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Rudolph W. Preisendorfer
and
Tim P. Barnett

Abstract

When a numerical model's representation of a physical field is to be compared with a corresponding real observed field, it is usually the case that the numbers of realizations of model and observed field are relatively small, so that the natural procedure of producing histograms of pertinent statistics of the fields (e.g., means, variances) from the data sets themselves cannot be usually carried out. Also, it is not always safe to adopt assumptions of normality and independence of the data values. This prevents the confident use of classical statistical methods to make significance statements about the success or failure of the model's replication of the data. Here we suggest two techniques of determinable statistical power, in which small samples of spatially extensive physical fields can be made to blossom into workably large samples on which significance decisions can be based. We also introduce some new measures of location, spread and shape of multivariate data sets which may be used in conjunction with the two techniques. The result is a pair of new data intercomparison procedures which we illustrate using GCM simulations of the January sea-level pressure field and regional ocean model simulations of the new-shore velocity field of South America. We include with these procedures a method of determining the spatial and temporal locations of non-random errors between the model and data fields so that models can be improved accordingly.

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Nicholas E. Graham
,
Tim P. Barnett
,
Robert M. Chervin
,
Michael E. Schlesinger
, and
Ulrich Schlese

Abstract

Many of the processes that have important effects on both the climatological distribution and interannual variability of sea surface temperatures (SSTs) in the tropical oceans are greatly affected by the surface wind field. For this reason accurate simulation of the surface wind is a key factor governing the success of coupled tropical ocean-atmosphere models. This paper presents the results of two analyses that investigate the quality of wind fields produced by three general circulation models (GCMs) over the tropical Indian and Pacific oceans.

The first analysis concerns the annual cycles of the tropical wind fields simulated by versions of the GCM at the Oregon State University (OSU), European Centre for Medium Range Forecasts (ECMWF), and National Center for Atmospheric Research (NCAR). These models have similar horizontal resolutions but vary widely in vertical resolution. The results show that although there are substantial differences in model performance, apparently related to differences in vertical resolution, there are also clear similarities in their behavior. Each GCM did best in major trade wind regions and somewhat poorly in convectively active areas with light winds. This finding suggests that the formulations governing the interactions between persistent convection and the circulation may limit model performance.

A second analysis examines the response of the NCAR GCM, in terms of tropical Pacific wind stress, to prescribed SST anomalies over the period 1961–1972. It was found that the model response to SST anomalies associated with the El Niño/Southern Oscillation(ENSO) was distinct and in some respects resembled that of the real atmosphere. However, there were important discrepancies in the spatial configuration of the GCM field and in the amplitude of response of the GCM to the SST anomalies. An analysis of these discrepancies suggests that while the trapped equatorial Kelvin wave response of an ocean model coupled to this GCM would be qualitatively correct, differences in the GCM and observed forcing fields would result in large errors away from the equator. Tests with the Florida State University model of the tropical Pacific, to be reported in a later paper, support this conclusion.

Taken together, these findings suggest that while GCMs are capable of reproducing correctly many features of the tropical surface wind fields, discrepancies remain with respect to both the annual cycle and the response to the anomalous SST patterns associated with ENSO. These discrepancies appear to be related, at least in part, to interactions between organized convection and the circulation. To what degree these differences would affect the oceanic component of a coupled model is currently under study.

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