Endemic malaria in most of the hot and humid African climates is the leading cause of morbidity and mortality. In the last twenty or so years the incidence of malaria has been aggravated by the resurgence of highland malaria epidemics which hitherto had been rare. A close association between malaria epidemics and climate variability has been reported but not universally accepted. Similarly, the relationship between climate variability, intensity of disease mortality and morbidity coupled with socio-economic factors has been mooted. Analyses of past climate (temperature and precipitation), hydrological and health data , and socio-economics status of communities from the East African highlands confirm the link between climate variability and the incidence and severity of malaria epidemics. The communities in the highlands that have had less exposure to malaria are more vulnerable than their counterparts in the lowlands due to lack of clinical immunity. However, the vulnerability of human health to climate variability is influenced by the coping and adaptive capacities of an individual or community. Surveys conducted among three communities in the East African highlands reveal that the interplay of poverty and other socio-economic variables have intensified the vulnerability of these communities to the impacts of malaria.

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.

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.

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.

The Turkana Low-level Jet (LLJ) is an intrinsic part of the African climate system. It is the principle conduit for water vapour transport to the African interior from the Indian Ocean, and droughts in East Africa tend to occur when the jet is strong. The only direct observations of the Turkana Jet come from manual tracking of pilot balloons in the 1980s. Now, modern reanalysis datasets disagree with one another over the strength of jet winds and underestimate the strength of the jet by 25-75% compared to the pilot balloon data. This article gives an overview of a month-long field campaign based in northwest Kenya - the Radiosonde Investigation For the Turkana Jet (RIFTJet) - which measured the Turkana Jet for the first time in forty years using modern technologies. Radiosonde data reveal a persistent low-level jet, which formed on every night of the campaign, with an average low-level maximum wind speed of 16.8 m.s-1 at 0300LT. One of the latest reanalysis datasets (ERA5) underestimates low-level wind speeds by an average of 24% (4.1 m.s-1) at 0300LT, and by 33% (3.6 m.s-1) at 1500LT. The measurements confirm the role of the Turkana LLJ in water vapor transport: mean water vapour transport at Marsabit is 172 kg.m.s-1. The dataset provides new opportunities to understand regional dynamics, and to evaluate models in one of the most data sparse regions in the world.