Gilbert Ouma

Institutional challenges in scaling-up climate change adaptation actions: experiences from rural communities in Senegal and Kenya

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.

Temperature and heat in informal settlements in Nairobi.

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.

Tools and Procedures for Seasonal Downscaling of Climate Forecasts for Use by Farmers Over the Greater Horn of Africa: A Case Study for Western Kenya

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.

Near real-time tropospheric water vapour profiling using a ground-based GPS receiver

ABSTRACT 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.

Changes in Rainfall and Surface Temperature Over Lower Jubba, Somalia

Please cite this article as: Linda A.O, G. Ouma and P. Omondi, 2017. Changes in Rainfall and Surface Temperature Over Lower Jubba, Somalia. J. clim. chang. sustain. Vol 1, issue 2, pp. 38-50. https://doi.org/10.20987/jccs.1.08.2017 Climate is changing at an alarming rate threatening the critical pillars for environmental, social and economic development. Signals of climate change seems to be quite real for many African communities. Somalia, is one the countries of the GHA that has faced unique climate variability and climate change challenges, within severe conflict environment and lack of a stable government for many years. The objective of this study was to understand the past and present rainfall and temperature patterns over Lower Jubba. Rainfall data used extended from 1981-2015, while those of temperature 1981-2012. The study for rainfall concentrated within the two main rainfall seasons namely Gu and Deyr. Temperature data were however analysed for all the four seasons, June to August, December to February, September to November, and March to May. The data were subjected to various trend analysis methods that included time series plots of the graph of the specific rainfall and temperature observations. Two statistical approaches namely linear regression and Man-Kendal non-parametric statistics were employed in testing the significance of the slope of the rainfall and temperature time series for specific seasons. Evidences from tend analyses showed increasing trends in both minimum and maximum temperatures at all locations and all seasons, which is consistent with patterns that have been delineated in many parts of the Greater Horn of Africa. IPCC among many other past studies have linked global temperature increase worldwide to climate change induced global warming. Due to limitation in the length of temperature data used in this study, it be would be difficult to attribute the observed trends in temperature records entirely to climate change. The results from rainfall showed that most of the trends observed were not statistically significant. Few significant trends that were delineated at some locations were not spatially consistent over large areas. The most dominant characteristics of rainfall time series were high degree of interannual variability with recurrences in high/low value extremes that are often associated with floods/droughts. Some of these extremes occurred during El Nino /La Nina years. Results are consistent with those from some past studies in the region. The results from the study can be used in the planning and risk management of all climate sensitive socio-economic development activities in Somalia, especially in the development of strategy for sustainable community livelihoods and development in Lower Jubba.