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For a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to consider seriously the operational implementation of practical hectometric models. Many, but by no means all, of the applications are likely to relate to urban areas, where the enhanced resolution has obvious benefits. This article is concerned with the issues that need to be addressed to bridge the gap between research at 100‐m scales and practical models. We highlight a number of key issues that need to be addressed, with suggestions of important avenues for future development. An overarching issue is the high computational cost of these models. Although some ideas to reduce this are presented, it will always be a serious constraint. This means that the benefits of these models over lower resolution ones, or other techniques for generating high‐resolution forecasts, will need to be clearly understood, as will the trade‐offs with resolution. We discuss issues with model dynamical cores and physics–dynamics coupling. There are a number of challenges around model parameterisations, where some of the traditional problems (e.g., convection) become easier but a number of new challenges (e.g., around surface parameterisations) appear. Observational data at these scales present a challenge and novel types of observations will need to be considered. Data assimilation will be needed for short‐range forecasts, but there is currently little knowledge of this, although some of the likely issues are clear. An ensemble approach will be essential in many cases (e.g., convection), but research is needed into ensembles at these scales and significant work on post‐processing systems is required to make the best use of models at these grid lengths. [ABSTRACT FROM AUTHOR]

To evaluate numerical weather predictions (NWP) using observations, the horizontal, vertical and temporal resolution characteristics need to be considered to ensure consistency. Here, large‐aperture scintillometry (LAS) is used to derive turbulent sensible heat fluxes (QH), as the source area extents are comparable to NWP with horizontal grid box resolutions of order 1 km. We demonstrate our methodology using LAS observations undertaken in central London and the Met Office's operational forecast model for the United Kingdom (UKV). In the horizontal, we ensure consistency between the LAS source area locations and extent, as they vary with wind direction and stability, and therefore the NWP grid boxes that should be selected for comparison. In the vertical, the appropriate model level needs to be selected relative to the changing effective measurement height (zf) of the observations. The LAS fluxes time and space averaging allows QH to be obtained for time periods similar to the model timestep (e.g., 1 min) but the UKV does not explicitly represent higher‐frequency turbulent motions. During two spring days, three to five UKV grid boxes (1.5 km resolution) fall within the LAS source area (60%). However, with the model land cover data lacking realistic spatial variability, modelled effective surface QH spatial variability is small, leaving a central grid box on the LAS path representative. Larger differences occur between modelled QH at the surface and closest to zf, despite both theoretically being within the inertial sublayer. The modelled QH has better agreement with observed fluxes when averaged over long periods (10+ min cf. 1 min). As LAS‐derived QH has larger source areas than eddy covariance (EC) measurements, there are benefits to assessing NWP model performance with LAS. With multiple paths, spatial variability in response to changes in surface cover could be assessed at shorter times scales than possible with EC. [ABSTRACT FROM AUTHOR]

When using sub‐km models to forecast convection, it is important to have a large enough domain to allow convection to fully spin‐up from the lateral boundaries. However, running large domains is computationally expensive and while it may be feasible for research purposes it is not yet feasible for routinely run models, such as the Met Office 300‐m London model. To try and mitigate the spin‐up issues in the London model, a variable‐resolution 300‐m London Model (the 'LMV') has been developed, which allows the boundaries of the London model to be further away from areas of interest (e.g., London Heathrow) at lower computational cost. Results from several cases of summertime convection show that the convective storms in the variable‐resolution model are more like those in a large fixed‐resolution 300‐m model than those in the much smaller London model. This implies variable resolution is a viable option for increasing the size of the London model domain without increasing the computational costs too much. Extended evaluation of the LMV was conducted during summer 2022, running as an ensemble nested inside the Met Office's operational UK ensemble (MOGREPS‐UK). Overall, the LMV looks promising for high‐impact convective events as it is better able to represent the organisation of convection into lines or larger storms whereas MOGREPS‐UK tends to simulate isolated, circular storms. This often leads to more reliable probabilities of heavy rainfall in the LMV ensemble compared to MOGREPS‐UK. However, there is an issue with the LMV producing too many small precipitating showers in situations where there should only be shallow clouds. This is thought to be a result of shallow clouds getting too deep in the model and precipitating erroneously. [ABSTRACT FROM AUTHOR]

Operational Meteorologists (OMs) in the Met Office have a perception that elevated convection is not well represented in kilometre‐scale models, which are generally associated with an improved representation of convection. Here, we consider why there may be a problem with representing elevated convection and consider how OMs judge the model to be poor so often. Three OMs have subjectively scored and classified observed elevated convection cases over the UK from 2017 to 2020. Continental plumes (warm, moist, air coming from the near continent or Africa) account for 73% of the cases. The most frequent errors are associated with (i) location, (ii) organisation, (iii) timing and (iv) intensity of the convection. Thus, OMs perceive that the biggest problem with predicting elevated convection is constraining the location of the convective events. The location errors are particularly prevalent for events coming to the UK from the near continent. The location errors are most frequently identified for flow regimes coming from the near continent in weakly forced synoptic conditions. The identification of this problem enables the specific targeting of research into continental plumes (for UK elevated convection) but also raises questions around the role of lateral boundary conditions in the forecasts of elevated convection. [ABSTRACT FROM AUTHOR]

The UK Met Office has a 300‐m grid length numerical weather prediction (NWP) model running routinely over London and, in research mode, city‐scale hectometric grid length NWP has become commonplace. It is important to understand how moving from kilometre‐ to hectometre‐scale grid length NWP influences boundary‐layer vertical mixing. For a clear‐sky convective boundary layer (CBL) case study, using 55‐ and 100‐m grid length NWP, we demonstrate that CBL vertical mixing of passive scalar is almost fully resolved. Passive scalar converges near the surface after emission from an idealised pollution ground source representing city‐scale emissions, and is transported in updrafts preferentially into the upper boundary layer. Approximately 8 km downstream of the source edge, this causes 34%$$ 34\% $$ lower near‐surface concentrations compared with 1.5‐km grid length NWP, where vertical mixing is fully parameterised. This demonstrates that resolving ballistic‐type dispersion, which is not typically represented in NWP vertical mixing parameterisations, can have a leading‐order influence on city‐scale near‐surface pollution concentration. We present a simple analytical model that is able to capture diffusive and ballistic dispersion behaviour in terms of effective timescales. The timescale controlling how long it takes passive scalar to become well mixed in the CBL is ≈3$$ \approx 3 $$ times longer for 1.5‐km compared with 100‐ and 55‐m grid length NWP. [ABSTRACT FROM AUTHOR]

Differential reflectivity (ZDR$$ {Z}_{\mathrm{DR}} $$) columns were observed using a Met Office three‐dimensional radar composite. An algorithm for automatic detection of ZDR$$ {Z}_{\mathrm{DR}} $$ columns was developed, based on ZDR≥1.0$$ {Z}_{\mathrm{DR}}\ge 1.0 $$ dB and ZH≥10$$ {Z}_{\mathrm{H}}\ge 10 $$ dBZ. Across three case days, detected ZDR$$ {Z}_{\mathrm{DR}} $$ columns were found to precede severe convection in tracked convective cells with a range of lead times from 0 to 20 min depending on the case day. Requiring maxima above 1.4 dB and 30 dBZ of ZDR$$ {Z}_{\mathrm{DR}} $$ and ZH$$ {Z}_{\mathrm{H}} $$ respectively was an appropriate second condition for all three cases although the skill in the early detection of severe convection varied across case days. Despite the high probability of detections, the high false alarm rate accompanied by low critical success index and data latency limit performance based on the three cases considered in this study. Nevertheless, the ability to detect ZDR$$ {Z}_{\mathrm{DR}} $$ columns in operational radar data with a useful lead time prior to severe convection in certain conditions is a promising development towards advancing nowcasting of severe convection in the United Kingdom. [ABSTRACT FROM AUTHOR]

An important practical problem is to understand the depth to which pollutants will be mixed in the boundary layer over cities. This is particularly important shortly after sunrise on clear days when the mixed layer is often shallow and there may be large emissions from rush‐hour traffic. The 100 m scale NWP models currently under development have the potential to represent the boundary‐layer structure over cities on neighbourhood scales for air quality and other applications. Here we describe work with Met Office Unified Model (MetUM) configurations with grid lengths of 100, 50 and 25 m to represent the morning growth of a clear convective boundary layer over London compared to observations. All three models explicitly represent the convective overturning although it is not as well resolved at 100 m and this is a particular problem early in the day. It is found that in both the observations and in the models that the depth to which aerosol is mixed up into the model from the surface is lower than the turbulence mixed‐layer depth as measured from the vertical velocity variance. We present an analysis in the 25 m model that shows that the reason for the discrepancy is that the aerosol is transported upwards from the surface by convective plumes whereas further up there is wave motion which does not transport aerosol. The signature for these two layers can be seen both in the 25 m model and in the observations. We discuss the representation of these effects in the coarser‐resolution 100 and 55 m models and also possible mechanisms for the generation of the waves. [ABSTRACT FROM AUTHOR]

Convective‐scale ensemble simulations with perturbed initial and lateral boundary conditions have been performed to investigate the role of compensating errors in the model representation of a US Great Plains severe convective event. The convective‐scale ensembles were generated by nesting a 2.2 km grid‐length domain within the Met Office global ensemble. Within the ensemble framework, two different science configurations (i.e. parametrization set‐ups) were trialled in the 2.2 km model. The variability due to the use of a different driving global ensemble member was significant with differences in the pre‐convective thermodynamic environment and the initiation time of convection. The science changes also influence initiation time as well as the details in the convective structure. Comparison with observed soundings showed that most of the 2.2 km simulations had too little convective inhibition (CIN). The CIN was found to be independent of the science configuration, implying it is determined by the global model, which was also found to have less CIN than the observed soundings. In both 2.2 km ensembles, the member that produced one of the best simulations of the supercells that developed on this day had more CIN than the other members. However, comparisons with surface station data found that this member had a pre‐convective environment that was too cool and too dry. This suggests there are compensating errors in the factors controlling initiation in these models which comparisons with observations can help elucidate. [ABSTRACT FROM AUTHOR]

In numerical weather prediction (NWP), observations and models are quantitatively compared for the purposes of data assimilation and forecast verification. The spatial and temporal scales represented by the observation and model may differ and this results in a scale mismatch error which may be biased and correlated. The aim of this paper is to investigate the structure of representation error in convection‐permitting NWP models for four meteorological variables: temperature, specific humidity, zonal and meridional wind. We use high‐resolution data from the experimental Met Office London Model (approximately 300 m grid‐length) to simulate perfect observations and lower‐resolution model data. The scale mismatch error and its bias, variance and correlation are calculated from the perfect observation and low‐resolution model equivalents. Our new results show that the scale mismatch bias is significant in the boundary layer for temperature and specific humidity, whereas the variance is significant in the boundary layer for all analysed variables. Contrary to previous studies using low‐resolution (km‐scale) data, horizontal correlations are shown to be insignificant. However, all variables exhibit considerable vertical representation error correlation throughout the boundary layer. Our results suggest that significant biases and vertical correlations exist that should be accounted for to give maximum observation impact in data assimilation and for fairness in model verification and validation. [ABSTRACT FROM AUTHOR]

The Met Office runs an operational high‐resolution convection‐permitting model over Tropical Africa to support National Meteorological Services across the continent. This article evaluates the prediction of convective storms in two convection‐permitting versions of the Met Office Unified Model over the Lake Victoria basin region in East Africa. Two model configurations are compared for a case of severe convection: the first was tuned for tropical regions and the second was based on the operational UK model configuration. The tropical configuration compares better with satellite‐derived rainfall observations in terms of domain‐average rain‐rate and the distribution of rain‐rates is better, particularly for the more intense rain‐rates. However, both configurations generally produce too much rain, too many small storms, and a lack of light rain, which is compensated for by heavy rain in the cores of the storms. The tropical configuration was then assessed over two rainy seasons. In both seasons, the onset time of night‐time precipitation over Lake Victoria is delayed and the amount of precipitation is underestimated, which suggests the model may miss night‐time storms that occur over the lake. During the first 12–24 hr of the simulations, the precipitation field is still spinning up from the lower‐resolution global model fields used to initialise the convection‐permitting model. This leads to large overestimates in the domain‐average precipitation during this period and highlights the need to run convection‐permitting models for at least two days to reduce the impact of cold‐starting from a non‐convective‐permitting analysis. Despite the spin‐up issues, fractions skill score analysis shows that forecast skill decreases with increasing lead time. This implies that there is inherent skill in the early stages of the model forecast and underlines that short‐term forecast (0–48 hr) improvements in the model are likely to be achieved when using an improved analysis for initialisation. [ABSTRACT FROM AUTHOR]

Operational forecasting centres increasingly rely on convection‐permitting NWP simulations to assist in their forecasting of convective events. The evaluation of upgrades in the underlying NWP modelling system normally happens through routine verification using traditional metrics on two‐dimensional fields, such as gridded rainfall data. Object‐ and process‐based evaluation can identify specific physical mechanisms for model improvement, but such evaluation procedures normally require targeted and expensive field campaigns. Here, we explore the potential use of the UK operational radar network observations and its derived 3D composite product for evaluating the representation of convective storms in the Met Office Unified Model. A comparison of the 1 × 1 × 0.5 km 3D radar composites against observations made with the research‐grade radar at Chilbolton in the southern UK indicates that the 3D radar composite data can reliably be used to evaluate the morphology of convective storms. The 3D radar composite data are subsequently used to evaluate the development of convective storms in the Met Office Unified Model. Such analysis was previously unavailable due to a lack of 3D radar data of high temporal frequency. The operational nature of the UK radar data makes these 3D composites a valuable resource for future studies of the initiation, growth, development, and organisation of convective storms over the UK. [ABSTRACT FROM AUTHOR]

With a number of operational centres looking forward to the possibilities of "city scale" NWP and climate modelling it is important to understand the behaviour of order 100 m models over cities. A key issue is how to handle the representation of partially resolved turbulence in these models. In this article we compare the representation of a clear convective boundary‐layer case in London in 100 and 50 m grid‐length versions of the Unified Model (MetUM) with observations. Comparison of Doppler lidar observations of the vertical velocity shows that convective overturning in the boundary layer is broadly well represented in terms of its depth and magnitude. The role of model resolution was investigated by comparing a 50 m grid‐length model with the 100 m one. It is found that, although going to 50 m grid length does not greatly change many of the bulk properties (mixing height, heat flux profiles, etc.) the spatial structure of the overturning is significantly different. This is confirmed with spectral analysis which shows that the 50 m model resolves significantly more of the energetic eddies, and a length‐scale analysis that shows the 50 and 100 m models produce convective structures 2–3 times larger than observed. We conclude that, for the MetUM, model grid‐lengths of order 100 m may well be sufficient for predicting many bulk and statistical properties of convective boundary layers; however, the details of the spatial structures around convective overturning in these situations are likely to be still under‐resolved. Spin‐up artefacts emanating from the inflow boundary of the model are investigated by comparing with a smaller 100 m grid‐length domain which is more dominated by such effects. These manifest themselves as along‐wind boundary‐layer rolls which produce a less realistic comparison with the lidar observations. A stability analysis is presented in order to better understand the formation of these rolls. [ABSTRACT FROM AUTHOR]

Convective initiation is a challenge for convection‐permitting models due to its sensitivity to sub‐km processes. We evaluate the representation of convective storms and their initiation over South Africa during four summer months in Met Office Unified Model simulations at a 1.5‐km horizontal grid length. Storm size distributions from the model compare well with radar observations, but rainfall in the model is predominantly produced by large storms (50 km in diameter or larger) in the evening, whereas radar observations show that most rainfall occurs throughout the afternoon, from storms 10–50 km in diameter. In all months, the modelled maximum number of storm initiations occurs at least 2 hr prior to the radar‐observed maximum. However, the diurnal cycle of rainfall between the model and observations compares well, suggesting that the numerous storm initiations in the simulations do not produce much rainfall. Modelled storms are generally less intense than those in radar observations, especially in early summer. In February, when tropical influences dominate, the simulated storms are of similar intensity to observed storms. Simulated storms tend to reach their peak intensity in the first 15 min after initiation, then gradually become less intense as they grow. In radar observations, storms reach their peak intensity 15 min into their life cycle, stay intense as they grow larger, then gradually weaken after they have reached their maximum diameter. Two November case studies of severe convection are analysed in detail. A higher resolution grid length initiates convection slightly earlier (300 m as opposed to 1.5 km) with the same scientific settings. Two 1.5 km simulations that apply more subgrid mixing have delayed convective initiation. Analysis of soundings indicates little difference in the convective indices, suggesting that differences in convection may be attributed to the choice of subgrid mixing parameters. [ABSTRACT FROM AUTHOR]

Turbulent mixing processes are important in determining the evolution of convective clouds, and the production of convective precipitation. However, the exact nature of these impacts remains uncertain due to limited observations. Model simulations show that assumptions made in parametrizing turbulence can have a marked effect on the characteristics of simulated clouds. This leads to significant uncertainty in forecasts from convection‐permitting numerical weather prediction (NWP) models. This contribution presents a comprehensive method to retrieve turbulence using Doppler weather radar to investigate turbulence in observed clouds. This method involves isolating the turbulent component of the Doppler velocity spectrum width, expressing turbulence intensity as an eddy dissipation rate, ϵ. By applying this method throughout large datasets of observations collected over the southern United Kingdom using the (0.28° beam‐width) Chilbolton Advanced Meteorological Radar (CAMRa), statistics of convective cloud turbulence are presented. Two contrasting case days are examined: a shallow "shower" case, and a "deep convection" case, exhibiting stronger and deeper updraughts. In our observations, ϵ generally ranges from 10−3 to 10−1 m2/s3, with the largest values found within, around and above convective updraughts. Vertical profiles of ϵ suggest that turbulence is much stronger in deep convection; 95th percentile values increase with height from 0.03 to 0.1 m2/s3, compared to approximately constant values of 0.02–0.03 m2/s3 throughout the depth of shower cloud. In updraught regions on both days, the 95th percentile of ϵ has significant (p < 10−3) positive correlations with the updraught velocity, and the horizontal shear in the updraught velocity, with weaker positive correlations with updraught dimensions. The ϵ‐retrieval method presented considers a very broad range of conditions, providing a reliable framework for turbulence retrieval using high‐resolution Doppler weather radar. In applying this method across many observations, the derived turbulence statistics will form the basis for evaluating the parametrization of turbulence in NWP models. Turbulent mixing processes are important in determining the evolution of convective clouds, and the production of convective precipitation. To investigate turbulence in observed clouds, this contribution provides a comprehensive method to retrieve turbulence using Doppler weather radar. Statistics of convective cloud turbulence are presented through the analysis of retrievals (example in picture) over many observations in two contrasting case‐studies. [ABSTRACT FROM AUTHOR]

Since 2013, the Met Office have run a 2.2 km horizontal gridlength version of the Unified Model ( MetUM) as part of the National Oceanographic and Atmospheric Administration's Hazardous Weather Testbed Spring Forecasting Experiment. In this study, we perform high resolution MetUM simulations of the 20 May 2013 Oklahoma tornado outbreak at horizontal gridlengths between 2.2 km and 100 m. Here we present results showing that at 2.2 km gridlength the MetUM is able to simulate supercell-like storms whereas at O(100 m) gridlength it is able to simulate realistic-looking supercells with tornado-like vortices. This opens up the opportunity for using such simulations to highlight areas of enhanced tornado risk ahead of time. [ABSTRACT FROM AUTHOR]

Convection-permitting modelling has led to a step change in forecasting convective events. However, convection occurs within different regimes which exhibit different forecast behaviour. A convective adjustment timescale can be used to distinguish between these regimes and examine their associated predictability. The convective adjustment timescale is calculated from radiosonde ascents and found to be consistent with that derived from convection-permitting model forecasts. The model-derived convective adjustment timescale is then examined for three summers in the British Isles to determine characteristics of the convective regimes for this maritime region. Convection in the British Isles is predominantly in convective quasi-equilibrium, with 85% of convection having a timescale less than or equal to 3 h. This percentage varies spatially with more non-equilibrium events occurring in the south and southwest. The convective adjustment timescale exhibits a diurnal cycle over land. The non-equilibrium regime occurs more frequently at mid-range wind speeds and with winds from southerly to westerly sectors. Most non-equilibrium convective events in the British Isles are initiated near large coastal orographic gradients or on the European continent. Thus, the convective adjustment timescale is greatest when the location being examined is immediately downstream of large orographic gradients and decreases with distance from the convective initiation region. The dominance of convective quasi-equilibrium conditions over the British Isles argues for the use of large-member ensembles in probabilistic forecasts for this region. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

ABSTRACT 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 FROM AUTHOR]