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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]

Changes in the North Atlantic Oscillation (NAO) heavily influence the weather across the UK and the rest of Europe. Due to an incorrect representation of the polar jet stream and its associated physical processes, it is reasonable to believe that errors in numerical weather prediction models may also depend on the prevailing behaviour of the NAO. To address this, information regarding the NAO is incorporated into statistical post-processing methods through a regime-dependent mixture model, which is then applied to wind speed forecasts from the Met Office’s global ensemble prediction system, MOGREPS-G. The mixture model offers substantial improvements upon conventional post-processing methods when the local wind speed depends strongly on the NAO, but the additional complexity of the model can hinder forecast performance otherwise. A measure of regime dependency is thus defined that can be used to differentiate between situations when the numerical model output is, and is not, expected to benefit from regime-dependent post-processing. Implementing the regime-dependent mixture model only when this measure exceeds a certain threshold is found to further improve predictive performance, while also producing more accurate forecasts of extreme wind speeds. [ABSTRACT FROM AUTHOR]

Neutron diffraction studies with hydrogen/deuterium isotope substitution measurements are performed to investigate the water structure at the early, medium, and late periods of methane clathrate hydrate formation and decomposition. These measurements are coupled with simultaneous gas consumption measurements to track the formation of methane hydrate from a gas/water mixture, and then the complete decomposition of hydrate. Empirical potential structure refinement computer simulations are used to analyze the neutron diffraction data and extract from the data the water structure in the bulk methane hydrate solution. The results highlight the significant changes in the water structure of the remaining liquid at various stages of hydrate formation and decomposition, and give further insight into the way in which hydrates form. The results also have important implications on the memory effect, suggesting that the water structure in the presence of hydrate crystallites is significantly different at equivalent stages of forming compared to decomposing. These results are in sharp contrast to the previously reported cases when all remaining hydrate crystallites are absent from the solution. For these systems there is no detectable change in the water structure or the methane hydration shell before hydrate formation and after decomposition. Based on the new results presented in this paper, it is clear that the local water structure is affected by the presence of hydrate crystallites, which may in turn be responsible for the “history” or “memory” effect where the production of hydrate from a solution of formed and then subsequently melted hydrate is reportedly much quicker than producing hydrate from a fresh water/gas mixture. [ABSTRACT FROM AUTHOR]

Neutron diffraction with H/D isotope substitution has been used to study the formation and decomposition of the methane clathrate hydrate. Using this atomistic technique coupled with simultaneous gas consumption measurements, we have successfully tracked the formation of the sI methane hydrate from a water/gas mixture and then the subsequent decomposition of the hydrate from initiation to completion. These studies demonstrate that the application of neutron diffraction with simultaneous gas consumption measurements provides a powerful method for studying the clathrate hydrate crystal growth and decomposition. We have also used neutron diffraction to examine the water structure before the hydrate growth and after the hydrate decomposition. From the neutron-scattering curves and the empirical potential structure refinement analysis of the data, we find that there is no significant difference between the structure of water before the hydrate formation and the structure of water after the hydrate decomposition. Nor is there any significant change to the methane hydration shell. These results are discussed in the context of widely held views on the existence of memory effects after the hydrate decomposition. [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]

ABSTRACT Turbulence is a major source of weather-related aviation incidents. There are many different indicators used to try and predict where turbulence is likely to occur. The indicators are derived from deterministic models although they are often quoted as probabilities. This paper proposes the use of ensemble forecasts from the Met Office Global and Regional Ensemble Prediction System ( MOGREPS) to produce a probabilistic indicator of wind shear and convectively induced moderate or greater turbulence. An objective verification scheme using high-resolution automated aircraft observations from the Global Aircraft Data Set is used to compare the skill with the routinely available World Area Forecast Centre gridded turbulence forecasts. The forecasts are assessed globally over a 12 month period from November 2010 to October 2011 looking at the skill, reliability and economic value of the forecasts. [ABSTRACT FROM AUTHOR]