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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 contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling approaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.

The interactions among several stable-boundary-layer (SBL) processes occurring just after the evening transition of 2 July 2011 have been analysed using data from instruments deployed over the area of Lannemezan (France) during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The near-calm situation of the afternoon was followed by the formation of local shallow drainage flows (SDFs) of less than 10 m depth at different locations. The SDF stage ended with the arrival of a stronger wind over a deeper layer more associated with the mountain-plain circulation, which caused mixing and destruction of the SDFs. Several gravity-wave-related oscillations were also observed on different time series. Wavelet analyses and wave parameters were calculated from high resolution and accurate surface pressure data of an array of microbarometers. These waves propagated relatively long distances within the SBL. The effects of these phenomena on turbulent parameters (friction velocity and kinematic heat flux) have been studied through multi-resolution flux decomposition methods performed on high frequency data from sonic anemometers deployed at different heights and locations. With this method, we were able to detect the different time-scales involved in each turbulent parameter and separate them from wave contributions, which becomes very important when choosing averaging-windows for surface flux computations using eddy covariance methods. The extensive instrumentation allowed us to highlight in detail the peculiarities of the surface turbulent parameters in the SBL, where several of the noted processes were interacting and producing important variations in turbulence with height and between sites along the sloping terrain.

The representation of the atmospheric boundary layer is an important part of weather and climate models and impacts many applications such as air quality and wind energy. Over the years, the performance in modeling 2-m temperature and 10-m wind speed has improved but errors are still significant. This is in particular the case under clear skies and low wind speed conditions at night as well as during winter in stably stratified conditions over land and ice. In this paper, the authors review these issues and provide an overview of the current understanding and model performance. Results from weather forecast and climate models are used to illustrate the state of the art as well as findings and recommendations from three intercomparison studies held within the Global Energy and Water Exchanges (GEWEX) Atmospheric Boundary Layer Study (GABLS). Within GABLS, the focus has been on the examination of the representation of the stable boundary layer and the diurnal cycle over land in clear-sky conditions. For this purpose, single-column versions of weather and climate models have been compared with observations, research models, and large-eddy simulations. The intercomparison cases are based on observations taken in the Arctic, Kansas, and Cabauw in the Netherlands. From these studies, we find that even for the noncloudy boundary layer important parameterization challenges remain.

The numerical weather prediction of radiation fog is challenging, as many models typically show large biases for the timing of the onset and dispersal of the fog, as well as for its depth and liquid water content. To understand the role of physical processes, i.e. turbulence, radiation, land-surface coupling, and microphysics, we evaluate the HARMONIE and Weather Research and Forecasting (WRF) mesoscale models for two contrasting warm fog episodes at the relatively flat terrain around the Cabauw tower facility in the Netherlands. One case involves a radiation fog that arose in calm anticyclonic conditions, and the second is a radiation fog that developed just after a cold front passage. The WRF model represents the radiation fog well, while the HARMONIE model forecasts a stratus lowering fog layer in the first case and hardly any fog in the second case. Permutations of parametrization schemes for boundary-layer mixing, radiation and microphysics, each for two levels of complexity, have been evaluated within the WRF model. It appears that the boundary-layer formulation is critical for forecasting the fog onset, while for fog dispersal the choice of the microphysical scheme is a key element, where a double-moment scheme outperforms any of the single-moment schemes. Finally, the WRF model results appear to be relatively insensitive to horizontal grid spacing, but nesting deteriorates the modelled fog formation. Increasing the domain size leads to a more scattered character of the simulated fog. Model results with one-way or two-way nesting show approximately comparable results.

Wind is a key component of the urban climate due to its relevance for ventilation of air pollution and urban heat, wind nuisance, as well as for urban wind energy engineering. These winds are governed by the dynamics of the atmosphere closest to the surface, the atmospheric boundary layer (ABL). Making use of a conceptual bulk model of the ABL, we find that for certain atmospheric conditions the boundary-layer mean wind speed in a city can surprisingly be higher than its rural counterpart, despite the higher roughness of cities. This urban wind island effect (UWI) prevails in the afternoon, and appears to be caused by a combination of differences in ABL growth, surface roughness and the ageostrophic wind, between city and countryside. Enhanced turbulence in the urban area deepens the ABL, and effectively mixes momentum into the ABL from aloft. Furthermore, the oscillation of the wind around the geostrophic equilibrium, caused by the rotation of the Earth, can create episodes where the urban boundary-layer mean wind speed is higher than the rural wind. By altering the surface properties within the bulk model, the sensitivity of the UWI to urban morphology is studied for the 10 urban local climate zones (LCZs). These LCZs classify neighbourhoods in terms of building height, vegetation cover etc, and represent urban morphology regardless of culture or location. The ideal circumstances for the UWI to occur are a deeper initial urban boundary-layer than in the countryside, low-rise buildings (up to 12 m) and a moderate geostrophic wind (∼5 m s−1). The UWI phenomenon challenges the commonly held perception that urban wind is usually reduced due to drag processes. Understanding the UWI can become vital to accurately model urban air pollution, quantify urban wind energy potential or create accurate background conditions for urban computational fluid dynamics models.

We present the main results from the second model intercomparison within the GEWEX (Global Energy and Water cycle EXperiment) Atmospheric Boundary Layer Study (GABLS). The target is to examine the diurnal cycle over land in today’s numerical weather prediction and climate models for operational and research purposes. The set-up of the case is based on observations taken during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99), which was held in Kansas, USA in the early autumn with a strong diurnal cycle with no clouds present. The models are forced with a constant geostrophic wind, prescribed surface temperature and large-scale divergence. Results from 30 different model simulations and one large-eddy simulation (LES) are analyzed and compared with observations. Even though the surface temperature is prescribed, the models give variable near-surface air temperatures. This, in turn, gives rise to differences in low-level stability affecting the turbulence and the turbulent heat fluxes. The increase in modelled upward sensible heat flux during the morning transition is typically too weak and the growth of the convective boundary layer before noon is too slow. This is related to weak modelled near-surface winds during the morning hours. The agreement between the models, the LES and observations is the best during the late afternoon. From this intercomparison study, we find that modelling the diurnal cycle is still a big challenge. For the convective part of the diurnal cycle, some of the first-order schemes perform somewhat better while the turbulent kinetic energy (TKE) schemes tend to be slightly better during nighttime conditions. Finer vertical resolution tends to improve results to some extent, but is certainly not the solution to all the deficiencies identified.

Evapotranspiration (ET)$(ET)$is a key process in the hydrological cycle that can help mitigate urban heat. ET$ET$depends on the surface cover, as the surface affects the partitioning of precipitation between runoff and evapotranspiration. In urban neighborhoods, this surface cover is highly heterogeneous. The resulting neighborhood‐scale ET$ET$can be observed with eddy‐covariance systems. However, these observations represent the signal from wind‐ and stability‐dependent footprints resulting in a continuously changing contribution of surface cover types to the observation. This continuous change prevents quantifying the contribution of the surface cover types to neighborhood ET$ET$and their hourly dynamics. Here, we disentangle this neighborhood‐scale ET$ET$at two sites in Berlin attributing the patch‐scale ET$ET$dynamics to the four major surface cover types in the footprint: impervious surfaces, low vegetation, high vegetation, and open water. From the bottom‐up, we reconstruct neighborhood ET$ET$based on patch‐scale observations and conceptual models. Alternatively, we start top‐down and attribute neighborhood ET$ET$to the surface cover types solving a system of equations for three eddy‐covariance systems. Although data requirements for the bottom‐up approach are met more frequently, both approaches indicate that vegetation is responsible for more ET$ET$than proportional to its surface fraction in the footprint related to the large evaporating surface compared to the ground surface. Evaporation from impervious surfaces cannot be neglected, although it is less than from vegetation due to limited water availability. The limited water availability causes impervious surfaces to cease evaporation hours after rainfall, while vegetation and open water sustain ET$ET$for extended periods. Plain Language Summary Different types of surfaces, like grass, trees, pavement, and open water, affect how rainwater is divided between evaporation and runoff. In cities with lots of pavement and buildings, more water runs off than in natural areas leaving less water for evaporation. Measurement towers have been observing the evaporation from whole neighborhoods, but separating the effects of different surfaces is hard. In our study, we figure out how much each surface type contributes to evaporation with two methods: one starting from the separate surfaces and rebuilding the neighborhood evaporation, and the other starting with the neighborhood evaporation and breaking it down into evaporation from each surface. Both ways showed that plants evaporate more than proportionally to their surface area, but even built surfaces like pavement evaporate. Our findings confirm that more plants lead to more evaporation, but built surfaces cannot be ignored. This information can help urban planners create cities that manage water better, making cities nicer places to live. Key Points Neighborhood ET is reconstructed from patch‐scale data (bottom‐up) and disentangled attributing ET to four surface types (top‐down) The neighborhood and patch scale are connected through half‐hourly‐varying eddy‐covariance footprints ET dynamics after rainfall reveal that water limitation drives differences between surface cover types

In the present work Blackadar’s concept of nocturnal inertial oscillations is extended. Blackadar’s concept describes frictionless inertial oscillations above the nocturnal inversion layer. The current work includes frictional effects within the nocturnal boundary layer. It is shown that the nocturnal wind speed profile describes an oscillation around the nocturnal equilibrium wind vector, rather than around the geostrophic wind vector (as in the Blackadar case). By using this perspective, continuous time-dependent wind profiles are predicted. As such, information on both the height and the magnitude of the nocturnal low-level jet is available as a function of time. Preliminary analysis shows that the proposed extension performs well in comparison with observations when a simple Ekman model is used to represent the equilibrium state in combination with a realistic initial velocity profile. In addition to jet dynamics, backward inertial oscillations are predicted at lower levels close to the surface, which also appear to be present in observations. The backward oscillation forms an important mechanism behind weakening low-level winds during the afternoon transition. Both observational and theoretical modeling studies are needed to explore this phenomenon further.

Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban‐PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators expecting better scoring models to capture the latent heat flux more accurately. We find that the water budget is only closed in 57% of the model‐site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all water balance indicators for any site. Models passing more indicators do not capture the latent heat flux more accurately refuting our hypothesis. While output reporting inconsistencies may have negatively affected model performance, our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest. Plain Language Summary Urban environments have their own local climates including typically higher nocturnal temperatures compared with rural areas. Ideally, modeling cities should capture their influences on the atmosphere above them. As the energy and water balances are linked by evaporation, a good water balance representation will support a good energy balance simulation. Focusing on the water balance, we find the water balance in models could be improved by paying attention to closure and runoff. Key Points We evaluate the water balance in 19 urban land surface models (ULSM) from the Urban‐PLUMBER project ULSMs capture the timing of water fluxes more accurately than their magnitude The water balance appears unclosed in 43% of the model runs (19 models at 20 sites)

A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high-resolution NWP model. Results by the Weather Research and Forecasting model (WRF) and the High-Resolution Limited-Area Model (HIRLAM) are evaluated against detailed observations to determine the state-of-the-art in fog forecasting and to derive requirements for further research and development. For this particular difficult case, WRF is unable to correctly simulate the fog for any of the parameterizations and model configurations utilized. Contrary, HIRLAM does model the onset of fog, but is unable to represent it beyond the lowest model layer, which leads to an early dispersal of fog in the morning transition. The sensitivity of fog forecasts to model formulation is further analyzed with a high-resolution single-column version of HIRLAM, and with the Duynkerke single-column model as a reference. The single-column results are found to be sensitive to the proper specification of the external forcings. It is reconfirmed that high vertical resolution is essential for modeling the fog formation, the growth of the fog layer, and when the fog lifts for the maintenance of a stratus deck. The properly configured column models are able to accurately model the onset of fog and its maturation, but fail in the simulation of fog persistence and subsequent dispersal. Details of the turbulence parameterization appear to be important in this process. It is concluded that, despite all of the advances in numerical weather prediction, fog forecasting is still a major challenge.