This product provides HAQES 3-hourly ensemble mean surface PM2.5 Organic Carbon concentration at the county level over the continental United States (CONUS).

The Hazardous Air Quality Ensemble System (HAQES) is a real-time ensemble forecast of hazardous air quality events, such as wildfires, dust storms, and Volcanic eruptions. Both regional and global models from multiple agencies are used to create the ensemble, including the Goddard Earth Observing System (GEOS) from the National Aeronautics and Space Administration (NASA), the Navy Aerosol Analysis and Prediction System (NAAPS) from Naval Research Laboratory, the Global Ensemble Forecast System Aerosols (GEFS), High-Resolution Rapid Refresh (HRRR), and National Oceanic and Atmospheric Administration-U.S. Environmental Protection Agency (NOAA-EPA) Atmosphere-Chemistry Coupler-Community Multiscale Air Quality model (NACC-CMAQ) from NOAA. The prototypes of HAQES products were developed by the George Mason University Air Quality Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST).

This product provides HAQES 3-hourly ensemble mean surface PM2.5 Organic Carbon concentration at the census level over the continental United States (CONUS).

The Hazardous Air Quality Ensemble System (HAQES) is a real-time ensemble forecast of hazardous air quality events, such as wildfires, dust storms, and Volcanic eruptions. Both regional and global models from multiple agencies are used to create the ensemble, including the Goddard Earth Observing System (GEOS) from the National Aeronautics and Space Administration (NASA), the Navy Aerosol Analysis and Prediction System (NAAPS) from Naval Research Laboratory, the Global Ensemble Forecast System Aerosols (GEFS), High-Resolution Rapid Refresh (HRRR), and National Oceanic and Atmospheric Administration-U.S. Environmental Protection Agency (NOAA-EPA) Atmosphere-Chemistry Coupler-Community Multiscale Air Quality model (NACC-CMAQ) from NOAA. The prototypes of HAQES products were developed by the George Mason University Air Quality Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST).

This product provides HAQES 3-hourly ensemble mean surface PM2.5 Black Carbon concentration over the continental United States (CONUS) and surrounding regions. The data is mapped on Lambert projection.

The Hazardous Air Quality Ensemble System (HAQES) is a real-time ensemble forecast of hazardous air quality events, such as wildfires, dust storms, and Volcanic eruptions. Both regional and global models from multiple agencies are used to create the ensemble, including the Goddard Earth Observing System (GEOS) from the National Aeronautics and Space Administration (NASA), the Navy Aerosol Analysis and Prediction System (NAAPS) from Naval Research Laboratory, the Global Ensemble Forecast System Aerosols (GEFS), High-Resolution Rapid Refresh (HRRR), and National Oceanic and Atmospheric Administration-U.S. Environmental Protection Agency (NOAA-EPA) Atmosphere-Chemistry Coupler-Community Multiscale Air Quality model (NACC-CMAQ) from NOAA. The prototypes of HAQES products were developed by the George Mason University Air Quality Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST).

This product provides HAQES 3-hourly ensemble mean surface PM2.5 Black Carbon concentration at the census level over the continental United States (CONUS).

The Hazardous Air Quality Ensemble System (HAQES) is a real-time ensemble forecast of hazardous air quality events, such as wildfires, dust storms, and Volcanic eruptions. Both regional and global models from multiple agencies are used to create the ensemble, including the Goddard Earth Observing System (GEOS) from the National Aeronautics and Space Administration (NASA), the Navy Aerosol Analysis and Prediction System (NAAPS) from Naval Research Laboratory, the Global Ensemble Forecast System Aerosols (GEFS), High-Resolution Rapid Refresh (HRRR), and National Oceanic and Atmospheric Administration-U.S. Environmental Protection Agency (NOAA-EPA) Atmosphere-Chemistry Coupler-Community Multiscale Air Quality model (NACC-CMAQ) from NOAA. The prototypes of HAQES products were developed by the George Mason University Air Quality Laboratory as part of the NASA Health Air Quality Applied Science Team (HAQAST).

The Natural Resource Protection and Child Health Indicators, 2022 Release, is produced in support of the U.S. Millennium Challenge Corporation (MCC) as selection criteria for funding eligibility. The Natural Resource Protection Indicator (NRPI) and Child Health Indicator (CHI) are based on proximity-to-target scores ranging from 0 to 100 (at target). The NRPI covers 220 countries and is calculated based on the weighted average percentage of biomes under protected status. The CHI is a composite index for 195 countries derived from the average of three proximity-to-target scores for access to at least basic water and sanitation together with child mortality rates. The 2022 release includes a consistent time series of NRPI scores for 2010 to 2022 and CHI scores for 2010 to 2020.

The Natural Resource Protection and Child Health Indicators, 2021 Release, is produced in support of the U.S. Millennium Challenge Corporation (MCC) as selection criteria for funding eligibility. The Natural Resource Protection Indicator (NRPI) and Child Health Indicator (CHI) are based on proximity-to-target scores ranging from 0 to 100 (at target). The NRPI covers 135 countries and is calculated based on the weighted average percentage of biomes under protected status. The CHI is a composite index for 194 countries derived from the average of three proximity-to-target scores for access to at least basic water and sanitation, along with child mortality. The 2021 release includes a consistent time series of NRPI scores for 2017 to 2021 and CHI scores for 2010 to 2020.

The Natural Resource Protection and Child Health Indicators, 2020 Release, is produced in support of the U.S. Millennium Challenge Corporation as selection criteria for funding eligibility. The Natural Resource Protection Indicator (NRPI) and Child Health Indicator (CHI) are based on proximity-to-target scores ranging from 0 to 100 (at target). The NRPI covers 250 countries and is calculated based on the weighted average percentage of biomes under protected status. The CHI is a composite index for 194 countries derived from the average of three proximity-to-target scores for access to at least basic water and sanitation, along with child mortality. The 2020 release includes a consistent time series of NRPI scores for 2010 to 2020 and CHI scores for 2010 to 2019.

M2_TMAX_PM25 is a value-added product derived from the MERRA-2 aerosol monthly product M2TMNXAER_5.12.4 (or tavgM_2d_aer_Nx). The surface concentration of fine particulate matter (PM2.5) is calculated as the sum of individual aerosol components (organic carbon, black carbon, sulfate, sea salt, and dust) (Buchard et al., 2017) and is recast from the native MERRA-2 model grid. This data collection includes separate files for country-level (and territories) PM2.5 concentrations with and without population weighting applied.

MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.

Questions: If you have a question on data access, email to the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov), and the question on science, email to the MERRA-2 science team (merra-questions@lists.nasa.gov).

The Bering Sea is home to over 70 Indigenous communities of the Iñupiat, Central Yup’ik, Cup’ik, St. Lawrence Island Yupik, Unangan, and Chukchi Peoples. In recent years, the Bering Sea has experienced unprecedented declines in sea ice, threatening community food security, infrastructure, and travel. In winters 2018 and 2019, sea ice coverage was by far the lowest observed in at least the last 160 years. Such loss of ice, together with increasing air temperatures and recent winter storm activity, has shifted much focus to the region with renewed questions regarding how local communities and ecosystems are affected. In 2019, scientists from the Study of Environmental Arctic Change (SEARCH) partnered with the Bering Sea Elders Group (BSEG) to create opportunities for Elders to communicate their experiences and knowledge regarding rapid environmental change across their region. In September 2019, ten Elders from eight communities came together for a two-day round-table gathering in Nome, Alaska to share their perspectives, observations, and stories about what sea ice loss means to their villages, the resources they depend on, and their collective future as Arctic Indigenous Peoples.

The Shared Socioeconomic Pathways (SSPs) Literature Database, v1, 2014-2019 consists of biographic information, abstracts, and analysis of 1,360 articles published from 2014 to 2019 that used the SSPs. The database was generated from a Google Scholar search, followed by a manual examination of the results for papers that made substantial use of the SSPs. Each paper was then coded along a number of different dimensions, including categories of types of papers or analysis, number of subcategories for SSP Applications and SSP Extensions, particular Shared Socioeconomic Pathways (SSPs) used, particular Representative Concentration Pathways (RCPs) used, and particular SSP-RCP combinations used. Over the past ten years, the climate change research commUnity developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. This framework consists of Shared Socioeconomic Pathways (SSPs), Representative Concentration Pathways (RCPs), and Shared Policy Assumptions (SPAs), which together describe alternative visions of how society and climate may evolve over the coming decades, while providing a framework for combining these pathways in integrated studies. The tracking of the use of this framework in the literature allows for assessment of how it is being used, whether it is achieving its original goals, and what improvements to the framework would benefit future research.