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We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica.

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 Asia A LAM can adequately reproduce the precipitation characteristics of a Tropical wide simulation at 15% of the cost Further work within our model framework will investigate the upscale impacts of organized convection within the Tropical Channel

The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. A key feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land-breeze density current, possibly reinforced by convective cold pools, at ∼3 m s −1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s −1 . They trigger isolated cells of convection, usually farther offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial preexisting perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.

Soil moisture (SM) affects weather through its impact on surface flux partitioning, influencing vertical atmospheric profiles and circulations driven by differential surface heating. In West Africa, observational studies point to a dominant negative SM‐precipitation feedback, where dry soils help to initiate and maintain convection. In this context, serious concerns exist about the ability of models with parameterised convection to simulate this observed sensitivity of daytime convection to SM. Here, we evaluate the effect of initial SM perturbations in a short‐range ensemble forecast over West Africa, comparing the UK Met Office Global and Regional Ensemble Prediction System (MOGREPS) with parameterised convection (GLOB‐ENS) to its regional convection‐permitting counterpart (CP‐ENS). Results from both models suggest SM perturbations introduce considerable spread into daytime evaporative fraction (EF) and near‐surface temperatures. This spread is still evident on Day 3 of the forecast. Both models also show a tendency to increased afternoon rainfall frequency over negative EF anomalies, reproducing the observed feedback. However, this effect is more pronounced in CP‐ENS than GLOB‐ENS, which illustrates the potential for process‐based forecast improvements at convection‐permitting scales. Finally, we identify persistent biases in rainfall caused by land cover mapping issues in the operational GLOB‐ENS setup, emphasising the need for careful evaluation of different mapping strategies for land cover. Daily accumulated precipitation (mm·day−1) in IMERG observations (a), and ensemble mean forecasts for GLOB‐ENS (b) and CP‐ENS (c) for 25th April 2019, forecast‐day 1. Blue contours represent the inland water fraction (50%). (d, e) same as (b,c), but for the entire simulation domain of the respective models.

Analysis of a high-resolution, convection-permitting simulation of the tropical Indian Ocean has revealed empirical relationships between precipitation and gravity wave vertical momentum flux on grid scales typical of earth system models. Hence, the authors take a rough functional form, whereby the wave flux source spectrum has an amplitude proportional to the square root of total precipitation, to represent gravity wave source strengths in the Met Office global model’s spectral nonorographic scheme. Key advantages of the new source are simplicity and responsiveness to changes in convection processes without dependence upon model-specific details of their representation. Thus, the new source scheme is potentially a straightforward adaptation for a class of spectral gravity wave schemes widely used for current state-of-the-art earth system models. Against an invariant source, the new parameterized source generates launch-level flux amplitudes with greater spatial and temporal variability, producing probability density functions for absolute momentum flux over the ocean that have extended tails of large-amplitude, low-occurrence events. Such distributions appear more realistic in comparison with reported balloon observations. Source intermittency at the launch level affects mean fluxes at higher levels in two ways: directly, as a result of upward propagation of the new source variation, and indirectly, through changes in filtering characteristics that arise from intermittency. Initial assessment of the new scheme in the Met Office global model indicates an improved representation of the quasi-biennial oscillation and sensitivity that offers potential for further impact in the future.

High resolution simulations at 4.4 km and 1.5 km resolution have been performed for 12 historical tropical cyclones impacting Bangladesh. We use the European Centre for Medium-Range Weather Forecasting 5 th generation Re-Analysis (ERA5) to provide a 9-member ensemble of initial and boundary conditions for the regional configuration of the Met Office Unified Model. The simulations are compared to the original ERA5 data and the International Best Track Archive for Climate Stewardship (IBTrACS) tropical cyclone database for wind speed, gust speed and mean sea-level pressure. The 4.4 km simulations show a typical increase in peak gust speed of 41 to 118 knots relative to ERA5, and a deepening of minimum mean sea-level pressure of up to −27 hPa, relative to ERA5 and IBTrACS data. The downscaled simulations compare more favourably with IBTrACS data than the ERA5 data suggesting tropical cyclone hazards in the ERA5 deterministic output may be underestimated. The dataset is freely available from https://doi.org/10.5281/zenodo.3600201 . Measurement(s) atmospheric wind speed • wind speed of gust • temperature of air • humidity • geopotential height • water-based rainfall • snowfall • pressure of air • air pressure at sea level • wet bulb potential temperature • net down surface SW flux • surface downwelling SW flux in air Technology Type(s) computational modeling technique Factor Type(s) spatial resolution: 4.4 km & 1.5 km Sample Characteristic - Environment atmospheric weather • atmospheric boundary layer • cyclone Sample Characteristic - Location Bangladesh • South Asia Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13560560

A model for the spread of a wildfire is developed within the U.K. Met Office Unified Model (UM) and used to simulate the Kilmore East fire complex (in southeastern Australia) on Black Saturday (7 February 2009). The UM is configured with four nests with horizontal grid spacings of 4 km, 1.5 km, 444 m, and 144 m. In the first simulation, the UM simply provides predictions of the near‐surface conditions for the wildfire model with no feedbacks to the atmosphere from the fire. In the second, the atmosphere and fire are coupled, allowing the fire to affect the local‐scale weather. The agreement between the coupled simulation and the observed fire behavior is reasonably good. For example, the area burnt is approximately 80% of the actual area burnt. However, such agreement is achieved only by coupling the fire to the atmosphere and, importantly, by igniting 18 additional fires at the times and places the long‐range transport of burning material (spotting) was observed. Without coupling the burnt area is about half of that observed. The calculations reported here suggest that the behavior and spread of fires like the Kilmore East fire are predictable but only when long‐range spotting is included and the atmosphere and fires are coupled. Additional numerical experiments with coarser grids suggest that, although the details of the fire spread are lost, a grid spacing of 1.5 km may be sufficient to simulate the main features of the fire spread. Key Points A wildfire spread model is coupled to the U.K. Met Office Unified Model and used to simulate the Kilmore East fire There is reasonable agreement between the simulation and the actual Kilmore East fire Such agreement relies on the atmosphere and the fire being coupled and accurate but unforecastable, long‐range spotting

Atmospheric water vapor estimates from static ground-based Global Navigation Satellite System (GNSS) receivers are now operationally assimilated into numerical weather prediction models, either as total precipitable water vapor (PWV) or zenith total delay. To extend this concept, the estimation of water vapor using kinematic GNSS has been investigated for over a decade. Previous kinematic GNSS PWV studies suggest a 2–3-mm PWV measurement agreement with radiosondes, almost commensurate with static GNSS PWV measurement accuracy, but the only comprehensive experiments undertaken have been shipborne. As a first step toward extending sea level–based studies to airborne experiments that obtain atmospheric profiles, the authors considered the kinematic GNSS estimation of atmospheric water vapor along a repeatable trajectory spanning substantial topographic relief, namely, the Snowdon Mountain Railway, United Kingdom. The atmospheric water vapor was indirectly quantified through the GNSS estimation of zenith wet delay (ZWD). Static GNSS [GPS+ Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS)] reference receivers were installed at the 950-m-altitude profile’s extremities, providing ZWD reference values that were interpolated to the train’s altitude, together with profiles from 100-m-resolution runs of the Met Office Unified Model. Similar GNSS ZWD accuracies to those from shipborne studies are demonstrated, namely, 12.1 mm (RMS) using double-difference relative kinematic GPS and 16.2 mm using kinematic GPS precise point positioning (PPP), but which is improved to 11.6 mm when using kinematic GPS+GLONASS PPP, commensurate with the relative kinematic GPS. The PPP solution represents a more typical airborne estimation scenario, that is, without relying on nearby GNSS reference stations.

In this paper we define RAL2 – the second Regional Atmosphere and Land (RAL) science configuration for regional modelling. RAL2 uses the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL2 defines the science configuration of the dynamics and physics schemes of the atmosphere and land and builds on the baseline of RAL1. There are two RAL2 sub-releases, one for mid-latitudes (RAL2-M) and one for tropical regions (RAL2-T). We document the differences between them and where appropriate discuss how RAL2 relates to RAL1 and the corresponding configuration of the global forecasting model. Our results show an increase in medium and low cloud amounts in the mid-latitudes leading to improved cloud forecasts. The increase in cloud amount leads to a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates. RAL2 is expected to be the last RAL science configuration with two sub-releases as research effort is focused on producing a single defined configuration of the model that performs effectively in all regions of the world.

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.