Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY

The El Niño Southern Oscillation (ENSO) is a major driver of southern Africa droughts, but the nonlinearity of ENSO variation inhibits accurate prediction of droughts. While studies have identified multiple patterns of ENSO, most drought predictions over southern Africa are still based on only two E...

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Main Author: Gore, Michelle Jacqueline
Other Authors: Abiodun, Babatunde
Format: Dissertation
Language:English
Published: Faculty of Science 2020
Subjects:
Online Access:https://hdl.handle.net/11427/31879
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-318792020-07-22T05:07:32Z Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY Gore, Michelle Jacqueline Abiodun, Babatunde environmental and geographical science The El Niño Southern Oscillation (ENSO) is a major driver of southern Africa droughts, but the nonlinearity of ENSO variation inhibits accurate prediction of droughts. While studies have identified multiple patterns of ENSO, most drought predictions over southern Africa are still based on only two ENSO patterns. This study examines the relationship between southern African droughts and eight ENSO patterns: four El Niño SST conditions (EN1 - EN4) and four La Niña SST conditions (LN1 - LN4). In this study we analyzed multi-forcing ensemble simulations from SPEEDY (a general circulation model from the International Centre for Theoretical Physics) and used two drought indices (SPEI: Standardized Precipitation Evapotranspiration Index; SPI: Standardized Precipitation Index) to characterize drought. The capability of SPEEDY in reproducing southern Africa climate was evaluated by comparing the historical simulations (1979- 2008) with the Climate Research Unit (CRU) observation. To obtain the influence of ENSO patterns, we forced the SPEEDY simulations with SST of each ENSO pattern, analyzed the impacts on the simulated drought indices (SPEI and SPI), and studied the atmospheric dynamics that link each ENSO pattern to southern Africa droughts. The results show that SPEEDY generally captures the temporal and spatial distribution of climate variables over southern Africa well, although with warm and wet biases across the region. However, in most cases, these results are comparable with those from more complex atmospheric models. In agreement with previous studies, the results show that El Niño SST conditions weaken the Walker circulation and cause drier conditions over parts of southern Africa, whilst La Niña SST conditions strengthen the Walker Circulation and cause wetter conditions. However, the results show that the differences in the El Niño SST conditions (EN1 - EN4) alter the circulation, thereby influencing the spatial pattern and intensity of drought over the region. For instance, while EN2 induces the most severe drought in the tropical area, EN4 produces it in the southwestern region, because the two patterns feature different characteristics of anticyclonic moisture flux over southern Africa. The same is true of the La Niña SST conditions. Although, LN1 and LN4 show wet conditions across the southern part of the region, LN1 produces drought in the northern part, while LN4 induces it along the western coast. Hence, this study shows that accounting for the differences in El Niño (or La Niña) conditions may improve drought predictions in southern Africa. 2020-05-14T14:27:45Z 2020-05-14T14:27:45Z 2019 2020-05-14T14:27:19Z Masters Thesis Masters MSc https://hdl.handle.net/11427/31879 eng application/pdf Faculty of Science Department of Environmental and Geographical Science
collection NDLTD
language English
format Dissertation
sources NDLTD
topic environmental and geographical science
spellingShingle environmental and geographical science
Gore, Michelle Jacqueline
Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
description The El Niño Southern Oscillation (ENSO) is a major driver of southern Africa droughts, but the nonlinearity of ENSO variation inhibits accurate prediction of droughts. While studies have identified multiple patterns of ENSO, most drought predictions over southern Africa are still based on only two ENSO patterns. This study examines the relationship between southern African droughts and eight ENSO patterns: four El Niño SST conditions (EN1 - EN4) and four La Niña SST conditions (LN1 - LN4). In this study we analyzed multi-forcing ensemble simulations from SPEEDY (a general circulation model from the International Centre for Theoretical Physics) and used two drought indices (SPEI: Standardized Precipitation Evapotranspiration Index; SPI: Standardized Precipitation Index) to characterize drought. The capability of SPEEDY in reproducing southern Africa climate was evaluated by comparing the historical simulations (1979- 2008) with the Climate Research Unit (CRU) observation. To obtain the influence of ENSO patterns, we forced the SPEEDY simulations with SST of each ENSO pattern, analyzed the impacts on the simulated drought indices (SPEI and SPI), and studied the atmospheric dynamics that link each ENSO pattern to southern Africa droughts. The results show that SPEEDY generally captures the temporal and spatial distribution of climate variables over southern Africa well, although with warm and wet biases across the region. However, in most cases, these results are comparable with those from more complex atmospheric models. In agreement with previous studies, the results show that El Niño SST conditions weaken the Walker circulation and cause drier conditions over parts of southern Africa, whilst La Niña SST conditions strengthen the Walker Circulation and cause wetter conditions. However, the results show that the differences in the El Niño SST conditions (EN1 - EN4) alter the circulation, thereby influencing the spatial pattern and intensity of drought over the region. For instance, while EN2 induces the most severe drought in the tropical area, EN4 produces it in the southwestern region, because the two patterns feature different characteristics of anticyclonic moisture flux over southern Africa. The same is true of the La Niña SST conditions. Although, LN1 and LN4 show wet conditions across the southern part of the region, LN1 produces drought in the northern part, while LN4 induces it along the western coast. Hence, this study shows that accounting for the differences in El Niño (or La Niña) conditions may improve drought predictions in southern Africa.
author2 Abiodun, Babatunde
author_facet Abiodun, Babatunde
Gore, Michelle Jacqueline
author Gore, Michelle Jacqueline
author_sort Gore, Michelle Jacqueline
title Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
title_short Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
title_full Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
title_fullStr Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
title_full_unstemmed Understanding the impacts of ENSO patterns on droughts over southern Africa using SPEEDY
title_sort understanding the impacts of enso patterns on droughts over southern africa using speedy
publisher Faculty of Science
publishDate 2020
url https://hdl.handle.net/11427/31879
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