The development of NWP models with grid spacing down to ∼1 km should produce more realistic forecasts of convective storms. However, greater realism does not necessarily mean more accurate precipitation forecasts. The rapid growth of errors on small scales in conjunction with preexisting errors on larger scales may limit the usefulness of such models. The purpose of this paper is to examine whether improved model resolution alone is able to produce more skillful precipitation forecasts on useful scales, and how the skill varies with spatial scale. A verification method will be described in which skill is determined from a comparison of rainfall forecasts with radar using fractional coverage over different sized areas. The Met Office Unified Model was run with grid spacings of 12, 4, and 1 km for 10 days in which convection occurred during the summers of 2003 and 2004. All forecasts were run from 12-km initial states for a clean comparison. The results show that the 1-km model was the most skillful over all but the smallest scales (approximately <10–15 km). A measure of acceptable skill was defined; this was attained by the 1-km model at scales around 40–70 km, some 10–20 km less than that of the 12-km model. The biggest improvement occurred for heavier, more localized rain, despite it being more difficult to predict. The 4-km model did not improve much on the 12-km model because of the difficulties of representing convection at that resolution, which was accentuated by the spinup from 12-km fields.

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.

Convection-permitting models (CPMs) have provided weather forecasting centres with a step-change in capabilities for forecasting rainfall. They are now used operationally to forecast precipitation in many parts of the world, including the UK. CPMs are models in which the dynamics of atmospheric convection is treated with sufficient accuracy in order to make it viable to switch off convection parametrization. This review describes the current state-of-the-art in operational CPM-based numerical weather prediction (NWP), primarily within the UK, and the historical development of CPMs. The characteristics of CPM systems and forecasts are highlighted and placed in an international context to recognize similar trends and highlight some differences. It is shown that the realism of CPM-based forecasts can provide improved subjective guidance on convection, and, when measured on appropriate scales, can improve rainfall forecasting skill compared to coarser-resolution NWP. Data assimilation techniques used with operational CPMs are reviewed and given historical context. Examples of new types of observations that may increase the skill of forecasts from improved initial conditions are discussed. CPM-based nowcasting systems are shown to provide considerable improvements in short-range forecasts of rapidly developing, intense systems. As a result, these CPM-based systems provide a new forecasting capability. Finally, the development of CPMs has also required new techniques to verify forecasts and define their skill. These have revealed that the lack of predictability of the smallest scales involving convection means that ensemble techniques are required to represent forecast uncertainty, resulting in a new capability to provide objective forecast probabilities of local precipitation.

Abstract. In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against, and it is the intention that from this point forward significant changes to the system will be documented in the literature. This reproduces the process used for global configurations of the UM, which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented, and where appropriate we define how the model configuration relates to the corresponding configuration of the global forecasting model.

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.

High-resolution NWP models which can explicitly allow convection (albeit poorly resolved) are usually run in limited-area domains, and are nested inside coarser resolution models with parametrized convection. The mismatch of the grids and model physics at the boundaries of the limited-area fine resolution model can be a major source of model error. Two major issues are the change in the representation of convection (parameterized to explicit) as air enters the fine resolution model and the limited boundary updating frequency. In this paper, a variable-grid, fine-resolution, limited-area version of the Met Office's Unified Model (UM), developed with the aim of addressing this and related problems with nested models is described. In this variable resolution model, the grid size varies smoothly from coarser (but still convection permitting) resolution at the outer boundaries to a uniform fine resolution in the interior of the domain. In this paper we present results from a comparison of this variable grid model with the analogous results from an equivalent nested model set with uniform high-resolution model nested inside a lower resolution one. The comparison is carried out for a number of convective cases. It is found that the variable resolution model gives very similar results to the nested model system in the inner fixed resolution part of the domain away from the boundaries, both in individual case studies and when statistics are aggregated over cases. This gives confidence in the validity of the variable resolution approach. It is shown that the variable resolution model also gives the hoped for benefits of reducing artefacts at the boundaries.

Abstract. In this paper we define the first "Regional Atmosphere and Land" (RAL) science configuration for kilometre scale modelling using the UM and JULES. "RAL1" defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against and it is the intention that from this point forward significant changes to the system will be documented in literature. This is reproducing the process used for global configurations of the UM which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented and where appropriate, we define how the model configuration relates to the corresponding configuration of the global forecasting model.

To study why, where, and when deep convection