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WEATHER AND CIRCULATION OF MARCH 1980

Record Precipitation in the South and Central High Plains

Robert E. Livezey

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Robert E. Livezey

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Robert E. Livezey

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Evaluation of general circulation model (GCM) experiments presents one of the most challenging statistical inference problems in the study of climate. The problem is similar and comparable in difficulty to that encountered in empirical studies of global climate, because the data sets take the form of small samples of large numbers of cross-correlated climate statistics. Thus, in the absence of detailed a priori hypotheses the ability to detect all but the strongest of climate signals is severely limited.

Most studies directed at this problem have followed the lead of Chervin and Schneider and have emphasized parametric techniques to solve the univariate or “local” significance problem. Hasslemann was apparently the first to point out in the context of GCM problems that 1) a collection of “local” tests has dubious value in the absence of a “global” test, and 2) a sensitive global test is difficult to construct with multivariate methods without drastic a priori reduction in test dimensionality. Hasslemann's parametric strategy has subsequently guided a number of workers. Recently, in the vein of Mielke et al., Livezey and Chen, and Preisendorfer and Barnett, among others, have presented permutation or Monte Carlo approaches. These nonparametric methods obviate the need for limiting the choice of test statistics to those with known distributions.

Examples are presented of the kinds of questions that GCM climate experiments address and how they have been answered, together with considerations on significance testing in future experiments. The principal goals of the narrative are to provide a comprehensive, critical overview of the topic for the nonspecialist, and a compact, discriminating guide to the subject's extensive literature for the GCM climate experimenter.

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WEATHER AND CIRCULATION OF MARCH 1981

Drought Worsens in the East and Northern Plains

Robert E. Livezey

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WEATHER AND CIRCULATION OF NOVEMBER 1981

Widespread Warmth with Storminess in the Far West

Robert E. Livezey

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WEATHER AND CIRCULATION OF NOVEMBER 1980

A Late Heat Wave and Hurricane and Early Snow

Robert E. Livezey

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Robert E. Livezey

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Robert R. Dickson and Robert E. Livezey

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It is known that the Southern Oscillation Index (SOI) and the mean sea surface temperature off the Peru Coast are highly coherent and that variations of the latter are dominated by infrequent warming episodes. The present study examines the relative contribution of these warming episodes to the covariance of statistically significant correlations between the fall SOI and winter mean 700 mb heights in the Northern Hemisphere. The degree of dominance of the warming episode years in this context is evaluated by Monte Carlo methods.

It was found that, for the 30-year period studied, data pairs following tropical east Pacific warming events contributed disproportionately to major correlation maxima in much of the Northern Hemisphere. Such covariance concentrations, however, were found to be fairly likely outcomes (probability > 9%) if groups of years are chosen at random from the appropriate covariance arrays. Thus, we conclude that the influence of the fall SOI upon the subsequent winter mean 700 mb height distribution is a rather pervasive one, not limited to tropical east Pacific warming situations.

In contrast to other areas, correlation maxima in the North American sector received disproportionately small covariance contributions from the warming episode years. In northwest Canada, the contribution of those years was small and opposite in sign to the total covariance.

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Edward A. O'Lenic and Robert E. Livezey

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The relationship between the existence of low-frequency 700 mb height anomalies in the initial conditions of NMC's MRF global spectral model and subsequent 5-, 7-, and 10-day forecasts of 700 mb height from 1982 to 1988 is explored. Low-frequency 700 mb flow regimes are specified in each of four two-month seasons by performing a rotated principal component analysis (RPCA) on 38 or 39 year time series of daily, low-pass filtered 700 mb height analyses. In a given season, the amplitude time series (ATS) for each mode is used to decide which MRF forecast error maps should be used in forming a composite map corresponding to either the “+” phase or the “−” phase of the given mode. Several methods, including Monte Carlo simulations, are used to evaluate the statistical significance of the composite maps.

Many modes, including the Pacific North American (PNA) mode in winter and the leading summer mode, are found to be related to either unusually strong or unusually weak systematic error signature. Two different modes, one in spring and one in autumn, corresponding to quasi-stationary patterns over the United States and the North Atlantic, respectively, are related to unusually strong forecast error signatures. A statistically significant number of such modes is found in each of the four seasons, with the number of such results being smallest in autumn, and 1argest in spring. The results also indicate that the MRF model response to the presence of low-frequency regimes in the initial conditions is such that composite error signatures have a component with opposite phase and amplitude for opposite phases of a given mode (linear response). The overall results demonstrate the feasibility of using this technique to identify mode-linked forecast error signatures, and provides a potential opportunity to correct forecasts in the MRF, and possibly in other models, by removing the appropriate systematic error signatures.

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Thomas M. Smith and Robert E. Livezey

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Specifications of 1- and 3-month mean Pacific–North America region 700-hPa heights and U.S. surface temperatures and precipitation, from global sea surface temperatures (SSTs) and the ensemble average output of multiple runs of a general circulation model with the same SSTs prescribed, were explored with canonical correlation analysis. In addition to considerable specification skill, the authors found that 1) systematic errors in SST-forced model variability had substantial linear parts, 2) use of both predictor fields usually enhanced specification performance for the U.S. fields over that for just one of the predictor fields, and 3) skillful specification and model correction of the heights and temperatures were also possible for nonactive or transitional El Niño–Southern Oscillation situations.

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