Publications

Asilevi, P; Opoku, NK; Martey, F; Setsoafia, E; Ahafianyo, F; Quansah, E; Dogbey, F; Amankwah, S; Padi, M (2022). Development of High Resolution Cloud Cover Climatology Databank Using Merged Manual and Satellite Datasets over Ghana, West Africa. ATMOSPHERE-OCEAN, 60(5), 566-579.

Abstract
Accurate and reliable total cloud cover (TCC) observation is essential for astronomy, renewable energy resource assessment, climate impact studies, and agriculture. In order to improve the spatial coverage for a climatological distribution pattern of TCC observation across different climatic zones in Ghana - West Africa, this paper developed a merged database comprising ground-based manual TCC observation dataset (TCCM) at 22 tropical synoptic stations and satellite-based TCC dataset retrieved from the NASA Prediction of Worldwide Energy Resource (POWER) climatological archives (TCCN) spanning 30 years (1983-2013) for each dataset. Firstly, the satellite data was assessed statistically for merging with station data. From the results, it is shown that on the overall, the satellite data (TCCN) is a good representation of local TCC climatology comparative to station observation by a mean percentage deviation of 7.8 +/- 1.7, and indices of agreement between 0.7 and 0.99 +/- 0.01, indicating strong zonal and seasonal similarities. Moreover, the best station-by-station similarities are over the northern half, being predominantly Savannah climate areas, while the southernmost half show the weakest similarities. This can be attributed to a complex interplay of coastal ocean-land-atmosphere interactions obstructing satellite sensing. Finally, the gridded merged dataset established that December-February is the lowest TCC season countrywide, whereas June-August is the highest TCC season, more pronounced over the southern half, being predominantly Forest climate type and showing significant non-linearity with atmospheric clarity indices. The results have useful applications for solar energy resource assessment, crop yield models, and provides a framework for development of cloud property and cloud radiative effect assessment for climate related studies.

DOI:
10.1080/07055900.2022.2072266

ISSN:
1480-9214