With many operational centers moving toward order 1-km-gridlength models for routine weather forecasting, this paper presents a systematic investigation of the properties of high-resolution versions of the Met Office Unified Model for short-range forecasting of convective rainfall events. The authors describe a suite of configurations of the Met Office Unified Model running with grid lengths of 12, 4, and 1 km and analyze results from these models for a number of convective cases from the summers of 2003, 2004, and 2005. The analysis includes subjective evaluation of the rainfall fields and comparisons of rainfall amounts, initiation, cell statistics, and a scale-selective verification technique. It is shown that the 4-and 1-kmgridlength models often give more realistic-looking precipitation fields because convection is represented explicitly rather than parameterized. However, the 4-km model representation suffers from large convective cells and delayed initiation because the grid length is too long to correctly reproduce the convection explicitly. These problems are not as evident in the 1-km model, although it does suffer from too numerous small cells in some situations. Both the 4-and 1-km models suffer from poor representation at the start of the forecast in the period when the high-resolution detail is spinning up from the lower-resolution (12 km) starting data used. A scale-selective precipitation verification technique implies that for later times in the forecasts (after the spinup period) the 1-km model performs better than the 12-and 4-km models for lower rainfall thresholds. For higher thresholds the 4-km model scores almost as well as the 1-km model, and both do better than the 12-km model.

SUMMARYThis paper investigates daytime convective development over land and its representation in single-column models (SCMs) and cloud-resolving models (CRMs). A model intercomparison case is developed based on observations of the diurnal cycle and convection during the rainy season in Amazonia. The focus is on the 6 h period between sunrise and early afternoon which was identified in previous studies as critical for the diurnal cycle over summertime continents in numerical weather prediction and climate models. This period is characterized by the formation and growth of a well-mixed convective boundary layer from the early morning temperature and moisture profiles as the surface sensible-and latent-heat fluxes increase after sunrise. It proceeds with the formation of shallow convective clouds as the convective boundary layer deepens, and leads to the eventual transition from shallow to deep precipitating convection around local noon. To provide a benchmark for other models, a custom-designed set of simulations, applying increasing in time computational domain and decreasing spatial resolution, was executed. The SCMs reproduced the previously identified problem with premature development of deep convection, less than two hours after sunrise. The benchmark simulations suggest a possible route to improve SCMs by considering a time-evolving cumulus entrainment rate as convection evolves from shallow to deep and the cloud width increases up to an order of magnitude. The CRMs featuring horizontal grid length around 500 m are capable of capturing the qualitative aspects of the benchmark simulations, but there are significant differences among the models. Two-dimensional CRMs tend to simulate too rapid a transition from shallow to deep convection and too high a cloud cover.

This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.We perform simulations of several convective events over the southern UK with the Met Office Unified Model (UM) at horizontal grid lengths ranging from 1.5 km to 200 m. Comparing the simulated storms on these days with the Met Office rainfall radar network allows us to apply a statistical approach to evaluate the properties and evolution of the simulated storms over a range of conditions. Here we present results comparing the storm morphology in the model and reality which show that the simulated storms become smaller as grid length decreases and that the grid length that fits the observations best changes with the size of the observed cells. We investigate the sensitivity of storm morphology in the model to the mixing length used in the subgrid turbulence scheme. As the subgrid mixing length is decreased, the number of small storms with high area-averaged rain rates increases. We show that, by changing the mixing length, we can produce a lower-resolution simulation which produces similar morphologies to a higher-resolution simulation.

The 3D structures of over 1,000 convective storms observed by the Chilbolton radar are used to constrain storm dynamics and microphysics in models with resolutions between 100 and 1,500 m.

A set of high-resolution radar observations of convective storms has been collected to evaluate such storms in the Met Office Unified Model during the Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project. The 3-GHz Chilbolton Advanced Meteorological Radar was set up with a scan-scheduling algorithm to automatically track convective storms identified in real time from the operational rainfall radar network. More than 1000 storm observations gathered over 15 days in 2011 and 2012 are used to evaluate the model under various synoptic conditions supporting convection. In terms of the detailed three-dimensional morphology, storms in the 1500-m grid length simulations are shown to produce horizontal structures a factor of 1.5–2 wider compared to radar observations. A set of nested model runs at grid lengths down to 100 m show that the models converge in terms of storm width, but the storm structures in the simulations with the smallest grid lengths are too narrow and too intense compared to the radar observations. The modeled storms were surrounded by a region of drizzle without ice reflectivities above 0 dBZ aloft, which was related to the dominance of ice crystals and was improved by allowing only aggregates as an ice particle habit. Simulations with graupel outperformed the standard configuration for heavy-rain profiles, but the storm structures were a factor of 2 too wide and the convective cores 2 km too deep.

The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

We present a simple, physically consistent stochastic boundary layer scheme implemented in the Met Office’s Unified Model. It is expressed as temporally correlated multiplicative Poisson noise with a distribution that depends on physical scales. The distribution can be highly skewed at convection-permitting scales (horizontal grid lengths around 1 km) when temporal correlation is far more important than spatial. The scheme is evaluated using small ensemble forecasts of two case studies of severe convective storms over the UK. Perturbations are temporally correlated over an eddy-turnover timescale, and may be similar in magnitude to or larger than the mean boundary-layer forcing. However, their mean is zero and hence they, in practice, they have very little impact on the energetics of the forecast, so overall domain-averaged precipitation, for example, is essentially unchanged. Differences between ensemble members grow; after around 12 h they appear to be roughly saturated; this represents the time scale to achieve a balance between addition of new perturbations, perturbation growth and dissipation, not just saturation of initial perturbations. The scheme takes into account the area chosen to average over, and results are insensitive to this area at least where this remains within an order of magnitude of the grid scale.

This study presents an evaluation of the size and strength of convective updraughts in high‐resolution simulations by the UK Met Office Unified Model (UM). Updraught velocities have been estimated from range–height indicator (RHI) Doppler velocity measurements using the Chilbolton advanced meteorological radar, as part of the Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project. Based on mass continuity and the vertical integration of the observed radial convergence, vertical velocities tend to be underestimated for convective clouds due to the undetected cross‐radial convergence. Velocity fields from the UM at a resolution corresponding to the radar observations are used to scale such estimates to mitigate the inherent biases. The analysis of more than 100 observed and simulated storms indicates that the horizontal scale of updraughts in simulations tend to decrease with grid length; the 200 m grid length agreed most closely with the observations. Typical updraught mass fluxes in the 500 m grid length simulations were up to an order of magnitude greater than observed, and greater still in the 1.5 km grid length simulations. The effect of increasing the mixing length in the sub‐grid turbulence scheme depends on the grid length. For the 1.5 km simulations, updraughts were weakened though their horizontal scale remained largely unchanged. Progressively more so for the sub‐kilometre grid lengths, updraughts were broadened and intensified; horizontal scale was now determined by the mixing length rather than the grid length. In general, simulated updraughts were found to weaken too quickly with height. The findings were supported by the analysis of the widths of reflectivity patterns in both the simulations and observations.