Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya
The changing probabilities of extreme climate and weather events, in terms of frequency, intensity, spatial extent, duration, and timing is one of the most noticeable and damaging manifestations of human-induced climate change. During the March-April-May (MAM) rainfall season of 2012, 2016 and 2018,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Weather and Climate Extremes |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2212094722001086 |
| _version_ | 1811321759039750144 |
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| author | Joyce Kimutai Mark New Piotr Wolski Friederike Otto |
| author_facet | Joyce Kimutai Mark New Piotr Wolski Friederike Otto |
| author_sort | Joyce Kimutai |
| collection | DOAJ |
| description | The changing probabilities of extreme climate and weather events, in terms of frequency, intensity, spatial extent, duration, and timing is one of the most noticeable and damaging manifestations of human-induced climate change. During the March-April-May (MAM) rainfall season of 2012, 2016 and 2018, Kenya experienced high rainfall that caused both widespread and localised flooding, resulting in human and livestock deaths, destruction of infrastructure and property, bursting of riverbanks, submerging of farmlands and emergence of isolated cases of water-borne diseases. Here, we aim to quantify how the magnitude of heavy rainfall during these seasons may have been altered by human-induced climate change. We undertake a probabilistic attribution analysis using three different approaches utilising two observational datasets and two independent climate model experiment set-ups. We analyse three different seasonal heavy rainfall indices, maximum consecutive 5-day, 10-day, and 20-day rainfall, to compare the magnitude of maxima recorded in MAM 2012, 2016 and 2018 with the magnitude of maxima in a pre-industrial climate (with little or no anthropogenic influence). We find a shift towards intensification of extreme rainfall in today's climate, although these increases are not in all cases statistically distinguishable from our estimates of magnitudes in the preindustrial climate. Although we find no significant anthropogenic climate change influence, the intensification of extreme rainfall amid the observed drying trend and the projected increases in rainfall in the MAM season in Kenya, leave the already vulnerable societies with uncertainties about how to prepare for a changing climate. This study, therefore, provides a basis for an in-depth assessment of current and future trends of extreme rainfall in East Africa in adapting to changing climate risks for sustainable development in the already vulnerable and less resilient society. |
| first_indexed | 2024-04-13T13:23:20Z |
| format | Article |
| id | doaj.art-ea32c47c00514882a5500a87f0f4ac02 |
| institution | Directory Open Access Journal |
| issn | 2212-0947 |
| language | English |
| last_indexed | 2024-04-13T13:23:20Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Weather and Climate Extremes |
| spelling | doaj.art-ea32c47c00514882a5500a87f0f4ac022022-12-22T02:45:16ZengElsevierWeather and Climate Extremes2212-09472022-12-0138100529Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in KenyaJoyce Kimutai0Mark New1Piotr Wolski2Friederike Otto3African Climate Development Institute, University of Cape Town, Cape Town, South Africa; Kenya Meteorological Department, Nairobi, Kenya; Corresponding author. African Climate Development Institute, University of Cape Town, Cape Town, South Africa.African Climate Development Institute, University of Cape Town, Cape Town, South AfricaClimate Systems Analysis Group, University of Cape Town, South AfricaGrantham Institute, Imperial College, London, UKThe changing probabilities of extreme climate and weather events, in terms of frequency, intensity, spatial extent, duration, and timing is one of the most noticeable and damaging manifestations of human-induced climate change. During the March-April-May (MAM) rainfall season of 2012, 2016 and 2018, Kenya experienced high rainfall that caused both widespread and localised flooding, resulting in human and livestock deaths, destruction of infrastructure and property, bursting of riverbanks, submerging of farmlands and emergence of isolated cases of water-borne diseases. Here, we aim to quantify how the magnitude of heavy rainfall during these seasons may have been altered by human-induced climate change. We undertake a probabilistic attribution analysis using three different approaches utilising two observational datasets and two independent climate model experiment set-ups. We analyse three different seasonal heavy rainfall indices, maximum consecutive 5-day, 10-day, and 20-day rainfall, to compare the magnitude of maxima recorded in MAM 2012, 2016 and 2018 with the magnitude of maxima in a pre-industrial climate (with little or no anthropogenic influence). We find a shift towards intensification of extreme rainfall in today's climate, although these increases are not in all cases statistically distinguishable from our estimates of magnitudes in the preindustrial climate. Although we find no significant anthropogenic climate change influence, the intensification of extreme rainfall amid the observed drying trend and the projected increases in rainfall in the MAM season in Kenya, leave the already vulnerable societies with uncertainties about how to prepare for a changing climate. This study, therefore, provides a basis for an in-depth assessment of current and future trends of extreme rainfall in East Africa in adapting to changing climate risks for sustainable development in the already vulnerable and less resilient society.http://www.sciencedirect.com/science/article/pii/S2212094722001086Extreme rainfallExtreme event attributionFactual and counterfactualMagnitude ratioAttributable magnitude |
| spellingShingle | Joyce Kimutai Mark New Piotr Wolski Friederike Otto Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya Weather and Climate Extremes Extreme rainfall Extreme event attribution Factual and counterfactual Magnitude ratio Attributable magnitude |
| title | Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya |
| title_full | Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya |
| title_fullStr | Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya |
| title_full_unstemmed | Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya |
| title_short | Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya |
| title_sort | attribution of the human influence on heavy rainfall associated with flooding events during the 2012 2016 and 2018 march april may seasons in kenya |
| topic | Extreme rainfall Extreme event attribution Factual and counterfactual Magnitude ratio Attributable magnitude |
| url | http://www.sciencedirect.com/science/article/pii/S2212094722001086 |
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