Evaluation of thermal indices for their applicability in obstacle-resolving meteorology models

A thermally comfortable design of outdoor spaces favors social interaction and outdoor activities and thus contributes to the overall well-being of urban dwellers. To assess such a design, obstacle-resolving models (ORM) combined with thermal indices may be used. This paper reviews existing thermal indices to identify those suitable for thermal comfort assessment with ORMs. For the identification, 11 criteria and six index features are derived from literature analysis focusing on the characteristics of human environmental heat exchange, of outdoor urban environments, and of ORMs. An air temperature weighted world population distribution is calculated to derive the minimal air temperature range; a thermal index should cover to be applicable to 95% of the world population. The criteria are applied to 165 thermal indices by reviewing their original publications. Results show that only four thermal indices are suitable to be applied globally in their current form to various outdoor urban environments and also fulfill the requirements of ORMs. The evaluation of the index features shows that they differ with respect to the comprehensiveness of the thermophysiological model, the assessed human response, the treatment of clothing and activity, and the computational costs. Furthermore, they differ in their total application frequency in past ORM studies and in their application frequency for different climatic zones, as a systematic literature analysis of thermal comfort studies employing ORMs showed. By depicting the differences of the thermal indices, this paper provides guidance to select an appropriate thermal index for thermal comfort studies with ORMs

Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation

With increasing number and proximity of wind farms, it becomes crucial to consider wind farm effects (WFEs) in the numerical weather prediction (NWP) models used to forecast power production. Furthermore, these WFEs are also expected to affect other weather-related parameters at least locally. Thus, we implement the explicit wake parameterization (EWP) in the NWP model HARMONIE–AROME (hereafter HARMONIE) along-side the existing wind farm parameterization (WFP) by Fitch et al. (2012) (FITCH). We evaluate and compare the two WFPs against research flight measurements as well as against similar simulations performed with the Weather Research and Forecasting (WRF) model using case studies. The case studies include a case for WFEs above a wind farm as well as two cases for WFEs at hub height in the wake of farms. The results show that EWP and FITCH have been correctly implemented in HARMONIE. For the simulated cases, EWP underestimates the WFEs on wind speed and strongly underestimates the effect on turbulent kinetic energy (TKE). FITCH agrees better with the observations, and WFEs on TKE are particularly well captured by HARMONIE–FITCH. After this successful evaluation, simulations with all wind turbines in Europe will be performed with HARMONIE and presented in the second part of this paper series.</p