Version 1
: Received: 20 August 2018 / Approved: 21 August 2018 / Online: 21 August 2018 (04:23:52 CEST)
How to cite:
Ntsangwane, L.; Sivakumar, V.; Mabasa, B.; Zwane, N.; Ncongwane, K.; Botai, J. Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network. Preprints2018, 2018080363. https://doi.org/10.20944/preprints201808.0363.v1
Ntsangwane, L.; Sivakumar, V.; Mabasa, B.; Zwane, N.; Ncongwane, K.; Botai, J. Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network. Preprints 2018, 2018080363. https://doi.org/10.20944/preprints201808.0363.v1
Ntsangwane, L.; Sivakumar, V.; Mabasa, B.; Zwane, N.; Ncongwane, K.; Botai, J. Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network. Preprints2018, 2018080363. https://doi.org/10.20944/preprints201808.0363.v1
APA Style
Ntsangwane, L., Sivakumar, V., Mabasa, B., Zwane, N., Ncongwane, K., & Botai, J. (2018). Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network. Preprints. https://doi.org/10.20944/preprints201808.0363.v1
Chicago/Turabian Style
Ntsangwane, L., Katlego Ncongwane and Joel Botai. 2018 "Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network" Preprints. https://doi.org/10.20944/preprints201808.0363.v1
Abstract
Quality control (QC) may be a lengthy and tedious process. As a result, most data users use data from meteorological services without performing data quality checks. The South African Weather Service (SAWS) re-established the national solar radiometric network comprising of 13 new stations within the six climatic zones of the country. This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) QC procedures applied to the solar radiation data within the SAWS radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN QC methodology is 97.79%, 93.64%, 91.6% 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 (SARAH) data records for the GHI estimation for all the stations showed a Mean Bias Deviation (MBD) of -8.28 Wm-2, a Mean Absolute Deviation (MAD) of 9.06 Wm-2 and the Root Mean Square Deviation (RMSD) of 11.02 Wm-2. The correlation (quantified by R2) between ground-based and SARAH-derived GHI time series was ~ 0.98. The established network has the potential of providing 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 in South Africa.
Keywords
quality control; BSRN; solar radiation; satellite-retrieve irradiance; ground stations; validation
Subject
Physical Sciences, Applied Physics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
