Abstract: Multimodel combination is a pragmatic approach to estimating model uncertainties and to making climate projections more reliable. The simplest way of constructing a multimodel is to give one vote to each model (?equal ...

Abstract: The Brier skill score (BSS) and the ranked probability skill score (RPSS) are widely used measures to describe the quality of categorical probabilistic forecasts. They quantify the extent to which a forecast strategy ...

Abstract: This note describes how the widely used Brier and ranked probability skill scores (BSS and RPSS, respectively) can be correctly applied to quantify the potential skill of probabilistic multimodel ensemble forecasts. It ...

Abstract: Multimodel ensemble combination (MMEC) has become an accepted technique to improve probabilistic forecasts from short- to long-range time scales. MMEC techniques typically widen ensemble spread, thus improving the dispersion ...

Abstract: The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area ...

Abstract: Monthly forecasting bridges the gap between medium-range weather forecasting and seasonal predictions. While such forecasts in the prediction range of 1?4 weeks are vital to many applications in the context of weather and ...

Abstract: Current estimates of the European windstorm climate and their associated losses are often hampered by either relatively short, coarse resolution or inhomogeneous datasets. This study tries to overcome some of these ...

Abstract: Stratosphere?troposphere exchange (STE) is important for the chemical composition of both the stratosphere and troposphere. Modifications of STE in a changing climate may affect stratospheric ozone depletion and the oxidizing ...