DOI: 10.1175/JCLI-D-16-0168.1
Scopus记录号: 2-s2.0-85012298723
论文题名: Incorporating snow albedo feedback into downscaled temperature and snow cover projections for California's Sierra Nevada
作者: Walton D.B. ; Hall A. ; Berg N. ; Schwartz M. ; Sun F.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期: 4 起始页码: 1417
结束页码: 1438
语种: 英语
Scopus关键词: Climate models
; Feedback
; Snow
; Solar radiation
; Statistics
; Temperature
; Water resources
; Anthropogenic climate changes
; Climate change projections
; Complex terrains
; Dynamical downscaling
; Regional model
; Snow covers
; Snow-albedo feedbacks
; Statistical downscaling
; Climate change
; air temperature
; albedo
; climate change
; climate feedback
; climate modeling
; global climate
; mountain
; regional climate
; snow cover
; California
; Sierra Nevada [California]
; United States
英文摘要: California's Sierra Nevada is a high-elevation mountain range with significant seasonal snow cover. Under anthropogenic climate change, amplification of the warming is expected to occur at elevations near snow margins due to snow albedo feedback. However, climate change projections for the Sierra Nevada made by global climate models (GCMs) and statistical downscaling methods miss this key process. Dynamical downscaling simulates the additional warming due to snow albedo feedback. Ideally, dynamical downscaling would be applied to a large ensemble of 30 or more GCMs to project ensemble-mean outcomes and intermodel spread, but this is far too computationally expensive. To approximate the results that would occur if the entire GCM ensemble were dynamically downscaled, a hybrid dynamical-statistical downscaling approach is used. First, dynamical downscaling is used to reconstruct the historical climate of the 1981-2000 period and then to project the future climate of the 2081-2100 period based on climate changes from five GCMs. Next, a statistical model is built to emulate the dynamically downscaled warming and snow cover changes for any GCM. This statistical model is used to produce warming and snow cover loss projections for all available CMIP5 GCMs. These projections incorporate snow albedo feedback, so they capture the local warming enhancement (up to 3°C) from snow cover loss that other statistical methods miss. Capturing these details may be important for accurately projecting impacts on surface hydrology, water resources, and ecosystems. © 2017 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49810
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, United States; Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, United States; Department of Geosciences, University of Missouri-Kansas City, Kansas City, MO, United States
Recommended Citation:
Walton D.B.,Hall A.,Berg N.,et al. Incorporating snow albedo feedback into downscaled temperature and snow cover projections for California's Sierra Nevada[J]. Journal of Climate,2017-01-01,30(4)