ABSTRACT:Linkages between dominant spatio-temporal decadal rainfall variability modes and the global sea surface temperature (SST) modes are investigated over East Africa region for the period 1950-2008. Singular value decomposition (SVD) and canonical correlation analysis (CCA) techniques are employed to examine potential linkages and predictability of decadal rainfall variability over the region. When the ten-year periodicity is filtered out from the observed monthly rainfall data, distinct decadal rainfall regimes are exhibited in the time series of mean seasonal rainfall anomalies. Spectral density analysis of rainfall time series showed dominance of a ten-year periodicity, significant at 95% confidence level. The Principal Component Analysis (PCA) results yielded nine and seven homogeneous decadal rainfall zones for long rains; March-May (MAM), and the short rains: October-December (OND) seasons, respectively. The third season of June-August (JJA) which is mainly experienced in western and coastal sub-regions had eight homogenous zones delineated. Results show that the leading three SVD-coupled modes explain greater than 75% of the squared covariance between the two fields. The first SVD mode for Indian, Atlantic and Pacific Oceans contributed to 50, 43 and 38% of the total square covariance for MAM season, respectively. The same mode accounted for 65, 48 and 40% for OND rainfall season, respectively. For the JJA season, mode one contributed to about 61, 39 and 42% of the variance. The study showed that forcing of decadal rainfall over the region is associated with El Niño mode that is prominent over the Pacific Ocean, while Indian Ocean dipole is the leading mode over the Indian Ocean basin. An inter-hemispheric dipole mode that is common during ENSO was a prominent feature in the Atlantic Ocean forcing regional decadal rainfall. The high variability of these modes highlighted the significant roles of all the global oceans in forcing decadal rainfall variability over the region. In addition, results from multiple linear regression model showed substantial variation of the model prediction skill of the decadal rainfall variability modes within various homogenous zones and for different seasons.

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This study sought to investigate the spatial and temporal variations of aerosols over Kenya based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor Aerosol Optical Depth (AOD) data for the period between 2001 and 2012. A Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used for trajectory analysis in order to reconstruct the origins of air masses and understand the Spatial and temporal variability of aerosol concentrations. Validation of MODIS AOD using Aerosol Robotic Network (AERONET) indicated that MODIS overestimated the aerosol loading over the study region. Space time variability of MODIS AOD measurements over Kenya showed a decreasing trend in aerosol loading with a long term mean of between 0.02 and 0.56. Mean monthly AOD values showed two peaks during the months of July and December while seasonal variations indicated high aerosol loading during the December-January-February (DJF) and June-July-August (JJA) season. Back trajectory analyses showed that aerosols mainly dust and sea salt reaching Kenya were transported from either Arabian or Indian sub continent or western parts of the Indian Ocean respectively. Therefore, long term and more comprehensive satellite AOD retrievals are necessary in order to achieve a better understanding of spatial and temporal variations in aerosols over Kenya

Developing countries are becoming more urbanized leading to modification on climate over the cities. Proper urban atmospheric planning and management are thus fundamental for cities' sustainability. Urban weather and climate therefore needs continuous monitoring to offer accurate, reliable and timely update of any significant changes. This study examined the long term modification of temperature by urbanization utilizing decadal population data, monthly maximum and minimum temperature and land surface albedo for forty years. The data were subjected to homogeneity test using Short-Cut Bartlett test method that showed both maximum and minimum temperature increasing, though insignificant. Urbanization is evidenced by the reducing land surface albedo and increasing population. The study revealed the influence of urbanization on urban climate. The increase in temperatures is harmful to human comfort. Practical approaches, such as increasing the urban forest cover and a proper planning of the cities, have been suggested to help prevent further modification of weather and urban climate by urbanization. The findings of this work are thus important for multi-sectoral use in the Kenyan cities.

Most cities in Africa's developing countries are evidently growing leading to significant modification on climate over the cities that affect human comfort and his environment. Proper urban atmospheric planning and management are thus key to making cities environmentally sustainable. To achieve all these, urban weather and climate needs continuous monitoring to offer accurate, reliable and timely update of any significant changes. This study examined the modification of wind speed and direction by urbanization process. There is need to understand the modification of wind since the wind spped and direction greatly affects dispersion of pollutants in the city and distribution of heat which affect human comfort. The study utilized land surface albedo, decadal population data and daily wind speeds and direction. The wind was analyzed using wind rose plot and the population and albedo analyzed by carrying out trend analysis. The urbanization is evidenced by the reducing urban land surface reflectivity and the increasing population. Wind direction does not show modification by urbanization, however, its magnitude has exhibited a reduction with time. The reduction in wind speed is harmful to human and animal comfort and the environment at large. Practical approaches such as proper planning of the cities to minimize further modification by urbanization have been made. The choice of residential and industrial places is also emphasized with regard to these findings. The findings of this work are thus important for multi-sectoral use in the urban centres in Kenya.