Monitoring spatial-temporal variability of aerosol over Kenya

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 KenyaKey Words: Aerosol Optical Depth, MODIS, Keny

Analysis of the temporal evolution of total column nitrogen dioxide and ozone over Nairobi, Kenya using daily OMI measurements

Concurrent measurement and analysis of Nitrogen dioxide (NO2)and Ozone (O3) are essential for improved understanding of ozone distribution. This study sought to analyse the temporal evolution of total column NO2 and O3 over Nairobi using satellite-derived daily data between 2009 and 2013. Seasonality is observed in O3 distribution with minimum and maximum occurring during the dry and wet seasons, respectively. Additionally, a lag of about a month or two occurs between the onset of a season and corresponding minimum or maximum NO2 and O3 concentration. The established association between monthly NO2 and O3 is such that, above average concentration of NO2 is likely to lead to above average levels of O3 during the same month (r=0.79) and below average levels about 5 months later (r=0.39).  The Quasi Biennial Oscillation (QBO) is the main phenomenon behind the oscillating biennial feature exhibited by NO2 and O3 interannual trend. The study shows that NO2 and O3 are increasing at annual average rates of about 0.27% and 0.46% per year compared to mean values, respectively. Daily variation of both NO2 and O3 depicts stagnating trends over the entire period of study. This difference is attributed to the fact that, whereas daily NO2 and O3 are influenced by mechanisms that control the slow shift between the dry and wet periods within the course of a year, interannual variability is driven by the differences in each year’s general weather conditions. Key Words: Evolution, Nitrogen dioxide, Ozone, Total Column, Quasi Biennial Oscillatio

The future of African nowcasting

Nowcasting (weather forecasting predictions from zero to several hours) has enormous value and potential in Africa, where populations and economic activity are highly vulnerable to rapidly changing weather conditions. Timely issuing of warnings, a few hours before an event, can enable the public and decision-makers to take action. Rainfall radar estimates are not widely available in Africa, nor likely to be in the coming years, and numerical weather prediction (NWP) currently has low skill over the African continent. Therefore, for the delivery of nowcasting in Africa, satellite products are the best practical option and needed urgently (Roberts et al., 2021). Fifteen minute (or faster) updates of MSG (Meteosat Second Generation) images and NWC-SAF (Nowcasting Satellite Applications Facility) products are crucial for nowcasting to warn users (e.g. fisherfolk on Lake Victoria, flooding in urban areas, etc.) on pending severe storms. The possibility to have such products every 10 minutes, as well as data from the forthcoming MTG (Meteosat Third Generation) lightning imager, would be highly beneficial to all African countries, saving lives and livelihoods where high population growth and the most extreme impacts of climate change combine

Monitoring Spatio-Temporal Variability of Aerosol Over East Africa

This study sought to investigate the spatial and temporal variations of aerosols over East Africa based on Moderate Resolution Imaging  Spectroradiometer (MODIS) satellite sensor. 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 Spatio-temporal variability of aerosol concentrations. MODIS aerosol data (2001 to 2012) revealed decreasing aerosol loading over East Africa. An assessment of seasonal variability in AOD revealed maximum AOD values during the December –January –February (DJF) and June –July –August (JJA) season. Back trajectory analyses indicated that aerosols reaching East Africa were transported from either Arabian and Indian sub continent or western parts of the Indian Ocean. 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 East Africa.Key Words: Aerosol Optical Depth, MODIS, East Afric