Natural Disaster Hotspots Data

Transcription

1 Natural Disaster Hotspots Data Source: Dilley, M., R.S. Chen, U. Deichmann, A.L. Lerner-Lam, M. Arnold, J. Agwe, P. Buys, O. Kjekstad, B. Lyon, and G. Yetman Natural Disaster Hotspots: A Global Risk Analysis. Disaster Risk Management Series, Issue No. 5. The World Bank, Washington, D.C. Natural Disaster Frequency and Distribution Droughts The data are based upon the International Research Institute for Climate Prediction s (IRI) Weighted Anomaly of Standardized Precipitation (WASP). Utilizing average monthly precipitation data from 1980 through 2000 at a resolution of 2.5 degrees, WASP assesses the precipitation deficit or surplus over a three month temporal window that is weighted by the magnitude of the seasonal cyclic variation in precipitation. The three months' averages are derived from the precipitation data and the median rainfall for the 21 year period is calculated for each grid cell. Grid cells where the three month running average of precipitation is less than 1 mm per day are excluded. Drought events are identified when the magnitude of a monthly precipitation deficit is less than or equal to 50 percent of its long-term median value for three or more consecutive months. Grid cells are then divided into 10 classes having an approximately equal number of grid cells. Higher grid cell values denote higher frequencies of drought occurrences. Research (CHRR), International Research Institute for Climate Prediction (IRI), and the Columbia University Center for International Earth Science Information Network (CIESIN). Floods The frequency and distribution data are derived from a global listing of extreme flood events between 1985 and 2003 (poor or missing data in the early/mid 1990s) compiled by

2 Dartmouth Flood Observatory and georeferenced to the nearest degree. The data from the Dartmouth Flood Observatory contains various geospatial representations of flood events. Some floods are depicted as points georeferenced to the nearest degree. Other floods are characterized by polygons. To determine frequency of flood hazard, a 2.5 by 2.5 minute grid overlies the flood data and the number of flood events per grid cell is recorded. A flood event is defined as any portion of any type of flood representation occurring within a grid cell. Therefore, if a grid cell is crossed by a boundary of a flood polygon, then the frequency increases by one. If a point is within the grid cell boundaries, the frequency increases by one. Flooding of the same areas, but at different times, also increase the frequency. The resultant flood frequency grid was then classified into 10 classes of approximately equal number of grid cells. The greater the grid cell value in the final data set, the higher the relative frequency of flood occurrence. Note that areas of "No Data" are not necessarily without risk of hazard, but may be artifacts of a mask that excluded from analysis those areas that were of a population density less than 5 persons per square kilometer and without significant agriculture. Research (CHRR), and the Columbia University Center for International Earth Science Information Network (CIESIN). Landslides This global landslide and snow avalanche hazards dataset based upon work of the Norwegian Geotechnical Institute (NGI). The hazards mapping of NGI incorporates a range of data including slope, soil, soil moisture conditions, precipitation, seismicity, and temperature. Shuttle Radar Topography Mission (SRTM) elevation data at 30 seconds resolution are also incorporated. Areas were ranked from 1 to 9 (9 being highest) with regards to the propensity for a landslide or avalanche. Hazards values 4 and below are considered negligible and only values 5 through 9 are utilized in further analyses. To ensure compatibility with other datasets, 1 is added to each of the values to provide a hazard ranking ranging 6 through 10 in increasing hazard. Note that areas of no data are not necessarily without hazard risk but may rather be an artifact of the mask used to

3 exclude from analysis those areas that had a population density of less than 5 persons per square kilometer and were without significant agriculture. Research (CHRR), Norwegian Geotechnical Institute (NGI) and Columbia University Center for International Earth Science and Information Network (CIESIN). Cyclones The dataset is based on more than 1,600 storm tracks for the period 1 January 1980 through 31 December 2000 for the Atlantic, Pacific, and Indian Oceans that were assembled and modeled at UNEP/GRID-Geneva PreView. Windspeeds around storm tracks were modeled using Holland's model (1997) to assess the grid cells likely to have been exposed to high wind levels. The different wind speed buffers were translated into six categories using the Saffir-Simpson Hurricane scale. Overlaying a 1 km resolution grid produced a surface representing how often a grid cell is hit by a hurricane and the associated wind speed, a measure of severity. Post-modeling, the cells were divided into deciles, 10 classes consisting of approximately equal number of grid cells. The higher the value of the grid cell, the higher the decile ranking and the greater the frequency of the hazard relative to other cells. Note that areas of no data are not necessarily areas without hazard, but rather that a mask was used to exclude from analysis those areas that had a population density less than 5 persons per square kilometer and without significant agriculture. The dataset is the result of collaboration among the Center for Hazards and Risk Bank, United Nations Environment Programme Global Resource Information Database Geneva (UNEP/GRID-Geneva), and the Columbia University Center for International Earth Science Information Network (CIESIN).

4 Mortality Analyses Gridded Population of the World (GPW) Version 3.0 (beta) data provided a baseline population per grid cell from which to estimate potential mortality risks due to the natural hazard. Mortality loss estimates per disaster event are calculated using regional, hazardspecific mortality records of the Emergency Events Database (EM-DAT) that span the 20 years between 1981 and Data regarding the frequency and distribution of each natural hazard are obtained via the methodologies above. In order to more accurately reflect the confidence associated with the data and the procedures, the potential mortality estimate range is classified into deciles, 10 classes of increasing hazard with an approximately equal number of grid cells per class, producing a relative estimate of mortality risks. The datasets are a result of the collaboration among the Center for Hazards and Risk Bank, and the Columbia University Center for International Earth Science Information Network (CIESIN). Economic Analyses A process of spatially allocating gross domestic product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational units to their respective national GDP are determined using sources of various origins. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational unit. Once the national GDP has been spatially stratified into the smallest administrative units available, GDP values for grid cells are derived using Gridded Population of the World Version 3.0 (beta) data of population distributions. Once a standardized version of subnational GDP had been calculated, this value was further divided by the total population within the subnational unit. This subnational, per-person GDP value was multiplied by the grid cell population density to determine a GDP for the grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell

5 by the natural hazards. Note that areas of "No Data" are not necessarily without risk from hazards, but may be an artifact of a mask that excluded from analysis those areas with a population density below 5 persons per square kilometer and without significant agriculture. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. The datasets are a result of the collaboration among the Center for Hazards and Risk Bank, and the Columbia University Center for International Earth Science Information Network (CIESIN). Spatial Reference Information Horizontal Coordinate System Definition: Geographic: Latitude Resolution: (2.5 minute) Longitude Resolution: (2.5 minute) Geographic Coordinate Units: Decimal degrees Geodetic Model: Horizontal Datum Name: D_WGS_1984 Ellipsoid Name: WGS_1984 Semi-major Axis: Denominator of Flattening Ratio: