气候变化领域集成服务门户(CCPortal): Global Fire Forecasts Using Both Large-Scale Climate Indices and Local Meteorological Parameters

CCPortal

DOI	10.1029/2019GB006180
	Global Fire Forecasts Using Both Large-Scale Climate Indices and Local Meteorological Parameters
	Shen H.; Tao S.; Chen Y.; Odman M.T.; Zou Y.; Huang Y.; Chen H.; Zhong Q.; Zhang Y.; Chen Y.; Su S.; Lin N.; Zhuo S.; Li B.; Wang X.; Liu W.; Liu J.; Pavur G.K.; Russell A.G.
发表日期	2019
ISSN	0886-6236
EISSN	1944-9224
起始页码	1129
结束页码	1145
卷号	33 期号:8
英文摘要	Fire forecasts that predict dry-season fire activities several months in advance are beneficial for fire management. On a global scale, however, the predictability of fires is limited because fires depend on multiple factors and lack a single dominant predictor to describe diverse fire characteristics across regions. Here, based on 33 local meteorological parameters (MPs) and 37 large-scale climate indices (CIs), we establish four empirical model clusters to predict global interannual fire variability. We show that across various geographic locations, the models provide reliable fire forecasts at least three months prior to the peak fire months. Compared to MPs, CIs such as the Oceanic Niño Index are comparable or even superior predictors. Globally, as well as in most continents, the El Niño–Southern Oscillation is the major driving force, explaining 17% of interannual fire variability, with strong implications for fire carbon emissions and the global carbon cycle. Other important predictors include the Northern Atlantic sea surface temperature (9%), the Southern Atlantic sea surface temperature (5%), and the Pacific/North American Pattern (3%). The predictive models reveal a strong interaction between MPs and CIs, indicating potential climate-induced modification of fire responses to meteorological conditions. We show that the newly developed predictive models can benefit future fire management in response to climate change. © 2019. American Geophysical Union. All Rights Reserved.
英文关键词	climate change; climate indices; global fire forecasts; meteorological conditions
语种	英语
scopus关键词	annual variation; carbon cycle; carbon emission; dry season; El Nino-Southern Oscillation; fire management; forest fire; prediction; sea surface temperature; Pacific Coast [North America]
来源期刊	Global Biogeochemical Cycles
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/129714
作者单位	Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States; Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, United States; Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives–CNRS–Université de Versailles Saint-Quentin, Université Paris-Saclay, Gif-sur-Yvette, France; College of Environment, Zhejiang University of Technology, Hangzhou, China
推荐引用方式 GB/T 7714	Shen H.,Tao S.,Chen Y.,et al. Global Fire Forecasts Using Both Large-Scale Climate Indices and Local Meteorological Parameters[J],2019,33(8).
APA	Shen H..,Tao S..,Chen Y..,Odman M.T..,Zou Y..,...&Russell A.G..(2019).Global Fire Forecasts Using Both Large-Scale Climate Indices and Local Meteorological Parameters.Global Biogeochemical Cycles,33(8).
MLA	Shen H.,et al."Global Fire Forecasts Using Both Large-Scale Climate Indices and Local Meteorological Parameters".Global Biogeochemical Cycles 33.8(2019).