The OMPS_NPP_NMSO2_PCA_L2 product is part of the MEaSUREs (Making Earth Science Data Records for Use in Research Environments) suite of products.

It is retrieved from the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) spectrometer and provides contiguous daily global monitoring of anthropogenic and volcanic sulfur dioxide (SO2), an important pollutant and aerosol precursor that affects both air quality and the climate. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017), and continues (Zhang et al., 2017) NASA's Earth Observing System (EOS) standard Aura/Ozone Monitoring Instrument SO2 product (OMSO2).

The latest OMPS_NPP_NMSO2_PCA_L2 V2 product uses new Jacobian lookup tables and more realistic model based a priori profiles in anthropogenic SO2 retrievals. This helps to more accurately account for the pixel-to-pixel variation in SO2 sensitivity due to different factors such as the vertical distribution of SO2, solar and viewing angles, surface reflectivity, and cloudiness. As compared with the previous OMPS_NPP_NMSO2_PCA_L2 V1.2 product that assumes the same SO2 sensitivity for all OMPS pixels, the new V2 anthropogenic SO2 retrievals have reduced retrieval biases especially over background regions (see Figure 1 for an example). The same updated PCA SO2 retrieval algorithm (Li et al., 2020) is also used to produce the recently released OMSO2 V2 product (doi:10.5067/Aura/OMI/DATA2022). The new OMPS_NPP_NMSO2_PCA_L2 V2 product thus offers enhanced consistency between the NASA EOS standard (OMI) and continuity (OMPS) SO2 data records

Sulfur Dioxide (SO2) is a short-lived gas primarily produced by volcanoes, power plants, refineries, metal smelting and burning of fossil fuels. Where SO2 remains near the Earth's surface, it is toxic, causes acid rain, and degrades air quality. Where SO2 is lofted into the free troposphere, it forms aerosols that can alter cloud reflectivity and precipitation. In the stratosphere, volcanic SO2 forms sulfate aerosols that can result in climate change.

The daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Burned Area (VNP64A1) Version 1 data product is a monthly, global gridded 500-meter (m) product containing per-pixel burned area and quality information. The VNP64 burned area mapping approach employs 750 m VIIRS imagery coupled with 750 m VIIRS active fire observations. The hybrid algorithm applies dynamic thresholds to composite imagery generated from a burn-sensitive Vegetation Index (VI) derived from VIIRS shortwave infrared channels M8 and M11, and a measure of temporal texture. VIIRS bands that are both sensitive and insensitive to biomass burning are used to detect changes caused by fire and to differentiate them from other types of change. The mapping algorithm ultimately identifies the date of burn, to the nearest day, for 500 m grid cells within the individual sinusoidal tile being processed. The date is encoded in a single data layer of the output product as the ordinal day of the calendar year on which the burn occurred (range 1–366), with a value of 0 for unburned land pixels and additional values reserved for missing data and water grid cells. The VNP64A1 data product is designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined burned area product to promote the continuity of the Earth Observation System (EOS) mission.

VNP64A1 has been released on a limited basis due to concerns over the quality of the data along the edges of inland water bodies and at high latitudes. These regions contain grid cells falsely identified as burned as a result of coarse resolution inputs to the cloud mask used in the generation of the 750 m VIIRS active fire observations. Users are urged to exercise caution when using this provisional (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/NPP_QA/NPPpage.cgi?fileName=maturity&subdir=forPage) data in research. The Version 2 burned area product generated with an improved cloud mask is scheduled for release in the summer of 2020.

The data layers provided in the VNP64A1 product include Burn Date, Burn Date Uncertainty, and Quality Assurance (QA), along with First Day and Last Day of reliable change detection of the year. A low resolution browse is also provided showing the burned date layer with a color map applied in JPEG format.

Notification: VIIRS/NPP Burned Area Monthly L4 Global 500 m SIN Grid data product has been released on a limited basis due to falsely identified burned areas.

This product is a multi-variate data compilation that reconciles the variation scales of these multiple measurements from varies resources, merges and maps them into a comprehensive description of the near-surface atmospheric properties together with the land surface property variations on diurnal-to-decadal time scales. Many of these data products, especially those based on surface measurements, are spatially and/or temporally sparse or incomplete in coverage, so procedures were developed to fill missing values.
The data product is comprised of a sequence of daily global files, where quantities are mapped into 1.0-degree equivalent equal-area grid, with time sampling is reported at daily or 3-hourly intervals. The time period overlap among the products covers 10 years from 1998 to 2007.

The Global Multihazard Proportional Economic Loss Risks is a 2.5 minute grid of a multihazard-based economic loss risk as a proportion of the economic productivity of the analytical Unit, the grid cell. Representation of multihazard risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and landslides are included in the hydro category.

For each of the six hazards considered, a binary risk surface is constructed utilizing the three most-at-risk deciles of each hazard's global proportional economic loss risks data set (deciles 8-10). Each of the category risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those locations that are at higher-risk from multihazards. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Multihazard Mortality Risks and Distribution is a 2.5 minute grid identifying and characterizing the nature of multihazard risk at the global scale. For this study, multihazard considers the hazards posed by cyclones, droughts, earthquakes, floods, landslides and volcanoes. The specific hazards are grouped into the following hazard categories: drought (drought), seismic (earthquakes and volcanoes), and hydro (cyclones, floods, and landslides). Each grid cell is assessed for each hazard category; and is considered at high risk or not at high risk. Treated as a binary value, the at-risk values of the hazards categories function as a 3-digit index of multihazard.

For each of the hazard category combinations, aggregate analyses determine the total population, area, and length of major transportation features, as well as, the value of Gross Domestic Product (GDP) and agricultural GDP. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Landslide Proportional Economic Loss Risk Deciles is a 2.5 minute grid of landslide hazard economic loss as proportions of Gross Domestic Product (GDP) per analytical Unit. Estimates of GDP at risk are based on regional economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Flood Total Economic Loss Risk Deciles is a 2.5 minute grid of global flood total economic loss risks. 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 (GPWv3) data of population distributions. A per capita contribution value is determined within each subnational Unit, and this value is multiplied by the population per 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 by flood hazards. 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. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Earthquake Total Economic Loss Risk Deciles is a 2.5 minute grid of global earthquake total economic loss risks. 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 origin. 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 (GPWv3) data population distributions. A per capita contribution value is determined within each subnational Unit, and then this value is multiplied by the population per 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 by earthquake hazards. 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. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Drought Total Economic Loss Risk Deciles is a 2.5 minute grid of global drought total economic loss risks. 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 is spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data of population distributions. A per capita contribution value is determined within each subnational Unit, and this value is multiplied by the population per 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 by drought hazards. 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. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Earthquake Hazard Distribution - Peak Ground Acceleration is a 2.5 minute grid of global earthquake hazards developed using Global Seismic Hazard Program (GSHAP) data that incorporate expert opinion in predicting localities where there exists a 10 percent chance of exceeding a peak ground acceleration (pga) of 2 meters per second per second (approximately one-fifth of surface gravitational acceleration) in a 50 year time span. For the purpose of identifying hazard hotspots, values of 2 meters per second per second and less were excluded from analysis. The resulting ranges of pga values were classified into deciles, 10 classes of approximately an equal number of grid cells. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR) and Columbia University Center for International Earth Science Information Network (CIESIN).