Report on WRF model sensitivity studies and specifications for the mesoscale wind atlas production runs:Deliverable D4.3

This report describes the sensitivity studies performed with the mesoscale model WRF in preparation of the mesoscale wind atlas production runs. The objective of this work was to find a model setup that is not just a best practice setup but well-founded and based on scientific evaluation. We started with performing some initial sensitivity experiments changing the PBL scheme and the initialisation of the model. The work was distributed among several partners, each conducting the same set of experiments but on a different domain. The objective of this first phase was to ensure that everybody speaks the same language in terms of applying WRF in the context of NEWA. The results were analysed and compared in terms of the mean wind climate. To draw conclusions regarding the quality of the experiments, the results of one domain were compared to tall mast observations. Overall the model showed a good performance with slightly better results for one of the two tested PBL schemes (MYNN) and weekly initialisation of simulations (compared to daily). In the next phase, further sensitivity tests were conducted for one of the previously defined domains, varying a multitude of parameters as e.g. model version, vertical resolution, forcing data and land surface parameterisation. These studies showed that virtually each parameter change is affecting the results in some way, while significant effects on the wind climate are mostly obtained by changes in physical parameterisation e.g. PBL scheme, representation of the land surface and surface roughness. However, also non-physical parameters as the simulation length and the domain size affects the results considerably. The results suggest to use rather small domains and not too long simulations (in the order of 1–2 weeks). One of the objectives of NEWA is to create a probabilistic wind atlas, i.e. to provide uncertainty information to the mesoscale wind atlas (see Deliverables D3.1 and D4.4). This will be achieved by generating an ensemble of WRF simulations with different model configurations. While the final ensemble to be run over the complete NEWA domain will only include a few members, a much larger ensemble was run for a smaller sub-domain to find the ensemble members that generate the largest spread and will be used in the final NEWA ensemble. A second objective of this initial large ensemble was to find an optimal setup for the mesoscale production run. Based on the experience gained in the previous sensitivity experiments, a 47-member ensemble was assembled and run. The individual members were compared against each other, as well as against tall mast observations. Different metrics were explored to assess the performance of the members, i.e. not only the usual statistical measures as RMSE, BIAS and correlation but also metrics that compare the wind speed distributions. In the final part of this report we present the ultimate WRF setup for the NEWA production run that was run between August 2018 and March 2019 on the MareNostrum supercomputer in Barcelona

FOXES: Farm Optimization and eXtended yield Evaluation Software

Testing publishing to pypi via pypi.ymlIf you use this software, please cite our article in the Journal of Open Source Software

FOXES: Farm Optimization and eXtended yield Evaluation Software

<ul> <li>Bug fixes:<ul> <li>Bugs fixed that messed up the colorbar and the title in animations</li> </ul> </li> <li>Notebooks:<ul> <li>Improved animations in <code>timelines.ipynb</code> and <code>sequential.ipynb</code></li> </ul> </li> </ul> <p><strong>Full Changelog</strong>: <a href="https://github.com/FraunhoferIWES/foxes/commits/v0.5.2.1">https://github.com/FraunhoferIWES/foxes/commits/v0.5.2.1</a></p>If you use this software, please cite our article in the Journal of Open Source Software

FOXES: Farm Optimization and eXtended yield Evaluation Software

Testing publication workflow pypi.ymlIf you use this software, please cite our article in the Journal of Open Source Software

FOXES: Farm Optimization and eXtended yield Evaluation Software

Testing publication workflow pypi.ymlIf you use this software, please cite our article in the Journal of Open Source Software

FOXES: Farm Optimization and eXtended yield Evaluation Software

Testing publishing to pypi via workflow pypi.ymlIf you use this software, please cite our article in the Journal of Open Source Software

FOXES: Farm Optimization and eXtended yield Evaluation Software

<ul> <li>Dependencies:<ul> <li>The <code>windio</code> package is now an optional dependency, to be installed by hand if needed. This is due to windio being not available at conda-forge</li> </ul> </li> <li>Notebooks:<ul> <li>New notebook: <code>sequential.ipynb</code>, creating an animation showing state-by-state wake propagation</li> </ul> </li> </ul> <p><strong>Full Changelog</strong>: <a href="https://github.com/FraunhoferIWES/foxes/commits/v0.5.1">https://github.com/FraunhoferIWES/foxes/commits/v0.5.1</a></p>If you use this software, please cite our article in the Journal of Open Source Software