The impact of lateral boundary forcing in the CORDEX-Africa ensemble over southern Africa
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Published:2023-04-06
Issue:7
Volume:16
Page:1887-1908
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Karypidou Maria Chara, Sobolowski Stefan PieterORCID, Sangelantoni LorenzoORCID, Nikulin GrigoryORCID, Katragkou EleniORCID
Abstract
Abstract. The region of southern Africa (SAF) is among the most exposed climate change
hotspots and is projected to experience severe impacts across multiple
economical and societal sectors. For this reason, producing reliable
projections of the expected impacts of climate change is key for local
communities. In this work we use an ensemble of 19 regional climate model
(RCM) simulations performed in the context of the Coordinated Regional
Climate Downscaling Experiment (CORDEX) – Africa and a set of 10 global
climate models (GCMs) participating in the Coupled Model Intercomparison
Project Phase 5 (CMIP5) that were used as the driving GCMs in the RCM
simulations. We are concerned about the degree to which RCM simulations are
influenced by their driving GCMs, with regards to monthly precipitation
climatologies, precipitation biases and precipitation change signal,
according to the Representative Concentration Pathway (RCP) 8.5 for the end
of the 21st century. We investigate the degree to which RCMs and GCMs are
able to reproduce specific climatic features over SAF and over three
sub-regions, namely the greater Angola region, the greater Mozambique region,
and the greater South Africa region. We identify that during the beginning
of the rainy season, when regional processes are largely dependent on the
coupling between the surface and the atmosphere, the impact of the driving
GCMs on the RCMs is smaller compared to the core of the rainy season, when
precipitation is mainly controlled by the large-scale circulation. In
addition, we show that RCMs are able to counteract the bias received by
their driving GCMs; hence, we claim that the cascade of uncertainty over SAF
is not additive, but indeed the RCMs do provide improved precipitation
climatologies. The fact that certain bias patterns during the historical
period (1985–2005) identified in GCMs are resolved in RCMs provides
evidence that RCMs are reliable tools for climate change impact studies over
SAF.
Funder
Horizon 2020 Hellenic Foundation for Research and Innovation
Publisher
Copernicus GmbH
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