Pedro Quiroga Posted April 4, 2020 Posted April 4, 2020 Hi support team,I want to use results from a mesoscale model to make cross predictions in WAsP, I’ve read some papers where two maps are used, one mesoscale map to remove the effects over the mesoscale simulations, and a microscale map to insert the terrain effects with a better resolution. Is this procedure do manually? I mean, you use the mesoscale map to generate the GWC, then replace the previous map with the microscale map and make predictions over desired sites. In that case, is it possible to use the cross prediction script without recalculating the GWC?
Andreas Posted April 5, 2020 Posted April 5, 2020 Hi Pedro,If you have a GWC, then you can use your WAsP cross-prediction script, irrespectively if the GWC stems from measurement or mesoscale simulations. The hard part is to generate the GWC from mesoscale simulations. Generalisation depends not only on your mesoscale map but also on your mesoscale simulation parameters. When making a wind atlas from mesoscale-simulations, we generally try many different setups of the mesoscale model and validate each against measurements before we decide on which configuration we will use for production runs. Therefore, it is not trivial to generate the GWC files, but once produced it is trivial to apply them in WAsPKind regards,Andreas
Giorgos Posted October 13, 2023 Posted October 13, 2023 Hi Andreas, I have mesoscale EMD-WRF Europe+ ERA5 Mesoscale data and measurements from a mast at a distance around 1.5km. However, the cross prediction of each other data source deviates more than 20%. What is the reason for that, topography?, roughness map, wasp parameters? I understand that measurements are more reliable than mesoscale data. But, if everything else is set up correctly, shouldn 't the two data sources cross-predict each other with less deviation? I remark that the correlation among the two data sources is very good. ( >0.8 in 10-min averaging) Thank you Giorgos
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