DOI: 10.1175/JCLI-D-13-00029.1
Scopus记录号: 2-s2.0-84886245440
论文题名: Model estimates of land-driven predictability in a changing climate from CCSM4
作者: Dirmeyer P.A. ; Kumar S. ; Fennessy M.J. ; Altshuler E.L. ; Delsole T. ; Guo Z. ; Cash B.A. ; Straus D.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 21 起始页码: 8495
结束页码: 8512
语种: 英语
Scopus关键词: Atmosphere-land interactions
; Climate system model
; Climate variability
; Interannual variability
; Land surface modeling
; Land-atmosphere couplings
; National center for atmospheric researches
; Temporal structures
; Climate change
; Land use
; Soil moisture
; Surface measurement
; Climate models
; annual variation
; atmosphere-biosphere interaction
; climate change
; climate modeling
; climate prediction
; land use change
; soil moisture
; Great Plains
; Poaceae
英文摘要: The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the model's ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes during dry seasons. Despite these shortcomings, intriguing changes in predictability are found. Areas of historical land use change appear to have experienced changes in predictability, particularly where agriculture expanded dramatically into the Great Plains of North America, increasing land-driven predictability there. In a warming future climate, land-atmosphere coupling strength generally increases, but added predictability does not always follow; many other factors modulate land-driven predictability. © 2013 American Meteorological Society. 资助项目: NSF, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51567
Appears in Collections: 气候变化事实与影响
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作者单位: George Mason University, Fairfax, VA, United States; Center for Ocean-Land-Atmosphere Studies, Calverton, MD, United States
Recommended Citation:
Dirmeyer P.A.,Kumar S.,Fennessy M.J.,et al. Model estimates of land-driven predictability in a changing climate from CCSM4[J]. Journal of Climate,2013-01-01,26(21)