DOI: 10.1175/JCLI-D-13-00543.1
Scopus记录号: 2-s2.0-84899059129
论文题名: Harmonized European long-term climate data for assessing the effect of changing temporal variability on land-atmosphere CO2 fluxes
作者: Beer C. ; Weber U. ; Tomelleri E. ; Carvalhais N. ; Mahecha M. ; Reichstein M.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 13 起始页码: 4815
结束页码: 4834
语种: 英语
Scopus关键词: Carbon dioxide
; Climate change
; Climatology
; Distribution functions
; Ecosystems
; Experiments
; Meteorology
; Atmosphere-land interactions
; Bias-correction methods
; Biosphere-atmosphere interactions
; Climate variability
; Gross primary production
; Meteorological data distribution
; Meteorological variables
; Transformation functions
; Climate models
; air-soil interaction
; carbon dioxide
; carbon flux
; climate change
; climate variation
; climatology
; temporal variation
; Europe
英文摘要: Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two longterm climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51153
Appears in Collections: 气候变化事实与影响
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作者单位: Max Planck Institute for Biogeochemistry, Jena, Germany; Department of Applied Environmental Science (ITM), Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden; EURAC, Institute for Applied Remote Sensing, Bozen, Italy
Recommended Citation:
Beer C.,Weber U.,Tomelleri E.,et al. Harmonized European long-term climate data for assessing the effect of changing temporal variability on land-atmosphere CO2 fluxes[J]. Journal of Climate,2014-01-01,27(13)