Quality control of solar radiation data within the South African Weather Service solar radiometric network
DOI:
https://doi.org/10.17159/2413-3051/2019/v30i4a5586Keywords:
Quality control, BSRN, solar radiation, satellite-retrieve irradiance, ground stationsAbstract
This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) quality control procedures applied to the solar radiation data, from September 2013 to December 2017, within the South African Weather Service radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN quality control methodology was 97.79%, 93.64%, 91.60% and 92.23% for long wave downward irradiance (LWD), global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI), respectively, with operational problems largely dominating the percentage of bad data. The overall average performance of the surface solar radiation dataset – Heliosat data records for the GHI estimation for all stations showed a mean bias deviation of 8.28 Wm-2, a mean absolute deviation of 9.06 Wm-2 and the root mean square deviation of 11.02 Wm-2. The correlation, quantified by the square of correlation coefficient (R2), between ground-based and Heliosat-derived GHI time series was ~0.98. The established network has the potential to provide high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies.
Downloads
References
Jäger-Waldau, A. PV Status Report 2016. EUR 28159 EN; 2016, doi:10.2790/682995.
International Energy Agency. Analysis and forecast to 2022. IEA Publications 2017, ISSN 2520-2774.
Sengupta, M.; Habte, A.; Gueymard, C.; Wilbert, S.; Renné, D. Best practices handbook for the collection and use of solar resource data for solar energy applications, Second edition. National Renewable Energy Laboratory (NREL): Colorado, United States, 2017, NREL/TP-5D00-68886.
Antoñanzas-Torres, F.; Sanz-Garcia, A.; Martinez-de-Pison-Ascacibar, F.J.; Perpiñan-Lamiguiero, O. Evaluation and improvement of empirical models of global solar irradiation: Case study northern Spain. Renewable Energy 2013, 60, 604-614.
Meyer, A.J.; van Niekerk, J.L. Towards a Verified DNI Map for South Africa. In Third Southern African Solar Energy Conference, Kruger National Park, South Africa, 11 – 13 May 2015.
Brooks, M.J.; du Clou, S.; van Niekerk, W.L.; Gauche, P.; Leonard, C.; Mouzouris, M.J.; Meyer, R.; van der Westhuizen, N.; van Dyk, E.E.; Vorster, F.J. SAURAN: A new resource for solar radiometric data in Southern Africa. Journal of Energy in Southern Africa 2015, 26, 2-10.
Ciolkosz, D. SASRAD. An Hourly-Timestep Solar Radiation Database for South Africa. Journal of Energy in Southern Africa 2009, 20, 25–34.
Ineichen, P.; Barroso, C.S.; Geiger, B.; Hollmann, R.; Marsouin, A.; Müller, R. Satellite application facilities irradiance products: Hourly time step comparison and validation over Europe. International Journal of Remote Sensing 2009, 30, 5549-5571.
Lee, C. Baseline Surface Radiation Network, World Climate Research Programme, An overview of the requirements and operational issues. Derived from the BSRN Operations Manual Version 2.1, Customer Services Specialist, Kipp & Zonen B.V, 2014.
SANS 204. South African National Standard. Energy efficiency in buildings, Part 1: General requirements. SABS Standards Division. Available online: https://www.sabs.co.za/Sectors-and-Services/Services/Energy/energy_sp.asp (Accessed on 15 September 2013).
Conradie, D.C.U. South Africa’s Climatic Zones: Today, Tomorrow, International Green Building Conference and Exhibition Future Trends and Issues Impacting on the Built Environment, Sandton, South Africa, July 25-26 July 2012.
Urraca, R.; Gracia-Amillo, A.M.; Huld, T.; Martinez-de-Pisona, F.J.; Trentmanne, J.; Lindforsf, A.V.; Riihelaf, A.; Sanz-Garcia, A. Quality control of global solar radiation data with satellite-based products. Solar Energy 2017, 158, 49–62.
Huld, T.; Mueller, R.; Gambardella, A. A new solar radiation database for estimating PV performance in Europe and Africa. Solar Energy 2012, 86, 1803-1815.
Gracia-Amillo, A.; Huld, T.; Müller, R. A new database of global and direct solar radiation using the eastern meteosat satellite, models and validation. Remote Sens. 2014, 6, 8165-8189.
Müller, R.; Matcoukas, C.; Gratzki, A.; Behr, H.D.; Hollmann, R. The CM-SAF Operational scheme for the satellite based retrieval of solar Surface irradiance – A LUT based eigenvector hybrid approach. Remote Sens. and Environ. 2009, 113, 1012-1024.
Inness, A.; Baier, F.; Benedetti, A.; Bouarar, I., Chabrillat, S.; Clark, H.; Clerbaux, C.; Coheur, P.; Engelen, R.J.; Errera, Q.; et al. The MACC reanalysis: An 8-year data set of atmospheric composition. Atmos. Chem. Phys. 2013, 13, 4073-4109.
Müller, R.; Pfeifroth, U.; Träger-Chatterjee, C. Towards optimal aerosol information for the retrieval of solar surface radiation using Heliosat. Atmosphere 2015, 6, 863-878.
Müller, R.; Pfeifroth, U.; Träger-Chatterjee, C.; Trentmann, J.; Cremer, R. Digging the METEOSAT Treasure – 3 Decades of Solar Surface Radiation. Remote Sens. 2015, 7, 8067-8101.
Riihelä, A.; Carlund, T.; Trentmann, J.; Müller, R.; Lindfors, A.V. Validation of CM SAF Surface Solar Radiation Datasets over Finland and Sweden. Remote Sens. 2015, 7, 6663-6682.
Urraca, R.; Gracia-Amillo, A.M.; Koubli, E., Huld, T.; Trentmann, J.; Riihelä, A.; Lindfors, A.V.; Palmer, D.; Gottschalg, R.; Antonanzas-Torres, F. Extensive validation of CM SAF surface radiation products over Europe. Remote Sens. Environ. 2017, 199, 171-186.
Žák, M.; Mikšovský, J.; Pišoft, P. CMSAF Radiation Data: New Possibilities for Climatological Applications in the Czech Republic. Remote Sens. 2015, 7, 14445-14457.
Long, C.N.; Dutton, E.G. BSRN Global Network recommended QC tests, V2.0. Available online: http://epic.awi.de/30083/1/BSRN_recommended_QC_tests_V2.pdf (Accessed on 02 December 2017).
Roesch, A.; Wild, M.; Ohmura, A.; Dutton, E.G.; Long, C.N.; Zhang, T. Assessment of BSRN Radiation Records for the Computation of Monthly Means. Atmos. Meas. Tech. 2011, 4, 339-354.
Thomas, C.; Saboret, L.; Wey, E.; Blanc, P.; Wald, L. Validation of the New Helioclim-3 Version 4 Real-Time and Short-Term Forecast Service Using 14 BSRN Stations. Adv. Sci. Res. 2016, 13, 129-136.
Schulz, J.; Albert, P.; Behr, H.D.; Caprion, D.; Deneke, H.; Dewitte, S.; Dürr, B.; Fuchs, P.; Gratzki, A.; Hechler, P.; et al. Operational climate monitoring from space: THE EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF). Atmos. Chem. Phys. 2009, 9, 1687-1709.
Sengupta, M.; Habte, A.; Kurtz, S.; Dobos, A.; Wilbert, S.; Lorenz, E.; Stoffel, T.; Renné, D.; Gueymard, C.; Myers, D.; Wilcox, S.; Blanc, P.; Perez, R. Best practices handbook for the collection and use of solar resource data for solar energy applications, National Renewable Energy Laboratory (NREL): Colorado, United States, 2015, NREL/TP-5D00-63112.
Lorenz, E.; Kühnert, J.; Heinemann, D.; Nielsen, K.P.; Remund, J.; Müller, S.C. Comparison of irradiance forecast based on numerical weather prediction models with different spatio-temporal resolutions. In 31st EU PVSEC in Hamburg, Germany 2015.
Posselt, R.; Mueller, R.W.; Stockli, R.; Trentmann, J. Remote Sensing of Solar Surface Radiation for Climate Monitoring -The CM-SAF Retrieval in International Comparison, Remote Sens. Environ. 2012, 118,186–198.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 Lucky Ntsangwane, Brighton Mabasa, Venkataraman Sivakumar , Nosipho Zwane , Katlego Ncongwane, Joel Botai
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
.png){kind=spacer}