DOI: 10.1002/2013GL058879
论文题名: Retrieval of tropical cyclone statistics with a high-resolution coupled model and data
作者: Zhang S. ; Zhao M. ; Lin S.-J. ; Yang X. ; Anderson W.
刊名: Geophysical Research Letters
ISSN: 0094-10456
EISSN: 1944-10187
出版年: 2014
卷: 41, 期: 2 起始页码: 652
结束页码: 660
语种: 英语
英文关键词: Climate Estimation
; Climate Prediction
; Tropical Cyclone Statistics Retrieval
Scopus关键词: Climatology
; Background flow
; Climate prediction
; Continuous interactions
; Coupled modeling
; High resolution
; High-resolution models
; Initial conditions
; Tropical cyclone
; Hurricanes
; climate modeling
; climate prediction
; data set
; numerical model
; resolution
; sea state
; tropical cyclone
英文摘要: When observations are assimilated into a high-resolution coupled model, a traditional scheme that preferably projects observations to correct large-scale background tends to filter out small-scale cyclones. Here we separately process the large-scale background and the small-scale perturbations with low-resolution observations for reconstructing historical cyclone statistics in a cyclone-permitting model. We show that by maintaining the interactions between small-scale perturbations and successively corrected large-scale background, a model can successfully retrieve the observed cyclone statistics that in return improve estimated ocean states. The improved ocean initial conditions together with the continuous interactions of cyclones and background flows are expected to reduce model forecast errors. Combined with convection-permitting cyclone initialization, the new high-resolution model initialization along with the progressively advanced coupled models should contribute significantly to the ongoing research on seamless weather-climate predictions. ©2014. The Authors. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892450928&doi=10.1002%2f2013GL058879&partnerID=40&md5=fa4ae686a226502d461c9488b01caf99
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/7720
Appears in Collections: 气候减缓与适应
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作者单位: GFDL/NOAA, Princeton, NJ, United States
Recommended Citation:
Zhang S.,Zhao M.,Lin S.-J.,et al. Retrieval of tropical cyclone statistics with a high-resolution coupled model and data[J]. Geophysical Research Letters,2014-01-01,41(2).