NEWA Report on uncertainty quantification Deliverable D4.4

This report explores the quantification of uncertainty in the NEWA production run and probabilistic ensemble. Uncertainty quantification relies on the availability of model simulations and observations. In areas where observations are not available, uncertainty addresses the quantification of the variability resulting from the sensitivity of the model chain tool resulting from the sampling of all the available model configurations tested. Uncertainty can be here regarded as the quantification of model sensitivity or model spread. In areas with availability of observations, the realism of the model ensemble is evaluated by establishing metrics of model-data comparison. Therefore, uncertainty is understood here as the result of the contributions of model sensitivity to different model setups, and of model errors in a model-data comparison framework.

The first part of this report explores the uncertainty derived from model sensitivity subjected to the decisions taken regarding the use of different models setups and how these produce variability in model output. The range of this variability has been regarded as spread in model output and has been quantified in various manners. The second part of this report addresses how model performance can be characterised with the data at hand and whether decisions regarding selection of a given model setup for a production run can be taken on the basis of model performance in a variety of situations, using different variables and datasets as observational targets: wind data from tall masts in the Vestas database; wind speed profiles from tall masts and offshore lidars; surface (10-meter) wind data; satellite data and reanalysis outputs.