Preprints
https://doi.org/10.5194/gmd-2021-348
https://doi.org/10.5194/gmd-2021-348
Submitted as: model evaluation paper
18 Jan 2022
Submitted as: model evaluation paper | 18 Jan 2022
Status: this preprint is currently under review for the journal GMD.

The impact of lateral boundary forcing in the CORDEX-Africa ensemble over southern Africa

Maria Chara Karypidou1, Stefan Pieter Sobolowski2, Eleni Katragkou1, Lorenzo Sangelantoni3,4, and Grigory Nikulin5 Maria Chara Karypidou et al.
  • 1Department of Meteorology and Climatology, School of Geology, Faculty of Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 2NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
  • 3CETEMPS—Department of Physical and Chemical Sciences, University of L’Aquila, L’Aquila, Italy
  • 4Department of Physical and Chemical Sciences, University of L’Aquila, L’Aquila, Italy
  • 5Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

Abstract. The region of southern Africa (SAF) is among the most exposed climate change hotspots and is projected to experience severe impacts on 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 a set of 19 regional climate models (RCMs) 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 over 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.

Maria Chara Karypidou et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-348', Anonymous Referee #1, 19 Mar 2022
  • RC2: 'Comment on gmd-2021-348', Anonymous Referee #2, 22 May 2022

Maria Chara Karypidou et al.

Maria Chara Karypidou et al.

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Short summary
Southern Africa is listed among the climate change hot-spots, hence, accurate climate change information is vital for the optimal preparedness of local communities. In this work we assess the degree to which regional climate models (RCMs) are influenced by the global climate models (GCMs) from which they receive their lateral boundary forcing. We find that although GCMs exert a strong impact on RCMs, still RCMs are able to display substantial improvement relative to the driving GCMs.