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Climate Drift in a Coupled Land––Atmosphere Model

Climate Drift in a Coupled Land––Atmosphere Model A coupled land––atmosphere climate model is examined for evidence of climate drift in the land surface state variable of soil moisture. The drift is characterized as pathological error growth in two different ways. First is the systematic error that is evident over seasonal timescales, dominated by the error modes with the largest saturated amplitude: systematic drift. Second is the fast-growing modes that are present in the first few days after either initialization or a data assimilation increment: incremental drift. When the drifts are robust across many ensemble members and from year to year, they suggest a source of drift internal to the coupled system. This source may be due to problems in either component model or in the coupling between them. Evidence is presented for both systematic and incremental drift. The relationship between the two types of drift at any given point is shown to be an indication of the type and strength of feedbacks within the coupled system. Methods for elucidating potential sources of the drift are proposed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

Climate Drift in a Coupled Land––Atmosphere Model

Journal of Hydrometeorology , Volume 2 (1) – May 17, 2000

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References (25)

Publisher
American Meteorological Society
Copyright
Copyright © 2000 American Meteorological Society
ISSN
1525-7541
DOI
10.1175/1525-7541(2001)002<0089:CDIACL>2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

A coupled land––atmosphere climate model is examined for evidence of climate drift in the land surface state variable of soil moisture. The drift is characterized as pathological error growth in two different ways. First is the systematic error that is evident over seasonal timescales, dominated by the error modes with the largest saturated amplitude: systematic drift. Second is the fast-growing modes that are present in the first few days after either initialization or a data assimilation increment: incremental drift. When the drifts are robust across many ensemble members and from year to year, they suggest a source of drift internal to the coupled system. This source may be due to problems in either component model or in the coupling between them. Evidence is presented for both systematic and incremental drift. The relationship between the two types of drift at any given point is shown to be an indication of the type and strength of feedbacks within the coupled system. Methods for elucidating potential sources of the drift are proposed.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: May 17, 2000

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