D. Carvalho

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5-Yonsei University-Noah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques

Wind resource evaluation in two sites located in Portugal was performed using the mesoscale modelling system Weather Research and Forecasting (WRF) and the wind resource analysis tool commonly used within the wind power industry, the Wind Atlas Analysis and Application Program (WAsP) microscale model. Wind measurement campaigns were conducted in the selected sites, allowing for a comparison between in situ measurements and simulated wind, in terms of flow characteristics and energy yields estimates.

Influence of urban resilience measures in the magnitude and behaviour of energy fluxes in the city of Porto (Portugal) under a climate change scenario

Different urban resilience measures, such as the increase of urban green areas and the application of white roofs, were evaluated with the WRF-SUEWS modelling system. The case study consists of five heat waves occurring in Porto (Portugal) urban area in a future climate scenario. Meteorological forcing and boundary data were downscaled for Porto urban area from the CMIP5 earth system model MPI-ESM, for the Representative Concentration Pathway RCP8.5 scenario. The influence of different resilience measures on the energy balance components was quantified and compared between each other. Results show that the inclusion of green urban areas increases the evaporation and the availability of surface moisture, redirecting the energy to the form of latent heat flux (maximum increase of +200Wm(-2)) rather than to sensible heat. The application of white roofs increases the solar radiation reflection, due to the higher albedo of such surfaces, reducing both sensible and storage heat flux (maximum reductions of -62.8 and -35Wm(-2), respectively). The conjugations of the individual benefits related to each resilience measure shows that this measure is the most effective one in terms of improving the thermal comfort of the urban population, particularly due to the reduction of both sensible and storage heat flux. The obtained results contribute to the knowledge of the surface-atmosphere exchanges and can be of great importance for stakeholders and decision-makers.

Modelling Resilient Measures to Climate Change Impacts on Urban Air Quality

Considering different resilience measures such as the increase of urban green areas and the application of white roofs, a set of resilience scenarios were evaluated with a cascade of numerical models (MPI-ESM-LR/WRF/CAMx) using as case study a future heat wave occurring in Porto (Portugal) urban area. Meteorological forcing and boundary data was derived from the CMIP5 earth system model MPI-ESM (Representative Concentration Pathway RCP 8.5) downscaled to Porto urban area. The influence of different resilience scenarios on the air quality was quantified and compared for the different scenarios. The results show that all tested measures lead to an increased resilience to CC impacts, promoting the reduction of ozone concentrations. The application of green roofs was the measure that shows more benefits to air quality.