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Robert E. Dewar and James R. Wallis

Abstract

Interannual rainfall variability has important effects for the evolution of biotic and human communities. Historical records of monthly rainfall totals for 1492 stations within 30° of the equator were analyzed using the method of L-moments. The 0.1 quantile (QU10), or the proportion of mean annual rainfall expected in the driest year in 10, was selected as the measure of variability. A nonlinear regression was fit to the relationship between QU10 and mean annual rainfall, and regions were categorized into three classes on the basis of the residuals: the 25% with the most negative, the 25% with the most positive, and the middle 50%. Maps of the global and regional patterns of rainfall variability show marked geographical patterning of variability and identify areas where rainfall variability may be a particularly important environmental feature.

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Nathaniel B. Guttman, J. R. M. Hosking, and James R. Wallis

Abstract

Precipitation quantile values have been computed for 9 probabilities, 8 durations, 12 starting months, and 1 1 1 regions across the United States. L-moment methodology has been used for the calculations. Discussed are the rationale for selecting the Pearson type III (gamma) and Wakeby distributions, and the confidence that can be placed in the quantile values. Results show that distribution functions become more asymmetrical as the duration decreases, indicating that the median may be a better measure of central tendency than the mean. Portraying the quantile values as a percentage of the median value leads to smooth spatial fields.

Computation of quantile values was the first known large-scale application of L-moment methodology. In spite of the complexity of the techniques and the extensive use of personnel and computer resources, the results justify the procedures in terms of preparing easy to use probability statements that reflect underlying physical processes.

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Nathaniel B. Guttman, J. R. M. Hosking, and James R. Wallis

Extreme rainfall amounts that resulted in severe flooding during the spring and summer of 1993 along the Missouri and Mississippi Rivers are examined from a historical and probabilistic viewpoint. Long-term average precipitation amounts and the departures of the 1993 summer rainfall from these averages are presented. Also, climatic regionalization and precipitation probabilities developed for the National Drought Atlas using L-moment techniques have been applied to the drainage area that contributed to the flooding. The exceedance probabilities of monthly and multiple-month observed precipitation amounts have been calculated. The results show that the three-month period May–July experienced unusually heavy rainfall when compared to prior years, and that July was particularly wet. Recurrence intervals for the rainfall events vary widely depending on the specific time period and locality, but the observed precipitation was an extreme event.

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Dennis P. Lettenmaier, Eric F. Wood, and James R. Wallis

Abstract

Spatial patterns in trends of four monthly variables: average temperature, precipitation, streamflow, and average of the daily temperature range were examined for the continental United States for the period 1948–88. The data used are a subset of the Historical Climatology Network (1036 stations) and a stream gage network of 1009 stations. Trend significance was determined using the nonparametric seasonal Kendall's test on a monthly and annual basis, and a robust slope estimator was used for determination of trend magnitudes. A bivariate test was used for evaluation of relative changes in the variables, specifically, streamflow relative to precipitation, streamflow relative to temperature, and precipitation relative to temperature.

Strong trends were found in all of the variables at many more stations than would be expected due to chance. There is a strong spatial and seasonal structure in the trend results. For instance, although annual temperature increases were found at many stations, mostly in the North and West, there were almost as many downtrends, especially in the South and East. Among the most important trend patterns are (a) increases in March temperature at almost half of the stations; (b) increases in precipitation from September through December at as many as 25 percent of the stations, mostly in the central part of the country; (c) strong increases in streamflow in the period November–April at a maximum of almost half of the stations, with the largest trend magnitudes in the north-central states; (d) changes in the temperature range (mostly downward) at a large number of stations beginning in late spring and continuing through winter, affecting as many as over half of the stations. The observed trends in streamflow are not entirely consistent with the changes in the climatic variables and may be due to a combination of climatic and water management effects.

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