Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications
Abstract
:1. Introduction
2. Power Potential Estimation
2.1. Local Data Measurements
2.2. Official Meteorological Data
2.3. Satellite Obtained and Reanalysis Data
3. MERRA–2
4. Meteonorm
5. DWD
6. Methodology
7. Results and Discussion
7.1. MERRA-2 vs. Meteonorm
7.2. MERRA-2 vs. DWD
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Durrani, S.P.; Balluff, S.; Wurzer, L.; Krauter, S. Photovoltaic yield prediction using an irradiance forecast model based on multiple neural networks. J. Mod. Power Syst. Clean Energy 2018, 6, 255–267. [Google Scholar] [CrossRef]
- Yang, D.; Bright, J.M. Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years. Sol. Energy 2020, 210, 3–19. [Google Scholar] [CrossRef]
- Pfenninger, S.; Staffell, I. Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 2016, 114, 1251–1265. [Google Scholar] [CrossRef] [Green Version]
- Juruš, P.; Eben, K.; Resler, J.; Krč, P.; Kasanický, I.; Pelikán, E.; Brabec, M.; Hošek, J. Estimating climatological variability of solar energy production. Sol. Energy 2013, 98, 255–264. [Google Scholar] [CrossRef]
- Santos, J.; Sakagami, Y.; Haas, R.; Passos, J.; Machuca, M.; Radünz, W.; Dias, E.; Lima, M. Wind speed evaluation of MERRA-2, ERA-interim and ERA-5 reanalysis data at a wind farm located in brazil. In Proceedings of the ISES Solar World Congress 2019 (ISES 2019), Santiago, Chile, 4–7 November 2019. [Google Scholar]
- Sianturi, Y.; Marjuki; Sartika, K. Evaluation of ERA5 and MERRA2 reanalyses to estimate solar irradiance using ground observations over Indonesia region. AIP Conf. Proc. 2020, 2223, 020002. [Google Scholar]
- Bosilovich, M.G.; Lucchesi, R.; Suarez, M. MERRA-2: File Specification. GMAO Office Note No. 9 (Version 1.1). 2016. Available online: https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich785.pdf (accessed on 19 June 2018).
- Jourdier, B. Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France. Adv. Sci. Res. 2020, 17, 63–77. [Google Scholar] [CrossRef]
- Zhang, X.; Lu, N.; Jiang, H.; Yao, L. Evaluation of reanalysis surface incident solar radiation data in China. Sci. Rep. 2020, 10, 3494. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bendfeld, J.; Balluff, S.; Wübbeke, S.; Krauter, S. Performance of MERRA2 data compared to floating LIDAR. In Proceedings of the DEWEK 2017, Bremen, Germany, 17–18 October 2017. [Google Scholar]
- Bendfeld, J.; Balluff, S. Performance of MERRA data in Offshore Windenergy applications. In Proceedings of the DEWEK 2015, Bremen, Germany, 19–20 May 2015. [Google Scholar]
- Meteonorm. Meteonorm Software. Available online: https://meteonorm.com/en/ (accessed on 28 August 2020).
- Deutscher Wetterdienst (DWD). Available online: https://www.dwd.de/EN/aboutus/aboutus_node.html (accessed on 5 February 2021).
- Huld, T.; Urraca, R.; Gracia Amillo, A.; Trentmann, J. A global hourly solar radiation data set using satellite and reanalysis data. In Proceedings of the 33rd European Photovoltaic Solar Energy Conference and Exhibition, Amsterdam, The Netherlands, 25–29 September 2017. [Google Scholar]
- Gelaro, R.; Mccarty, W.; Suárez, M.J.; Todling, R.; Molod, A.; Takacs, L.; Randles, C.A.; Darmenov, A.; Bosilovich, M.G.; Reichle, R.; et al. The modern-era retrospective analysis for research and applications, Version 2 (MERRA-2). J. Clim. 2017, 30, 5419–5454. [Google Scholar] [CrossRef] [PubMed]
- Meteonorm, Meteonorm Documents. Available online: https://meteonorm.com/assets/downloads/broschuere-mn-7.1.pdf (accessed on 28 August 2020).
- Deutscher Wetterdienst (DWD). Sphere of Tasks. Available online: https://www.dwd.de/EN/aboutus/tasks/task_node.html (accessed on 5 February 2021).
- DWD. Available online: ftp://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/hourly/solar/ST_Stundenwerte_Beschreibung_Stationen.txt (accessed on 5 February 2021).
- DWD. Available online: ftp://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/hourly/air_temperature/historical/TU_Stundenwerte_Beschreibung_Stationen.txt (accessed on 5 February 2021).
Parameter Name | Description | Units |
---|---|---|
ALBEDO | “Surface albedo” | 1 |
CLDTOT | “Total cloud area fraction” | 1 |
SWGDN | “Surface incoming shortwave flux” | W/m2 |
SWGNT | “Surface net downward shortwave flux” | W/m2 |
TS | “Surface skin temperature” | K |
T10M | “10-meter air temperature” | K |
U10M | “10-meter eastward wind” | m/s |
V10M | “10-meter northward wind” | m/s |
PS | “Surface pressure” | Pa |
Station | Meteonorm Coordinates | MERRA-2 Coordinates | Distance (km) ≈ | Altitude Difference (m) ≈ |
---|---|---|---|---|
Adelboden (Switzerland) | 46.492° N, 7.5611° E | 46.5° N, 7.5° E | 4.73 | 1038 |
Brisbane (Australia) | 27.383° S, 153.1° E | 27.5° S, 153.125° E | 13.30 | 5 |
Burlington (USA) | 44.467° N, 73.15° W | 44.5° N, 73.125° W | 4.19 | 3 |
Puerto Montt-El Tepu (Chile) | 41.417° S, 73.083° W | 41.5° S, 73.125° W | 9.82 | 27 |
Bremen (Germany) | 53.05° N, 8.8° E | 53° N, 8.75° E | 6.49 | 5 |
Oroomieh (Iran) | 37.533° N, 45.083° E | 37.5° N, 45° E | 8.19 | 93 |
Skagen Fyr (Denmark, off-shore) | 57.733° N, 10.633° E | 57.5° N, 10.625° E | 25.89 | 0 |
Minamitorishima (Japan, off-shore) | 24.3° N, 153.967° E | 24.5° N, 153.75° E | 31.26 | 0 |
Parameter | Name in Meteonorm | Name in MERRA-2 |
---|---|---|
Mean irradiance of global radiation horizontal | Gh | SWGDN |
Air temperature | Ta | T2M |
Wind speed (10 m) | FF | U10M, V10M |
Station | Radiation Period | Gh Uncertainty | Wind and Temperature Period | Ta Uncertainty |
---|---|---|---|---|
Adelboden (Switzerland) | 1996–2015 | 3% | 2000–2009 | 0.3 °C |
Brisbane (Australia) | 1990–2008 | 2% | 2000–2009 | 0.3 °C |
Burlington (USA) | 1991–2005 | 3% | 2000–2009 | 0.3 °C |
Puerto Montt-El Tepu (Chile) | 1997–2013 | 4% | 2000–2009 | 0.3 °C |
Bremen (Germany) | 2006–2015 | 2% | 2000–2009 | 0.3 °C |
Oroomieh (Iran) | 1985–2000 | 3% | 2000–2009 | 0.3 °C |
Skagen Fyr (Denmark, off-shore) | 2001–2010 | 2% | 2000–2009 | 0.3 °C |
Minamitorishima (Japan, off-shore) | 1991–2010 | 2% | 2000–2009 | 0.3 °C |
Global Irradiance | R | MAE (Wh/m2 d) | RMSE (Wh/m2 d) | NRMSE |
---|---|---|---|---|
Adelboden | 0.9973 | 759.02 | 879.24 | 0.205 |
Brisbane | 0.9925 | 416.44 | 469.52 | 0.122 |
Burlington | 0.9956 | 415.87 | 479.11 | 0.097 |
Puerto Montt-El Tepu | 0.9986 | 872.30 | 1004.41 | 0.215 |
Bremen | 0.9974 | 567.95 | 700.28 | 0.148 |
Oroomieh | 0.9997 | 194.55 | 207.09 | 0.034 |
Skagen Fyr | 0.9986 | 140.65 | 177.03 | 0.029 |
Minamitorishima | 0.9593 | 284.01 | 334.64 | 0.095 |
Air Temperature | R | MAE (°C) | RMSE (°C) | NRMSE |
---|---|---|---|---|
Adelboden | 0.9995 | 2.59 | 2.85 | 0.182 |
Brisbane | 0.9972 | 0.51 | 0.66 | 0.064 |
Burlington | 0.9998 | 1.68 | 1.84 | 0.066 |
Puerto Montt-El Tepu | 0.9982 | 0.31 | 0.36 | 0.046 |
Bremen | 0.9997 | 0.61 | 0.71 | 0.046 |
Oroomieh | 0.9977 | 0.87 | 1.13 | 0.043 |
Skagen Fyr | 0.9994 | 0.25 | 0.32 | 0.020 |
Minamitorishima | 0.9929 | 0.28 | 0.33 | 0.052 |
Wind Speed 10 m | R |
---|---|
Brisbane | 0.8128 |
Burlington | 0.9011 |
Puerto Montt-El Tepu | 0.9180 |
Bremen | 0.9453 |
Skagen Fyr | 0.9900 |
Minamitorishima | 0.8809 |
Year | Hourly Global Irradiance Measurements (GI) | Hourly Surface Temperature Measurements (TS) |
---|---|---|
2016 | 8783 | 8783 |
2017 | 8717 | 8759 |
MERRA-2 vs. DWD | Global Irradiance 2016 | Global Irradiance 2017 | Surface Temperature 2016 | Surface Temperature 2017 |
---|---|---|---|---|
R | 0.9164 | 0.9145 | 0.9677 | 0.9690 |
MAE | 42.12 W/m2 | 41.50 W/m2 | 1.82 °C | 1.71 °C |
RMSE | 87.22 W/m2 | 85.93 W/m2 | 2.23 °C | 2.08 °C |
NRMSE | 0.0957 | 0.0913 | 0.0531 | 0.0518 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Khatibi, A.; Krauter, S. Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications. Energies 2021, 14, 882. https://doi.org/10.3390/en14040882
Khatibi A, Krauter S. Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications. Energies. 2021; 14(4):882. https://doi.org/10.3390/en14040882
Chicago/Turabian StyleKhatibi, Arash, and Stefan Krauter. 2021. "Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications" Energies 14, no. 4: 882. https://doi.org/10.3390/en14040882
APA StyleKhatibi, A., & Krauter, S. (2021). Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications. Energies, 14(4), 882. https://doi.org/10.3390/en14040882