Updated
9 October 2017
| Dataset date: January 01, 1950-September 30, 2017
The Oceanic Niño Index (ONI) has become the de facto standard that the National
Oceanic and Atmospheric Administration (NOAA) uses to identify El Niño (warm) and
La Niña (cool) events in the tropical Pacific. It is the three month mean SST
anomaly for the El Niño 3.4 region (i.e., 5°N-5°S, 120°-170°W). Events are defined as five
consecutive overlapping three month periods at or above the +0.5°C anomaly for warm (El
Niño), events and at or below the -0.5 anomaly for cold (La Niña) events. The threshold
is further broken down into Weak (with a 0.5 to 0.9 SST anomaly), Moderate (1.0 to 1.4)
and Strong (≥ 1.5) events. For an event to be categorized as weak, moderate or strong. it
must have equalled or exceeded the threshold for at least three consecutive overlapping
three month periods.
Updated
13 September 2017
| Dataset date: June 16, 2017-July 17, 2017
Displacement Tracking Matrix (DTM) R3 in Peru is a representative study of the displaced population in the shelters of the districts of Catacaos and Cura Mori in Piura, Peru.
La Matriz de Monitoreo de Desplazamiento (DTM) R3 en Perú es un estudio representativo de la población desplazada en los albergues de los distritos de Catacaos y Cura Mori en Piura, Perú.
Updated
16 August 2016
| Dataset date: June 01, 2016-December 31, 2016
List of projects being developed currently in Haiti in the context of the drought response.
The data of this document was collected only for 4 towns, that are considered to be in IPC phase 3 by the National coordination of Food Security (CNSA)
The dataset contains the list of projects organized by sectors: Food Security, Agriculture, Nutrition and WASH. The document also contains the estimated populations in need by commune and sector.
The caseload for the nutrition projects corresponds only to children under five years old.
An analysis document developed with this data is available at: https://goo.gl/NBHRZI
Updated
21 June 2016
| Dataset date: April 21, 2016-April 21, 2016
This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December
period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.
Updated
18 December 2015
| Dataset date: November 13, 2015-November 13, 2015
This dataset shows the Shabelle and Juba Riverine Basin Population Displacement Estimates - 2015.
Working assumptions:
• Displaced population defined as direct displacement through flood inundation
• Displaced population calculated by multiplying the number of hh's by hh size of 6
• If a range is provided to quantify displacement the upper figure is used
Updated
16 December 2015
| Dataset date: December 08, 2015-December 08, 2015
This dataset contains a list of 42 countries that are of particular concern for both WFP and FAO due to their climatic risk (both on-going and potential) due to the 2015/16 El Niño. Food Security Cluster (FSC) presence is indicated for each affected country. The presence of other coordination structures with FSC monitoring is also indicated for each country in the dataset.
Updated
14 October 2015
| Dataset date: September 30, 2015-September 30, 2015
This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa.
It was last updated on September 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
westafrica201304_ML1 Most likely food security outcome for July-September 2015
westafrica201304_ML2 Most likely food security outcome for October-December 2015
Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used:
66 = water
88 = parks, forests, reserves
99 = missing data (usually urban centers)
