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William H. Klein

Abstract

The “perfect prog” method of combining numerical and statistical weather prediction is applied to develop an automated system for forecasting the probability of precipitation at 108 cities on the mainland of the United States during daytime and nighttime periods from 12–60 hr in advance. Multiple regression equations are derived from a 4–5 year sample of data by seasons for each city by screening twice-daily geographical arrays of the following predictors: initial 850-mb height, initial 850–700 mb mean dew-point spread, and previous 12-hr precipitation at the network of surface stations. Each of the three predictor fields contributes about equally toward explaining the variance of the observed precipitation, but considerable geographical variation is exhibited by the equations. The forecast system is applied in an iterative fashion in 12-hr time steps by using as input numerical predictions of height and moisture at standard grid points as well as prior values of precipitation. The resulting computerized forecasts of precipitation probability, when applied on an operational basis in real time, may offer valuable guidance to the local weather forecaster.

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WILLIAM H. KLEIN

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William H. Klein

Abstract

The simultaneous relation between temperature and circulation during the winter season is studied by correlating anomalies of monthly mean surface temperature at 109 stations in the United States from 1948 through 1981 with monthly mean 700 mb height anomalies at a network of 133 grid points in North America and surrounding oceans. The data are screened by a stepwise forward selection procedure to yield multiple regression equations for specifying the monthly mean temperature anomaly at each city from the field of simultaneous 700 mb height plus the previous month's temperature anomaly.

Several sets of multiple regression equations are derived on a dependent sample of 90 winter months by using two different grids of heights and applying various cut-off criteria, such as the F-ratio, additional explained variance and number of variables, to terminate the selection of additional predictors. Optimum termination points are determined by testing 19 alternate criteria on independent data from 1978 to 1981 in terms of five different verification statistics. It is concluded that use of 8 variables in the multiple regression equations is optimum in this lest. The 8-variable cut-off performed better than climatology, persistence, an older set of equations derived by screening 5-day mean data, or equations based on empirical orthogonal functions.

By combining dependent and independent samples and by applying the best cut-off criteria plus synoptic experience, final specification equations are computed. These equations explain about three-fourths of the temperature variance by means of from 3 to 9 variables but with marked regional variation. They can readily give objective forecasts of the monthly mean surface temperature distribution over the United States by using any prognostic monthly mean 700 mb map as input. A short set of these equations, with about five terms per station, is currently being applied by the Climate Analysis Center of the National Weather Service on an operational basis.

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WILLIAM H. KLEIN

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WILLIAM H. KLEIN

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WILLIAM H. KLEIN

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THE WEATHER AND CIRCULATION OF JUNE 1957

Including an Analysis of Hurricane Audrey in Relation to the Mean Circulation

WILLIAM H. KLEIN

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WILLIAM H. KLEIN

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William H. Klein

Abstract

The mean spatial distributions of the one-day lag auto-correlation, the standard deviation of interdiurnal pressure change, and the standard deviation of daily pressure are analyzed on maps covering much of the northern hemisphere. Well-defined isopleth patterns, which vary only slightly with season and elevation, are obtained. Although these isopleths are primarily zonal in orientation, they indicate two hemispheric centers of maximum pressure variability associated with the Icelandic and Aleutian lows, and a secondary center near Novaya Zemlya. It is found that the centers of extreme values for each of the three statistics at sea level lie along the principal cyclone track, with the minimum auto-correlation near the Great Lakes, the maximum interdiurnal pressure change in Labrador, and the maximum standard deviation of pressure in the Icelandic area. It is also pointed out that pressure variability in eastern North America generally exceeds that in both Europe and eastern Asia. Vertical cross sections are constructed for the North American region and reveal a level of maximum pressure variability around 500 mb and a level of minimum variability around 700 mb. They also show that pressure variability is least at sea level in low latitudes and around the 100-mb level in high latitudes. This implies that higher-level maps are of special importance in forecasting tropical weather.

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William H. Klein

Abstract

An objective method of forecasting surface temperature at 39 cities in the United States for 1, 2 and 3 days in advance has been developed and tested under operational conditions. This method utilizes daily input to multiple regression equations derived previously for predicting 5-day mean temperature from fields of 700-mb height and surface temperature. Comparative verification shows that the objective method produces forecasts which approximate the skill of subjective predictions made by experienced meteorologists.

Recent experiments are described which indicate that improved forecasts result when 700–1000 mb thickness is included as a predictor. The beneficial synoptic climatology which accrues from these studies is also illustrated.

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