The application is integrated in a cloud environment, its use is simple and it is highly automated, in such way that an end-user can execute the computational tool just by choosing the area where he/she wants to get the wind information; thus, no previous knowledge is needed regarding numerical simulation, nor necessary to have computational resources to use the tool developed.

Once the end-user chooses a location, the Weather Research & Forecasting Model, WRF, carries out a weather reanalysis along one year, centered in the location of interest. WRF is an open-source software widely used for weather forecasting and research of atmospheric phenomena. Its maximum standard resolution (around 1km) is not enough to study the local wind in urban environments. Thus, the results obtained are treated from the reanalysis are treated by means of an ad-hoc developed software to determine a reduced number of typical events (wind speed and direction) that represent the wind behaviour at the chosen location.

In parallel, an application based in GIS techiques is run, to build a 3D model of the geometry at the location chosen by the end-user. This application uses public information sources and open-source code, such as QGIS and Meshlab. (**This module of the tool is currently under development and works only for Spain; for other countries, a 3D model of the area of interest should be necessary**).

Next, the computational meshes required to simulate the selected events are generated with SnappyHexMesh (SHM), an open-source mesh generator. To that end, SHM uses as data input the 3D model of the urban environment previously created and the direction of the selected events (in order to properly orient each computational mesh).

The next step is the CFD simulation of each event, using the open-source code OpenFOAM. This software solves the air flow in a detailed way in the chosen environment with a resolution of 1.5 m. As input, OpenFOAM uses the computational meshes just created and the wind velocity profile (as a function of height), calculated by WRF for each event.

Finally, the results of these detailed simulations are treated statistically to obtain a wind rose and the Weibull parameters at roofs on the selected area. Besides, several images are automatically generated representing velocity contours and Weibull parameters at a number of generic views. To that end, a series of scripts have been developed for the task, using Python language and Paraview, an open-source tool for data analysis and visulization.