--- - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'This is a subset of Populated Alaska Places that is used primarily for large scale mapping. Locations of statewide cities were entered by latitude-longitude, digitized from USGS 1:250,000 quadrangle maps, and heads-up digitizing from USGS 1:250,000 maps based on relative positioning of digital hydrography and digital township lines. Many locations were later updated by snapping them to points in the USGSNAMES coverage obtained from USGS. List of populated places were acquired from Alaska Department of Community and Regional Affairs (DCRA). The classifications of cities is determined by the Department of Community and Regional Affairs. An excellent description of city classifications was prepared by the Local Boundary Commission Staff of the Alaska Department of Community & Regional Affairs.' description_attribution: http://dnr.alaska.gov/mdfiles/cities.txt doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/adnr-alaska-towns-1998.yaml identifier: adnr-alaska-towns-1998 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: ADNR Alaska Towns 1998 native_id: ~ processing_level: ~ publication_year: 1998 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/adnr-alaska-towns-1998 url: http://www.asgdc.state.ak.us/#7 variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: 'Cite datasets in publications such as journal papers, articles, presentations, posters, and websites. Include the DOI when available (each RTC ALOS PALSAR dataset processed by ASF has an assigned DOI). Please send copies of, or links to, published works citing data, imagery, or tools accessed through ASF to uso@asf.alaska.edu with "New Publication" on subject line.' data_qualifier: ~ description: "The Phased Array type L-band Synthetic Aperture Radar (PALSAR) is an active microwave sensor using L-band frequency to achieve cloud-free and day-and-night land observation. It provides higher performance than theJERS-1's synthetic aperture radar (SAR). Fine resolution in a conventional mode, but PALSAR will have another advantageous observation mode. ScanSAR, which will enable us to acquire a 250 to 350km width of SAR images (depending on the number of scans) at the expense of spatial resolution. This swath is three to five times wider than conventional SAR images. The development of the PALSAR is a joint project between JAXA and the Japan Resources Observation System Organization (JAROS)." description_attribution: https://www.eorc.jaxa.jp/ALOS/en/about/palsar.htm doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/asf-alos-palsar.yaml identifier: asf-alos-palsar lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: ASF ALOS PALSAR native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/asf-alos-palsar url: https://www.asf.alaska.edu/sar-data/palsar/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The Consumer Price Index for All Urban Consumers (CPI-U) is a monthly measure of the average change over time in the prices paid by consumers for a market basket of consumer goods and services. The CPI-U is based on the spending patterns of urban consumers. Index data are available for the U.S. City Average (or national average), for various geographic areas (regions and metropolitan areas), for national population size classes of urban areas, and for cross-classifications of regions and size classes. Individual indexes are available for more than 200 items (e.g., apples, men's shirts, airline fares), and over 120 different combinations of items (e.g., fruits and vegetables, food at home, food and beverages, and All items)." description_attribution: https://www.bls.gov/help/one_screen/cu.htm doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/bls-all-urban-consumers-current-series-consumer-price-index-cpi.yaml identifier: bls-all-urban-consumers-current-series-consumer-price-index-cpi lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'BLS All Urban Consumers (Current Series) - (Consumer Price Index - CPI)' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/bls-all-urban-consumers-current-series-consumer-price-index-cpi url: https://www.bls.gov/data/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: 'Peters et al, 2007, "An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker", PNAS, November 27, 2007 , vol. 104, no. 48, 18925-18930.' data_qualifier: ~ description: 'CarbonTracker is a CO2 measurement and modeling system developed by NOAA to keep track of sources (emissions to the atmosphere) and sinks (removal from the atmosphere) of carbon dioxide around the world. CarbonTracker uses atmospheric CO2 observations from a host of collaborators and simulated atmospheric transport to estimate these surface fluxes of CO2. The current release of CarbonTracker, CT2017, provides global estimates of surface-atmosphere fluxes of CO2 from January 2000 through December 2016.' description_attribution: https://www.esrl.noaa.gov/gmd/ccgg/carbontracker/ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/carbontracker-ct2007b-release.yaml identifier: carbontracker-ct2007b-release lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: CarbonTracker CT2007B release native_id: CT2007B processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/carbontracker-ct2007b-release url: https://www.esrl.noaa.gov/gmd/ccgg/carbontracker/CT2007B/ variables: ~ version: CT2007B vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The observations of atmospheric CO2 mole fraction by over 40 different laboratories are at the heart of CarbonTracker. They inform us on changes in the carbon cycle, whether they are regular (such as the seasonal growth and decay of leaves and trees), or irregular (such as the release of tons of carbon by a wildfire). The results in CarbonTracker depend directly on the quality, amount and location of observations available, and the degree of detail at which we can monitor the carbon cycle reliably increases strongly with the density of our observing network' description_attribution: https://www.carbontracker.eu/version.shtml doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/carbontracker-europe-2015-cte2015.yaml identifier: carbontracker-europe-2015-cte2015 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: CarbonTracker Europe 2015 (CTE2015) native_id: ~ processing_level: ~ publication_year: ~ release_dt: 1970-01-01T00:33:36 scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/carbontracker-europe-2015-cte2015 url: https://www.carbontracker.eu/version.shtml variables: ~ version: CTE2015 vertical_extent: ~ - access_dt: 2013-05-06T00:00:00 attributes: 'Monthly maximum 1-day precipitation, Maximum number of consecutive days with RR < 1mm, and other temperature and precipitation indices (see http://etccdi.pacificclimate.org/list_27_indices.shtml).' cite_metadata: "Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013a: Climate extremes indices in the CMIP5 multi-model ensemble. Part 1: Model evaluation in the present climate. J. Geophys. Res., doi:10.1002/jgrd.50203.\r\n\r\nSillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013b: Climate extremes indices in the CMIP5 multi-model ensemble. Part 2: Future projections. J. Geophys. Res., doi:10.1002/jgrd.50188." data_qualifier: ~ description: 'The climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are computed for a number of global climate models participating in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5), and reanalyses. The definitions of the indices are given here. The validation of climate extremes indices and analysis of their projected future changes simulated by the CMIP5 models is presented in Sillmann et al. (2013a, 2013b)' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cccma-etccdi-extreme-indices-archive.yaml identifier: cccma-etccdi-extreme-indices-archive lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: ETCCDI Extremes Indices Archive native_id: Unknown processing_level: ~ publication_year: 2013 release_dt: 2012-09-12T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90; minimum_latitude: -90; maximum_longitude: 180; minimum_longitude: -180;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1850-01-01T00:00:00 2300-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/cccma-etccdi-extreme-indices-archive url: http://www.cccma.ec.gc.ca/data/climdex/climdex.shtml variables: ~ version: N/A vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'ArboNET is a national arboviral surveillance system managed by CDC and state health departments. In addition to human disease, ArboNET maintains data on arboviral infections among presumptive viremic blood donors, veterinary disease cases, mosquitoes, dead birds, and sentinel animals. As with other national surveillance data, ArboNET data have several limitations that should be considered in analysis, interpretation, and reporting: ArboNET is a passive surveillance system. It is dependent on clinicians considering the diagnosis of an arboviral disease and obtaining the appropriate diagnostic test, and reporting of laboratory-confirmed cases to public health authorities. Diagnosis and reporting are incomplete, and the incidence of arboviral diseases is underestimated. Reported neuroinvasive disease cases are considered the most accurate indicator of arboviral activity in humans because of the substantial associated morbidity. In contrast, reported cases of nonneuroinvasive arboviral disease are more likely to be affected by disease awareness and healthcare-seeking behavior in different communities and by the availability and specificity of laboratory tests performed. Surveillance data for nonneuroinvasive disease should be interpreted with caution and generally should not be used to make comparisons between geographic areas or over time. Provisional ArboNET data are provided to help track recent arboviral disease activity. However, these data may change substantially before they are finalized. Provisional data from the current year should not be combined with or compared to final data from previous years.' description_attribution: https://www.cdc.gov/westnile/resourcepages/survResources.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-arbonet.yaml identifier: cdc-arbonet lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: CDC Arbonet native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-arbonet url: https://wwwn.cdc.gov/arbonet/Maps/ADB_Diseases_Map/index.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "COVIS data\r\n\r\nData are collected at local level and clinically confirmed cases of any Vibrio infection (any species) are reported to the COVIS system (Cholera and Other Vibrio Surveillance). \r\n\r\nCOVIS surveillance reports allow for the reporting of metadata including: patient information, geographic location of isolation, type of infection (wound, blood, gastrointestinal), source of exposure, species confirmed, foreign travel, food consumption, etc. Completeness in reporting of clinical information, epidemiological information, clinical information, and seafood trace-back currently ranges from 21% - 71%." description_attribution: http://www.cdc.gov/nationalsurveillance/cholera-vibrio-surveillance.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-cholera-other-vibrio-illness-surveillance.yaml identifier: cdc-cholera-other-vibrio-illness-surveillance lat_max: 71.32 lat_min: 18.91 lon_max: -66.57 lon_min: -160.16 name: Cholera and Other Vibrio Illness Surveillance COVIS native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1996-01-01T00:00:01 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-cholera-other-vibrio-illness-surveillance url: http://www.cdc.gov/nationalsurveillance/cholera-vibrio-surveillance.html variables: 'confirmed vibrio infections per 1,000,000 people' version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: The FluView National Flu Activity Map is a complementary widget to the state-by-state flu map widget introduced in the 2007-2008 flu season. This interactive map allows users to see the most recent seasonal influenza activity map for the entire country as well as the activity levels from previous weeks in the current flu season. description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-fluview-national-flu-activity-map.yaml identifier: cdc-fluview-national-flu-activity-map lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: FluView National Flu Activity Map native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-fluview-national-flu-activity-map url: http://www.cdc.gov/Widgets/#fluview variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "This is an RSS Feed of Food Safety information that’s produced in real-time by the CDC. This RSS feed is the integration of two other XML feeds, one from the USDA's Food Safety Inspection Service (FSIS) - http://www.fsis.usda.gov/RSS/usdarss.xml - and one from the FDA's Food Safety Recalls - http://www.fda.gov/AboutFDA/ContactFDA/StayInformed/RSSFeeds/FoodSafety/.... Most users will prefer the CDC feed linked above, but developers may prefer the individual XML feeds." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-food-safety-information-rss-feed.yaml identifier: cdc-food-safety-information-rss-feed lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Food Safety Information RSS feed native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-food-safety-information-rss-feed url: http://www2c.cdc.gov/podcasts/createrss.asp?c=146 variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Health Data Interactive (HDI) presents a broad range of important public health indicators through an interactive web-based application that provides access to pre-tabulated national and state data for the US. The primary objective is to provide national estimates of public health measures cross tabulated by a common set of variables. HDI tables contain national health statistics for infants, children, adolescents, adults, and older adults. The tables can be customized by age, gender, race/ethnicity, and geographic location to explore different trends and patterns.n' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-health-data-interactive-hdi.yaml identifier: cdc-health-data-interactive-hdi lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Health Data Interactive (HDI) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-health-data-interactive-hdi url: http://www.cdc.gov/nchs/hdi.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The National Ambulatory Medical Care Survey (NAMCS) is a national survey designed to meet the need for objective, reliable information about the provision and use of ambulatory medical care services in the United States. Findings are based on a sample of visits to non-federal employed office-based physicians who are primarily engaged in direct patient care.' description_attribution: http://www.cdc.gov/nchs/ahcd/ahcd_questionnaires.htm doi: ~ end_time: 1972-12-31T19:00:00 href: https://data.globalchange.gov/dataset/cdc-national-ambulatory-medical-care-survey-namcs.yaml identifier: cdc-national-ambulatory-medical-care-survey-namcs lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: National Ambulatory Medical Care Survey (NAMCS) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1972-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-national-ambulatory-medical-care-survey-namcs url: https://www.cdc.gov/nchs/ahcd/index.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The National Death Index (NDI) is a centralized database of death record information on file in state vital statistics offices. Working with these state offices, the National Center for Health Statistics (NCHS) established the NDI as a resource to aid epidemiologists and other health and medical investigators with their mortality ascertainment activities.
Assists investigators in determining whether persons in their studies have died and, if so, provide the names of the states in which those deaths occurred, the dates of death, and the corresponding death certificate numbers. Investigators can then make arrangements with the appropriate state offices to obtain copies of death certificates or specific statistical information such as manner of death or educational level. Cause of death codes may also be obtained using the NDI Plus service.
Records from 1979 through 2011 are currently available and contain a standard set of identifying information on each death. Death records are added to the NDI file annually, approximately 12 months after the end of a particular calendar year. 2012 should be available summer 2014. Early Release Program for 2013 is now available.
The NDI service is available to investigators solely for statistical purposes in medical and health research. The service is not accessible to organizations or the general public for legal, administrative, or genealogy purposes.' description_attribution: http://www.cdc.gov/nchs/ndi.htm doi: ~ end_time: 2010-12-31T19:00:00 href: https://data.globalchange.gov/dataset/cdc-national-death-index.yaml identifier: cdc-national-death-index lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: National Death Index native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1978-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-national-death-index url: http://www.cdc.gov/nchs/ndi/index.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The National Environmental Public Health Tracking Network is a system of integrated health, exposure, and hazard information and data from a variety of national, state, and city sources. On the Tracking Network, you can explore information and view maps, tables, and charts about health and environment across the country.' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-national-environmental-public-health-tracking-network-tracking-network.yaml identifier: cdc-national-environmental-public-health-tracking-network-tracking-network lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: CDC National Environmental Public Health Tracking Network (Tracking Network) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-national-environmental-public-health-tracking-network-tracking-network url: http://www.cdc.gov/ephtracking/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: Interactive online tool for creating and manipulating tables based on birth and perinatal (fetal and infant death) data files. Tabulated data can be graphed or mapped within VitalStats or exported to Excel for further analysis. description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-vitalstats.yaml identifier: cdc-vitalstats lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: VitalStats native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-vitalstats url: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by year, state and metropolitan areas (MSA), age group, race, ethnicity, gender, childhood cancer classifications and cancer site. Report case counts, deaths, crude and age-adjusted incidence and death rates, and 95% confidence intervals for rates. The USCS data are the official federal statistics on cancer incidence from registries having high-quality data and cancer mortality statistics for 50 states and the District of Columbia. USCS are produced by the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), in collaboration with the North American Association of Central Cancer Registries (NAACCR). Mortality data are provided by the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Vital Statistics System (NVSS).' description_attribution: http://wonder.cdc.gov/cancer.html doi: ~ end_time: 2006-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-cancer-statistics.yaml identifier: cdc-wonder-cancer-statistics lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Cancer Statistics' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-cancer-statistics url: http://wonder.cdc.gov/cancer.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979 -2008. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-2008: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause of death (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The Compressed Mortality data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/cmf.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-compressed-mortality-underlying-cause-death.yaml identifier: cdc-wonder-compressed-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Compressed Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1967-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-compressed-mortality-underlying-cause-death url: http://wonder.cdc.gov/mortSQL.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Daily Air Temperature and Heat Index data available on CDC WONDER are county-level daily average air temperatures and heat index measures spanning the years 1979-2010. Temperature data are available in Fahrenheit or Celsius scales. Reported measures are the average temperature, number of observations, and range for the daily maximum and minimum air temperatures, and also percent coverage for the daily maximum heat index. Data are available by place (combined 48 contiguous states, region, division, state, county), time (year, month, day) and specified maximum and minimum air temperature, and heat index value. The data are derived from the North America Land Data Assimilation System (NLDAS) through NLDAS Phase 2, a collaboration project among several groups: the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Princeton University, the National Weather Service (NWS) Office of Hydrological Development (OHD), the University of Washington, and the NCEP Climate Prediction Center (CPC). In a study funded by the NASA Applied Sciences Program/Public Health Program, scientists at NASA Marshall Space Flight Center/ Universities Space Research Association developed the analysis to produce the data available on CDC WONDER.' description_attribution: http://wonder.cdc.gov/wonder/help/nldas.html doi: ~ end_time: 2010-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-daily-air-temperatures-and-heat-index.yaml identifier: cdc-wonder-daily-air-temperatures-and-heat-index lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Daily Air Temperatures and Heat Index' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1978-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-daily-air-temperatures-and-heat-index url: http://wonder.cdc.gov/nasa-nldas.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Detailed Mortality - Underlying Cause of Death data on CDC WONDER are county-level national mortality and population data spanning the years 1999-2009. Data are based on death certificates for U.S. residents. Each death certificate contains a single underlying cause of death, and demographic data. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., region, state, and county), age group (including infants and single-year-of-age cohorts), race (4 groups), Hispanic ethnicity, gender, year of death, and cause-of-death (4-digit ICD-10 code or group of codes, injury intent and mechanism categories, or drug and alcohol related causes), year, month and week day of death, place of death and whether an autopsy was performed. The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/ucd.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-detailed-mortality-underlying-cause-death.yaml identifier: cdc-wonder-detailed-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Detailed Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-detailed-mortality-underlying-cause-death url: http://wonder.cdc.gov/ucd-icd10.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The Mortality - Infant Deaths (from Linked Birth / Infant Death Records) online databases on CDC WONDER provide counts and rates for deaths of children under 1 year of age, occuring within the United States to U.S. residents. Information from death certificates has been linked to corresponding birth certificates. Data are available by county of mother's residence, child's age, underlying cause of death, gender, birth weight, birth plurality, birth order, gestational age at birth, period of prenatal care, maternal race and ethnicity, maternal age, maternal education and marital status. Data are available since 1995. The data are produced by the National Center for Health Statistics." description_attribution: http://wonder.cdc.gov/wonder/help/lbd.html doi: ~ end_time: 2005-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-infant-deaths.yaml identifier: cdc-wonder-mortality-infant-deaths lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Infant Deaths' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1994-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-infant-deaths url: http://wonder.cdc.gov/lbd.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Mortality - Multiple Cause of Death data on CDC WONDER are county-level national mortality and population data spanning the years 1999-2009. Data are based on death certificates for U.S. residents. Each death certificate contains a single underlying cause of death, up to twenty additional multiple causes (Boolean set analysis), and demographic data. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., region, state, and county), age group (including infants and single-year-of-age cohorts), race (4 groups), Hispanic ethnicity, gender, year of death, and cause-of-death (4-digit ICD-10 code or group of codes, injury intent and mechanism categories, or drug and alcohol related causes), year, month and week day of death, place of death and whether an autopsy was performed. The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/mcd.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-multiple-cause-death.yaml identifier: cdc-wonder-mortality-multiple-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Multiple Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-multiple-cause-death url: http://wonder.cdc.gov/mcd.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979. Data are updated annually. The number of deaths, crude death rates, age-adjusted death rates, standard errors and confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-present: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause ofdeath (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/cmf.html doi: ~ end_time: 2007-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-underlying-cause-death.yaml identifier: cdc-wonder-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-underlying-cause-death url: http://wonder.cdc.gov/mortSQL.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Population - Bridged-Race July 1st Estimates online databases report bridged-race population estimates of the July 1st resident population of the United States, based on Census 2000 counts, for use in calculating vital rates. These estimates result from "bridging" the 31 race categories used in Census 2000, as specified in the 1997 Office of Management and Budget (OMB) standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (Asian or Pacific Islander, Black or African American, American Indian or Alaska Native, White). Many data systems, such as vital statistics, are continuing to use the 1977 OMB standards during the transition to full implementation of the 1997 OMB standards. Postcensal estimates are available for year 2000 - 2009; intercensal estimates are available for the years 1990-1999. Obtain population counts by Year, State, County, Race (4-categories), Ethnicity, Sex and Age (1-year or 5-year groups). The data are released by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/bridged-race.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-population-bridged-race-july-1st-estimates.yaml identifier: cdc-wonder-population-bridged-race-july-1st-estimates lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Population - Bridged-Race July 1st Estimates' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1989-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-population-bridged-race-july-1st-estimates url: http://wonder.cdc.gov/bridged-race-population.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: ~ description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdec-water-storage-levels-shasta-dam-reservoir.yaml identifier: cdec-water-storage-levels-shasta-dam-reservoir lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Storage Levels in the Shasta Dam Reservoir native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdec-water-storage-levels-shasta-dam-reservoir url: http://cdec.water.ca.gov/resapp/ResDetail?resid=SHA variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: 'Houghton, R.A. 2008. Carbon Flux to the Atmosphere from Land-Use Changes: 1850-2005. In TRENDS: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.' data_qualifier: ~ description: 'The methods and data sources used to derive this time series of flux estimates are described in Houghton (1999, 2003), Houghton and Hackler (1995), and Houghton et al. (1983). In summary, this database provides estimates of regional and global net carbon fluxes, on a year-by-year basis from 1850 through 2005, resulting from changes in land use (such as harvesting of forest products and clearing for agriculture), taking into account not only the initial removal and oxidation of the carbon in the vegetation, but also subsequent regrowth and changes in soil carbon. The net flux of carbon to the atmosphere from changes in land use from 1850 to 2005 was modeled as a function of documented land-use change and changes in aboveground and belowground carbon following changes in land use. Annual rates of land-use change (for example, conversion of forest to cropland) and per hectare changes in carbon stocks (vegetation, slash, wood products, and soils) as a result of changes in land use were used in a carbon accounting model to calculate the annual net flux of carbon between land and the atmosphere that results from land management. The net flux includes both emissions of carbon from deforestation and sinks of carbon in forests recovering from harvests or agricultural abandonment. Changes in land use included the expansion and contraction of croplands and pastures, plantation establishment, and harvest of wood. Carbon budgeting included only those ecosystems converted to other uses or harvested; unmanaged ecosystems were not considered. Further, rates of growth and decomposition were ecosystem specific and did not vary in response to variations in climatic factors, CO2 concentrations, or other elements of environmental change. The analyses were spatially aggregated. Two to six types of ecosystems, with average carbon stocks, were considered for each of ten world regions.' description_attribution: https://cdiac.ess-dive.lbl.gov/trends/landuse/houghton/houghton.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005.yaml identifier: cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Carbon flux to the atmosphere from land-use changes 1850-2005 native_id: ~ processing_level: ~ publication_year: 2008 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005 url: https://cdiac.ess-dive.lbl.gov/trends/landuse/houghton/1850-2005.txt variables: ~ version: ~ vertical_extent: ~