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We investigate the sensitivity of modeled tropical precipitation accumulation, intensity and structures to the extent of convection‐permitting limited area model (LAM) domain size. Our comparison focusses on two LAM domains, with identical physical parameterization schemes and using 2.2 km grid spacing. One LAM domain spans almost the full tropical belt while the other focusses on southeast Asia. We show that the LAMs both capture the complex diurnal cycle of precipitation and that the timing and intensity of precipitation are comparable with satellite observations. Systematic differences between the LAMs are largest within ∼1,000 km of the western and eastern boundaries of the southeast Asia LAM. This is due to convective spin‐up at the western boundary of the southeast Asia LAM and a lack of propagating deep convection. We highlight that showing the added value of global storm‐resolving models by comparing with LAMs will help to accelerate their operational implementation. Plain Language Summary: Accurately capturing the location, timing and intensity of heavy tropical precipitation is key to providing early warnings of meteorological hazards that impact lives and livelihoods in the tropics. Here we investigate whether new high‐resolution weather forecast model simulations that almost fully span the tropics provide additional information (for precipitation), compared with smaller regional forecast models. We find that both versions of our model show similar intensity and timing of precipitation events in southeast Asia—and compare reasonably well with satellite derived observations. Differences between our simulations are largest close to the boundaries of the southeast Asia region, we explore and discuss the causes of these differences. We also discuss the need for more studies focusing on how new higher resolution global forecasts provide added value compared with current approaches to obtaining regional weather forecast information. Key Points: We compare precipitation in a limited area model (LAM) to a novel 2.2 km resolution Tropical Channel domain, focusing on southeast AsiaA LAM can adequately reproduce the precipitation characteristics of a Tropical wide simulation at 15% of the costFurther work within our model framework will investigate the upscale impacts of organized convection within the Tropical Channel [ABSTRACT FROM AUTHOR]

Numerical weather prediction (NWP) capabilities in the Maritime Continent are not as developed as in the midlatitudes. Countries in the region do not develop their own modelling systems; rather they adapt models primarily developed for the midlatitudes. Due to the complexity of processes involved in the region, this adaptation is non‐trivial. In this article the developments made by the Meteorological Service Singapore (MSS) and the United Kingdom Met Office (UKMO) to implement a convective‐scale NWP system for short‐range weather prediction for Singapore and the surrounding regions are presented. In particular, this article describes the changes to the initial model configuration, which was based on the UKMO's convective‐scale NWP system (the UKV), to produce operational forecasts over this region. Results presented here demonstrate the benefit of convection‐permitting simulations over convection parametrized simulations and show that the model performance is greatly affected by the choice of driving model, the cloud scheme, and the turbulence scheme. [ABSTRACT FROM AUTHOR]

The importance of probabilistic weather predictions and climate projections is growing. One of the key elements of the former is stochastic physics, schemes that perturb some uncertain processes in a general circulation model (GCM), such as physical parametrizations or diffusion. They help to increase the ensemble dispersion of ensemble prediction systems (EPS) and in some cases improve certain atmospheric processes by noise-induced drifts. We have developed a new configuration of stochastic physics schemes for the Met Office Unified Model (MetUM). It consists of an improved Stochastic Kinetic Energy Backscatter v2 (SKEB2), plus the Stochastic Perturbation of Tendencies (SPT). The improvements to SKEB2 remove spurious physical artefacts, e.g. a spurious wave caused by low-wave-number perturbations, and improve the resolution sensitivity of the scheme. The SPT produces a larger ensemble spread in the Tropics than present schemes, but its impact on long-term climate budgets makes the use of conservation constraints for water vapour and energy essential. The new configuration produces a higher impact in the Tropics, increasing the ensemble spread and improving some long-standing climate biases in areas of excessive convection, whilst minimizing the negative impact on tropical processes like tropical convective waves. [ABSTRACT FROM AUTHOR]

Stochastic physics is one of the preferred methods to represent model uncertainty in ensemble prediction systems of medium-range weather prediction and seasonal forecasting. These schemes increase the ensemble spread and improve probabilistic skill scores. However, little is known about how the stochastic perturbations interact with different atmospheric processes. In order to provide deeper insight into the impacts of stochastic physics on the representation of the atmosphere the stochastic kinetic energy backscatter (SKEB2) scheme has been used in the Met Office Unified Model (MetUM) across different time-scales. We use 'classic' verification techniques such as the Root Mean Error Square (RMSE) index in combination with novel 'object-oriented' verification metrics such as the Reading University Tracking system (RUTRACK) for extratropical cyclones. We find that the SKEB2 degrades the RMSE and Anomaly Correlation Coefficient (ACC) of individual short-range deterministic forecasts. On average the kinetic energy backscatter by the SKEB2 counteracts the excessive dissipation of extratropical cyclones, improving the model, but its forcing does not scale well across resolutions. Over the Tropics the SKEB2 improvements of the mean climatology and temporal variability are noteworthy, but driven by spurious Rossby waves. There are aspects of the SKEB2 that could be improved to create a more realistic stochastic representation of model uncertainty. [ABSTRACT FROM AUTHOR]