DOI: 10.1175/JCLI-D-13-00684.1
Scopus记录号: 2-s2.0-84908438141
论文题名: Contribution of dynamic vegetation phenology to decadal climate predictability
作者: Weiss M. ; Miller P.A. ; van den Hurk B.J.J.M. ; van Noije T. ; Ştefănescu S. ; Haarsma R. ; van Ulft L.H. ; Hazeleger W. ; Le Sager P. ; Smith B. ; Schurgers G.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 22 起始页码: 8563
结束页码: 8577
语种: 英语
Scopus关键词: Atmospheric temperature
; Budget control
; Climatology
; Computer simulation
; Earth atmosphere
; Evaporative cooling systems
; Sea ice
; Soil moisture
; Vegetation
; Water treatment
; Atmosphere-land interactions
; Climate prediction
; Climate variability
; Forecast verification/skill
; Surface temperatures
; Forecasting
; atmosphere-biosphere interaction
; atmosphere-ocean coupling
; climate prediction
; climate variation
; leaf area index
; surface temperature
; vegetation cover
; weather forecasting
英文摘要: In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere-land-ocean-sea ice model, the European Consortium Earth System Model (EC-Earth). Similar to the impact of initializing the model with the observed oceanic state, initializing the leaf area index (LAI) fields obtained from an offline LPJ-GUESS simulation forced by the observed atmospheric state leads to a systematic drift.A different treatment of the water and soil moisture budget in LPJ-GUESS is a likely cause of this drift. The coupled system reduces the cold bias of the reference model over land by reducing LAI (and the associated evaporative cooling), particularly outside the growing season. The coupling with the interactive vegetation module implies more degrees of freedom in the coupled model, which generates more noise that can mask a portion of the extra signal that is generated. The forecast reliability improves marginally, particularly early in the forecast. Ranked probability skill scores are also improved slightly in most areas analyzed, but the signal is not fully coherent over the forecast interval because of the relatively low number of ensemble members. Methods to remove the LAI drift and allow coupling of other variables probably need to be implemented before significant forecast skill can be expected. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51356
Appears in Collections: 气候变化事实与影响
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作者单位: Royal Netherlands Meteorological Institute, De Bilt, Netherlands; Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden; ECMWF, Reading, United Kingdom; Wageningen University, Wageningen, Netherlands
Recommended Citation:
Weiss M.,Miller P.A.,van den Hurk B.J.J.M.,et al. Contribution of dynamic vegetation phenology to decadal climate predictability[J]. Journal of Climate,2014-01-01,27(22)