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Department of Environmental and Geographical Science

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using an adaptive Stretched-Grid Global Climate Model

Abstract

dc:description.abstract

Tropical Cyclones are one of the most devastating natural phenomena. Previous attempts to simulate Tropical Cyclones (TCs) over the South West Indian Ocean (SWIO) have used Global Circulation Models (GCMs) with uniform grid. This study examines the capability of a GCM with adaptive grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the SWIO. In the study, the CEU model is applied with a fine horizontal grid resolution (0.5°x0.5°) over the SWIO and coarser resolution (1°x1° - 2°x2.25°) over the rest of the globe. The model simulation is performed for 11 years (1999-2010) and validated against the Joint Typhoon Warning Centre (JTWC) best track observation, Global Precipitation Climatology Project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis data. The study also considers the impact of El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and the South Atlantic Subtropical Dipole (SASD) on TC counts over the SWIO.

Degree

thesis:*
Grantor dc:publisher.institution
Department of Environmental and Geographical Science
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Maoyi, Molulaqhooa Linda
Advisors dc:contributor.advisor
  • Abiodun, Babatunde Joseph
  • Jackson-Veitch, Jennifer

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/19989
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/19989

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Maoyi, Molulaqhooa Linda. Simulating the characteristics of tropical cyclones over the South West Indian Ocean using an adaptive Stretched-Grid Global Climate Model. Department of Environmental and Geographical Science, 2015. http://hdl.handle.net/11427/19989