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A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no comparison of these models has been conducted; in

Urban land surface schemes have been developed to model the distinct features of the urban surface and the associated energy exchange processes. These models have been developed for a range of purposes and make different assumptions related to the inclusion and representation of the relevant processes. Here, the first results of Phase 2 from an international comparison project to evaluate 32 urban land surface schemes are presented. This is the first large-scale systematic evaluation of these models. In four stages, participants were given increasingly detailed information about an urban site for which urban fluxes were directly observed. At each stage, each group returned their models' calculated surface energy balance fluxes. Wide variations are evident in the performance of the models for individual fluxes. No individual model performs best for all fluxes. Providing additional information about the surface generally results in better performance. However, there is clear evidence that poor choice of parameter values can cause a large drop in performance for models that otherwise perform well. As many models do not perform well across all fluxes, there is need for caution in their application, and users should be aware of the implications for applications and decision making.

Data assimilation (DA) methods for convective‐scale numerical weather prediction at operational centres are surveyed. The operational methods include variational methods (3D‐Var and 4D‐Var), ensemble methods (LETKF) and hybrids between variational and ensemble methods (3DEnVar and 4DEnVar). At several operational centres, other assimilation algorithms, like latent heat nudging, are additionally applied to improve the model initial state, with emphasis on convective scales. It is demonstrated that the quality of forecasts based on initial data from convective‐scale DA is significantly better than the quality of forecasts from simple downscaling of larger‐scale initial data. However, the duration of positive impact depends on the weather situation, the size of the computational domain and the data that are assimilated. Furthermore it is shown that more advanced methods applied at convective scales provide improvements over simpler methods. This motivates continued research and development in convective‐scale DA. Challenges in research and development for improvements of convective‐scale DA are also reviewed and discussed. The difficulty of handling the wide range of spatial and temporal scales makes development of multi‐scale assimilation methods and space–time covariance localization techniques important. Improved utilization of observations is also important. In order to extract more information from existing observing systems of convective‐scale phenomena (e.g. weather radar data and satellite image data), it is necessary to provide improved statistical descriptions of the observation errors associated with these observations.

Abstract. The ALADIN System is a numerical weather prediction (NWP) system developed by the international AL-ADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the AL-ADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations.The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the AL-ADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

ABSTRACT:A new high-resolution dynamical downscaling strategy to examine how rural and urban areas respond to change in future climate, is presented. The regional climate simulations have been performed with a new version of the limited-area model of the ARPEGE-IFS system running at 4 km resolution coupled with the Town Energy Balance (TEB) scheme. To downscale further the regional climate projections to a urban scale, at 1-km resolution, a stand-alone surface scheme is employed in offline mode. We performed downscaling simulations according to three model set-ups: (1) reference run, where TEB is not activated neither in 4 km simulations nor in 1 km urban simulation, (2) offline run, where TEB is activated only for 1 km urban simulation and (3) inline run, where TEB is activated both for regional and urban simulations. The applicability of this method is demonstrated for Brussels Capital Region, Belgium. For present climate conditions, another set of simulations were performed using European Center for Medium-Range Weather Forecasts global reanalysis ERA40 data. Results from our simulations indicate that the reference and offline runs have comparable values of daytime and nocturnal urban heat island (UHI) and lower values than the inline run. The inline values are closer to observations. In the future climate, under and A1B emission scenario, the three downscaling methods project a decrease of daytime UHI between −0.24 and −0.20• C, however, their responses are different for nocturnal UHI: (1) reference run values remains unaltered, (2) for the offline runs, the frequency of present climate weak nocturnal UHI decreases to the benefit of negative UHIs leading to a significant decrease in the nocturnal UHI over the city and (3) for the inline run, nocturnal UHIs stays always positive but the frequency of the strong UHI decreases significantly in the future by 1 • C. The physical explanation is put forth.

The Town Energy Balance module bridges the micro-and mesoscale and simulates local-scale urban surface energy balance for use in mesoscale meteorological models. Previous offline evaluations show that this urban module is able to simulate in good behavior road, wall, and roof temperatures and to correctly partition radiation forcing into turbulent and storage heat fluxes. However, to improve prediction of the meteorological fields inside the street canyon, a new version has been developed, following the methodology described in a companion paper by Masson and Seity. It resolves the surface boundary layer inside and above urban canopy by introducing a drag force approach to account for the vertical effects of buildings. This new version is tested offline, with one-dimensional simulation, in a street canyon using atmospheric and radiation data recorded at the top of a 30-m-high tower as the upper boundary conditions. Results are compared with simulations using the original single-layer version of the Town Energy Balance module on one hand and with measurements within and above a street canyon on the other hand. Measurements were obtained during the intensive observation period of the Basel Urban Boundary Layer Experiment. Results show that this new version produces profiles of wind speed, friction velocity, turbulent kinetic energy, turbulent heat flux, and potential temperature that are more consistent with observations than with the single-layer version. Furthermore, this new version can still be easily coupled to mesoscale meteorological models.

Using the regional climate model ALARO-0, the Royal Meteorological Institute of Belgium and Ghent University have performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979-2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44 •. ALARO-0 is char-acterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989-2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature, some large biases, which are often also found in the ARPEGE results, persist. For precipitation , on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust , meaning independent of the period used to calculate them. Periods of 20 years are sampled from the 32-year simulation and used to construct the 95 % confidence interval for each score. For most scores, these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant.