El Niño - 2015-2016
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  • 60+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Cabo Verde. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 200+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Cambodia. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across India. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 60+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Gambia. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Ecuador. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Ethiopia. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Chile. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: Dec 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Iraq. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 80+ Downloads
    Updated May 23, 2018 | Dataset date: May 23, 2018
    This dataset updates: Every year
    Mide el estado nutricional de los niños de primer grado, se basa en los resultado del VIII censo de Talla en Escolares de Primer Grado en el cual se recopilaron los resultado de las comparación de talla/edad con tablas de referencia internacional, todos los niños y niñas debajo del valor de referencia se consideran desnutridos.
  • 100+ Downloads
    Updated February 7, 2018 | Dataset date: May 2, 2016
    This dataset updates: Every year
    Cobertura de vacunación por SPR. Niños de 1 a 2 años. Guatemala. 2015
  • 100+ Downloads
    Updated February 6, 2018 | Dataset date: May 2, 2016
    This dataset updates: Every year
    Permite medir la evolución del estado de la educación en Guatemala de manera Municipalizada, está integrado por dos variables educativas: a) la cobertura; que es estimada en cada uno de los niveles desde su valor neto; es decir, el total de niños y niñas que asisten a la escuela con la edad correspondiente, entre el total de los del municipio que tienen esa edad; y b) la terminación: que es relativa al total de niños aprobados en el último año del nivel respecto al total de niños que, en esa edad residen en el municipio.
  • 500+ Downloads
    Updated December 18, 2017 | Dataset date: Jan 1, 2016
    This dataset updates: Never
    Change in monthly rainfall in Indonesia region with 1° increase in sea surface temperature of NINO-3.4 region
  • 600+ Downloads
    Updated October 9, 2017 | Dataset date: Jan 1, 1950-Sep 30, 2017
    This dataset updates: Every month
    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.
  • 400+ Downloads
    Updated September 13, 2017 | Dataset date: Jun 16, 2017-Jul 17, 2017
    This dataset updates: Every month
    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.
  • 300+ Downloads
    Updated August 16, 2016 | Dataset date: Jun 1, 2016-Dec 31, 2016
    This dataset updates: Every three months
    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
  • 400+ Downloads
    Updated June 21, 2016 | Dataset date: Apr 21, 2016
    This dataset updates: Every three months
    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.
  • 300+ Downloads
    Updated April 20, 2016 | Dataset date: Feb 9, 2016
    This dataset updates: Every six months
    Projected IPC population Estimates February - June 2016 by FAO-FSNAU ( http://www.fsnau.org/ipc/population-table)
  • 100+ Downloads
    Updated April 13, 2016 | Dataset date: Feb 11, 2016
    This dataset updates: Never
    This dataset shows the drought situation in Somalia. The year 2015 rainy season experienced El Nino conditions that resulted into good rains in many parts of the country. Despite this, the northern parts of the country are facing drought conditions.
  • 500+ Downloads
    Updated January 22, 2016 | Dataset date: Oct 1, 2015-Jan 19, 2016
    This dataset updates: Never
    This dataset shows the number of people affected by elnino rains per county
  • 300+ Downloads
    Updated January 21, 2016 | Dataset date: Nov 9, 2015
    This dataset updates: Never
    This dataset shows the reported flooded areas in somalia
  • 300+ Downloads
    Updated December 18, 2015 | Dataset date: Nov 13, 2015
    This dataset updates: Never
    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
  • 100+ Downloads
    Updated December 18, 2015 | Dataset date: Nov 13, 2015
    This dataset updates: Never
    Dataset shows the reported flooded Areas in Somalia
  • 300+ Downloads
    Updated December 16, 2015 | Dataset date: Dec 8, 2015
    This dataset updates: Never
    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.
  • 20+ Downloads
    Updated December 10, 2015 | Dataset date: Nov 16, 2015
    This dataset updates: Never
    This map illustrates satellite-detected waters in the Jowhar, Middle Shabelle region of Somalia. Using satellite imagery acquired 16 November 2015 and 02 January 2015, UNITAR-UNOSAT identified a total affected area of roughly 8,300 hectares in the Shabelle Dhexe and Hoose provinces. As of 16 November 2015, approximately 8,300 hectares of probable standing rain waters were detected over the districts of Jowhar, Balcad and, Afgooye. Due to the characteristics of satellite data used for this analysis, the exact limit of flood water is uncertain. Detected water bodies likely reflect an underestimation of all flood-affected areas within the map extent. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Pre-flood assessment performed by SWALIM.
  • Updated December 10, 2015 | Dataset date: Nov 18, 2015
    This dataset updates: Never
    This map illustrates satellite-detected waters over the Shabelle hoose region of Somalia. Using satellite imagery acquired 16 November 2015 and 02 January 2015, UNITAR-UNOSAT identified a total affected area of roughly 2,790 hectares in the Shabelle Hoose province. As of 16 November 2015, approximately 2,970 hectares of probable standing rain waters were detected over the districts of Qoryooley, Kurtunwaarey, Marka, Baraawe and Sablaale. Due to the characteristics of satellite data used for this analysis, the exact limit of flood water is uncertain. Detected water bodies likely reflect an underestimation of all flood-affected areas within the map extent. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Pre-flood assessment performed by SWALIM.