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Projections of precipitation extremes based on bias‐corrected Coupled Model Intercomparison Project phase 6 models ensemble over southern Africa.

Authors :
Lim Kam Sian, Kenny Thiam Choy
Hagan, Daniel Fiifi Tawia
Ayugi, Brian Odhiambo
Nooni, Isaac Kwesi
Ullah, Waheed
Babaousmail, Hassen
Ongoma, Victor
Source :
International Journal of Climatology; 12/30/2022, Vol. 42 Issue 16, p8269-8289, 21p
Publication Year :
2022

Abstract

The increasing awareness of climate change requires accurate, reliable and timely information on possible precipitation (PRE) changes to build climate resilience. This study uses the Coupled Model Intercomparison Project phase 6 (CMIP6) data to examine the effectiveness of bias correction on simulated historical mean and extreme PRE, and investigates the projected changes in extreme PRE events over southern Africa (SAF). Quantile mapping on a gamma distribution bias correction method is applied to the historical and projected CMIP6 data, with the Global Precipitation Climatology Centre (GPCC) PRE dataset as reference data. The projection analyses are conducted for the wet (December–March) and dry (May–October) seasons for two shared socioeconomic pathway (SSP) scenarios: SSP2‐4.5 and SSP5‐8.5. The results affirm that the bias correction significantly reduces (by more than 90%) the biases in the modelled mean and extreme PRE. The projected extreme PRE shows a general drying pattern over SAF. In the wet season, wet days (R1mm) are projected to decrease by 1 and 2 days by the end of the 21st century for SSP2‐4.5 and SSP5‐8.5, respectively, while very heavy PRE days (R20mm) show a slight upward pattern over SAF, reaching 0.1 and 0.4 days for the two scenarios. In contrast, the dry season exhibits a more pronounced drying tendency, with a consistent decrease in R1mm of 2 and 0.1 days by 2100 for SSP2‐4.5 and SSP5‐8.5, respectively. R20mm is projected to decrease by 4 and 0.2 days for SSP2‐4.5 and SSP5‐8.5, respectively. This implies that SAF is expected to get drier during the dry season while the PRE intensity during the wet season is projected to increase. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08998418
Volume :
42
Issue :
16
Database :
Complementary Index
Journal :
International Journal of Climatology
Publication Type :
Academic Journal
Accession number :
161063320
Full Text :
https://doi.org/10.1002/joc.7707