This paper describes and evaluates physical parameterizations accounting for the effect of rooftop mitigation strategies (RMSs) on the urban environment, in the context of the mesoscale model Weather Research and Forecasting (WRF). Through the new implementation, the sensitivity of near‐surface air temperature and building energy consumption to different RMSs is evaluated by means of numerical simulations in idealized urban areas, for typical summer and winter conditions. Rooftop mitigation strategies considered include cool roofs, green roofs, and rooftop photovoltaic panels. The reference case simulations are performed assuming buildings made by bricks, with roof composed of clay tiles. Results indicate that near‐surface air temperature is reduced by cool and green roofs during summer: cool roofs are the most efficient in decreasing air temperature, followed by irrigated green roofs. Photovoltaic panels, instead, induce a temperature increase during daytime and a small decrease during nighttime. Cool roofs reveal to be the most efficient strategy in reducing the energy consumption by air conditioning systems. During wintertime, green roofs maintain a higher near‐surface air temperature than clay tile roofs and largely decrease energy consumption. Even PVPs increase air temperature, as in the summer case. On the other hand, cool roofs reduce near‐surface air temperature during daytime, inducing an increase in energy consumption. The results presented here show that the parameterization schemes implemented in the WRF model can be a valuable tool to evaluate the effects of mitigation strategies in the urban environment.

Comprehensive studies comparing impacts of building and street levels interventions on air temperature at metropolitan scales are still lacking despite increased urban heat‐related mortality and morbidity. We therefore model the impact of 9 interventions on air temperatures at 2 m during 2 hot days from the summer 2018 in the Greater London Authority area using the WRF BEP‐BEM climate model. We find that on average cool roofs most effectively reduce temperatures (∼−1.2°C), outperforming green roofs (∼0°C), solar panels (∼−0.5°C) and street level vegetation (∼−0.3°C). Application of air conditioning across London (United Kingdom) increases air temperatures by ∼+0.15°C. A practicable deployment of solar panels could cover its related energetic consumption. Current practicable deployments of green roofs and solar panels are ineffective at large scale reduction of temperatures. We provide a detailed decomposition of the surface energy balance to explain changes in air temperature and guide future decision‐making.

A new one-dimensional 1.5-order planetary boundary layer (PBL) scheme, based on the K–ε turbulence closure applied to the Reynolds-averaged Navier–Stokes (RANS) equations, is developed and implemented within the Weather Research and Forecasting (WRF) Model. The new scheme includes an analytic solution of the coupled equations for turbulent kinetic energy and dissipation rate. Different versions of the PBL scheme are proposed, with increasing levels of complexity, including a model for the calculation of the Prandtl number, a correction to the dissipation rate equation, and a prognostic equation for the temperature variance. Five different idealized cases are tested: four of them explore convective conditions, and they differ in initial thermal stratification and terrain complexity, while one simulates the very stable boundary layer case known as GABLS. For each case study, an ensemble of different large-eddy simulations (LES) is taken as reference for the comparison with the novel PBL schemes and other state-of-the-art 1- and 1.5-order turbulence closures. Results show that the new PBL K–ε scheme brings improvements in all the cases tested in this study. Specifically, the more significant are obtained with the turbulence closure including a prognostic equation for the temperature variance. Moreover, the largest benefits are obtained for the idealized cases simulating a typical thermal circulation within a two-dimensional valley. This suggests that the use of prognostic equations for dissipation rate and temperature variance, which take into account their transport and history, is particularly important with the increasing complexity of PBL dynamics.

Various urban canopy parameterizations (UCPs) have been developed in the last two decades to take into account the modifications induced by buildings on mean flow and turbulent fields in mesoscale meteorological models, the typical spatial resolution of which cannot resolve urban structures explicitly. In particular, several multilayer UCPs have been proposed, successfully reproducing wind‐flow characteristics in the urban environment. However, they often rely on length scales for the calculation of the eddy viscosity and the dissipation rate, which need to be tuned for various urban configurations. The main objective of this work is to address this shortcoming, by developing a new one‐dimensional turbulence closure that takes building‐induced turbulence into account independently of turbulence length scales. This model directly solves not only the equation for turbulent kinetic energy but also the equation for its dissipation rate (– model). Similar closure schemes have been successfully adopted for vegetated canopies, but their applicability to urban canopies is still unknown. The performance of the new – model, with additional sources and sinks for wind speed, turbulent kinetic energy, and dissipation rate, is tested by means of single‐column simulations in idealized urban areas, using different building packing densities. Results are in good agreement with spatially averaged building‐resolving CFD simulations. In particular, vertical profiles of mean and turbulent variables show better results with respect to simulations using turbulence closures adopting a parameterization of turbulence length scales. The best improvements are obtained for wind speed, reducing errors to half the typical values for standard UCP for high packing densities, and for the dissipation rate. Furthermore, besides the enhancement in the reproduction of the mean flow for urban areas, the proposed turbulence closure does not need additional tuning of coefficients depending on the packing density, resulting in a more general and efficient scheme.

In response to the global challenges brought on by climate change, cities around the world are adapting, innovating through nature-based strategies for sustainable development. Climate adaptation requires new interdisciplinary approaches in which different disciplines as well as research and practice proactively co-create and collaborate on adaptation to reduce the ongoing effects of anthropogenic climate change. Although awareness on climate adaptation is on the rise, new approaches for urban development are still in development. Moreover, existing approaches mainly focus on local-scale levels or lack a crossover with urban and landscape planning. The present contribution offers an example of an integrated approach bridging urban climatology, landscape planning, and governance to assess and develop climate adaptation solutions linking city and district levels. The city of Verona was taken as a case study to test this approach and its implications for the development of a green and blue infrastructure with a climate-responsive master plan for the district of Verona South. Through critical reflection on the application of the approach to the case study, we aimed to identify its potentials and barriers. Based on this reflection, we provide herein recommendations on how climate modelling can be integrated into planning, as well as on how urban planners and urban climatologists can support each other in making credible and salient climate adaptation solutions.