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When statistically postprocessing temperature forecasts, it is almost always assumed that the future temperature follows a Gaussian distribution conditional on the output of an ensemble prediction system. Recent studies, however, have demonstrated that it can at times be beneficial to employ alternative parametric families when postprocessing temperature forecasts that are either asymmetric or heavier-tailed than the normal distribution. In this article, we compare choices of the parametric distribution used within the ensemble model output statistics (EMOS) framework to statistically postprocess 2-m temperature forecast fields generated by the Met Office's regional, convection-permitting ensemble prediction system, MOGREPS-UK Specifically, we study the normal, logistic, and skew-logistic distributions. A flexible alternative is also introduced that first applies a Yeo–Johnson transformation to the temperature forecasts prior to postprocessing, so that they more readily conform to the assumptions made by established postprocessing methods. It is found that accounting for the skewness of temperature when postprocessing can enhance the performance of the resulting forecast field, particularly during summer and winter and in mountainous regions. [ABSTRACT FROM AUTHOR]

An objective verification system for the Met Office's 5‐day thunderstorm and cumulonimbus (CB) risk forecasts is described. The forecasts are designed specifically to forecast the impact of CB on aviation in the London Terminal Manoeuvring Area, known as the London TMA, and are produced by meteorologists at the Met Office. Challenges faced in developing the verification system resulting from the subjective nature of the forecasts themselves and the limitations of the data (from the UK Air Navigation Service Provider [UK ANSP]) available to assess the true impact on aviation are discussed. The forecasts include the likelihood of medium impact events as well as the likelihood of high impact events resulting from thunderstorms. A unique approach has been taken to verifying these forecasts which has involved working closely with the primary user, the UK ANSP. An objective verification system has been developed to assess the forecast accuracy across all lead times for high and medium impact events. This system provides the tools necessary for routine, year‐on‐year evaluation of the forecast performance. Verification of impact‐based forecasts is challenging and using traditional weather observations to verify the forecasts is not possible. The verification system developed to assess the performance of the Met Office's thunderstorm risk forecasts takes a unique approach to identifying observed medium impact and high impact convective events using data provided by the UK Air Navigation Service Provider to verify the 5‐day forecasts. Results from the 2014 and 2015 seasons of operation indicate that forecast performance is good. [ABSTRACT FROM AUTHOR]