At present atmospheric models for weather and climate use enhanced turbulent drag under stable conditions, because these empirically provide the necessary momentum drag for accurate forecast of synoptic systems. The enhanced mixing (also known as the ‘long tail’), introduces drag that cannot be physically justified and degrades the score for near‐surface temperature, wind and boundary‐layer height, and degrades fog and frost forecasting. This study hypothesizes that the insufficient representation of small‐scale orographic gravity wave drag in the stable boundary layer may explain the need for the enhanced drag formulation. Hence, we introduce a new scheme in the Weather Research and Forecasting model that accounts for this drag as a superposition on the turbulent drag induced by a so‐called short‐tail mixing function. The latter is consistent with boundary‐layer observations and large‐eddy simulations. We evaluate this scheme, against a short‐tail and a long‐tail scheme for sixteen eight‐day forecasts over the Atlantic Ocean and Europe in winter. The new scheme outperforms the short‐ and long‐tail schemes on sea‐level pressure, height of the 500 hPa field, 10 m wind and the cyclonic core pressure. Cyclonic core pressure bias is reduced by approximately 45 to 80% compared to the short‐tail scheme. Sea‐level pressure bias is reduced by up to 0.48 hPa (50%) over the whole domain compared to the short‐tail run. The new scheme has even smaller biases than the long‐tail scheme, supporting our hypothesis that small‐scale gravity wave drag may explain the need for a long‐tail function. Near‐surface wind bias is reduced by up to 40% compared to the long‐tail and up to 32% compared to the short‐tail scheme, while the 2 m temperature bias is only slightly increased (19%).

Urban canopy models are essential tools for forecasting weather and air quality in cities. However, they require many surface parameters, which are uncertain and can reduce model performance if inappropriately prescribed. Here, we evaluate the model sensitivity of the single‐layer urban canopy model (SLUCM) in the Weather Research and Forecasting (WRF) model to surface parameters in two different configurations, one coupled to the overlying atmosphere (on‐line) in a 1D configuration and one without coupling (off‐line). A two‐day summertime period in London is used as a case study, with clear skies and low wind speeds. Our sensitivity tests indicate that the SLUCM reacts differently when coupled to the atmosphere. For certain surface parameters, atmospheric feedback effects can outweigh the variations caused by surface parameter settings. Hence, in order to fully understand the model sensitivity, atmospheric feedback should be considered.

<p>Models for weather and climate have been actively populated with urban canopy models in the last decade. Urban canopy models are available with different levels of complexity. In an earlier study several urban canopy models have been evaluated in offline mode (Grimmond et al. 2011). However, in reality these schemes operate within a numerical weather prediction model, and are coupled with the atmospheric boundary layer. Within the SUBLIME model intercomparison study, single-column models equipped with urban canopy models are evaluated against observations for a clear sky case over London. As such we aim to unravel whether model sensitivity for urban morphological parameters is similar in coupled and uncoupled model. Moreover, the SUBLIME project provides a benchmark for future model evaluation and further development. The SUBLIME experiment consists of a forecast task over a 54 hour period (23-25 July 2012), during which clear sky conditions persisted over London. It consists of two main stages, firstly an offline urban canopy model run, to determine how the surface scheme performs. This is followed by a run in which the urban canopy model is coupled to a single-column model to simulate the coupling to the urban boundary layer. Model forcing data were provided by flux tower, LIDAR and radiosonde observations. Additional external forcings for geostrophic wind speed and advection of heat, moisture and momentum which could not be directly observed were simulated using, 3-D WRF (Weather Research and Forecasting model) model runs. This presentation will discuss the modelling results using the new revised external forcings. We evaluate model outcomes against surface radiation and energy balance observations for both stages. For the second stage, modelled vertical profiles of wind, temperature and humidity as well as boundary-layer height are compared against observations and between models. Finally, differences in model results are identified and the physical processes responsible for these are explored using process diagrams.</p>

Understanding the physical processes that affect the turbulent structure of the nocturnal urban boundary layer (UBL) is essential for improving forecasts of air quality and the air temperature in urban areas. Low-level jets (LLJs) have been shown to affect turbulence in the nocturnal UBL. We investigate the interaction of a mesoscale LLJ with the UBL during a 60-h case study. We use observations from two Doppler lidars and results from two high-resolution numerical-weather-prediction models (Weather Research and Forecasting model, and the Met Office Unified Model for limited-area forecasts for the U.K.) to study differences in the occurrence frequency, height, wind speed, and fall-off of LLJs between an urban (London, U.K.) and a rural (Chilbolton, U.K.) site. The LLJs are elevated ($$\approx $$ ≈ 70 m) over London, due to the deeper UBL, while the wind speed and fall-off are slightly reduced with respect to the rural LLJ. Utilizing two idealized experiments in the WRF model, we find that topography strongly affects LLJ characteristics, but there is still a substantial urban influence. Finally, we find that the increase in wind shear under the LLJ enhances the shear production of turbulent kinetic energy and helps to maintain the vertical mixing in the nocturnal UBL.