhou; Chen Anping; Yu Yan; Shi Xiaoying; Zhang Yulong; Hoffman Forrest M; Xu Min; Wang Yaoping
来源期刊	Advances in Climate Change Research
ISSN	1674-9278
出版年	2021
卷号	12 期号:5 页码:686-695
英文摘要	Understanding historical wildfire variations and their environmental driving mechanisms is key to predicting and mitigating wildfires. However, current knowledge of climatic responses and regional contributions to the interannual variability (IAV) of global burned area remains limited. Using recent satellite-derived wildfire products and simulations from version v1.0 of the land component of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM land model [ELM] v1) driven by three different climate forcings, we investigated the burned area IAVand its climatic sensitivity globally and across nine biomes from 1997 to 2018. We found that 1) the ELM simulations generally agreed with the satellite observations in terms of the burned area IAV magnitudes, regional contributions, and covariations with climate factors, confirming the robustness of the ELM to the usage of different climate forcing sources; 2) tropical savannas, tropical forests, and semi-arid grasslands near deserts were primary contributors to the global burned area IAV, collectively accounting for 71.7%e99.7% of the global wildfire IAV estimated by both the satellite observations and ELM simulations; 3) precipitation was a major fire suppressing factor and dominated the global and regional burned area IAVs, and temperature and shortwave solar radiation were mostly positively related with burned area IAVs; and 4) noticeable local discrepancies between the ELM and remote-sensing results occurred in semi-arid grasslands, croplands, boreal forests, and wetlands, likely caused by uncertainties in the current ELM fire scheme and the imperfectly derived satellite observations. Our findings revealed the spatiotemporal diversity of wildfire variations, regional contributions and climatic responses, and provided new metrics for wildfire modeling, facilitating the wildfire prediction and management.
英文关键词	Wildfire Burned area Climatic sensitivity E3SM land model Global fire emission database
类型	Article
语种	英语
开放获取类型	gold
收录类别	CSCD
WOS类目	Science & Technology - Other Topics
CSCD记录号	CSCD:7117030
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/377405
作者单位	Tang Rongyun, Institute for a Secure and Sustainable Environment,University of Tennessee;;Environmental Sciences Division and Climate Change Science Institute, ;;Oak Ridge National Laboratory, Knoxville;;Oak Ridge, USA;;USA 37996;;37830.; Mao Jiafu, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, 37830, USA.; Shi Xiaoying, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, 37830, USA.; Jin Mingzhou, Institute for a Secure and Sustainable Environment,University of Tennessee, Knoxville, 37996, USA.; Zhang Yulong, Institute for a Secure and Sustainable Environment,University of Tennessee, Knoxville, 37996, USA.; Wang Yaoping, Institute for a Secure and Sustainable Environment,University of Tennessee, Knoxville, 37996, USA.; Chen Anping, Department of Biology and Graduate Degree Program in Ecology,Colorado State University, Fort Collins, 80523, USA.; Yu Yan, Atmospheric and Oceanic Scie...
推荐引用方式 GB/T 7714	Tang Rongyun,Mao Jiafu,Jin Mingzhou,et al. Interannual variability and climatic sensitivity of global wildfire activity[J],2021,12(5):686-695.
APA	Tang Rongyun.,Mao Jiafu.,Jin Mingzhou.,Chen Anping.,Yu Yan.,...&Wang Yaoping.(2021).Interannual variability and climatic sensitivity of global wildfire activity.Advances in Climate Change Research,12(5),686-695.
MLA	Tang Rongyun,et al."Interannual variability and climatic sensitivity of global wildfire activity".Advances in Climate Change Research 12.5(2021):686-695.