@inproceedings{24551,
  abstract     = {{Access to precise meteorological data is crucial to be able to plan and install renewable energy systems 
such as solar power plants and wind farms. In case of solar energy, knowledge of local irradiance and air temperature 
values is very important. For this, various methods can be used such as installing local weather stations or using 
meteorological data from different organizations such as Meteonorm or official Deutscher Wetterdienst (DWD). An 
alternative is to use satellite reanalysis datasets provided by organizations like the National Aeronautics and Space 
Administration (NASA) and European Centre for Medium-Range Weather Forecasts (ECMWF). In this paper the 
“Modern-Era Retrospective analysis for Research and Applications” dataset version 2 (MERRA-2) will be presented, 
and its performance will be evaluated by comparing it to locally measured datasets provided by Meteonorm and DWD. 
The analysis shows very high correlation between MERRA-2 and local measurements (correlation coefficients of 0.99) 
for monthly global irradiance and air temperature values. The results prove the suitability of MERRA-2 data for 
applications requiring long historical data. Moreover, availability of MERRA-2 for the whole world with an acceptable 
resolution makes it a very valuable dataset.}},
  author       = {{Khatibi, Arash and Krauter, Stefan}},
  booktitle    = {{Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021)}},
  isbn         = {{3-936338-78-7}},
  keywords     = {{Energy potential estimation, Photovoltaic, Solar radiation, Temperature measurement, Satellite data, Meteonorm, MERRA-2, DWD}},
  pages        = {{1141 -- 1147}},
  title        = {{{Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD)}}},
  doi          = {{10.4229/EUPVSEC20212021-5BV.4.11}},
  year         = {{2021}},
}

@article{21265,
  abstract     = {{<jats:p>Fast-growing energy demand of the world makes the researchers focus on finding new energy sources or optimizing already-developed approaches. For an efficient use of solar and wind energy in an energy system, correct design and sizing of a power system is of high importance and improving or optimizing the process of data obtaining for this purpose leads to higher performance and lower cost per unit of energy. It is essential to have the most precise possible estimation of solar and wind energy potential and other local weather parameters in order to fully feed the demand and avoid extra costs. There are various methods for obtaining local data, such as local measurements, official organizational data, satellite obtained, and reanalysis data. In this paper, the Modern-Era Retrospective analysis for Research and Applications dataset version 2 (MERRA-2) dataset provided by NASA is introduced and its performance is evaluated by comparison to various locally measured datasets offered by meteorological institutions such as Meteonorm and Deutscher Wetterdienst (DWD, or Germany’s National Meteorological Service) around the world. After comparison, correlation coefficients from 0.95 to 0.99 are observed for monthly global horizontal irradiance values. In the case of air temperature, correlation coefficients of 0.99 and for wind speed from 0.81 to 0.99 are observed. High correlation with ground measurements and relatively low errors are confirmed, especially for irradiance and temperature values, that makes MERRA-2 a valuable dataset, considering its world coverage and availability.</jats:p>}},
  author       = {{Khatibi, Arash and Krauter, Stefan}},
  issn         = {{1996-1073}},
  journal      = {{Energies}},
  keywords     = {{Solar irradiance, MERRA 2, Meteonorm, DWD}},
  number       = {{4}},
  publisher    = {{MDPI}},
  title        = {{{Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications}}},
  doi          = {{10.3390/en14040882}},
  volume       = {{14}},
  year         = {{2021}},
}