DOI: 10.1007/s00382-016-3372-4
Scopus记录号: 2-s2.0-84990842093
论文题名: Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth
作者: Alessandri A. ; Catalano F. ; De Felice M. ; Van Den Hurk B. ; Doblas Reyes F. ; Boussetta S. ; Balsamo G. ; Miller P.A.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2017
卷: 49, 期: 4 起始页码: 1215
结束页码: 1237
语种: 英语
英文关键词: Climate prediction
; Climate simulation
; Earth system modeling
; Land-climate interactions
; Multi-scale prediction enhancement
; Vegetation dynamics
英文摘要: The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration. © 2016, The Author(s). 资助项目: FP7, Seventh Framework Programme
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/53133
Appears in Collections: 过去全球变化的重建
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作者单位: Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA), Bldg C59, Sp. 118 CR Casaccia, Via Anguillarese, 301, Santa Maria di Galeria, Rome, Italy; Royal Netherlands Meteorological Institute, De Bilt, Netherlands; Institut Català de Ciències del Clima (IC3), Barcelona, Spain; European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, United Kingdom; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS), Barcelona, Spain; Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Recommended Citation:
Alessandri A.,Catalano F.,De Felice M.,et al. Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth[J]. Climate Dynamics,2017-01-01,49(4)