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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]

High-rise buildings, increasingly a feature of many large cities, impact local atmospheric flow conditions. Tall building wakes affect air quality downstream due to turbulent mixing and require parametrization in dispersion models. Previous studies using numerical or physical modelling have been idealised and under neutral conditions. There has been a lack of data available in real urban environments due to the difficulty in deploying traditional wind sensors. Doppler wind lidars (DWLs) have been used frequently for studying wind turbine wakes but never building wakes. This study is a year-long deployment of a DWL in a complex urban environment studying tall building wakes under atmospheric conditions. A HALO Photonic Streamline DWL was deployed in a low- and mid-rise densely packed area in central London. From its roof-top position (33.5 m agl compared to mean building height 12.5 m), Velocity Azimuth Display (VAD) scans at zero-degree elevation intersected with two, taller nearby buildings of 90 and 40 m agl. Using an ensemble averaging approach, wake dimensions were investigated in terms of wind direction, stability and wind speed. Boundary-layer stability categories were defined using eddy covariance observations from the BT Tower (191 m) and mixing height estimations from vertical stare scans. A method for calculating normalised velocity deficit from VAD scans is presented. For neutral conditions, wake dimensions around both buildings for the prevailing wind direction were compared with the ADMS-Build wake model for a single, isolated cube. The model underpredicts wakes dimensions, confirming previous wind tunnel findings for the same area. Under varying stability, unstable and deep boundary layers were shown to produce shorter, narrower wakes. Typical observed wake lengths were 120–300 m and widths were 80–150 m and were reduced by 50–100 m downwind. Stable and shallow boundary layers were less frequent and produced an insignificant difference in wake dimensions to neutral conditions. The sensitivity to stability was weakened by enhanced turbulence upstream (i.e., due to other building wakes). Weakened stability dependence was confirmed if there were more obstacles upstream as the wind direction incident on the buildings changed. The results highlight the potential for future wake studies using multiple DWLs deploying both vertical and horizontal scan patterns. Dispersion models should incorporate the effect of a complex urban canopy within which tall buildings are embedded. [ABSTRACT FROM AUTHOR]

Cities are a source of complex land–atmosphere interactions. Spatial differences in the energy balance and enhanced surface roughness interact with the atmosphere to alter clouds and precipitation. Here, we explore how London (UK) alters cloud formation during the spring and summer. The Met Office's high‐resolution operational forecasts predict enhanced cloud cover over the city, as found in observations, but underpredicts the intensity. During low wind speeds, cloud enhancement over the city is strongest and linked to an urban‐induced thermal circulation. These circulations advect moist air from the city edge inwards, transporting it upwards with a large moisture convergence over the urban area. At around 1,000 m above the surface, the turbulent moisture flux takes over the moisture transport to the cloud layer. A relative humidity budget shows the moisture flux in the upper boundary layer to be the largest contribution to the urban–rural differences in relative humidity. [ABSTRACT FROM AUTHOR]

ABSTRACT The urban heat island (UHI) effect, defined as the air temperature difference between the urban canyon and the nearby rural area, is investigated. Because not all cities around the world are equipped with an extensive measurement network, a need exists for a relatively straightforward equation for the UHI effect. Here, we derive a simple, diagnostic equation for the UHI using dimensional analysis. This equation provides a first-order estimation of the daily maximum UHI based on routine meteorological observations and straightforward urban morphological properties. The equation is tested for 14 cities across northwestern Europe and appears to be robust. The comprehensiveness of this analytical equation allows for applications beyond urban meteorological studies. [ABSTRACT FROM AUTHOR]