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Robert E. Livezey and Thomas M. Smith

Abstract

Rotated canonical correlation analysis between seasonal- and longer-mean global SSTs and either U.S. surface temperatures or 700-hPa heights in the Pacific–North America region have led to decompositions into three distinct signals. One of these represents the interannual variability of ENSO and a second is related to the North Atlantic oscillation and exhibits considerable variability on interdecadal timescales. In contrast the temporal behavior of the third, which is referred to here as the global signal, is mostly characterized by a steady trend since the late 1960s. The robustness of this time series to variations in the analyses, as well as the robustness of the spatial structure of the SST pattern accompanying it, suggests that the decomposition represents a successful separation of the climate signal from the climate noise. When viewed in the context of other recent work, the global signal cannot be discounted as a “fingerprint” of global warming. Finally, calculations that exploit ensemble mean output from prescribed-SST GCM runs reveal notable systematic errors in the simulation of the features of all three signals.

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Robert E. Livezey and Thomas M. Smith

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Anthony G. Barnston and Robert E. Livezey

Abstract

A recently discovered association between the 11-year solar cycle and the Northern Hemispheric low-frequency atmospheric circulation structure, which is most easily delectable when the two phases of the Quasi-biennial Oscillation (QBO) are considered individually, is described and subjected to global statistical significance tests.

Highly significant relationships are found during the January–February period. This is especially true for the west QBO phase, in which the solar flux is positively correlated with 700 mb heights and surface temperatures over central and northern Canada, and negatively correlated with heights in the western Atlantic along 30°N and with temperature in the southern and much of the eastern portions of the United States. The pattern of the flux-height correlation field resembles primarily the Tropical/Northern Hemisphere (TNH) long-wave circulation pattern and secondarily the North Atlantic Oscillation (NAO) pattern. For east QBO phase years a different structure is found, and for all years pooled a weaker but quite Characterizable pattern emerges.

January–February correlations are studied for sensitivity to lead time in the QBO phase definition and for shorter period means for the west QBO phase. The latter inquiry reveals a concentration of the west phase relationship during the latter half of January.

The climate of the October–November period also appears to participate, to a lesser but significant degree, in a solar–QBO relationship for west phase QBO years.

For the west QBO phase, the January–February solar flux versus 700 mb height (and United States–Canada surface temperature) correlation pattern contains sufficient amplitude and field significance to be exploited for operational forecasting purposes at the Climate Analysis Center. However, in the absence of a verifiable physical basis of the solar–QBO–atmosphere association, and because the 45 mb stratospheric winds were selected to characterize the QBO in an a posteriors manner, the relationships are accepted with caution and will be regularly reevaluated.

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Thomas M. Smith and Robert E. Livezey

Abstract

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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Anthony G. Barnston and Robert E. Livezey

Abstract

An expanded version of the multifield analog prediction system developed by Barnett and Preisendorfer (1978) was described and applied to the winter season in Part I of this two-part series (Livezey and Barnston 1988). This second part reviews briefly the major design features detailed in Part I, and then describes the predictive skills in spring, summer, fall and all other intermediate 3-month seasons.

In none of the 11 nonwinter seasons is the United States surface temperature predicted with as much skill as in winter. The major winter skill peak (16%) extends partially into the following two seasons (January–February–March and February–March–April), and a secondary maximum in summer (13%) similarly includes the two following seasons (July–August–September and August–September–October). In both skillful periods of the year the skill tends to be greatest over the eastern third of the United States and the immediate Pacific Coast and lowest over the Rockies and Plateau. More predictor variables are used as criteria for analog selection during the skillful times of the year, while fewer are found to contribute to skill levels at other times. The annual cycle of skill of simple persistence forecasts has its primary maximum in August–September–October, when it slightly exceeds the skill of the analog method, and a secondary maximum in winter when it is outperformed by the analog method by a substantial margin. The analog-forecasted temperature patterns are found to be statistically largely independent of the temperature patterns of persistence forecasts at all times of the year.

In an exercise aimed at determining which part of the predicted period within the season is most skilfully forecast, it is found that from fall through winter the later month(s) of the season are better predicted than the earlier months, suggesting a potential for useful long-lead forecasting of subseasonal periods in much of the coldest part of the year.

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Anthony G. Barnston and Robert E. Livezey

Abstract

The association between the 11-year solar cycle and the tropospheric Northern Hemisphere climate in January-February for the 21 west QBO phase years in the 1951–88 period failed strongly in 1989. This failure is explained in part by the high Southern Oscillation (SO) episode of 1988/89, whose influence on the climate conflicted with that hypothesized from the solar flux/QBO in much of North America. The occurrence of high flux during the west QBO phase along with a high SO (i.e., mid tropical Pacific SST event) was unprecedented before 1989. Bivariate multiple linear regression is used to predict Northern Hemisphere 700 mb heights and United States surface temperatures on the basis of the solar flux and the SO for each QBO phase. Exploratory analyses are carried out to describe more generally the associations among flux, QBO, SO, and the climate.

Major findings are: 1) Interactions among the four phenomena include primarily the SO-climate and solar flux-climate relationships, with the QBO phase as a required stratifier for the latter. Within this stratified framework the solar flux and the SO are essentially independent influences on the tropospheric climate, but act with moderate strength in overlapping regions such that their effects may offset or enhance one another; and 2) the true strength and nature of the solar flux-QBO-climate association still has large uncertainty because of the small samples resulting from QBO stratification and sharing of predictive power with the SO.

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Thomas M. Smith, Robert E. Livezey, and Samuel S. Shen

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An improved method for interpolating sparsely sampled climatological data onto a regular grid is shown. The method uses the spatial and temporal covariance of the field, along with the sparse data, to fill the full grid. This improves on similar methods that have recently been developed by eliminating the development of features that are not sufficiently supported by the data (i.e., overfitting). Statistical tests are used to tune the method to represent as much variability as the spatial–temporal information will support without overfitting. The method is further improved by a data-checking procedure that detects and removes suspect data. The method is developed and evaluated by interpolating tropical Pacific sea surface temperature (SST) monthly anomalies to a regular grid for the 1856–1995 period. Ship data averaged to 5° squares are used as input and are interpolated to a complete 1° grid. Comparing the results to interpolations using other methods shows this method’s quantitative improvements where satellite data are available for validation. Comparisons in the presatellite era show sharper and stronger anomaly patterns with this method, compared to another method developed for use with sparse data. Also shown are several periods when data are so sparse that only very weak SST anomalies may be reliably reconstructed in the tropical Pacific (i.e., before 1870 and 1915–25). In future research, the global SST and possibly other climatological fields will be gridded using improved methods.

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Anthony G. Barnston, Robert E. Livezey, and Michael S. Halpert

Abstract

A possible relationship between the phase of the Quasi-Biennial Oscillation (QBO) and the effect of the Southern Oscillation (SO) on the January-February climate in the Northern Hemisphere is examined. Findings suggest a preference for the tropical/Northern Hemisphere (TNH) circulation pattern in response to anomalies in the SO in east QBO phase years, and for the Pacific/North American (PNA) pattern in west QBO phase years. This extends previous findings relating the strength of the TNH pattern to tropical Pacific sea surface temperature during ENSO episodes.

This differentiation has fairly clear-cut implications for the January-February United States surface temperature anomaly pattern when a low (high) SO episode is in progress. The TNH emphasizes warmth (cold) in the Great Lakes/western Midwest; whereas the PNA induces a generally higher amplitude pattern, emphasizing cold (warmth) in the Southeast and warmth (cold) in the western third of the country. The SO-climate relationships appear approximately linear for each of the two QBO phases. A hypothetical physical mechanism through which this process might operate is briefly mentioned.

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John E. Janowiak, Arnold Gruber, C. R. Kondragunta, Robert E. Livezey, and George J. Huffman

Abstract

The Global Precipitation Climatology Project (GPCP) has released monthly mean estimates of precipitation that comprise gauge observations and satellite-derived precipitation estimates. Estimates of standard random error for each month at each grid location are also provided in this data release. One of the primary intended uses of this dataset is the validation of climatic-scale precipitation fields that are produced by numerical models. Nearly coincident with this dataset development, the National Centers for Environmental Prediction and the National Center for Atmospheric Research have joined in a cooperative effort to reanalyze meteorological fields from the present back to the 1940s using a fixed state-of-the-art data assimilation system and large input database.

In this paper, monthly accumulations of reanalysis precipitation are compared with the GPCP combined rain gauge–satellite dataset over the period 1988–95. A unique feature of this comparison is the use of standard error estimates that are contained in the GPCP combined dataset. These errors are incorporated into the comparison to provide more realistic assessments of the reanalysis model performance than could be attained by using only the mean fields. Variability on timescales from intraseasonal to interannual are examined between the GPCP and reanalysis precipitation. While the representation of large-scale features compares well between the two datasets, substantial differences are observed on regional scales. This result is not unexpected since present-day data assimilation systems are not designed to incorporate observations of precipitation. Furthermore, inferences of deficiencies in the reanalysis precipitation should not be projected to other fields in which observations have been assimilated directly into the reanalysis model.

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Robert E. Livezey, Michiko Masutani, Ants Leetmaa, Hualan Rui, Ming Ji, and Arun Kumar

Abstract

A prominent year-round ensemble response to a global sea surface temperature (SST) anomaly field fixed to that for January 1992 (near the peak of a major warm El Niño–Southern Oscillation episode) was observed in a 20-yr integration of the general circulation model used for operational seasonal prediction by the U.S. National Weather Service. This motivated a detailed observational reassessment of the teleconnections between strong SST anomalies in the central equatorial Pacific Ocean and Pacific–North America region 700-hPa heights and U.S. surface temperatures and precipitation. The approach used consisted of formation of monthly mean composites formed separately from cases in which the SST anomaly in a key area of the central equatorial Pacific Ocean was either large and positive or large and negative. Extensive permutation tests were conducted to test null hypotheses of no signal in these composites. The results provided a substantial case for the presence of teleconnections to either the positive- or negative-SST anomalies in every month of the year. These signals were seasonally varying (sometimes with substantial month to month changes) and, when present for both SST-anomaly signs in a particular month, usually were not similarly phased patterns of opposite polarity (i.e., the SST–teleconnected variable relationships were most often nonlinear).

A suite of 13 45-yr integrations of the same model described above was run with global SST analyses reconstructed from the observational record. Corresponding composites from the model were formed and compared visually and quantitatively with the high-confidence observational signals. The quantitative comparisons included skill analyses utilizing a decomposition that relates the squared differences between two maps to phase correspondence and amplitude and bias error terms and analyses of the variance about composite means. For the latter, in the case of the model runs it was possible to estimate the portions of this variance attributable to case to case variation in SSTs and to internal variability. Comparisons to monthly mean maps and analyses of variance for the 20-yr run with SSTs fixed to January 1992 values were also made.

The visual and quantitative comparisons all revealed different aspects of prominent model systematic errors that have important implications for the optimum exploitation of the model for use in prediction. One of these implications was that the current model’s ensemble responses to SST forcing will not be optimally useful until after nonlinear correction of SST-field-dependent systematic errors.

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