Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

A convection-permitting multiyear regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM (CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, nested within a global atmospheric model driven by observations at the sea surface, which does include a convection scheme. An additional regional simulation, with identical resolution and physical parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa, giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent.

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0: the latest science configurations of the Met Office Unified Model and JULES land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model’s physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe Global Atmosphere 6.1 and Global Land 6.1, which include a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global NWP, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

In this article we show that entrainment during the developing stages of deep convection over land is much higher than convection at equilibrium. A series of idealised cloud-resolving model simulations are performed for a range of environmental conditions, and these show that the interaction with the environment via the entrainment and detrainment rates gradually decreases as the day progresses, reverting to the values found at equilibrium. The entrainment and detrainment rates are themselves found to depend on the environmental humidity and stability, and are also strongly linked to cloud size, suggesting that the representation of the horizontal growth of clouds in convective parametrizations is important for the representation of the diurnal cycle. We propose a simple new entrainment and detrainment formulation to take account of these findings, and show that this

The Met Office single-column model is used to examine the development phase of the diurnal cycle of tropical convection over land by comparing against previous results from an idealized cloud-resolving model study. Changing the deep convective parametrization over land to make the entrainment vary with the height of the lifting condensation level reduces the depth of the convection early in the day. The changes made to improve the early phase of diurnal cycle over land are tested in an atmosphere-only version of the Met Office Hadley Centre climate model and result in an improvement in the amplitude and timing of the diurnal peak in precipitation over land.

Climate projections at very high resolution (kilometre-scale grid spacing) are becoming affordable. These ‘convection-permitting’ models (CPMs), commonly used for weather forecasting, better represent land-surface characteristics and small-scale processes in the atmosphere such as convection. They provide a step change in our understanding of future changes at local scales and for extreme weather events. For short-duration precipitation extremes, this includes capturing local storm feedbacks, which may modify future increases. Despite the major advance CPMs offer, there are still key challenges and outstanding science issues. Heavy rainfall tends to be too intense; there are challenges in representing land-surface processes; sub-kilometre scale processes still need to be parametrized, with existing parametrization schemes often requiring development for use in CPMs; CPMs rely on the quality of lateral boundary forcing and typically do not include ocean-coupling; large CPM ensembles that comprehensively sample future uncertainties are costly. Significant progress is expected over the next few years: scale-aware schemes may improve the representation of unresolved convective updrafts; work is underway to improve the modelling of complex land-surface fluxes; CPM ensemble experiments are underway and methods to synthesize this information with larger coarser-resolution model ensembles will lead to local-scale predictions with more comprehensive uncertainty context for user application. Large-domain (continental or tropics-wide) CPM climate simulations, potentially with additional earth-system processes such as ocean and wave coupling and terrestrial hydrology, are an exciting prospect, allowing not just improved representation of local processes but also of remote teleconnections. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Year‐to‐year variability in Northern European summer rainfall has profound societal and economic impacts; however, current seasonal forecast systems show no significant forecast skill. Here we show that skillful predictions are possible (r ~0.5, p < 0.001) using the latest high‐resolution Met Office near‐term prediction system over 1960–2017. The model predictions capture both low‐frequency changes (e.g., wet summers 2007–2012) and some of the large individual events (e.g., dry summer 1976). Skill is linked to predictable North Atlantic sea surface temperature variability changing the supply of water vapor into Northern Europe and so modulating convective rainfall. However, dynamical circulation variability is not well predicted in general—although some interannual skill is found. Due to the weak amplitude of the forced model signal (likely caused by missing or weak model responses), very large ensembles (>80 members) are required for skillful predictions. This work is promising for the development of European summer rainfall climate services.

SUMMARYA cloud-resolving model is used to investigate the impact of spatial variability in moisture and temperature on the timing of deep convection over land. Using a simulation of a diurnal cycle of convection, horizontal variations in moisture and temperature are shown to have a significant impact on the development of convection. The onset of deep convection can change by several hours and total rainfall amounts can change by up to 70%.Further sensitivity studies are carried out to investigate the impacts of vertical location, horizontal scale and magnitude of the variability. It is shown that variability of relative humidity in the boundary layer has the most significant impact and this is linked to its strong influence on local convective inhibition. Horizontal scales larger than 10 km are shown to have the strongest influence on the timing of convection, and the strongest amplitude of convectively generated fluctuations is shown to be on these larger scales.