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.

The World Urban Database and Access Portal Tools (WUDAPT) is an international community-based initiative to acquire and disseminate climate relevant data on the physical geographies of cities for modeling and analysis purposes. The current lacuna of globally consistent information on cities is a major impediment to urban climate science toward informing and developing climate mitigation and adaptation strategies at urban scales. WUDAPT consists of a database and a portal system; its database is structured into a hierarchy representing different levels of detail, and the data are acquired using innovative protocols that utilize crowdsourcing approaches, Geowiki tools, freely accessible data, and building typology archetypes. The base level of information (L0) consists of local climate zone (LCZ) maps of cities; each LCZ category is associated with a range of values for model-relevant surface descriptors (roughness, impervious surface cover, roof area, building heights, etc.). Levels 1 (L1) and 2 (L2) will provide specific intra-urban values for other relevant descriptors at greater precision, such as data morphological forms, material composition data, and energy usage. This article describes the status of the WUDAPT project and demonstrates its potential value using observations and models. As a community-based project, other researchers are encouraged to participate to help create a global urban database of value to urban climate scientists.

The effects of urban heat islands (UHIs) have a substantial bearing on the sustainability of cities and environs. This paper examines the efficacy of green and cool roofs as potential UHI mitigation strategies to make cities more resilient against UHI. We have employed the urbanized version of the Weather Research and Forecasting (uWRF) model at high (1 km) resolution with physically-based rooftop parameterization schemes (conventional, green and cool), a first-time application to the Chicago metropolitan area. We simulated a hot summer period (16-18 August 2013) and assessed (i) UHI reductions for different urban landuse with green/cool roofs, (ii) the interaction of lake breeze and UHI, and (iii) diurnal boundary layer dynamics. The performance of uWRF was evaluated using sensible heat flux and air temperature measurements from an urban mini-field campaign. The simulated roof surface energy balance captured the energy distribution with respective rooftop algorithms. Results showed that daytime roof temperature reduced and varied linearly with increasing green roof fractions, from less than 1°C for the case of 25% green roof to ∼3°C during peak daytime for 100% green roof. Diurnal transitions from land to lake breeze and vice versa had a substantial impact on the daytime cycle of roof surface UHI, which had a 3-4 hour lag in comparison to 2 m UHI. Green and cool roofs reduced horizontal and vertical wind speeds and affected lower atmosphere dynamics, including reduced vertical mixing, lower boundary layer depth, and weaker convective rolls. The lowered wind speeds and vertical mixing during daytime led to stagnation of air near the surface, potentially causing air quality issues. The selection of green and cool roofs for UHI mitigation should therefore carefully consider the competing feedbacks. The new results for regional land-lake circulations and boundary layer dynamics from this study may be extended to other urbanized areas, particularly to coastal areas.

Croplands are important in land‐atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled Weather Research and Forecasting/Noah with multiparameterization (Noah‐MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah‐MP and evaluated the enhanced model (Noah‐MP‐Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed‐leaf area index (LAI)‐driven methods in Noah‐MP, the Noah‐MP‐Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah‐MP‐Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah‐MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah‐MP‐Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah‐MP allows further crop‐related studies and development.