Ensemble post-processing methods are used in operational weather forecasting to form probability distributions that represent forecast uncertainty. Several such methods have been proposed in the literature, including logistic regression, ensemble dressing, Bayesian model averaging and non-homogeneous Gaussian regression. We conduct an imperfect model experiment with the Lorenz 1996 model to investigate the performance of these methods, especially when forecasting the occurrence of rare extreme events. We show how flexible bias-correction schemes can be incorporated into these post-processing methods, and that allowing the bias correction to depend on the ensemble mean can yield considerable improvements in skill when forecasting extreme events. In the Lorenz 1996 setting, we find that ensemble dressing, Bayesian model averaging and non-homogeneous Gaussian regression perform similarly, while logistic regression performs less well.

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Ensemble forecasts of weather and climate are subject to systematic biases in the ensemble mean and variance, leading to inaccurate estimates of the forecast mean and variance. To address these biases, ensemble forecasts are post-processed using statistical recalibration frameworks. These frameworks often specify parametric probability distributions for the verifying observations. A common choice is the normal distribution with mean and variance specified by linear functions of the ensemble mean and variance. The parameters of the recalibration framework are estimated from historical archives of forecasts and verifying observations. Often there are relatively few forecasts and observations available for parameter estimation, and so the fitted parameters are also subject to uncertainty. This artefact is usually ignored. This study reviews analytic results that account for parameter uncertainty in the widely used Model Output Statistics recalibration framework. The predictive bootstrap is used to approximate the parameter uncertainty by resampling in more general frameworks such as non-homogeneous Gaussian regression. Forecasts on daily, seasonal and annual time-scales are used to demonstrate that accounting for parameter uncertainty in the recalibrated predictive distributions leads to probability forecasts that are more skilful and reliable than those in which parameter uncertainty is ignored. The improvements are attributed to more reliable tail probabilities of the recalibrated forecast distributions.

339of the insurance department of the state, and the re-establishment of the metropolitan police system in Kansas City.Governor Stark, a Democrat, advocated and won through legislative action social security legislation, extending old age assistance, direct relief, and aid to dependent children ; expansion of the eleemosynary institutions ; improvement of the penal institutions ; slum clearance projects ; a state cancer clinic, the first of its kind in the United States ; and other reforms and developments. He organized the state, too, for defense at the approach of war.The documents here published are a bare introduction to an important administration. They are arranged chronologically in the several categories. Historians, reading this book, should remember that it is addressed primarily to social psychologists and sociologists, for whom presumably it will be of great interest as a treatise on methodological techniques. It is also necessary, in order to avoid hasty conclusions for which the authors would not be responsible, constantly to keep in mind that the army was primarily an instrument for fighting a war and only incidentally a sociological laboratory. The scientific care and thoroughness with which the authors discuss their data excite the greatest respect. They accompany their conclusions with the necessary reservations. They never pretend to prove too much. Indeed, to the layman they often seem to labor the obvious, and to give statistical proof for something already taken for granted by men with army experience. Occasionally they suggest an optimism as to what may be possible with improved techniques in social science which a skeptical historian may not share.It might be facetious but it would not be inaccurate to call this volume "Prolegomena for a History of Griping." It is a useful companion to The Procurement and Training of Ground Combat Troops recently published as part of The U. S. Army in World War II. Both discuss the problems and dilemmas attendant upon raising mass citizen armies in a democratic society; how to turn reluctant civilians into effective soldiers quickly, and particularly how to find leaders at the lower levels where the demands of combat are most pressing. If we are considering the history of military institutions at

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