Simulating the link between ENSO and summer drought in Southern Africa using regional climate models

Meque, Arlindo; Abiodun, Babatunde J.

doi:10.1007/s00382-014-2143-3

Cited by 74 publications

(53 citation statements)

References 72 publications

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“…By comparing the African rainfall anomalies and vegetation condition for selected months (see Figures 8-10), drought conditions during El Niño events were observed over southern Africa, which agrees with observations from numerous scientific studies e.g., [9,27,33,70,71]. Eastern African rainfall anomalies and vegetation are sensitive to ENSO during both first growing seasons (Ethiopian "meher", Somalian "deyr" and Kenyan "short rains" from October to December) and the early second growing seasons (Ethiopian "belg", Somalian "gu" and Kenyan "long rains" from February to May) over areas with bimodal rainfall cycles (compare also Figure 3).…”

Section: Spatio-temporal Variability Of Agricultural Droughts Duringsupporting

confidence: 71%

“…In this connection, operational approaches on global-and continental-scale drought monitoring [6,[17][18][19][20] as well as remote sensing-based studies on droughts in Africa focussing on selected regions and/or periods are to be mentioned. Here, topics of current interest are the ongoing debate on the Sahelian "greening" [21][22][23], drought during 2010/2011 in the Horn of Africa [13,[24][25][26], rainfall and vegetation-related drought dynamics in southern Africa [27][28][29][30], continental-scale drought assessment [12,31,32] as well as the relation between droughts in Africa and ENSO [9,[33][34][35][36]. However, either studies accounted for drought assessment on rather small regional scales and did not assess the continental level or little attention was paid to drought affecting agriculturally relevant areas and time periods.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

2017

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Droughts are amongst the most destructive natural disasters in the world. In large regions of Africa, where water is a limiting factor and people strongly rely on rain-fed agriculture, droughts have frequently led to crop failure, food shortages and even humanitarian crises. In eastern and southern Africa, major drought episodes have been linked to El Niño-Southern Oscillation (ENSO) events. In this context and with limited in-situ data available, remote sensing provides valuable opportunities for continent-wide assessment of droughts with high spatial and temporal resolutions. This study aimed to monitor agriculturally relevant droughts over Africa between 2000–2016 with a specific focus on growing seasons using remote sensing-based drought indices. Special attention was paid to the observation of drought dynamics during major ENSO episodes to illuminate the connection between ENSO and droughts in eastern and southern Africa. We utilized Tropical Rainfall Measuring Mission (TRMM)-based Standardized Precipitation Index (SPI) with 0 . 25 ∘ resolution and Moderate-resolution Imaging Spectroradiometer (MODIS)-derived Vegetation Condition Index (VCI) with 500 m resolution as indices for analysing the spatio-temporal patterns of droughts. We combined the drought indices with information on the timing of site-specific growing seasons derived from MODIS-based multi-annual average of Normalized Difference Vegetation Index (NDVI). We proved the applicability of SPI-3 and VCI as indices for a comprehensive continental-scale monitoring of agriculturally relevant droughts. The years 2009 and 2011 could be revealed as major drought years in eastern Africa, whereas southern Africa was affected by severe droughts in 2003 and 2015/2016. Drought episodes occurred over large parts of southern Africa during strong El Niño events. We observed a mixed drought pattern in eastern Africa, where areas with two growing seasons were frequently affected by droughts during La Niña and zones of unimodal rainfall regimes showed droughts during the onset of El Niño. During La Niña 2010/2011, large parts of cropland areas in Somalia (88%), Sudan (64%) and South Sudan (51%) were affected by severe to extreme droughts during the growing seasons. However, no universal El Niño- or La Niña-related response pattern of droughts could be deduced for the observation period of 16 years. In this regard, we discussed multi-year atmospheric fluctuations and characteristics of ENSO variants as further influences on the interconnection between ENSO and droughts. By utilizing remote sensing-based drought indices focussed on agricultural zones and periods, this study attempts to contribute to a better understanding of spatio-temporal patterns of droughts affecting agriculture in Africa, which can be essential for implementing strategies of drought hazard mitigation.

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Section: Spatio-temporal Variability Of Agricultural Droughts Duringsupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

2017

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“…Relative to Central and East Africa, there has been more research into understanding the modeled circulation (e.g., Shongwe et al 2009;Tozuka et al 2014;Lazenby et al 2016), modes of variability (e.g., Kataoka et al 2012;Boulard et al 2013;Dieppois et al 2015), and mechanisms of future change (Engelbrecht et al 2009), as well as efforts to characterize atmospheric states based on winds, moisture, and temperature, which suggests more similarity between models based on atmospheric circulation than precipitation (Hewitson and Crane 2006). There has also been an emphasis on regional climate models (RCMs; e.g., Crétat et al 2012;Kalognomou et al 2013;Meque and Abiodun 2015;Shongwe et al 2015;Favre et al 2016;Pinto et al 2016).…”

Section: Pan-africanmentioning

confidence: 99%

Evaluating Climate Models with an African Lens

James

Washington

Abiodun

et al. 2018

Bulletin of the American Meteorological Society

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“…According to the standard developed by ENSO monitoring groups, Oceanic Niño Index (ONI) data provided by the US National Oceanic and Atmospheric Administration and a literature search, there are six El Niño years (1991, 1992, 1997, 2002, 2004, and 2009) and six La Niña years (1998, 1999, 2000, 2008, 2010, and 2011) during 1990-2014. Prior studies showed that although the relationship between ENSO and precipitation is nonlinear, global land annual precipitation is less offset in most El Niño years, while it is more offset in La Niña years (Meque and Abiodun 2014;Sasaki et al 2015;Tang and Yuan 2010). Annual frequencies of flood disasters showed several peaks in 1996-2000, 2006-2008, and 2010-2012.…”

Section: Inter-annual Changes and Influencing Factorsmentioning

confidence: 99%

Spatio-temporal distribution of flood disasters and analysis of influencing factors in Africa

Chai

Yang

et al. 2016

Nat Hazards

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To analyse inner-and inter-annual changes, disaster events of 55 countries in Africa from 1990 to 2014 recorded in the International Disaster Database (EM-DAT) were recounted by year and month and were reorganised in five different regions. Thematic maps of flood disasters in Africa between 1990 and 2014 were drawn using ArcGIS 9.3 to research the spatial distribution patterns of average annual flood frequency, total deaths, total affected, and damage. There were eight natural and socio-economic indicators chosen to explore the main factors influencing the spatio-temporal distribution of flood disasters in Africa, including precipitation, ENSO, runoff, forest coverage rate, reservoir capacity, per capita GDP, population, and urbanisation rate. Studies show that seasonal changes of flood disasters in various regions of Africa, except North Africa, are closely related to precipitation. Annual flood frequencies, from 1990 to 2014, showed a fluctuating upward trend and were in good agreement with ENSO years. In terms of spatial distributions, Ethiopia, Kenya, Somalia, Tanzania in eastern Africa, Nigeria in western Africa, and Libya, and Sudan in northern Arica are flood-prone countries, and main factors influencing spatial disparities include runoff, per capita GDP, population, and urbanisation rate.

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Simulating the link between ENSO and summer drought in Southern Africa using regional climate models

Cited by 74 publications

References 72 publications

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

Evaluating Climate Models with an African Lens

Spatio-temporal distribution of flood disasters and analysis of influencing factors in Africa

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