Editorial Type:
Article
Article Type:
Research Article

Using a Global Soil Wetness Dataset to Improve Seasonal Climate Simulation

Paul A. Dirmeyer Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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Print Publication:
15 Aug 2000
DOI:
https://doi.org/10.1175/1520-0442(2000)013<2900:UAGSWD>2.0.CO;2
Page(s):
2900–2922
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Abstract

Ensembles of boreal summer coupled land–atmosphere climate model integrations for 1987 and 1988 are conducted with and without interactive soil moisture to evaluate the degree of climate drift in the coupled land–atmosphere model system, and to gauge the quality of the specified soil moisture dataset from the Global Soil Wetness Project (GSWP). Use of specified GSWP soil moisture leads to improved simulations of rainfall patterns, and significantly reduces root-mean-square errors in near-surface air temperature, indicating that the GSWP product is of useful quality and can also be used to supply initial conditions to fully coupled climate integrations. Integrations using specified soil moisture from the opposite year suggest that the interannual variability in the GSWP dataset is significant and contributes to the quality of the simulation of precipitation above what would be possible with only a mean annual cycle climatology of soil moisture. In particular, specification of soil wetness from the wrong year measurably degrades the correlation of simulated precipitation and temperature patterns compared to observed.

Corresponding author address: Dr. Paul A. Dirmeyer, Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705-31060.

Abstract

Ensembles of boreal summer coupled land–atmosphere climate model integrations for 1987 and 1988 are conducted with and without interactive soil moisture to evaluate the degree of climate drift in the coupled land–atmosphere model system, and to gauge the quality of the specified soil moisture dataset from the Global Soil Wetness Project (GSWP). Use of specified GSWP soil moisture leads to improved simulations of rainfall patterns, and significantly reduces root-mean-square errors in near-surface air temperature, indicating that the GSWP product is of useful quality and can also be used to supply initial conditions to fully coupled climate integrations. Integrations using specified soil moisture from the opposite year suggest that the interannual variability in the GSWP dataset is significant and contributes to the quality of the simulation of precipitation above what would be possible with only a mean annual cycle climatology of soil moisture. In particular, specification of soil wetness from the wrong year measurably degrades the correlation of simulated precipitation and temperature patterns compared to observed.

Corresponding author address: Dr. Paul A. Dirmeyer, Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705-31060.

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