Contribution of anthropogenic climate change to the magnitude of extreme rainfall events and associated synoptic conditions during recent flooding in Kenya

Kimutai, Joyce

Contribution of anthropogenic climate change to the magnitude of extreme rainfall events and associated synoptic conditions during recent flooding in Kenya

Thesis / Dissertation

2023

Abstract

The changing probabilities of extreme climate and weather events, in terms of frequency, intensity, spatial extent, duration and timing, are one of the most noticeable and damaging manifestations of human-induced climate change. The Greater Horn of Africa has experienced a number of extreme weather and seasonal climate events over the past two decades. While droughts have predominated, several heavy precipitation events with devastating impacts have also been recorded. During the MarchApril-May (MAM) rainfall seasons 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. This research aimed to assess whether human influence on climate played a role in modifying the rainfall intensity and associated synoptic conditions of extreme rainfall in these years. The work had three specific objectives: (i) Characterise the rainfall magnitude and associated synoptic conditions at the time of the flooding events; (ii) Evaluate the role of human influence on the magnitude of heavy rainfall; (iii) Evaluate the role of human influence on the synoptic conditions associated with heavy rainfall. By using three different attribution approaches, and utilising two observational datasets, one reanalysis data and two independent climate model experiment setups, the study was able to quantify how the local thermodynamic and regional dynamic conditions driving the flood-inducing rainfall in these seasons may have been altered by human-induced climate change. The rainfall magnitudes and associated atmospheric states were first characterised and then differences in the rainfall magnitudes and frequency of the atmospheric states in MAM 2012, 2016 and 2018 were compared to those in preindustrial climate. Three different seasonal heavy rainfall indices were analysed; seasonal maximum consecutive 5-day, 10-day, and 20-day rainfall. The atmospheric states were based on Self Organizing Maps analysis of specific humidity, air temperature, and zonal and meridional wind at 850hPa on surface level pressure and zonal moisture flux.

Keywords

Environmental and Geographical Science

Reference:

Collections

PhD / Doctoral

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