A stochastic parameterization scheme for deep convection is described, suitable for use in both climate and NWP models. Theoretical arguments and the results of cloud-resolving models are discussed in order to motivate the form of the scheme. In the deterministic limit, it tends to a spectrum of entraining/detraining plumes and is similar to other current parameterizations. The stochastic variability describes the local fluctuations about a large-scale equilibrium state. Plumes are drawn at random from a probability distribution function (PDF) that defines the chance of finding a plume of given cloud-base mass flux within each model grid box. The normalization of the PDF is given by the ensemble-mean mass flux, and this is computed with a CAPE closure method. The characteristics of each plume produced are determined using an adaptation of the plume model from the Kain–Fritsch parameterization. Initial tests in the single-column version of the Unified Model verify that the scheme is effective in producing the desired distributions of convective variability without adversely affecting the mean state.

Recent increases in computing power mean that atmospheric models for numerical weather prediction are now able to operate at grid spacings of the order of a few hundred meters, comparable to the dominant turbulence length scales in the atmospheric boundary layer. As a result, models are starting to partially resolve the coherent overturning structures in the boundary layer. In this resolution regime, the so‐called boundary layer “gray zone,” neither the techniques of high‐resolution atmospheric modeling (a few tens of meters resolution) nor those of traditional meteorological models (a few kilometers resolution) are appropriate because fundamental assumptions behind the parameterizations are violated. Nonetheless, model simulations in this regime may remain highly useful. In this paper, a newly formed gray zone boundary layer community lays the basis for parameterizing gray zone turbulence, identifies the challenges in high‐resolution atmospheric modeling and presents different gray zone boundary layer models. We discuss both the successful applications and the limitations of current parameterization approaches, and consider various issues in extending promising research approaches into use for numerical weather prediction. The ultimate goal of the research is the development of unified boundary layer parameterizations valid across all scales.

The role of latent‐heat release in an explosively developing cyclone from the Fronts and Atlantic Storm‐Track Experiment is examined within the potential vorticity (PV) framework. Using conventional synoptic analysis, piecewise PV inversion and numerical simulations, the development is described in terms of an upper‐level PV (UPV) anomaly, a surface potential‐temperature anomaly and diabatically generated PV anomalies in the lower and upper troposphere. The relative contributions of each anomaly to the cyclogenesis are investigated, along with the interactions between anomalies.In contrast to previous case‐studies, the results of PV inversion and sensitivity tests reveal that the contribution from the surface thermal anomaly is much weaker than those associated with the upper‐level and diabatically generated PV anomalies. A low‐level PV (LPV) anomaly is generated rapidly in response to the UPV anomaly, and dominates the intensification of the system, but its associated circulation has only a modest feedback effect on the upper levels. However, diabatic reduction of PV in the upper troposphere is found to have important effects on the UPV anomaly. In particular, latent heating tends to destroy the UPV anomaly by inhibiting its downward penetration and reducing its horizontal extent. Copyright © 2004 Royal Meteorological Society

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.

A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, the authors have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. They have related these structures to storm life cycles derived by tracking features in the rainfall from the U.K. radar network and compared them statistically to storm structures in the Met Office model, which they ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. The authors also evaluated the scale and intensity of convective updrafts using a new radar technique. They find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms.