Please use this identifier to cite or link to this item:
doi:10.22028/D291-44840
Title: | Multi-Timescale Validation of Satellite-Derived Global Horizontal Irradiance in Côte d’Ivoire |
Author(s): | Kakou, Pierre-Claver Konin Laouali, Dungall Aka, Boko Osei, Janet Appiah Ette, Nicaise Franck Kassi Frey, Georg |
Language: | English |
Title: | Remote Sensing |
Volume: | 17 |
Issue: | 6 |
Publisher/Platform: | MDPI |
Year of Publication: | 2025 |
Free key words: | remote sensing global horizontal irradiance Kolmogorov–Smirnov test satellite data Côte d’Ivoire solar radiation |
DDC notations: | 500 Science |
Publikation type: | Journal Article |
Abstract: | Accurate solar radiation data are crucial for solar energy applications, yet groundbased measurements are limited in many regions. Satellite-derived and reanalysis products offer an alternative, but their accuracy varies across spatial and temporal scales. This study evaluated the performance of four widely used GHI products—CAMS, SARAH-3, ERA5 and MERRA-2—against ground measurements at hourly, daily (summed from hourly) and monthly (averaged from daily) timescales. The analysis also examined how temporal aggregation influenced error characteristics using correlation coefficients, the rMBD, the rRMSD and the combined performance index (CPI). At an hourly scale under clear-sky conditions, satellite products outperformed reanalysis products, with r ≈ 1 and R 2 ≈ 0.9 and the rMBD, rRMSD and CPI ranging from 0.1%, 11.4% and 11.8% to −14.7%, 33.3% and 75.1% for CAMS; 0.2%, 11.4% and 10.9% to 13.5%, 22.4% and 120.7% for SARAH-3; −0.2%, 21.6% and 23.8% to 21.5%, 40.9% and 128.8% for MERRA-2; and 0.8%, 14.6% and 16.3% to 22%, 48.2% and 88.3% for ERA5. Under cloudy conditions, all products overestimated GHI, with the rMBD reaching up to 39.7% (SARAH-3), 35.9% (CAMS), 22.9% (MERRA-2) and 28% (ERA5), while the rRMSD exceeded 40% for all. Overcast conditions yielded the poorest performance, with the rMBD ranging from 45.8% to 124.6% and the CPI exceeding 800% in some cases. From the hourly to daily and monthly datasets, aggregation reduced errors for reanalysis products by 5.5% and up to 12.4%, respectively, in clear-sky conditions, but for satellite-based products, deviations slightly increased up to 3.1% for the monthly dataset. Under all-sky conditions, all products showed reductions up to 23%. These results highlight the significant challenges in estimating GHI due to limited knowledge of aerosol and cloud dynamics in the region. They emphasize the need for improved parameterization in models and dedicated measurement campaigns to enhance satellite and reanalysis product accuracy in West Africa. |
DOI of the first publication: | 10.3390/rs17060998 |
URL of the first publication: | https://doi.org/10.3390/rs17060998 |
Link to this record: | urn:nbn:de:bsz:291--ds-448403 hdl:20.500.11880/39859 http://dx.doi.org/10.22028/D291-44840 |
ISSN: | 2072-4292 |
Date of registration: | 27-Mar-2025 |
Faculty: | NT - Naturwissenschaftlich- Technische Fakultät |
Department: | NT - Systems Engineering |
Professorship: | NT - Prof. Dr. Georg Frey |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
---|---|---|---|---|
remotesensing-17-00998-v2.pdf | 12,87 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License