Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

The Ångström-Prescott Regression Coefficients for Six Climatic Zones in South Africa

Version 1 : Received: 31 July 2020 / Approved: 2 August 2020 / Online: 2 August 2020 (15:14:49 CEST)

A peer-reviewed article of this Preprint also exists.

Mabasa, B.; Lysko, M.D.; Tazvinga, H.; Mulaudzi, S.T.; Zwane, N.; Moloi, S.J. The Ångström–Prescott Regression Coefficients for Six Climatic Zones in South Africa. Energies 2020, 13, 5418. Mabasa, B.; Lysko, M.D.; Tazvinga, H.; Mulaudzi, S.T.; Zwane, N.; Moloi, S.J. The Ångström–Prescott Regression Coefficients for Six Climatic Zones in South Africa. Energies 2020, 13, 5418.

Journal reference: Energies 2020, 13, 5418
DOI: 10.3390/en13205418

Abstract

The South African Weather Service (SAWS) manages an in-situ solar irradiance radiometric network of 13 stations and a very dense sunshine recording network; located in all six macro-climate zones of South Africa. A sparsely distributed radiometric network and over a landscape with dynamic climate and weather shifts is inadequate for solar energy studies and applications. Therefore, there is a need to develop mathematical models to estimate solar irradiation for a multitude of diverse climates. In this study, the annual regression coefficients, a and b, of the Ångström-Prescott (AP) model that can be used to estimate global horizontal irradiance from observed sunshine hours were calibrated and validated with observed station data. The AP regression coefficients were calibrated and validated for each of the six macro-climate zones of South Africa using the observation data that spans 2013 to 2019. The predictive effectiveness of the calibrated AP model coefficients was evaluated by comparing estimated and observed daily global horizontal irradiance. The maximum annual relative Mean Bias Error (rMBE) was 0.371 %, relative Mean Absolute Error (rMAE) was 0.745 %, relative Root Mean Square Error (rRMSE) was 0.910 % and the worst-case correlation coefficient (R2) was 0.910. The statistical validation metrics results show that there is a strong correlation and linear relation between observed and estimated solar radiation values. The AP model coefficients calculated in this study can be used with quantitative confidence in estimating daily GHI data at locations in South Africa where the daily observation sunshine duration data is available.

Subject Areas

South African Weather Services; radiometric network; climatic zone; Angström-Prescott; Global Horizontal Irradiance; sunshine duration

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