Investigation of Physical and Radiative Properties of Clouds Over the Three Environmentally Distinct Regions in Kenya

Clouds form a very crucial component of the atmosphere and plays a pivotal role in regulating the Earth’s energy budget. The knowledge on climate change and its effects lies in the assessment of the cloud properties and therefore it is important to study the properties of clouds. The study asesses the physical and radiative properties of clouds over three environmentally distinct regions in Kenya i.e  (Nairobi 1º S, 36º E, Malindi 4º S, 40º E and Mbita 0º S, 34º E). The study used the terra satellite on board of the MODerate resolution Imaging Spectroradiometer (MODIS), The Tropical Rainfall Measurement Missiom (TRMM) and the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) model to investigate the spatial and temporal physical and radiatiative cloud properties over the study regions. The datasets were manipulated with the aid of Adobe Illustrator and Grid Analysis and Display System (GRADS) version 2.2.1.oga.1 for the cluod parameters. Research methods such as the Linear regression analysis, trend analysis and seasonal variability were used in order to generate the trends, significance of the trends and the spatial maps. Four seasons (DJF, MAM, JJA and SON) were considered with special focus on cloud parameters; COT, CF, CER, CTP, CTT, PR, CA and WV and PR based on 16 years period (from January 2005 to December 2020). The known cloud parameters were used to infer on the properties of clouds of the three regions. The above parameters were chosen since their variations indicates the general variations in both clouds physical and radiative properties. Spatial maps were drawn for all the seasons and comparisons done using the maps. Variations in trends in the cloud parameters per year (year^-1) were observed ranging from negative trends to positive trends. Trends in CER were found as follows (Nairobi 0.04, 0, -0.04 and -0.01 for the four seasons respectively), Malindi (0.04, 0.01, 0.04 and 0.01µm) and lastly Mbita, (-0.06, -0.06, 0.04 and -0.05). For CTT, (Nairobi,-0.1, -0.2,-0.1 and -0.2, Malindi, 0.1, -0.2,0.1 and 0.05 and Mbita, 0.2, 0.2, -0.2 and 0.15 respectively for every season). Trends in CTP were observed to vary seasonally a follows (Nairobi -0.5, -1, 0.5 and -0.5, Malindi -0.5, -3, 1, and 0.5 and lastly Mbita 0.5, 0, -1 and -1 respecively). COT, (Nairobi, -0.05, -0.09, 0 and -0.05, Malindi,-0.05, -0.03, 0 and -0.05 and Mbita, -0.05, 0.03, -0.12 and -0.15 respectively). WV, (Nairobi -0.01, 0.01, 0 and 0, Malindi 0.005, 0.005, 0 and 0 and lastly for Mbita, 0.005, 0.015, 0 and 0.01 respectively for all the seasons). The trends in CF were also observed; Nairobi, 0.3, 0, -0.002 and 0, Malindi 0.3, 0.002, 0 and 0.001 and for Mbita, 0.3, 0.003, 0.001 and 0.001 for the SON season. Also, trends in PR were recorded as; (Mbita; 0.005,0.005.0 and 0.005), (Nairobi;-0.005,-0.1,0 and -0.005) and over (Malindi; -0.005,-0.1,-0.05 and -0.1). And lastly seasonal trends in Cloud Albedo (Mbita, 0.0015,-0.001,-0.001 and 0.0005), (Malindi;0.0045,-0.002,-0.004 and -0.003) and lastly Nairobi;0.003,-0.001,-0.003 and -0.001. It was evident that the spatial-temporal variability of the cloud parameters depicted variations in the cloud properties in the study domains. The findings of this study can be utilized by the government through the ministry of environment, ministry of information, communication and digital economy to regulate the anthropogenic emissions from industries, vehicles and biomass burning and reduce deforestation to strengthen emergency response to climate change.