Global climate model performance over Alaska and Greenland

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Standard

Global climate model performance over Alaska and Greenland. / Walsh, John E.; Chapman, William L.; Romanovsky, Vladimir; Christensen, Jens H.; Stendel, Martin.

I: Journal of Climate, Bind 21, Nr. 23, 01.12.2008, s. 6156-6174.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Walsh, JE, Chapman, WL, Romanovsky, V, Christensen, JH & Stendel, M 2008, 'Global climate model performance over Alaska and Greenland', Journal of Climate, bind 21, nr. 23, s. 6156-6174. https://doi.org/10.1175/2008JCLI2163.1

APA

Walsh, J. E., Chapman, W. L., Romanovsky, V., Christensen, J. H., & Stendel, M. (2008). Global climate model performance over Alaska and Greenland. Journal of Climate, 21(23), 6156-6174. https://doi.org/10.1175/2008JCLI2163.1

Vancouver

Walsh JE, Chapman WL, Romanovsky V, Christensen JH, Stendel M. Global climate model performance over Alaska and Greenland. Journal of Climate. 2008 dec 1;21(23):6156-6174. https://doi.org/10.1175/2008JCLI2163.1

Author

Walsh, John E. ; Chapman, William L. ; Romanovsky, Vladimir ; Christensen, Jens H. ; Stendel, Martin. / Global climate model performance over Alaska and Greenland. I: Journal of Climate. 2008 ; Bind 21, Nr. 23. s. 6156-6174.

Bibtex

@article{fd771f4a122c433cb49fa466523c7a75,
title = "Global climate model performance over Alaska and Greenland",
abstract = "The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958-2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model's climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models' root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.",
author = "Walsh, {John E.} and Chapman, {William L.} and Vladimir Romanovsky and Christensen, {Jens H.} and Martin Stendel",
year = "2008",
month = dec,
day = "1",
doi = "10.1175/2008JCLI2163.1",
language = "English",
volume = "21",
pages = "6156--6174",
journal = "Journal of Climate",
issn = "0894-8755",
publisher = "American Meteorological Society",
number = "23",

}

RIS

TY - JOUR

T1 - Global climate model performance over Alaska and Greenland

AU - Walsh, John E.

AU - Chapman, William L.

AU - Romanovsky, Vladimir

AU - Christensen, Jens H.

AU - Stendel, Martin

PY - 2008/12/1

Y1 - 2008/12/1

N2 - The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958-2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model's climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models' root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

AB - The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958-2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model's climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models' root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

UR - http://www.scopus.com/inward/record.url?scp=60749122616&partnerID=8YFLogxK

U2 - 10.1175/2008JCLI2163.1

DO - 10.1175/2008JCLI2163.1

M3 - Journal article

AN - SCOPUS:60749122616

VL - 21

SP - 6156

EP - 6174

JO - Journal of Climate

JF - Journal of Climate

SN - 0894-8755

IS - 23

ER -

ID: 186941334