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Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean–Atmosphere Model.

Authors :
Cocke, S.
LaRow, T. E.
Source :
Monthly Weather Review. Mar2000, Vol. 128 Issue 3, p689. 20p. 2 Graphs, 10 Maps.
Publication Year :
2000

Abstract

This paper describes a new climate model and its potential application to the study of ENSO impacts. The model is a regional spectral model embedded within a global coupled ocean–atmosphere model. The atmospheric part of the model consists of a global spectral model with triangular truncation T63 and a nested regional spectral model. The regional model is a relocatable spectral perturbation model that can be run at any horizontal resolution. In this paper the regional model was run with a resolution of 40 km. The global atmosphere model is coupled to the Max Planck global ocean model. No flux correction or anomaly coupling is used. An ensemble of 120-day integrations was conducted using the coupled nested system for the boreal winters of 1987 and 1988. A control integration was also performed in which observed SSTs were used in both the global and regional models. Two domains were chosen for the regional model: the southeast United States and western North America. Results from the global models show that the models reproduce many of the large-scale ENSO climate variations including the shifts in the Pacific ITCZ and SPCZ along with a Pacific–North America response in the 500-hPa height field. These results are compared against the corresponding ECMWF and Global Precipitation Climatology Centre analysis. Over the southeast United States both the global and regional models captured the precipitation variations between the two years as compared with the monthly mean cooperative station data. It is shown that the regional model solution is consistent with the global model solution, but with more realistic detail. Finally prospects for using this coupled nested ocean–atmosphere regional spectral model for downscaling are discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00270644
Volume :
128
Issue :
3
Database :
Academic Search Index
Journal :
Monthly Weather Review
Publication Type :
Academic Journal
Accession number :
6408413
Full Text :
https://doi.org/10.1175/1520-0493(2000)128<0689:SPUARS>2.0.CO;2