%0 Journal Article %1 Boilley2015Comparison %A Boilley, Alexandre %A Wald, Lucien %D 2015 %J Renewable Energy %K solar dataset energy renewables era merra %P 135--143 %R 10.1016/j.renene.2014.09.042 %T Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface %U http://dx.doi.org/10.1016/j.renene.2014.09.042 %V 75 %X Highlights • Daily solar irradiation estimated by MERRAA and ERA-Interim re-analyses is analysed. • They are compared to ground measurements from stations in Europe and Africa. • Re-analyses often predict clear sky conditions while actual conditions are cloudy. • Variability of errors within a homogeneous area is surprisingly large. • Satellite-derived data sets offer less uncertainty and should be preferred. Abstract This paper compares the daily solar irradiation available at surface estimated by the MERRA (Modern-Era Retrospective Analysis for Research and Applications) re-analysis of the NASA and the ERA-Interim re-analysis of the European Center for Medium-range Weather Forecasts (ECMWF) against qualified ground measurements made in stations located in Europe, Africa and Atlantic Ocean. Using the clearness index, also known as atmospheric transmissivity or transmittance, this study evidences that the re-analyses often predict clear sky conditions while actual conditions are cloudy. The opposite is also true though less pronounced: actual clear sky conditions are predicted as cloudy. This overestimation of occurrence of clear sky conditions leads to an overestimation of the irradiation and clearness index by MERRA. The overall overestimation is less pronounced for ERA-Interim because the overestimation observed in clear sky conditions is counter-balanced by underestimation in cloudy conditions. The squared correlation coefficient for clearness index ranges between 0.38 and 0.53, showing that a very large part of the variability in irradiation is not captured by the re-analyses. Within an irradiation homogeneous area, the variability of the bias, root mean square error and correlation coefficient are surprisingly large. MERRA and ERA-Interim should only be used in solar energy with proper understanding of the limitations and uncertainties. In regions where clouds are rare, e.g. North Africa, MERRA or ERA-Interim may be used to provide a gross estimate of monthly or yearly irradiation. Satellite-derived data sets offer less uncertainty and should be preferred.

@article{Boilley2015Comparison, abstract = {Highlights • Daily solar irradiation estimated by MERRAA and ERA-Interim re-analyses is analysed. • They are compared to ground measurements from stations in Europe and Africa. • Re-analyses often predict clear sky conditions while actual conditions are cloudy. • Variability of errors within a homogeneous area is surprisingly large. • Satellite-derived data sets offer less uncertainty and should be preferred. Abstract This paper compares the daily solar irradiation available at surface estimated by the MERRA (Modern-Era Retrospective Analysis for Research and Applications) re-analysis of the NASA and the ERA-Interim re-analysis of the European Center for Medium-range Weather Forecasts (ECMWF) against qualified ground measurements made in stations located in Europe, Africa and Atlantic Ocean. Using the clearness index, also known as atmospheric transmissivity or transmittance, this study evidences that the re-analyses often predict clear sky conditions while actual conditions are cloudy. The opposite is also true though less pronounced: actual clear sky conditions are predicted as cloudy. This overestimation of occurrence of clear sky conditions leads to an overestimation of the irradiation and clearness index by MERRA. The overall overestimation is less pronounced for ERA-Interim because the overestimation observed in clear sky conditions is counter-balanced by underestimation in cloudy conditions. The squared correlation coefficient for clearness index ranges between 0.38 and 0.53, showing that a very large part of the variability in irradiation is not captured by the re-analyses. Within an irradiation homogeneous area, the variability of the bias, root mean square error and correlation coefficient are surprisingly large. MERRA and ERA-Interim should only be used in solar energy with proper understanding of the limitations and uncertainties. In regions where clouds are rare, e.g. North Africa, MERRA or ERA-Interim may be used to provide a gross estimate of monthly or yearly irradiation. Satellite-derived data sets offer less uncertainty and should be preferred.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Boilley, Alexandre and Wald, Lucien}, biburl = {https://www.bibsonomy.org/bibtex/2ff0eb6702a4811db4da75f3aed383e71/pbett}, citeulike-article-id = {13389400}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.renene.2014.09.042}, comment = {(private-note)Open access}, doi = {10.1016/j.renene.2014.09.042}, interhash = {5e5e5b457f6c694dfa5823e198583cf2}, intrahash = {ff0eb6702a4811db4da75f3aed383e71}, issn = {09601481}, journal = {Renewable Energy}, keywords = {solar dataset energy renewables era merra}, month = mar, pages = {135--143}, posted-at = {2014-10-12 17:36:44}, priority = {2}, timestamp = {2018-06-22T18:34:29.000+0200}, title = {Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface}, url = {http://dx.doi.org/10.1016/j.renene.2014.09.042}, volume = 75, year = 2015 }