Survey on the Utilization of Weather Information and Products for Selected Districts in Kenya

Muthama, Nzioka John; Masieyi, W.B.; Opere, Alfred; Mukabana, Joseph; Nyakwada, W; Aura, Stella; Chanzu, B. A.; Manene, M.M.

doi:10.20987/jmrs.08.2012.605

Cited by 7 publications

(5 citation statements)

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“…Rainfall is the most valuable weather parameter in EA (Muthama et al ., ), which explains why rainfall has been studied in more depth relative to other weather variables. Although temperature does not adversely affect many economic activities in the region, studies have shown that temperature has a strong influence on malaria cases, especially in highland areas.…”

Section: Introductionmentioning

confidence: 99%

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

Ongoma

Chen

Gao

2017

Intl Journal of Climatology

103

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This study presents potential future variations of mean rainfall and temperature over East Africa (EA) based on five models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and representative concentration pathways (RCPs): 4.5 and 8.5. In this study, climate simulations of two timeframes, a baseline period (1961–1990) and projection period (2071–2100), are compared. The models reproduce EA's bimodal rainfall pattern but overestimate and underestimate seasonal rainfall of October–December (OND) and March–May (MAM), respectively. Rainfall is projected to increase under the two scenarios. Larger increases in rainfall will occur during the OND season than during the MAM season and in RCP8.5 than in RCP4.5. During the last half of the 21st century, EA is likely to warm by 1.7–2.8 and 2.2–5.4 °C under the RCP4.5 and RCP8.5 scenarios, respectively, relative to the baseline period. Scenario uncertainty is projected to exceed model uncertainty from the middle to the end of the 21st century. The central parts of Kenya and the Lake Victoria Basin will witness the highest increases in seasonal rainfall. The probability density functions (PDFs) of future seasonal rainfall show a positive shift and a statistically insignificant increase in variance relative to the baseline. Thus, EA is likely to experience an increase in extreme rainfall events. Understanding the future climate variability in EA is important for planning purposes but these results are based on relatively course resolution models prone to bias and therefore should be used with caution. There is a need for further research on climate projections over EA, including determining the causes of the poor performance of global models in reproducing rainfall climatology and trends over the region.

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Section: Introductionmentioning

confidence: 99%

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

Ongoma

Chen

Gao

2017

Intl Journal of Climatology

103

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“…The most commonly used statistical methods non-parametric methods based on rank statistics such as Mann-Kendall and the Spearman rank tests (Ogallo, 1980;1981;Muthama , et al, 2012). In Mann Kendall analysis, positive values indicate an increase in constituent with time, whereas negative values indicate a decrease in constituent with time.…”

Section: Trend Analysismentioning

confidence: 99%

Changes in Rainfall and Surface Temperature Over Lower Jubba, Somalia

Ogallo¹,

Ouma²,

Omondi³

2017

J. Clim. Chang. Sustain

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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 socioeconomic development activities in Somalia, especially in the development of strategy for sustainable community livelihoods and development in Lower Jubba.

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“…Rainfall is the most important weather parameter in Kenya, and many other developing nations whose economy mainly depend on rain-fed agriculture (Muthama, et al, 2012). Extreme weather events are thus associated with huge socio-economic losses that can be avoided through provision of accurate and timely weather forecast.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS)

Sagero¹,

Shisanya²,

Ongoma³

et al. 2016

Geogr Pannon

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This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD). It reviews the skill and accuracy of the Weather Research and Forecasting (WRF)-Environmental Modeling System (EMS) model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

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Survey on the Utilization of Weather Information and Products for Selected Districts in Kenya

Cited by 7 publications

References 0 publications

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

Changes in Rainfall and Surface Temperature Over Lower Jubba, Somalia

Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS)

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