Hourly global horizontal irradiance over West Africa: A case study of one-year satellite- and reanalysis-derived estimates vs. in situ measurements

Convection‐Permitting ICON‐LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa

“…Actually, large discrepancies in the rsds under cloudy skies are also found between reanalysis and the in situ observations as well as satellite products and the in situ observations. Sawadogo et al (2023a) reported that the MAE varies from 153 to 232 W m 2 for the rsds under cloudy skies for the reanalysis (ERA5 and MERRA-2) and satellite (CAMS and SARAH-2) products, compared to 37 observing stations over western Africa. Evaluation of satellite-estimated rsds over South Africa (Mabasa et al, 2022) showed excellent performance under clear skies with rMAE smaller than 6.5% and poorer performance under cloudy skies with rMAE 29%, whereas satellite-based rsds estimate outperform the reanalysis-based estimate over South Africa (Mabasa et al, 2021).…”

“…This sky clearness index has been applied in many studies but the thresholds used to differentiate distinct sky conditions vary with the focus area: 0.82 was recognized as the boundary threshold between clear‐ and cloudy‐sky for studies in China (Du et al., 2022; Shi et al., 2021), K t ≥ 0.6 was accepted as clear‐sky and cloudy‐sky was treated as 0.12 ≤ K t < 0.35 in another study focusing on western Africa (Sawadogo et al., 2023a). Here we follow studies for South Africa (Apeh et al., 2021; Govindasamy & Chetty, 2018) and determine clear‐sky as K t > 0.7 and cloudy‐sky as K t < 0.3.…”

“…In a study evaluating GHI from reanalysis and satellite products, Sawadogo et al. (2023a) compared ERA5 and MERRA‐2 reanalysis products with CAMS and SARAH‐2 satellite products, using 37 in situ measurements from western Africa. The study found that satellite data outperform reanalysis data under distinct sky conditions.…”

“…It has a grid spacing of 0.25°with a temporal resolution of 3 hr and a continuous temporal coverage.Satellite driven rsds observations have been widely used to evaluate climate model simulations(Bichet et al, 2019;Sawadogo et al, 2021; Tang et al, 2019). Surface Solar Radiation Parameters edition 3 (SARAH-3)(Pfeifroth et al, 2023) is the successor of the SARAH-2(Pfeifroth et al, 2017), which has been proved to provide viable solar energy assessment data over Africa(Mabasa et al, 2021;Sawadogo et al, 2023a); SARAH-3 is provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF). It provides rsds based on geostationary satellite observations with a half hourly temporal resolution and a high spatial resolution of 0.05°, covering an area from 65°E to 65°E and 65°N to 65°N.…”

Increasing electricity access for health facilities in Ghana through solar powered mini-grids—a GIS-based energy system modelling approach

“…The solar yield estimate provided by PVGIS-Era-5 may not have taken into account the effects of shading on the modules caused by the seasonal northeast trade wind. This wind brings fine sand dust from the Sahara, known as Harmattan, which affects the atmospheric aerosol concentration and may cause differences in solar irradiance on the ground [52]. Therefore, it is important to consider the impact of shading losses on solar power output, which can be caused by various factors such as topographical obstructions, meteorological conditions, and structures where the modules are installed on.…”