El Nino 2015 in South Sudan: Impacts and Perspectives. Raul Cumba

Transcription

1 El Nino 2015 in South Sudan: Impacts and Perspectives Raul Cumba

2 El Nino The El Nino Event of The 2015/16 El Nino Event Officially declared in March 2015 Now approaching peak intensity Expected to last through 1 st Quarter 2016 Long lived and definitely one of the strongest in the long term record. 1997/ /16

3 South Sudan Seasonal Timings and El Nino May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Coverage of Seasonal Forecasts Millet, Sorghum, Maize Millet, Sorghum Maize: Main and Second seasons El Nino Evolution El Nino peak intensity Timing of Growing Seasons and El Nino development The figure above shows the timing of the South Sudan crop cycles along with the temporal coverage of seasonal forecasts. The growing season of 2015 took place during the development of one of the strongest events of the past 35 years.

4 El Nino Global Evolution and Timeline: A Long Build Up to Record Intensity El Nino: 1997/1998 vs 2014/ El Nino Declared 1996/97/ Central America: Severe drought March-July 2014 Southern Africa: Drought and regional crop deficits Nov 2014-Mar 2015 Southern Africa: Likelihood of Drought Nov 2015-Mar /15/ Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Senegal/Mauritania: Severe drought July-Sept 2014 Central America: Severe drought March-July 2015 Ethiopia Severe drought March-May 2015 July-Sept 2015 SE Asia Dryness July-Sept 2015 Indonesia and Pacific Severe drought July-Dec East Africa Flood Risk Oct-Dec 2015

5 El Nino El Nino Regional Impacts: April to October 2015 April August Ethiopia: hit by severe drought on both the first and second (main) growing seasons. Pastoral livelihoods severely affected, situation extends to Djibouti and Somaliland. Sudan, Eritrea: drought on main and marginal cereal producing regions. South Sudan-Karamoja (NE Uganda)-Turkana (NW Kenya): an excellent start followed by very dry conditions from July to September.

6 SOUTH SUDAN SEASONAL ANALYSIS Onset of Season Date of onset of the growing season compared to average. Pinks and yellows to reds for delayed growing seasons, green shades for earlier than average growing seasons. The growing season started earlier than usual (good rains during the earlier stages of the season) in: Western areas (Western Equatoria and Greater Bahr-el- Ghazal). Along the border with Sudan and in Upper Nile state. The season started moderately later than usual (due to drier than average conditions in ApriI) in: Central and eastern areas (Central Equatoria, parts of Jonglei). Overall, no significant perturbations of the planting dates were noticeable in this season

7 SOUTH SUDAN SEASONAL ANALYSIS Seasonal Rainfall Performance and Vegetation Status 30 days cumulative rainfall until 30 of September 2015, as a percentage of the 20-year average. Hashed pattern indicates main agricultural areas. Brown shades indicate belowaverage rainfall; blue shades indicate above-average seasonal rainfall. Substantial rainfall deficits From July to September Field reports on dry spell FSNMS report as major shock lack of rainfall Vegetation Index as a percentage of the 12-year average. Hashed pattern indicates main agricultural areas. Orange shades for below-average; green shades for above-average vegetation.

8 SOUTH SUDAN SEASONAL ANALYSIS Seasonal Rainfall Performance and Vegetation Status 30 days cumulative rainfall until 31 of Ocober 2015, as a percentage of the 20-year average. Hashed pattern indicates main agricultural areas. Brown shades indicate belowaverage rainfall; blue shades indicate above-average seasonal rainfall. Improvement on rainfall performance in month of October Vegetation Index as a percentage of the 12-year average. Hashed pattern indicates main agricultural areas. Orange shades for below-average; green shades for above-average vegetation. A bit of improvement in vegetation with a tendency to return to average levels. In pastoralists areas, the favorable rainfall are expected to improve the water and pasture condition for the livestock, after a fairly dry mid season. Field reports indicate an improvement in the conditions of the second crop mainly in Eastern Equatoria and Central Equatoria as a result of the October rainfall.

9 El Nino El Nino Regional impacts: October December 2015 Historical Evidence Historical Evidence Historically, El Nino strongly associated with wetter than average conditions during October to January in East Africa. Current forecasts confirm this tendency. However only relevant for SE South Sudan (East Equatoria, some southern Jonglei) Historically, wetter than average season leads to better than usual pasture and crop development. Good pasture conditions and water resources expected in EEQ

10 El Nino Outlook: December 2015 and Beyond Forecasts confirm historical tendency: wetter than average conditions expected in EEQ and southern Jonglei for December-February Wetter than average conditions in EEQ should last into first quarter of 2016, so good perspectives for livestock. Also elsewhere, but amounts there are very small.

11 El Nino Summary of El Nino Impact Good prospects of second agriculture season in Southern Jonglei, Eastern and part of Central Equatoria States. Good prospects for the livestock (pastoralist areas) wetter than average conditions up to first quarter of Cases of malaria and other water-bone related diseases (cholera) may increase due to the expected enhanced rainfall. No adverse effects except a section of Equatoria that may potentially receive some floods that may disrupt transport routes. Higher than normal rains in South Sudan typically will worsen the already bad infrastructure. However, South Sudan operations is likely to be affected by the impact of El Nino in the region: Eg, is the current drought in Ethiopia, thus likelihood of stiffer competition for resources to support ongoing interventions Flooding in Kenya and other transport routes- may be disrupted supply chain

12 Data Sources: Rainfall: CHIRPS, Climate Hazards Group, UCSB Vegetation: MODIS NDVI, EOSDIS-NASA Land Cover: FAO GLC-Share Processing: VAM software components, ArcGIS