Browsing by Author "Muthama, John Nzioka"

Now showing 1 - 3 of 3

Aerosol optical depth and precipitation rate projections over east africa utilizing self organizing map
(The International Journal Of Science & Technoledge, 2017-03-01) Makokha, John Wanjala; Angeyo, H.K.; Muthama, John Nzioka
Assessment of future aerosols impacts on both regional and global climate change requires a comprehensive projection tool that reliably provides information on aerosol evolution characteristics with high fidelity. In the current study, we propose an algorithm based on Self-Organizing Map (SOM) and Community Atmosphere Model 4 (CAM4) for long term Aerosol Optical Depth (AOD) and Precipitation Rate (PR) projections over East Africa. To start with, AOD and PR retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measurement Mission (TRMM) respectively were cross validated with simulation from CAM4 so as to assess the uncertainty between the measured and simulated retrievals from 2000 to 2014.The error analysis between CAM4 simulations and MODIS measurements (from 2000 to 2014)shows a close match where R2 varies from 0.58 to 0.83 with a corresponding RMSE of between 0.014 and 0.065 (for AOD). Likewise, the uncertainty between simulate and measured PR from CAM4 and TRMM showed an estimated R2 to range between 0.40 and 0.78 while the RMSE varied from 0.021 to 0.091 in the same period and study sites. Based on proposed SOM algorithm and simulated CAM4 retrievals over each study site, an increase of between 1.34-2.43 % for AOD and a decrease of between 1.03-1.98 % in PR are projected over the region by 2030.
Simulation of radiative forcing due to aerosols over some Counties in Kenya
(BEST:IJHAMS, 2015-11-05) shem, Godfrey Juma; Muthama, John Nzioka; Mutai, Bethuel K
The Coupled Ocean and Atmosphere Radiative Transfer (COART) model solved a radiative transfer equation from aerosol optical thickness data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) spanning 2000 to 2015. The temporal and spatial variation of aerosols optical depth was determined on Giovanni platform. Trajectory modelling was carried out using Hybrid Single Particle Langrangian Model (HYSPLIT). Integrated fluxes were generated from COART model. Counties investigated are Mombasa, Lamu,Nairobi, Kakamega, Bungoma, Nyeri, Meru, Machakos, Turkana, Tranzoia, Baringo, Nakuru, Narok, Kisumu, Kisii, Nyamira and Busia. Simulation of future warming over Kenya was also done using MAGGIC SCENGEN model under two scenarios. Results of the study revealed that Turkana, ASAL and Maritime Counties had the highest aerosols loading while Kisii County had the lowest aerosols loading respectively and that aerosol loading was highest during the JJA season and that Garrissa County had the highest interannual variability of aerosols. The study revealed that aerosol loading across all Kenyan counties is reducing and that long distance transport and dispersion of aerosols was facilitated by low level winds over Kenya. It was observed that Kisii County had higher radiative forcing estimate due to aerosols while counties in the ASAL, Maritime counties and Turkana County had relatively lower corresponding estimates. It was also noted that forcing due to aerosols over Kenya is reducing and lies in the range of -0.187 to -0.05 w/m2. SCENGEN Projections gave a warming of 0.17 0C, 0.45 0C, and 2.96 0C by the year
Sun-photometric study and multivariate analysis ofaerosol optical depth variability over some representative sites of the Kenyan atmosphere
(International Journal of BioChemiPhysics,, 2015-12-01) Makokha, John Wanjala; Angeyo, H.K.; Muthama, John Nzioka
The goal of this study was to explore the temporal-spatial characteristics of aerosol optical depth (τ)over the Kenyan urban (Nairobi-1°S, 36°E), rural (Mbita-0°S, 34°E) and maritime (Malindi-2°S, 40°E) atmospheres using sun spectrophotometric measurements obtained from Aerosol Robotic Network (AERONET).AERONET measurements have been taken in Kenya since 2006 and are aimed at assessing aerosol effects on climate and improving the aerosol data base in the region. The multivariate nature of environmental measurements however allows only a limited understanding of atmospheric aerosol characteristics when univariate analysis technique is used. Temporal-spatial characteristics of atmospheric aerosol optical depth can be understood comprehensively if it is appropriately retrieved from ground-based spectrophotometric measurements and then decoupled and analyzed using multivariate analysis techniques since they can explore groups of variables simultaneously, thus providing a more meaningful insight into the temporal-spatial variability of τ is inevitable. The influence of rain and dry spells and temperature on τ at wavelengths, λ = 440 nm and λ = 1020 nm as quantified by Principal Component Analysis (PCA) ranged between 76-83 % and 7-14 %and 4-7 % respectively for all the sites. It was found out that urban heat island (over Nairobi) and local air circulation effects (over Mbita and Malindi) modulate the characteristics of aerosol optical depth over the studied sites. Spatial variability in τ as shown by Hierarchical Cluster Analysis (HCA) is independent of measurement wavelength but dependent on aerosol burden in the atmosphere for each site. The individual and coupled influence of weather parameters on atmospheric aerosols has been\ isolated and quantified and found to be site dependent.