Tamuka Magadzire

El Niño–Southern Oscillation diversity and Southern Africa teleconnections during Austral Summer

Abstract A wide range of sea surface temperature (SST) expressions have been observed during the El Niño–Southern Oscillation events of 1950–2010, which have occurred simultaneously with different global atmospheric circulations. This study examines the atmospheric circulation and precipitation during December–March 1950–2010 over the African Continent south of 15

Anthropogenic Enhancement of Moderate-to-Strong El Niño Events Likely Contributed to Drought and Poor Harvests in Southern Africa During 2016

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Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

∘S, a region hereafter known as Southern Africa, associated with eight tropical Pacific SST expressions characteristic of El Niño and La Niña events. The self-organizing map method along with a statistical distinguishability test was used to isolate the SST expressions of El Niño and La Niña. The seasonal precipitation forcing over Southern Africa associated with the eight SST expressions was investigated in terms of the horizontal winds, moisture budget and vertical motion. El Niño events, with warm SST across the east and central Pacific Ocean and warmer than average SST over the Indian Ocean, are associated with precipitation reductions over Southern Africa. The regional precipitation reductions are forced primarily by large-scale mid-tropospheric subsidence associated with anticyclonic circulation in the upper troposphere. El Niño events with cooler than average SST over the Indian Ocean are associated with precipitation increases over Southern Africa associated with lower tropospheric cyclonic circulation and mid-tropospheric ascent. La Niña events, with cool SST anomalies over the central Pacific and warm SST over the west Pacific and Indian Ocean, are associated with precipitation increases over Southern Africa. The regional precipitation increases are forced primarily by lower tropospheric cyclonic circulation, resulting in mid-tropospheric ascent and an increased flux of moisture into the region.

A probabilistic approach to assess agricultural drought risk to maize in Southern Africa and millet in Western Sahel using satellite estimated rainfall

Introduction. In northern Ethiopia (7°–14°N, 36.5°– 40.5°E, NE) during June–September (JJAS) of 2015 and in southern Africa (13.5°–27°S, 26.5°–36°E, SA) during December–February (DJF) of 2015/16, main growing seasons rains were extremely poor. In Ethiopia, Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) (Funk et al. 2015c) and Centennial Trends (Funk et al. 2015b) data indicated one of the worst droughts in more than 50 years (FEWSNET 2015). More than ten million people currently require humanitarian relief (FEWSNET 2016a). SA rains were also extremely poor (FEWSNET 2016b); in Mozambique and Malawi, February maize prices were more than twice the five-year average, and in Zimbabwe the president has declared a national disaster in view of the El Niño–induced poor rains and the escalating food insecurity situation. NE has been experiencing long-term rainfall declines (Funk et al. 2008; Funk et al. 2005; Jury and Funk 2013; Viste et al. 2012; Williams et al. 2012). The eastern Ethiopian highlands have exhibited recurrent soil moisture and runoff deficits since the 1990s (Funk et al. 2015c). NE rains in 2015 were the driest on record, but station data density prior to 1950 is very sparse for Ethiopia (Funk et al. 2015b). SA rainfall does not exhibit a decline, but the 2015–16 drought was severe. The impact of ENSO on Ethiopian rainfall is well documented (Fig. S15.1; Camberlin 1997; Degefu 1987; Diro et al. 2011; Gissila et al. 2004; Korecha and Barnston 2007; Korecha and Sorteberg 2013; Segele and Lamb 2005): the warm phase of ENSO is associated with suppressed rains during the main wet season (JJAS) over north and central Ethiopia. There have also been numerous papers documenting a negative teleconnection between El Niño and SA rainfall (Supplemental Fig. S15.1; Hoell et al. 2015; Jury et al. 1994; Lindesay 1988; Misra 2003; Nicholson and Entekhabi 1986; Nicholson and Kim 1997; Reason et al. 2000; Rocha and Simmonds 1997).

Developing seasonal rainfall scenarios for food security early warning

Introduction. In December–February (DJF) of 2015/16, a strong El Niño (Niño‐3.4 SST >29°C) contributed to a severe drought over southern Africa (SA; Funk et al. 2016). A 9‐million ton cereal deficit resulted in 26 mil‐ lion people in need of humanitarian assistance (SADC 2016). While SA rainfall has a well‐documented nega‐ tive teleconnection with Niño‐3.4 SSTs (Hoell et al. 2015, 2017; Jury et al. 1994; Lindesay 1988; Misra 2003; Nicholson and Entekhabi 1987; Nicholson and Kim 1997; Reason et al. 2000; Rocha and Simmonds 1997), the link between climate change and El Niño remains unclear (Christensen et al. 2013) due to the large natural variability of ENSO SSTs (Wittenberg 2009), uncertainties surrounding measurements and trends (Solomon and Newman 2012), intermodel differences in ENSO representation and feedbacks (Guilyardi et al. 2012; Kim et al. 2014), and difficulties associated with quantifying ENSO strength (Cai et al. 2015). Figure 18.1a highlights observational uncertain‐ ties (Compo and Sardeshmukh 2010; Solomon and Newman 2012) using four datasets: ERSSTv4 (Huang et al. 2015), HadISST (Rayner et al. 2003), Kaplan SST (Kaplan et al. 1998), and Hurrell (Hurrell et al. 2008). These products differ substantially in their represen‐ tation of cool events and Niño‐3.4 variance. Two SST products indicate significant upward trends; two SST products do not. These data have been standardized to remove systematic differences in variance. Focusing just on the behavior of moderate–strong El Niño events (MSENEs), we can produce more ro‐ bust (first order) statistics by comparing the means of the top ten warmest Niño‐3.4 events between 1921–80 and the top six warmest events between 1981–2016. Rather than using a set SST threshold, MSENEs are defined as 1‐in‐6‐year warm events. This provides a simple nonparametric approach that takes advantage of the well understood quasi‐periodic nature of ENSO to identify MSENEs across multiple models and simulations. Modest changes in the number of events (say, 1‐in‐7 or 1‐in‐5) produced modest increases and decreases in El Niño temperatures, but did not sub‐ stantially change the results. We begin our analysis in 1921 (because ship data before 1921 is limited), and divide the remaining 96 years into two time periods with relatively weak and strong radiative forcing, respectively. Examining changes in MSENE means (horizontal lines in Fig. 18.1a), we find that all the observational datasets identify significant increases (Fig. ES18.1 examines ERSSTv4 errors). Note that we are not explicitly ex‐ amining changes in ENSO variance, ENSO means, or Niño‐3.4 SST trends, but only Niño‐3.4 magnitudes AFFILIATIONS: Funk—U.S. Geological Survey, Center for Earth Resources Observation and Science, and UC Santa Barbara Climate Hazards Group, Santa Barbara, California; Davenport, harrison, shukLa, pomposi, anD husak—UC Santa Barbara Climate Hazards Group, Santa Barbara, California; magaDzire, gaLu, anD koreCha—UC Santa Barbara Climate Hazards Group, Santa Barbara, California, and Famine Early Warning Systems Network; artan—Intergovernmental Authority on Development (IGAD) Climate Prediction & Applications Centre, Nairobi, Kenya; inDeje—IGAD USAID/Kenya and East Africa Planning for Resilience in East Africa Through Policy Adaptation, Research, and Economic Development, Nairobi, Kenya; maCharia—Regional Center for Mapping of Resources for Development, Nairobi, Kenya; nsaDisa—Director of the Southern African Development Community’s Climate Services Centre.

Distinguishing southern Africa precipitation response by strength of El Niño events and implications for decision-making

AbstractSouthern Africa precipitation during December–March (DJFM), the height of the rainy season, is closely related with two modes of climate variability, El Nino–Southern Oscillation (ENSO) and the subtropical Indian Ocean dipole (SIOD). Recent research has found that the combined effects of ENSO and SIOD phasing are linked with changes to the regional southern Africa atmospheric circulation beyond the individual effects of either ENSO or SIOD alone. Here, the authors extend the recent research and examine the southern Africa land surface hydrology associated with the synchronous effects of ENSO and SIOD events using a macroscale hydrologic model, with particular emphasis on the evolution of the hydrologic conditions over three critical Transfrontier Conservation Areas: the Kavango–Zambezi Conservation Area, the Greater Limpopo Transfrontier Park, and the Kgalagadi Transfrontier Park. A better understanding of the climatic effects of ENSO and SIOD phase combinations is important for regional-scale tra...