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Downscaling of climate model output for Alaskan stakeholders.

Authors :
Walsh, John E.
Bhatt, Uma S.
Littell, Jeremy S.
Leonawicz, Matthew
Lindgren, Michael
Kurkowski, Thomas A.
Bieniek, Peter A.
Thoman, Richard
Gray, Stephen
Rupp, T. Scott
Source :
Environmental Modelling & Software. Dec2018, Vol. 110, p38-51. 14p.
Publication Year :
2018

Abstract

Abstract The paper summarizes an end-to-end activity connecting the global climate modeling enterprise with users of climate information in Alaska. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent bias-adjustment, and the provision of products to a range of users through visualization software that empowers users to explore the downscaled output and its sensitivities. An additional software tool enables users to examine skill metrics and relative rankings of 21 global models for Alaska and six other domains in the Northern Hemisphere. The downscaled temperatures and precipitation are made available as calendar-month decadal means under three different greenhouse forcing scenarios through 2100 for more than 4000 communities in Alaska and western Canada. The visualization package displays the uncertainties inherent in the multi-model ensemble projections. These uncertainties are often larger than the projected changes. Highlights • Downscaled climate data for more than 4000 communities are viewable by users. • A software tool allows users to evaluate skill 22 climate models for eight regions. • Across-model uncertainties often exceed changes of temperature and precipitation. • Projected warming and wetting are largest in winter and summer, respectively. • Emission scenario is a key determinant of future warming of Arctic communities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13648152
Volume :
110
Database :
Academic Search Index
Journal :
Environmental Modelling & Software
Publication Type :
Academic Journal
Accession number :
133168569
Full Text :
https://doi.org/10.1016/j.envsoft.2018.03.021