SOLWEIG

SOLWEIG is a radiation-dedicated module of the Urban Multi-scale Environmental Predictor (UMEP) [128], which was developed by the Earth Sciences Department in Gothenburg University, and it is extensively described by Lindberg et al. [129]. UMEP is a climate service plugin for QGIS. It is an open-source tool and can be used for various applications related to urban metabolism processes such as thermal energy balance, energy consumption, etc. UMEP consists of a coupled modelling system, which combines "stateof-the-art" 1D and 2D models related to the processes essential for scale-independent urban climate estimations. SOLWEIG, together with the energy balance model SUEWS available in the UMEP QGIS plugin, simulates spatial gradients of 3D radiation fluxes and the mean radiant temperature (Tmrt); therefore, it is particularly useful for the assessment of thermal comfort indicators in the cityscape. Mean radiant temperature is derived by modelling short- and long-wave radiation fluxes in six directions, i.e., upward, downward, and from the four cardinal points (horizon) taking into account angular factors. The model requires a relatively limited number of inputs, such as irradiance components (direct, diffuse radiation), air temperature, relative humidity, urban geometry, and geographical coordinates. The output refers mainly to radiation components' fluxes and Tmrt distribution.

The framework theory, based on which the mean radiant temperature is calculated, is that one introduced by Hoppe [130] in which radiation fluxes in all six directions are considered. As an energy balance model, it presents the general shortcomings of this certain family of models; e.g., it disregards the velocity pattern in the domain of interest as well as its fluctuations (turbulence). Another shortcoming is that SOLWEIG does not account for evapotranspiration from vegetation. Lindberg et al. (2008) [129] demonstrated its usefulness by performing mean radiant temperature simulations in an urban area of Gothenburg and validated numerical results through comparisons with field measurements. Using SOLWEIG, Chen et al. [131] investigated the spatial variation of mean radiant temperature in different urban settings in Shanghai towards the detection of "hot-spots" with the highest thermal discomfort within the cityscape. In terms of its accuracy, it has been proven that SOLWEIG is equally useful with the microscale ENVI-met model referring to the modelling of the radiation field; however, it presents higher discrepancies because of its less comprehensive calculation model of diffuse radiation [132]. Hosseini-Haghighi et al. [133] developed a systematic approach to upgrade the outdoor thermal comfort using ArcGIS CityEngine for 3D city modeling and SOLWEIG as the climate assessment model, in view of the warmest forecasted year, 2047. The suggested workflow revealed the heat-stress areas and facilitated the efficient intervention regarding tree placement as a passive strategy for heat mitigation.

#### Rayman

The Rayman [134] software was developed in the Meteorological Institute of Albert Ludwigs University of Freiburg. The capabilities of the tool are described by Matzarakis et al. [135]. Similarly to SOLWEIG, it is a variant of energy balance models, and it mainly computes radiant heat conservation between human skin and its environment. It focuses on the calculation of the mean radiant temperature towards the prediction

of thermal comfort conditions. The most important inputs required are Geographical coordinates, meteorological data (temperature, relative humidity, and cloud covering), personal parameters (clothing and activity level), Geological morphology, and urban features (buildings, trees). The results obtained by the model include, among others, Distribution of mean radiant temperature, radiation fluxes, and thermal comfort indices (PMV and PET). In contrast to SOLWEIG it computes more thermal comfort indicators and comprises a more user-friendly environment. However, it should be mentioned that Rayman disregards evapotranspiration from vegetation, while it treats trees as simple obstacles to radiation fluxes. Wind-induced effects and turbulence flow are also ignored. In comparison to SOLWEIG, RayMan has a higher calculation sensitivity and faster simulation speed, while it achieves the best accuracy at high solar altitudes on clear summer days [132]. Battisti [136] used both Rayman and ENVI-met tools to study the impact of using cool materials enhanced with more vegetation and permeable surfaces and demonstrated dramatic improvements regarding summer thermal comfort. Using both ENVI-met and Rayman, Peng and Jim [137] verified that green-roof cooling effects are not restricted to rooftops but extend to the ground to improve neighborhood microclimate.
