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Tropical and Subtropical Agroecosystems
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://dx.doi.org/10.60692/xe...
Other literature type . 2023
Data sources: Datacite
https://dx.doi.org/10.60692/nm...
Other literature type . 2023
Data sources: Datacite
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ASSESSMENT OF TEMPORAL VARIABILITY OF TEMPERATURE AND PRECIPITATION TRENDS IN KARGI, MAIKONA, DAKABARICHA AND SOLOLO WARDS OF MARSABIT COUNTY, KENYA

تقييم التباين الزمني لاتجاهات درجات الحرارة وهطول الأمطار في كارغي ومايكونا وداكاباريشا وسولو واردز في مقاطعة مارسابيت، كينيا
Authors: Armara Macimiliam Galwab; Oscar Kipchirchir Koech; Oliver Vivian Wasonga; Godfrey Kironchi;

ASSESSMENT OF TEMPORAL VARIABILITY OF TEMPERATURE AND PRECIPITATION TRENDS IN KARGI, MAIKONA, DAKABARICHA AND SOLOLO WARDS OF MARSABIT COUNTY, KENYA

Abstract

<p><strong>Background.</strong> Climate change is a global phenomenon, with varying indicators and impacts from one region to another. The impacts of the changing climate are high in developing countries that are mainly dependent on climate-driven economic sectors such as pastoral and agro-pastoral livelihoods. <strong>Objective.</strong> Analyze the temporal trend, the variability in temperature and precipitation, and the relationship between both parameters to determine the influence of the El Niño phenomenon in Marsabit County, Kenya, from 1981 to 2021. <strong>Methodology.</strong> Daily rainfall and temperature data for the four study locations (Maikona, Kargi, Dakabaricha, and Sololo) were obtained. The analysis of extremes was the main method used in the analysis of the temporal and spatial variability of rainfall and temperature to establish the frequency and magnitude of climate variability in the study area. The seasonal mean plus or minus 1 Standard deviation for the entire period of study was used in the analysis of extremes. <strong>Results.</strong> Findings from trend analysis showed that rainfall trends have significantly increased in Marsabit County. Further, results on seasonal trends and variability of rainfall showed that March-April-May rainfall has been decreasing over the years. Below average rainfall has been experienced in Maikona in 2000 and 2011 with a magnitude of -42.9 mm, and -39.3 mm, respectively, while below average rainfall has been experienced in Kargi in 2000, 2009, 2011, and 2012 with a magnitude of -41.7 mm, -24.2 mm, -35.3 mm, and -34.3 mm, respectively. Analysis of the temperature trends and variability showed that both night and day temperatures have significantly increased over the years in Marsabit County. The magnitude of warming was found to be double that of cooling. The regression analysis further showed that there exists a negative correlation between temperatures and rainfall, implying that generally, rainfall decreases with increasing temperatures. <strong>Implications.</strong> This finding is important because it could help policymakers and people working on development in Marsabit County see what temperature and precipitation changes are happening locally. This could help them plan for climate change better. Both pastoral and agro-pastoral areas have been affected by both El Niño and La Niña activities, with the El Niño years recording the highest amounts of rainfall while the La Niña years recording the lowest amounts. <strong>Conclusion</strong><strong>s</strong><strong>.</strong> This study recommends the use of rainwater harvesting during the October to December Season to take advantage of the increasing Trends and flood episodes associated with high magnitudes and frequencies of above average rainfall and use the same to cope with reduced rainfall in the March to May season. </p>

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Keywords

climate variability, Physical geography, temporal variability, Agriculture (General), Astronomy, Precipitation, Management, Monitoring, Policy and Law, Environmental science, S1-972, Livelihood, Meteorology, Rangeland Degradation and Pastoral Livelihoods, Climate change, Magnitude (astronomy), marsabit county-kenya., Biology, Climatology, Global and Planetary Change, precipitation trends, Geography, Ecology, S, temperature trends, Physics, Climate Change and Environmental Impact, Agriculture, Geology, FOS: Earth and related environmental sciences, Sustainability, Archaeology, FOS: Biological sciences, Environmental Science, Physical Sciences

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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