DR OUMA GILBERT ONG'ISA

Abstract
Recent years have marked the emergence of the innovation systems approach as a shift from the conventional linear models of technology transfer. Linear technology diffusion models hinder participatory approaches of local actors such as smallholder farmers and regards them as spectators in the development process, which impedes wide adoption of technology by the intended beneficiary. This article sought to understand the potential of the innovations systems approach as an incentive to enhance the adoption of climate services by smallholder farmers through regarding them and other relevant stakeholders as part of the process, fostering knowledge sharing and interactive learning. The methodology included stakeholder/actor identification, mapping of stakeholder linkages, capacity building and active involvement of stakeholders through the climate services process. The results showed that unlike the conventional linear knowledge delivery process, the innovation systems approach takes into consideration the complex processes that are highlighted by non-linear processes, feedback loops, and other complex interactions that occur among heterogeneous actors. As such in place of the linear knowledge delivery approach, a more systems approach is necessary to help mobilize science and technology such as climate services to deliver benefits, which has the potential to enhance access, salience, credibility, and legitimacy of the scientific information.

Keywords
Innovation systems approach; Climate services; Stakeholder linkages; Adoption

Community vulnerability to climate change can be conceptualized as an aggregate of three vulnerability components: exposure to climatic stress, sensitivity to climate stress and adaptive capacity. However, even within similar regions these vulnerability components are spatially differentiated necessitating the understanding of a regions vulnerability pattern before targeting adaptation assistance. This research sought to understand the differentiated vulnerability patterns of communities in Kitui County as well as the existing coping strategies to guide implementation of adaptation assistance. Indicator approach to vulnerability assessment and focus group discussions were used to understand the vulnerability pattern and coping strategies respectively. Results showed a differentiated vulnerability pattern with a west to east gradient across Kitui County. The pattern exhibited less vulnerability scores on the western and central parts and more vulnerability scores on the eastern and northern parts of the County. Existing coping strategies have become inadequate with increasing climate variability, severity and frequency of extreme climate events, which render the communities even more vulnerable. The patterns of vulnerability can guide appropriate targeting of adaptation assistance and in turn lead to improved climate change resilience and community livelihoods.

Somalia has faced severe challenges linked to climate variability, which has been exacerbated by conflict and limited governance that persisted for decades. Today climate extremes such as floods, drought, and coastal marine severe systems among others are always associated with the destruction of property and livelihoods; losses of lives lost, migrations, and resource based conflicts among many other miseries. Intergovernmental Panel on Climate Change (IPCC) has shown that climate change is real and requires sound knowledge of local future climate change scenarios. The study attempted to provide projected rainfall and temperature change scenarios over Lower Jubba, Somalia. This was done using the downscaled Coordinated Regional Downscaling Experiment (CORDEX) RCMs data. The simulated temperature and rainfall data derived from the CORDEX RCMs ensemble were compared with the observed data. The study focused on the IPCC projected periods of
2030, 2050 and 2070 benchmarks. Analysis of the projected rainfall indicated a decreasing trend in rainfall leading up to 2030 followed by an increase in rainfall with the 2050 and 2070 scenarios. In the case of temperature, the projections from all the models showed increase in minimum and maximum temperatures in all seasons and sub periods, like being observed by temperature projection over other parts of the world. The 2030, 2050 and 2070 projected rainfall and temperature change scenarios show that Somalia future development and livelihoods will in future face increased threats of climate extremes unless effective climate smart adaptation systems form integral components of national development strategies.

The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74˚C and 0.60˚C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater
than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.

Due to global land surface warming, severe temperature events are expected to occur more frequently and more extremely causing changes in biodiversity and altering movement and survival of large herbivores. There are increasing observations of escalating wildlife range losses worldwide. In this study, we investigated 15 large wild herbivores (4 migratory, 1 dispersing and 10 residents) and their potential range changes in relation to projected temperatures changes based on three Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. Previous studies of Kenyan savannah have shown that increases in temperature can reduce the densities of wildlife significantly and after certain thresholds the species can be lost in those landscapes. The range maps of the 15 species were developed from aerial censuses that have been conducted in the arid and semi-arid lands of Kenya. We analysed temperature changes for the three RCPs for the periods 2030s, 2050s and 2070s. And based on the temperature threshold for each of the 15 species we analysed which wildlife range areas will be lost. Our results project that for the RCP 2.6, 3 out of the 15 species are projected to lose more than 50% of their range by the year 2030s, and 5 out 15 by 2050s and 4 of 15 by 2070s. The second climate scenario of RCP 4.5 projects that by 2030s, 3 species will lose more than 50% of their range, and in 2050s and 2070s 5 species. The RCP 8.5 which is the extreme scenario of temperature changes projects 5 species to lose their range by 50% in 2030s, 7 species by 2050s and 10 species by 2070s. The extent of range loss was different among species but was severe for buffalo, Thomson’s gazelle, waterbuck, and wildebeest which are also water dependent species.
However, the elephant, gerenuk, hartebeest, lesser kudu, and oryx are expected to retain most of their range in all the RCPs scenarios. These range contractions raise serious concerns about the future of wildlife in Kenyan savannah based on projected climate changes. And therefore, it is imperative the wildlife sector develops climate policies and plans that take into account the projected climate scenarios.

Human adaptive responses to climate change occur at the local level, where climatic variability is experienced. Therefore analyzing vulnerability at the local level is important in planning effective adaptation options in a semi-arid environment. This study was conducted to assess vulnerability of Maasai pastoralist communities in Kajiado County, Kenya to climate change by generating vulnerability index for the communities. Data was collected
using questionnaires that were administered to 305 households in the five different administrative wards (Oloosirkon/Sholinke, Kitengela, Kapetui North, Kenyawa-Poka and Ilmaroro) in Kajiado East. Vulnerability was measured as the net effect of adaptive capacity, sensitivity and exposure to climate change. Principal Component Analysis (PCA) was used to assign weights to the vulnerability indicators used for the study and also to calculate the household vulnerability index. A vulnerability map was produced using the GIS software package ArcGIS 10.2. Results showed that gender of household head, age of household head, educational level, access to extension agents, herd size, livestock diversity and access to credit facility influenced vulnerability of the Maasai pastoralists  to  climate  change  in  Kajiado  East.  The  result  showed  that  the  most  vulnerable communities with the highest negative vulnerability index value are Ilpolosat (‐2.31), Oloosirikon (‐2.22), Lenihani (‐2.05), Konza (‐1.81) and Oloshaiki (‐1.53). The communities with the highest positive vulnerability index values were Kekayaya (4.02), Kepiro (3.47), Omoyi (2.81), Esilanke (2.23), Kisaju (2.16) and Olmerui (2.15). We conclude that provision of basic amenities such as good roads and electricity; access to extension agents, access to credit facilities and herd mobility will reduce vulnerability of Maasai pastoralists in Kajiado east to climate change and variability.

Regional institutions in Africa have the potential to reinforce the adaptive capacity of rural communities in handling climate change impacts. The institutional arrangements provide the rationale for scaling-up adaptation actions by setting the roles of individual players involved in the planning process at local, national and regional levels. The scaling-up then seeks to extend and disseminate the lessons learnt across the levels to support refinement and inclusive implementation of long-term climate change adaptation strategies. This article discusses these considerations through studies of two rural communities faced with the implementation of climate change adaptation strategies in Senegal and Kenya. The cases illustrate different approaches of institutional arrangements and scaling-up of adaptation actions from community to national levels. The lessons from the
communities are typical of most vulnerable rural regions and were hence important for extended dissemination
considering that the impacts of climate change in Africa are felt largely at community levels. A reduction of this
vulnerability requires efficient and realistic adaptation strategies that seek to understand the rural communities while developing considerate policy-based alternatives at all levels of administration

This article presents a remote-sensing tool employing an artificial neural networks algorithm for near real-time determination of the relative humidity (RH) profile above a site using global positioning system (GPS) data recorded by a ground-based GPS receiver. GPS data were processed to obtain Integrated Water Vapour. The integrated water vapour in conjunction with ground level information for temperature, pressure, and RH was fed as inputs to the developed neural network which in turn generated the instantaneous RH profile, at six standard pressure levels of 100, 150, 200, 300, 500, and 700 hPa, as output. GPS and radiosonde data for the years 2009 and 2010 were used to train the system while the same data for 2011 were used to validate the system. The relative humidity profile results for 2011 generated using GPS data and the neural network, upon comparison
with recorded in situ radiosonde RH profile measurements for the same days and times in the year 2011, had root mean square error of less than 4%, which falls within the margin of error of the Vaisala RS92 Radiosonde’s humidity measurement regime.

Nairobi, Kenya exhibits a wide variety of micro-climates and heterogeneous surfaces. Paved roads and high-rise buildings interspersed with low vegetation typify the central business district, while large neighborhoods of informal settlements or “slums” are characterized by dense, tin housing, little vegetation, and limited access to public utilities and services. To investigate how heat varies within Nairobi, we deployed a high density observation network in 2015/2016 to examine summertime temperature and humidity. We show how temperature, humidity and heat index differ in several informal settlements, including in Kibera, the largest slum neighborhood in Africa, and find that temperature and a thermal comfort index known colloquially as the heat index regularly exceed measurements at the Dagoretti observation station by several degrees Celsius. These temperatures are within the range of temperatures previously associated with mortality increases of several percent in youth and elderly populations in informal settlements. We relate these changes to surface properties
such as satellite-derived albedo, vegetation indices, and elevation.

Seasonal climate outlooks have become a necessary input to agricultural planning and execution of all farming activities as a form of adaptation to climate change and variability. Extended climate forecasts of 3–4 months pose a challenge to farmers as it is difficult for them to pinpoint exactly what might happen on daily, weekly or decadal time scales. In addition, such forecasts are presented in form of probability maps and in very coarse resolution, making them difficult for farmers to comprehend. Community-specific downscaled forecasts offer an opportunity for farmers to decide on what, where and when to plant, allocation of resources and on other investment options. This study evaluated various downscaling tools and procedures for seasonal forecast interpretation over the Greater Horn of Africa (GHA) region. The tools evaluated were: analogue year approach, Fact-Fit tool, Water Requirement Satisfaction Index (WRSI) and GeoCLIM tool. Analogue year approach turned out to be good but highly dependent on accuracy of the selected year; Fact-Fit tool was able to convert the seasonal probability forecasts into amounts but unable to disaggregate rainfall amounts at daily, weekly or dekadal time scales; the WRSI tool used was limited to a number of crops, seasons and regions but was necessary for monitoring seasonal progress and predicting crop performance. The current GeoCLIM software used was unable to disaggregate rainfall amounts to daily, weekly or dekadal scales but was good for suitability analysis and producing spatial distribution rainfall maps. An integrated approach is therefore desirable for producing more reliable and dependable location-specific seasonal forecasts for direct application by farmers and other agricultural practitioners. This is so important in the Horn of Africa region, where climate change is already affecting populations, and adaptation is seen as a major approach to cope with the impacts of climate change.

Lodwar town in Turkana County faces water security issues relating to its strategic location, (semi-)arid climate, hydroclimatic variability, high poverty rates, low piped water service and a rapidly growing population challenges that are also relevant to many Kenyan and African small towns in fragile environments. Political, economic and environmental changes affecting Lodwar, including devolution, climate variation and change, demographic shifts, and the exploration of subterranean resources (both water and oil), make this an important time to examine the challenges and prospects for inclusive water security. This working paper discusses findings from a 2016 study of the institutions involved in water decision-making in Lodwar, focusing on their access to and use (or non-use) of weather and climate information. What organisations are involved in water decisions affecting Lodwar town; how do they negotiate information access, accountability and uncertainty; and what is at stake? Drawing on qualitative material collected during a 10-week study of institutional arrangements and decision-making, this paper explores
connections and mismatches between weather/climate knowledge and water decisions in Lodwar town and the wider Turkwel basin.

The aim of this study is to assess adaptation and coping strategies of Maasai pastoralist to climate change and identify viable adaptation options to reduce the impact of climate change among Maasai pastoralist in the arid and semi-arid (ASALS) in Kenya. The study was carried out in Kajiado County and multiple data collection
techniques such as in-depth interview with 305 households, focus group discussion, and key informant interview
were used to assess adaptation strategies of pastoralist household and identify viable adaptation options for the study area. Rainfall data used for the study was also collected from Kenya Meteorological Service (KMS) and used for standard precipitation index (SPI) analysis. SPI was used to analyze drought severity in the study area between 1970 and 2013. SPI was designed to quantify precipitation deficit for multiple time scale. Results showed that drought is the major climatic challenge affecting pastoralist in the study area. The SPI result showed increase in drought occurrence in Kajiado County in recent years with six years (2000, 2003, 2004, 2007, 2008 and 2011) having negative SPI values between 2000-2011. The year 2000 was also the driest year recorded in the study with an SPI value of -3.09. The study also showed that Maasai pastoralists already have many adaptation measures to cope with the impacts of climate extremes. However, increase in drought occurrence in the last few years is reducing their resilience. This study observed that most of the adaptation and coping strategies adopted by Maasai pastoralist are autonomous and are unlikely to build resilience of pastoralist livelihoods and ecosystems to cope with the projected magnitude and scale of climate change in the 21st Century. The study identified adaptation strategies such as effective early warning system, water harvesting, rapid infrastructural development, encouraging table banking and cooperative societies, Building and equipping schools, migration, livestock diversification and child education as long term no regret adaptation option that can enhance resilience of Maasai pastoralist to climate change and its extremes in the arid and semi arid lands of Kenya.

Keywords: adaptation strategies, drought, climate change, Maasai pastoralist

Extreme heat events significantly stress all organisms in the ecosystem, and are likely to be amplified in peri-urban and urban areas. Understanding the variability and drivers behind these events is key to generating early warnings, yet in Equatorial East Africa, this information is currently unavailable. This study uses daily maximum and minimum temperature records from weather stations within Nairobi and its surroundings to characterize variability in daily minimum temperatures and the number of extreme heat events. ERA-Interim reanalysis is applied to assess the drivers of these events at event and seasonal time scales. At seasonal time scales, high temperatures in Nairobi are a function of large scale climate variability associated with the Atlantic Multi-decadal Oscillation (AMO) and Global Mean Sea Surface Temperature (GMSST). Extreme heat events, however, are more strongly associated with the El Nino Southern Oscillation (ENSO). For instance, the persistence of AMO and ENSO, in particular, provide a basis for seasonal prediction of extreme heat events/days in Nairobi. It is also apparent that the temporal signal from extreme heat events in tropics differs from classic heat wave definitions developed in the mid-latitudes, which suggests that a new approach for defining these events is necessary for tropical regions.

This study provides an overview of changing climatic conditions in Kajiado County based on analysis of climatic data and perception of pastoralist on key climatic variables. It collates the two sources of knowledge on climate change, indicating the consistency and inconsistency between the two. Rainfall and temperature data of the study area for a period of 43 years
(1970-2013) was collected from Kenya Meteorological Service, organized and analyzed using Microsoft excel. The perception of Maasai pastoralist to climate change was determined using questionnaires, focus group discussions and key informant interview. Result shows that rainfall trend in Kajiado County have a high variability level (CV %) of 27.5% for Kajiado North, 21.5% for Kajiado West, 26.4% for Kajiado East and 25.2% for Kajiado Central. Although, there is no significant change for rainfall over the study period, result on perception revealed that 83% of respondent perceive that rainfall amount is reducing in the last 30 years. However, perception of pastoralist about years of extreme drought corroborates the meteorological trend of years with very low rainfall. A rise in minimum temperature (1.410C), maximum temperature (0.470C) and average temperature (0.940C) occurred between 1970 and 2013. This agrees with the perception of 81% of Maasai pastoralist, which perceived that temperature has been increasing in the last 30 years. Overall, the results of this study are in line with recent trend of global warming in the region as reported by the latest Intergovernmental panel on Climate Change (IPCC 2014) report.

Keywords: climate change, rainfall, temperature, perception

In this study, a statistical analysis between three solar activity indices (SAI) namely; sunspot number (ssn), F10.7
index (sf) and Mg II index (mg) and total column ozone (TCO) time series over three cities in Kenya namely;
Nairobi (1.17º S; 36.46º E), Kisumu (0.03º S; 34.45º E) and Mombasa (4.02º S; 39.43º E) for the period 1985 -
2011 are considered. Pearson and cross correlations, linear and multiple regression analyses are performed. All
the statistical analyses are based on 95% confidence level. SAI show decreasing trend at significant levels with
highest decrease in international sunspot number and least in Mg II index. TCO are highly correlated with each
other at (0.936< r < 0.955, p < 0.001). SAI are also highly correlated with each other at (0.941< r < 0.976, p <
0.001) and are significantly positively correlated with TCO over the study period except Mg II index at Kisumu.
TCO and SAI have correlations at both long and short lags. At all the cities, F10.7 index has an immediate
impact and Mg II index has a delayed impact on TCO. A linear relationship exists between the two variables in
all the cities. An increase in TCO of about 2 – 3 % (Nairobi), 1 – 2% (Kisumu) and 3 – 4 % (Mombasa) is
attributed to solar activity indices. The multiple correlation coefficients and significant levels obtained show that 3
– 5% of the TCO at Nairobi, Kisumu and Mombasa can be predicted by the SAI.

Keywords: correlation, F10.7 index, Mg II index, regression, solar activity indices, sunspot number, time series,
total column ozone

Access to sound climate information is vital for anticipating climate-related risks and adapting to climate change. As such, it is recognised as an essential input to projects being funded by the Building Resilience and Adaptation
to Climate Extremes and Disasters (BRACED) programme.

Kenya is one of Africa’s most dynamic and entrepreneurial economies, but one with increasing water security risks. These risks are of growing concern to the poor; where it is clear current poverty metrics do not capture the impact and implications of water shocks or long-term human exposure to water risks. This report highlights 4 significant but uncertain developments that will interact to determine Kenya’s progress in its quest to reach middle-income status by 2030 and improve water security for over 17 million poor people: the impacts of decentralisation resilience to climate shocks reducing inequality harnessing mobile ecosystems. The report presents potential locations to establish Water Security Observatories that address these key issues and developments. Through a risk-based approach and science-practitioner partnerships, the observatories are proposed to examine ‘small towns in fragile lands’ and ‘build water secure institutions’ with the goal of reducing water security risks for the poor. This paper is an output from the REACH Improving Water Security for the Poor programme

L'accès, l'utilisation et l'application d'informations météorologiques et climatiques en Afrique et en Asie augmentent.• Cependant, les utilisateurs finaux sont confrontés à différents défis au niveau de l'application des informations qu'ils reçoivent. Cela est lié à la qualité des produits d'information, au fait de ne pas disposer des données aux échelles appropriées et aux difficultés en matière de communication et d'interprétation des renseignements produits. Les informations climatiques doivent être axées sur le service et intégrées à la prise de décision, de l'échelon national au niveau des communautés.

Recent Intergovernmental Panel on Climate Change (IPCC) reports [1] indicate that disasters associated with current climate extremes are impacting negatively on livelihoods and socio-economic systems. Extreme weather events such as floods and droughts are negatively impacting on agricultural production and other socio-economic sectors in the Greater Horn of Africa (GHA) region [2]. It is expected that climate change will increase the severity and frequency of these extreme weather events
with adverse effects particularly on vulnerable and poor communities.

This study analyzes the trends of rainfall in four (4) different Sub Counties (Kajiado North, Kajiado Central, Kajiado East and Kajiado West) in Kajiado County, Kenya. Average monthly rainfall data were collected from Ngong Forest station (Kajiado North), Kajiado Maasai rural training centre Isinya (Kajiado East), Magadi soda works (Kajiado West) and Mashuru (Kajiado Central). The study compares the trend of rainfall in the study area to determine the existence and level of climate variability in Kajiado County. It determines the rainfall variability both spatially, seasonally and inter annually in Kajiado County. Rainfall data for a period of 44years (1970–2013) from the various stations were organized and analyzed using Microsoft excel. Graphs for trend analysis, standard deviation, mean and co-efficient of variance (CV) for the four meteorological stations were calculated.

The effects of conceptual land cover change scenarios on the generation of storm runoffs were evaluated in the Nyando Basin. The spatial scenarios represented alternatives that vary between full deforestation and reforestation. Synthetic storm events of depths 40, 60 and 80 mm were formulated according to the rainfall patterns and assumed to have durations corresponding to the runoff times of concentration. The Natural Resource Conservation Service–Curve Number model was used to generate runoff volumes within the sub‐catchments, which were subsequently routed downstream to obtain effects in the whole basin. The simulated land cover change impacts were evaluated relative to values obtained from the actual land cover state of the basin in the year 2000. From the results, an agricultural land cover scenario constituting of about 86 per cent of agriculture indicated increased runoff volumes in the entire basin by about 12 per cent. An agricultural‐forested land cover scenario with 40 and 51 per cent of forest and agriculture respectively revealed reduced runoff volumes by about 12 per cent. Alternatively, a scenario depicting a largely forested land cover state with about 78 per cent of forests reduced the runoff volumes by about 25 per cent according to the model estimates. Runoff volumes in the basin were also likely to reduce by about 15 per cent if the appropriate land cover scenario for the respective sub‐catchments were to be assumed for runoff management purposes. Considering the prevalent data uncertainty, the study effectively highlights the potential hydrological vulnerability of the basin. The results obtained can form a basis for appropriate catchment management of the area. Copyright © 2012 John Wiley & Sons, Ltd.

Lake Naivasha and its environs usually experience increased levels of pesticide application due to the rapid increase in acreage under flower production in the catchment. Previous studies have shown detectable levels of organo-chlorines residues; which is an indication of contamination. Organochlorines persist in the environment and bio accumulates in the body tissue of living organisms while, the organophosphates which have been adopted as an alternatives are highly toxic. Such occurrences are linked to the declining trends in water bird numbers witnessed earlier. The objectives of the present study were to determine pesticide residue concentrations of organophosphates and organo-chlorines and determine their effects on water bird numbers. The Lake was subjected to a cross-sectional study between the months of February to July, 2011. The sampling sites were selected on the basis of their uniqueness in the nature of discharge released into the Lake. There was no mathematical formula applied to calculate sample size, due to the discrete nature of variables. The water bird counts were recorded on Microsoft excel spread sheet and subjected to analysis while applying statistical package of social science (SPPS) using one way ANOVA at p<0.05. The study showed an upward trend in the
water bird numbers while Gas Liquid Chromatography technique showed non detectable limits for the targeted analytes. These results were good signs indicative of the Lake being on its pathway to restoration to the previous state of non-contamination. The study further, recommends that the government through its enforcement agencies should continue to carry out regular inspections on the ongoing human activities in the Lake and its environs to prevent sporadic contamination and discourage any further discharge of contaminants into the Lake. Moreover, this will enable the government to generate useful information for decision making purpose as they formulate policy framework for the protection, conservation and sustainable utilization of natural resources.
Key words: Organophosphates, organo-chlorines, Gas Liquid Chromatography, contamination.

The daily meteorological data of relative humidity, maximum, minimum, and average temperatures obtained from five stations of the Kenya Meteorological Department over the period 1986 to 2005 were filtered and reduced to monthly means. Monthly data of solar indices: Sunspot number, F10.7 cm solar radio flux and Mg II core-to-wing ratio covering the same period were employed to model the meteorological variables using the linear multivariate model and applying least square fittings. Validity of the models was tested using Mean Bias Error (MBE) and Root Mean Square Error (RMSE) statistical indicators. The correlations between the observed and predicted values from the models were significant at above 95% level of confidence. The models show the effect of solar forcing on the climatic parameters at different locations in Kenya. Solar forcing of climate is evident in Kenya.
Keywords: modeling, climatic parameters, solar indices, statistical indicators.

A study was conducted to investigate the effect of increasing amounts of Prosopis juliflora seedpod meal on the growth rate of weaner Galla goats. The overall aim of this study was to assess the feasibility of incorporating Prosopis seedpods into a typical dryland livestock production system. Twenty weaner Galla goats of similar age (6 months) and weights (11-14 kg) were randomly assigned to four treatments of five weaners each. The treatments were T1 No Prosopis (control treatment), T2 (100 g /goat /day Prosopis), T3 (200 g /goat /day Prosopis), and T4 (400g /goat /day Prosopis). Prosopis contained 88.4% dry matter (DM), 18.5% crude protein (CP), 83.2% organic matter (OM), 51.8% neutral detergent fibre (NDF), 29.8% acid detergent fibre and 5.2% Ash. The experiment lasted for 70 days. Overall, all the treatment groups exhibited higher average weekly weight gains than T1 (control) throughout the experimental period. However, for the first 3 weeks, these differences were not statistically significant (P<0.05). From the fifth week on wards, however, the differences in growth rates were statistically significant (P<0.05). Treatment T3 exhibited highest total weight gain (3.96 kg), followed by T4 (2.70kg). Group T1 lost weight by the end of the experiment. This study demonstrated that Prosopis could be used as goats feed up to 200g/goat/day giving good weight gains and no negative effects on feed intakes and digestibility.

Key words: Supplementation, feed conversion efficiency, Prosopis juliflora, weight gains

Most vulnerable groups in countries in Sub Saharan Africa including Kenya are the poor who have least capacity for coping with the adverse impacts of the current climate extremes, and adapting to future climate changes. Lack of suitable coping and adaptation strategies coupled with limited institutional, economic, and technological capacity to support the required actions increases the vulnerability of the country to adverse climatic impacts. This project aims at exploring ways of enhancing Kenya’s capacity through training to adequately respond to the devastating climatic extremes such as droughts, floods and other weather related disasters that have impacted
negatively to its socio-economic development and community livelihoods. This was addressed through four supervised projects by postgraduate meteorology and agrometeorology students of the university of Nairobi. Both field work and desk top studies involving analysis of secondary data of various project concerns were carried out. Decision on-farm experiments covering potential adaptation strategies targeting both crop (pigeon pea and sugarcane) and livestock (pasture) production systems were conducted in selected study districts of the country. Preliminary results of the project show great potential for using remote sensing data for rainfall estimation and identification of pasture availability and management by ASAL communities as well as policy makers. With regard to sugarcane-based livelihoods, climate variability as determined by rainfall variability during the grand growth stage of sugarcane was identified as exerting greater influence on sugarcane productivity. The study also showed that the use of basal phosphorus fertilizer in pigeon pea growing area of Makueni district resulted into tremendous crop yield increase.

Key words: Agriculture, climate change, climate risk reduction, food security

Extreme climatic events, such as droughts and floods, as well as changes in the mean climate, have a direct
effect on crops and livestock and, thus, people’s livelihoods. Food security is at risk, particularly in sub-Saharan Africa where local production remains largely rain-fed. Given that climate variability is likely to increase with increasing greenhouse gas emissions, it is more important than ever to understand how this variability can be managed to reduce the negative consequences.
The impact is already significant. In Malawi, for example, as a result of the 2002 drought, approximately 5 million
people needed emergency food aid, which took a long time to be delivered. A similar situation occurred in Niger
in 2004–2005 when approximately 2.5 million people — or a fifth of the population — was in need of food rations
(UNDP 2007). In 2009, approximately 3.8 million people in Kenya required food aid because of the prolonged
drought (FEWS Net 2010). In 2006, sub-Saharan Africa accounted for 13% of the world’s population and 25% of the undernourished people in the developing world (FAO 2006).

The objective of this study was to monitor grassland phenological stages in selected arid and semi-arid lands (ASALs) of Kenya, so as to provide information useful in pasture management. Five years of Normalized Difference Vegetation Index (NDVI) data from the VEGETATION instrument onboard SPOT were extracted over three ASAL districts. Extraction points were based on a land cover map that showed the location of grassland
in the three districts. Piecewise logistic functions were applied on the NDVI data in order to identify phenological stages. RFE data were then used to relate the identified stages to rainfall using lagged correlation. Curves of the correlated lagged rainfall and NDVI from the determined phenological stages were plotted to compare their temporal patterns. Spatial patterns of length of the growth period were also assessed. Interannual phenological stages appeared to follow a clear growth –senescence temporal pattern. Two growth periods were identified in all the districts, consistent with known cycles of different grass and browse species in the areas. Peak growth
was seen to occur during the short rains in Kajiado district and during the long rains in Baringo district. Growth in the two seasons was almost the same in Garissa district. Phenological stages were significantly correlated to different lags of rainfall, with response to a longer lag observed during the March to June growth period. Patterns of lagged rainfall were also found to be similar to those of NDVI at the different stages. The length of both growth periods showed spatially coherent patterns that signified the distribution of different pasture species. Given these results, logistic functions were able to model grassland phenological stages in the ASALs.

Key words: ASALs, logistic functions, NDVI, pasture, phenological stages

At heart, these elders are fellow scientists, and some of their myths and taboos serve to protect endangered species the community depends on for medicines, rituals and other uses. Launched in 2006 by Canada's International Development Research Centre and Britain's Department for International Development, this program aims to improve the capacity of African countries to adapt to climate change in ways that benefit the most vulnerable. The participation of the Kenya Industrial Property Institute, a department under the Ministry of Trade and Industry, is also crucial to preserving the Nganyi's intellectual property rights.

Recent Intergovernmental Panel on Climate Change (IPCC) reports [1] indicate that disasters associated with current climate extremes are impacting negatively on livelihoods and socio-economic systems. Extreme weather events such as floods and droughts are negatively impacting on agricultural production and other socio-economic sectors in the Greater Horn of Africa (GHA) region [2]. It is expected that climate change will increase the severity and frequency of these extreme weather events with adverse effects particularly on vulnerable and poor communities.

Precipitation is one of the major components of the earth’s climate system. Many countries in the tropics depend on rainfall for the agricultural and hydrological activities which are dominant in their economies. Rainfall information is a crucial aspect not only for sustainable social-economic development of many countries but also for study of atmospheric circulations, climate analysis and global energy balance. Hence it is important to use reliable and accurate rainfall data in any planning. This study aims at validating satellite-derived rainfall estimates
retrieved from TRMM’s monthly rainfall retrieval algorithm, (3B-43 algorithm), over Kenya. The study analyzes eleven years of monthly rainfall estimates (1998-2008) produced by Tropical Rainfall Measuring Mission (TRMM)’s 3B-43 algorithm and compares them with gridded monthly rainfall totals from 26 synoptic and Agrometeorological stations in Kenya for the same period. Preliminary results suggest that satellite rainfall estimates can be modeled to represent areal rainfall in areas with inadequate ground based rainfall observations, especially over Northwestern, Northern, Northeastern and Southern Kenya.

Key words: Agrometeorology, rainfall data, remote sensing

Using the fast Fourier transform (FFT) method, we determined the spectral characteristics of some meteorological variables over Kenya and identified the prominent periodicities associated with the variables. The meteorological variables studied are the maximum temperature, mini-mum temperature, average temperature, wind speed, precipitation, relative humidity, solar radia-tion intensity, evaporation and sunshine duration. Data from five terrestrial stations, represent-ing the regional climatic zones in Kenya, were employed in the study. The result reveals periods that are associated with solar activity. It is established that solar forcing is very significant over the Kenyan climate. The Sun-Climate relations were influenced at some locations by local ef-fects such as orography and vegetation.

Keywords: periodicity, solar activity, Sun-climate relations

This paper investigates the inter-relationship between solar radiation intensity RD and relative humidity RH in Kenya using daily data obtained at five meteorological stations; Nairobi (1.3°S, 36.75°E), Kericho (0.37˚S, 35.72˚E), Kisumu (0.10˚S, 34.75˚E), Mombasa (4.03˚S, 39.65˚E) and Garissa (0.48˚S, 39.63˚E) during the solar minimum year 1986. Statistical methods were employed and the coefficients of correlation, r obtained range from 0.16094 to -0.6758618 between the two variables for the five stations. The linear equation relating the solar radiation intensity RD to relative humidity RH is obtained using linear regression analysis as RH = 109.1091-1.5997RD for the Nairobi station. Jandel scientific and Megastat software analyses gave fairly similar trends of results for Nairobi and other stations, and for all the seasons except for those of Garissa station. Obviously there exists a negative interdependence between solar radiation intensity and relative humidity such that the relative humidity decreases as solar radiation increases and vice versa. This observation is explicable in terms of the dynamics of atmospheric heating and advection traceable to solar activity.

For hydrological, agricultural and other raindependent activities, the estimates of the average rainfall over a catchment are very important.' Most of the methods formulated for estimating the areal average rainfall make use use of raingauges has several disadvantages which are, sometimes, not easily controlled. Due to these drawbacks, recent attempts ha~e been made to utilize remote sensing techniques in the estimation of areal rainfall. Areal estimation of rainfall from METEOSAT satellite data is the main objective of this study. 10-day and monthly total cold-cloud durations (CCD) for the months of January and February, 1987 covering the area within Latitudes 34°E to 400E and Longitudes 50S to 90S of S'butQ.ernTanzania, digitized corresponding to the raingauge statiction network,for three different temperature thresholds was used. These records of • -!Meteosat
data were'compiled at University of Reading, U.K. Daily raingauge records from 147 stations located within the study area were used. These records were used in generating 10-day and monthly total rainfall records which were employed in the study as "ground truth" records. The rainfall records were obtained from the Directorate of Meteorology df Tanzania, Dar es Salaam. The study was divided into three sections. The first section deals with the relationship between the point CCDs and the surface recorded rainfall. Si!.ipl