Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections

Version 1 : Received: 5 January 2021 / Approved: 6 January 2021 / Online: 6 January 2021 (11:37:37 CET)

How to cite: Ayugi, B.; Dike, V.; Ngoma, H.; Babaousmail, H.; Ongoma, V. Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections. Preprints 2021, 2021010112 (doi: 10.20944/preprints202101.0112.v1). Ayugi, B.; Dike, V.; Ngoma, H.; Babaousmail, H.; Ongoma, V. Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections. Preprints 2021, 2021010112 (doi: 10.20944/preprints202101.0112.v1).

Abstract

This paper presents an analysis of precipitation extremes over the East African region. The study employs six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) to evaluate possible climate change. Observed datasets and CMIP6 simulations and projections are employed to assess the changes during the two main rainfall seasons of March to May (MAM) and October to December (OND). The study evaluated the capability of CMIP6 simulations in reproducing the observed extreme events during the period 1995 – 2014. Our results show that the multi-model ensemble (herein referred to as MME) of CMIP6 models can depict the observed spatial distribution of precipitation extremes for both seasons, albeit with some noticeable exceptions in some indices. Overall, MME's assessment yields considerable confidence in CMIP6 to be employed for the projection of extreme events over the study area. Analysis of extreme estimations shows an increase (decrease) in CDD (CWD) during 2081 – 2100 relative to the baseline period in both seasons. Moreover, SDII, R95p, R20mm, and PRCPTOT demonstrate significant OND estimates compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while reduction is observed over the Tanzania region. The increase in projected extremes during two main rainfall seasons poses a significant threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are encouraged to examine the underlying physical features modulating the occurrence of extremes incidences projected for relevant policies.

Subject Areas

CMIP6; extreme precipitation; model evaluation; east Africa

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