Senior lecturer in the Faculty of Science and Technology, University of Nairobi.

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Muita, R, Dougill A, Mutemi J, Aura S, Graham R, Awolala D, Nkiaka E, Hirons L, Opijah F.  2021.  Understanding the Role of User Needs and Perceptions Related to Sub-Seasonal and Seasonal Forecasts on Farmers’ Decisions in Kenya: A Systematic Review. Frontiers in Climate. 3(1): Frontiers in Climate


Mugo, JW, Opijah FJ, Ngaina J, Karanja F, Mburu M.  2020.  Suitability of Green Gram Production in Kenya Under Present and Future Climate Scenarios Using Bias-corrected Cordex RCA4 Models. Agricultural Sciences. 11:882-896.
Mugo, JW, Opijah F, Ngaina J, Karanja F, Mburu M.  2020.  Rainfall variability under present and future climate scenarios using the Rossby Center Bias-corrected Regional Climate Model. American Journal of Climate Change. 9(1):243-265.



Sabiiti, G, et al.  2018.  Adapting Agriculture to Climate Change: Suitability of Banana Crop Production to Future Climate Change over Uganda. Limits to Climate Change Adaptation. : Springer, Cham Abstract

The aim of this study was to determine suitability zones of future banana growth under a changing climate to guide the design of future adaptation options in the banana sub-sector of Uganda. The study used high resolution (~ 1km) data on combined bioclimatic variables (rainfall and temperature) to map suitability zones of the banana crop while the Providing Regional Climate for Impacts Studies (PRECIS) regional climate model temperature simulations were used to estimate the effect of rising temperature on banana growth assuming other factors constant. The downscaled future climate projections were based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs, 2.6, 4.5, 6.0 and 8.5) and Special Report on Emission Scenarios (SRES, A1B and A2) across the period 2011-2090. The methodology involved identification of banana-climate growth thresholds and developing suitability indices for banana production under the high mitigation (RCP 2.6, less adaptation), medium mitigation (RCP 4.5 and RCP 6.0, medium adaptation), no mitigation (RCP 8.5, very high adaptation) scenarios, SRES A1B and A2 scenarios. The FAO ECO-Crop tool was used to determine and map future suitability of banana growth. Banana production indices were determined using a suitability model in the Geographical Information System (GIS) spatial analyst tool. The non-linear banana-temperature regression model was used to assess the impact of future changes in temperature on banana growth.

Otieno, G, Mutemi J, Opijah F, Ogallo L, Omondi H.  2018.  The Impact of Cumulus Parameterization on Rainfall Simulations over East Africa. Atmospheric and Climate Sciences. 8(3):355. AbstractScientific Research Publishing Inc.

The study explored the ability of four cumulus parameterization schemes (CPSs) from Weather and Research Forecasting model (WRF) to simulate mean rainfall patterns, number of rainy days (NRD) and vertically integrated moisture flux (VIMF) during the composite of wet years for the core rainfall seasons of March-April-May (MAM; 1989, 1998 and 2012) and Octo-ber-November-December (OND; 1997, 2006 and 2015) seasons. The CPSs used were Kain-Fritsch (KF), Kain-Fritsch with a moisture-advection based trigger function (KFT), Grell Dévényi (GRELL) and Betts Miller Janjic (BML). The simulations by the GRELL and KF schemes were clearly separated by the dry and wet rainfall gradient in the simulations. For example, the GRELL scheme rainfall simulations were drier over the eastern parts of the region bet-ter. The KF and KFT schemes generated wetter rainfall conditions mainly con-fined to the western parts of the region. The BML scheme simulations were not consistent with the observations. The western and eastern parts of the region were characterized by more and fewer NRD, in both the KF and GRELL schemes. The root mean square error (RMSE) and spatial correlation by KF scheme was 2 mm/day and 0.6. The GRELL scheme however simulated low correlation of 0.45 and RMSE of about 3.0 mm/day over most of the sub-domains. The moisture convergence biases were found to be larger conti-nentally and parts of the nearby Indian Ocean. The persisting rainfall biases constituting of too wet and dry conditions were associated with the KF and GRELL cumulus schemes. The findings from the current study are very funda-mental for the improvement of numerical weather prediction (NWP) tools and cumulus modification processes over the region. The accurate and higher skill rainfall forecasts would provide early warning information for disaster risk re-duction and the related risks on the livelihoods.


Opijah, FJ, Mutemi JN, Ogallo LA.  2017.  Seasonal Climate Predictability over Kenya Using the Regional Spectral Model. J. Meteorol. 10(1) AbstractResearchgate

Seasonal climate prediction over Kenya poses a considerable challenge to the modeling community due to the intricate interactions among the atmospheric, oceanic and land surface processes. This paper assesses the performance of the Regional Spectral Model (RSM) in downscaling the European Centre-Hamburg (ECHam) global model outputs from 1970 to 1999 over Kenya with respect to rainfall and temperature prediction using standard verification techniques. The results show that the accuracy of simulating the annual cycle and spatial distribution of convection and precipitation over the country is still poor. The seasonal rainfall predictability over Kenya by the RSM is better during the October-December season (correlation coefficient [r] of 26%; proportion correct [PC] of 60%; Frequency Bias Index [FBI] of 111%) than in the March-May season (r of 8%; PC of 54%; FBI of 83%), but the prediction for temperature is better in the March-May season (r of 25%; PC of 53%; FBI of 124%) than the OND season (r of-11%; PC of 46%; FBI of 100%). The predictability for rainfall during the cool-dry June-August period is still low (r of-4%; PC of 49%; FBI of 52%) but that for temperature has better skill as compared to the March-May and October-December seasons (r of 49%; PC of 70%; FBI of 90%). There is need to improve the development of convective processes that govern tropical precipitating systems in the region through sensitivity analysis of cloud simulation modules in the RSM applied as well as address rare systems that episodically influence the weather over the country and the region.


Sabiiti, G, et al.  2016.  Empirical Relationships between Banana Yields and Climate Variability over Uganda. J. Environ. Agric. Sci. 7:3-13. AbstractResearchgate

Variations in weather and climate have a significant impact on rain-fed banana yields in East Africa. This study examined empirical linkages between banana yields and variations in rainfall and temperature over Uganda for the historical period (1971-2009) using time series moments, correlation and regression analysis. The Food and Agriculture Organization (FAO) Crop Water Assessment Tool (CROPWAT) was used to estimate banana crop water requirements, soil moisture deficits and their effects on banana yield levels under rain-fed conditions for different regions. The study observed high comparability in moment indices with some significant differences reflected in the values of the banana yields and rainfall and temperature moment indices. The cumulative effect of rainfall and temperature variations on banana yields was discernible from strong correlation coefficients of up to 78%. The CROPWAT simulations indicated up to 46% reductions in optimal banana yields due to soil moisture deficits within banana plantations. In conclusion, the study observed stronger linkages between banana yields and temperature variations than rainfall. In addition, temperature manifests both direct and indirect effects on banana growth while rainfall exhibits comparatively high intra-seasonal and intra-annual variability with lag effects on banana yields. The study provides a strong scientific basis for the development of coping, adaptation and mitigation strategies in the banana farming subsector in the region due to the anticipated shifts in rainfall and temperature extremes and changes across Uganda and neighbouring regions.

Rwigi, S, Muthama NJ, Opere A, Opijah FJ.  2016.  Assessment of Potential Changes in Hydrologically Relevant Rainfall Statistics over the Sondu River Basin in Kenya Under a Changing Climate. J. Meteorol.

Scenarios of past, present and intermediate future climates for Sondu River basin were analysed in this study to evaluate the potential changes in hydrologically relevant rainfall statistics that are likely to be observed by the middle of this century as a result of climate change. These climate scenarios were developed by applying dynamical downscaling of the relatively course resolution climate scenarios simulated by the fourth generation coupled Ocean-Atmosphere European Community Hamburg Model (ECHAM4) using the Providing Regional Climates for Impacts Studies (PRECIS) modelling system. The regional climate scenarios, which were available at a daily time-step and a spatial grid resolution of 0.5 over the Eastern Africa region, were matched to the Sondu river basin in the western region of Kenya. The possible hydrological impacts of climate change were assessed by applying the scenarios in a daily time-step hydrological model. The analysis of hydrologically relevant rainfall statistics focussed on determining changes in rainfall patterns and the likely hydrological implications to the basin. The results indicated that more rainfall is projected for the region in the immediate and intermediate future in form of increased seasonal rainfall during the December-January-February (DJF), March-April-May (MAM) and September-October-November (SON) seasons resulting from increased number of days of rainfall and higher probabilities of a wet day following a dry day in a month.

Kipkogei, O, Bhardwaj A, Kumar V, Ogallo LA, Opijah FJ, Mutemi JN, Krishnamurti TN.  2016.  Improving multimodel medium range forecasts over the Greater Horn of Africa using the FSU superensemble. Meteorology and Atmospheric Physics. 128(4):441-451. AbstractSpringer Nature

This study makes use of the WMO’s multimodel data set called THORPEX integrated grand global ensemble (TIGGE) towards the construction of multimodel superensemble forecasts covering a period of 10 days. The goal of this study is to explore the forecast skill for precipitation forecasts over the Greater Horn of Africa (this is a consortium of 11 countries). The multimodels include forecast data set from a suite of models that include: The European Centre for Medium Range Weather Forecasts (ECMWF), the National Centre for Environmental Prediction (NCEP), the Center for Weather Forecast and Climatic Studies (CPTEC) and the United Kingdom Meteorological Office (UKMO). After performing a training phase for the superensemble weights covering the previous 450 days of October, November and December months of 2008–2012, forecasts of precipitation were prepared for the multimodel

Rwigi, SK, Muthama JN, Opere AO, Opijah FJ, Gichuki FN.  2016.  Simulated Impacts of Climate Change on Surface Water Yields over the Sondu Basin in Kenya. International Journal of Innovation Education and Research. 4(8):160-172. AbstractInternational Journal of Innovation Education and Research

Potential impacts of climate change on surface water yields over the Sondu River basin in the western region of Kenya were analysed using the Soil and Water Assessment Tool (SWAT) model with climate input data obtained from the fourth generation coupled Ocean-Atmosphere European Community Hamburg Model (ECHAM4) using the Providing Regional Climates for Impacts Studies (PRECIS) model. Daily time step regional climate scenarios at a spatial grid resolution of 0.44 Ëš over the Eastern Africa region were matched to the Sondu river basin and used to calibrate and validate the SWAT model. Analysis of historical and projected rainfall over the basin strongly indicated that the climate of the area will significantly change with wetter climates being experienced by 2030 and beyond. Projected monthly rainfall distribution shows increasing trends in the relatively dry DJF and SON seasons while showing decreasing trends in the relatively wet MAM and JJA seasons. Potential changes in water yields resulting from climate change were computed by comparing simulated yields under climate change scenarios with those simulated under baseline conditions.



The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. The reduction of errors increases the reliability of the information. Therefore, for any given region to have sustainable development there is need to apply climate information into its socio-economic strategic plans.
The overall objective of the study was to assess the performance of the Coupled Model Intercomparison Project (CMIP5) over the Lake Victoria Basin. The data used in the study included the observed point station data, gridded rainfall data from Climate Research Unit, University of East Anglia (CRU) and hindcast data from eight Coupled Model Intercomparison Project 5 (CMIP5) for the period 1971 to 2005 for historical and 2006-2100 for model future projections. The methodology employed included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score.


Bosire, E, Opijah F, Gitau W.  2014.  Assessing the Skill of Precipitation Forecasts on Seasonal Time Scales over East Africa from a Climate Forecast System Model. Global Meteorology. 3(1) AbstractPagepress

It is becoming increasingly important to be able to verify the skill of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction models. This study focused on assessing the skill of climate forecast system (CFS) model in predicting rainfall on seasonal time scales over East Africa region for the period January 1981 to December 2009. The rainfall seasons considered were March to May (MAM) and October to December (OND). The data used in the study included the observed seasonal rainfall totals from January 1981 to December 2009 and CFS model forecast data for the same period. The model had 15 Runs. The measure of skill employed was the categorical skill scores and included Heidke skill scores, bias, probability of detection and false alarm ratio. The results from the categorical skill scores confirmed relatively higher skills during OND season as compared to MAM. When compared with individual Runs, the mean of all the 15 Runs depicted relatively higher accuracy during OND season. Some individual Runs–1, 7, 9 and 10–also performed better during OND season. During MAM season, the mean of all the 15 Runs showed relatively lower accuracy in predicting rainfall. Some individual Runs–5, 10, 12 and 14–performed better than the mean of all the 15 Runs

Otieno, GL, Opijah FJ, Mutemi JN, Ogallo LA, Anyah RO, Ongoma V, Sabiiti G.  2014.  Seasonal rainfall forecasting using the Multi-Model Ensemble Technique over the Greater Horn of Africa. International Journal of Physical Sciences. 2(6):095-104. AbstractICPAC

This study evaluated the skill of forecasting seasonal rainfall over the Greater Horn of Africa (GHA) using Ensemble Model Technique from a cluster of four General Circulation Climate Models (GCMs) from Global Producing Centers (GPCs). The spatial distribution of rainfall anomalies of the observed models output during extreme events showed that the ensemble model was able to simulate El-Niño (1997) and La-Niña (2000) years. The ensemble models did not show good skill in capturing the magnitude of the extreme events. The skill of the ensemble model was higher than that for the member models in terms of its ability to capture the rainfall peaks during the El-Niño Southern Oscillation (ENSO) phenomena. The analysis for the correlation coefficients showed higher values for the ensemble model output than for the individual models over the Equatorial region with the stations in the northern and southern sectors of the GHA comparatively giving low skill. The ensemble modeling technique significantly improved the skill of forecasting, including the sectors where individual models had low skill. In general, the skill of the models was relatively higher during the onset of the ENSO event and became low towards the decaying phase of the ENSO period. Generally, the study has shown that the ensemble seasonal forecasting significantly adds skill to the forecasts especially for October-December (OND) rainy seasons. From the study, ensemble seasonal forecasting significantly adds skill to the forecasts over the region

Opijah, FJ, Akenga P, Salim A, Onditi A, Amir Y, Waudo W.  2014.  Green Energy Potential in East Africa. Abstract

Background Analgesics in clinical used have many side effects and are not always effective. Hence need for safer and more effective agents. Hydrazinocurcumin is an azole derivative of the natural product curcumin.

Opijah, F, et al.  2014.  Application of the Ems-Wrf Model in Decadal Rainfall Prediction over the Gha Region. Africa Journal of Physical Sciences . 1-1f.opijah.pdf



FRANKLIN, DROPIJAH.  2012.  Are Weather and Climate Forecasts by National Meteorological Centres Reliable? Bulletin of the Kenya Meteorological Society. : Weather and Climate Bulletin of the Kenya Meteorological SocietyWebsite


FRANKLIN, DROPIJAH.  2011.  Golden Sunbeams in Shadowy Storms. Experimewntal Mechanics. : WordAlive


FRANKLIN, DROPIJAH.  2009.  Natural Hazards and the Art of Forecasting. Experimewntal Mechanics. : Kenya Meteorological Society


FRANKLIN, DROPIJAH.  2008.  Simulation of the Impact of Deforestation on Rainfall in the Lake Victoria Basin. Experimewntal Mechanics. : J. Kenya Meteorological Soc
FRANKLIN, DROPIJAH.  2008.  Cloud Cover Estimation Over Selected Locations in East Africa Using Satellite Derived Reflectivity Data. Experimewntal Mechanics. : J. Kenya Meteorological Soc
FRANKLIN, DROPIJAH, R DRMUKABANAJOSEPH, K PROFNGANGAJOHN.  2008.  Response of the Moisture Budget to the Growth and Development of Nairobi City . Experimewntal Mechanics. : Africa J. of Sc. and Tech
FRANKLIN, DROPIJAH, R DRMUKABANAJOSEPH, K PROFNGANGAJOHN.  2008.  Contribution to the Heat Budget in Nairobi Metro-Area by the Anthropogenic Heat Component.. Experimewntal Mechanics. : J. Kenya Meteorological Soc Abstract
This study quantifies the ejected waste heat from artificial supplies comprising road transport and industrial, commercial, domestic and metabolic heating activities which may enhance the urban temperatures in Nairobi metro area, taking into account the energy intensity of a given activity and the level of the activity, considering expended fossil and biofuels, electrical energy consumption and human metabolism. Translation of linear source strengths to area averages from the road transport sector yields about 4% of the total anthropogenic energy over the city. The contribution from the road sector is likely to rise to 10.8 W m-2 in 2029 as the City expands. The industrial/commercial sector contributes up to 35.5 W m-2 or 57% of the total anthropogenic energy, and could increase to 284 W m-2 by 2029 due to industrialization and economic growth. Domestic utilities account for up to 13 W m-2, which is 21% of the total anthropogenic energy. Depending on the activity engaged in, human metabolism contributes up to 11.4 W m-2, which is about 18% of the total anthropogenic energy supplies. The sum total area-averaged anthropogenic energy consumption over the city centre is currently small, constituting about 11 to 18% of the global radiation for the warmer and colder seasons, respectively. Notably, only a part of this energy is released into the atmosphere as waste heat as most is used for the intended purposes. If the current trends of rising population, increased motor vehicle density and enhanced industrialization persist, the anthropogenic waste heat ejection would be large enough to alter the heat balance of the study area appreciably in future by 2030.


FRANKLIN, DROPIJAH.  2007.  Relationship between ENSO parameters and trends and periodic fluctuations in East Africa rainfall. Experimewntal Mechanics. : J. Kenya Meteorological Soc
FRANKLIN, DROPIJAH.  2007.  Inter-comparison of Satellite, Dobson Spectrophotometer and Ozonsonde Ozone Data Observations over Nairobi. Experimewntal Mechanics. : Kenya Meteorological Society
FRANKLIN, DROPIJAH.  2007.  Anthropogenic Energy Component and Climate Change in Nairobi Metro-area. Experimewntal Mechanics. : Kenya Meteorological Society
R, DRMUKABANAJOSEPH, K PROFNGANGAJOHN, FRANKLIN DROPIJAH.  2007.  Rainfall Distribution over Nairobi Area. Experimewntal Mechanics. : J. Kenya Meteorological Soc


FRANKLIN, DROPIJAH.  2005.  Introduction to GrADS. Experimewntal Mechanics. : IGAG Climate Prediction and Applications Centre
FRANKLIN, DROPIJAH.  2005.  Numerical Simulation of the Influence of Urbanisation on Convective Activities over Nairobi City. Experimewntal Mechanics. : International Human Dimensions Programme
FRANKLIN, DROPIJAH.  2005.  Tropical Meteorology I. Experimewntal Mechanics. : University of Nairobi
FRANKLIN, DROPIJAH.  2005.  Tropical Meteorology II. Experimewntal Mechanics. : University of Nairobi
FRANKLIN, DROPIJAH.  2005.  General Circulation and Climatology. Experimewntal Mechanics. : University of Nairobi


Opijah, FJ, Mukabana JR.  2004.  On the influence of urbanization on the water budget in Nairobi city: A numerical study. AbstractOn the influence of urbanization on the water budget in Nairobi city: A numerical study

The impact of the growth and development of the City of Nairobi on the water budget is simulated using a high-resolution limited-area numerical model. The water substance fields are modelled with full physics in a control experiment. Five sensitivity experiments are then performed by altering the land-use/cover over the domain of study to assess the influence of the city, forests and terrain undulations on the water substance fields. Results showed that the highest evaporation occurred in areas of the study domain with open grasslands/scattered bush-land's vegetation types and the least at the city centre. Deforestation would lead to a substantial increase in the loss of water effected through evaporation despite a reduction in transpiration. The observed rainfall amount and frequency were highest in the high ground portions to the northwest of the study domain. Numerical analyses showed that the urban heat island had a destabilizing effect on the flow, which enhanced convection that resulted in increased rainfall downwind of the urban area. Further growth and expansion of the city of Nairobi would increase the area and amount of rainfall received. Deforestation would decrease rainfall amounts. Massive reforestation would increase the observed rainfall. There has been a decrease in soil moisture at the current location of the city centre; the decrease is bound to increase with the expansion of the city. The City of Nairobi has resulted in a large decrease in the soil moisture through converting the natural fabric to concrete/asphalt material. Deforestation would result in a marginal decrease in the soil moisture. Further growth and development of Nairobi City would modify the water substance budget appreciably.

FRANKLIN, DROPIJAH.  2004.  Advances of Numerical Weather Prediction over the GHA Region. Experimewntal Mechanics. : IGAD Climate Prediction and Applications Centre
FRANKLIN, DROPIJAH.  2004.  Introduction to Unix. Experimewntal Mechanics. : IGAG Climate Prediction and Applications Centre


FRANKLIN, DROPIJAH.  2003.  Principles of Numerical Weather Prediction. Experimewntal Mechanics. : IGAD Climate Prediction and Applications Centre
FRANKLIN, DROPIJAH.  2003.  Introduction to Meteorology I. Experimewntal Mechanics. : University of Nairobi

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