气候变化领域集成服务门户(CCPortal): Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET

CCPortal

DOI	10.1038/s41612-019-0094-4
	Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET
	Gerken T.; Ruddell B.L.; Yu R.; Stoy P.C.; Drewry D.T.
发表日期	2019
ISSN	23973722
卷号	2 期号:1
英文摘要	Feedbacks between atmospheric processes like precipitation and land surface fluxes including evapotranspiration are difficult to observe, but critical for understanding the role of the land surface in the Earth System. To quantify global surface-atmosphere feedbacks we use results of a process network (PN) applied to 251 eddy covariance sites from the LaThuile database to train a neural network across the global terrestrial surface. There is a strong land–atmosphere coupling between latent (LE) and sensible heat flux (H) and precipitation (P) during summer months in temperate regions, and between H and P during winter, whereas tropical rainforests show little coupling seasonality. Savanna, shrubland, and other semi-arid ecosystems exhibit strong responses in their coupling behavior based on water availability. Feedback couplings from surface fluxes to P peaks at aridity (P/potential evapotranspiration ETp) values near unity, whereas coupling with respect to clouds, inferred from reduced global radiation, increases as P/ETp approaches zero. Spatial patterns in feedback coupling strength are related to climatic zone and biome type. Information flow statistics highlight hotspots of (1) persistent land–atmosphere coupling in sub-Saharan Africa, (2) boreal summer coupling in the central and southwestern US, Brazil, and the Congo basin and (3) in the southern Andes, South Africa and Australia during austral summer. Our data-driven approach to quantifying land atmosphere coupling strength that leverages the global FLUXNET database and information flow statistics provides a basis for verification of feedback interactions in general circulation models and for predicting locations where land cover change will feedback to climate or weather. © 2019, The Author(s).
语种	英语
scopus关键词	artificial neural network; database; eddy covariance; evapotranspiration; land surface; land-atmosphere interaction; latent heat flux; precipitation (climatology); sensible heat flux; summer; surface flux
来源期刊	npj Climate and Atmospheric Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178104
作者单位	Montana State University, Department of Land Resources and Environmental Sciences, 334 Leon Johnson Hall, Bozeman, MT 59717, United States; Northern Arizona University, School of Informatics, Computing, and Cyber Systems, 1295 N Knoles Dr., Flagstaff, AZ 86011, United States; University of Nebraska-Lincoln, School of Natural Resources, 101 Hardin Hall, Lincoln, NE 68583, United States; NASA Jet Propulsion Laboratory, Carbon Cycle and Ecosystems Group, 4800 Oak Grove Drive, Pasadena, CA 91109, United States; The Ohio State University, Department of Food, Agricultural and Biological Engineering, 590 Woody Hayes Drive, Columbus, OH 43210, United States; The Pennsylvania State University, Department of Meteorology and Atmospheric Science, 503 Walker Building, University Park, PA 16802, United States; University of Wisconsin–Madison, Department of Biological Systems Engineering, 460 Henry Mall, Madison, WI 53706, United States
推荐引用方式 GB/T 7714	Gerken T.,Ruddell B.L.,Yu R.,et al. Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET[J],2019,2(1).
APA	Gerken T.,Ruddell B.L.,Yu R.,Stoy P.C.,&Drewry D.T..(2019).Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET.npj Climate and Atmospheric Science,2(1).
MLA	Gerken T.,et al."Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET".npj Climate and Atmospheric Science 2.1(2019).