skip to main content

Title: Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

Sampling networks rarely conform to spatial and temporal ideals, often comprised of network sampling points which are unevenly distributed and located in less than ideal locations due to access constraints, budget limitations, or political conflict. Quantifying the global, regional, and temporal representativeness of these networks by quantifying the coverage of network infrastructure highlights the capabilities and limitations of the data collected, facilitates upscaling and downscaling for modeling purposes, and improves the planning efforts for future infrastructure investment under current conditions and future modeled scenarios. The work presented here utilizes multivariate spatiotemporal clustering analysis and representativeness analysis for quantitative landscape characterization and assessment of the Fluxnet, RAINFOR, and ForestGEO networks. Results include ecoregions that highlight patterns of bioclimatic, topographic, and edaphic variables and quantitative representativeness maps of individual and combined networks.
; ; ;
Publication Date:
DOE Contract Number:
Product Type:
Research Org(s):
Climate Change Science Institute (CCSI), Oak Ridge National Laboratory (ORNL), Oak Rdige, TN (US)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
54 Environmental Sciences; CCSI; climate datasets; Landscape Characterization; Representativeness Analysis; ORNL
OSTI Identifier:
  1. The Climate Change Science Institute (CCSI) was formed in 2009 to integrate climate science activities across Oak Ridge National Laboratory. Approximately, 130 scientists are doing research in the areas of (i) earth system modeling, (ii) data integration, dissemination, and informatics, (iii) integrative ecosystem scienceterrestrial ecosystem and carbon cycle science, and (iv) climate impacts, adaptation, and vulnerability science. CCSI works to strengthen the predictive capabilities and effectiveness of climate and biogeochemical models and develop useful climate adaptation and mitigation tools and information in collaboration with land-energy-water system stakeholders.
No associated Collections found.
  1. In the 1960s, thermonuclear bomb tests released significant pulses of radioactive 14C into the atmosphere. This major perturbation allowed scientists to study the dynamics of the global carbon cycle by measuring and observing rates of isotopic exchange. The Radiological Dating Laboratory at the Norwegian Institutemore » of Technology performed 14C measurements in atmospheric CO2 from 1962 to 1993 at a network of ground stations in the Northern and Southern hemispheres. These measurements were supplemented during 1965 with high-altitude (9-12.6 km) air samples collected using aircraft from the Norwegian Air Force. The resulting database, coupled with other 14C data sets, provides a greater understanding of the dynamic carbon reservoir and a crude picture of anomalous sources and sinks at different geographical latitudes. This database is outstanding for its inclusion of early 14C measurements, broad spatial coverage of sampling, consistency of sampling method, and 14C calculation results corrected for isotopic fractionation and radioactive decay. This database replaces previous versions published by the authors and the Radiological Dating Laboratory. Fourteen stations spanning latitudes from Spitsbergen (78° N) to Madagascar (21° S) were used for sampling during the lifetime of the Norwegian program. Some of the stations have data for only a brief period, while others have measurements through 1993. Sampling stations subject to local industrial CO2 contamination were avoided. The sites have sufficient separation to describe the latitudinal distribution of 14C in atmospheric models. The sampling procedure for all the surface (10-2400 m asl) 14C measurements in this database consisted of quantitative absorption of atmospheric CO2 in carbonate-free 0.5 N NaOH solution. The 14C measurements were made in a CO2 proportional counter and calculated (14C) as per mil excess above the normal 14C level defined by the US National Institute of Standards and Technology (NIST). Atmospheric 14C content is finally expressed as 14C, which is the relative deviation of the measured 14C activity from the NIST oxalic acid standard activity, after correction for isotopic fractionation and radioactive decay related to age. The data are organized by sampling station, and each record of the database contains the sampling dates; values for 14C excess (14C) relative to the NIST standard, fractionation 13C (13C) relative to the Pee Dee Belemnite (PDB) standard, and corrected 14C ( 14C) excess; and the standard deviation for 14C. The 14C calculation results presented here are thus corrected for isotopic fractionation and radioactive decay, and constitute the final product of a research effort that has spanned three decades. The 14C station data show a sharp increase in tropospheric radiocarbon levels in the early 1960s and then a decline after the majority of nuclear tests came to an end on August 5, 1963 (Test Ban Treaty). The sharp peaks in tropospheric radiocarbon in the early 1960s are more pronounced in the Northern Hemisphere, reflecting the location of most atomic weapons tests. The measurements show large seasonal variations in the 14C level during the early 1960s mainly as a result of springtime transport of bomb 14C from the stratosphere. During the 1970s, the seasonal variations are smaller and due partly to seasonal variations in CO2 from fossil-fuel emissions. The rate of decrease of atmospheric radiocarbon provides a check on the exchange constants of the atmosphere and ocean. This report and all data it describes are available from the Carbon Dioxide Information Analysis Center (CDIAC) without charge. The Nydal and Lövseth atmospheric 14C database comprises 21 data files totaling 0.2 megabytes in size. The following report describes the sampling methods and analysis. In addition, the report includes a complete discussion of CDIAC's data-processing efforts, the contents and format of the data files, and a reprint of a Nydal and Lövseth journal article. « less
  2. This data package provides daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompassmore » 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893-1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station's daily data values for a period of one month, including data source, measurement, and quality flags. The snow depth data have undergone extensive manual and automated quality assurance checks by NCDC and the Carbon Dioxide Information Analysis Center (CDIAC). These reviews involved examining the data for completeness, reasonableness, and accuracy, and included comparison of some data records with records in NCDC's Summary of the Day First Order online database. Since the snow depth measurements have been taken at NWS first-order stations that have long periods of record, they should prove useful in monitoring climate change. « less
  3. To help guide its future data collection efforts, The DOE GTO funded a data gap analysis in FY2012 to identify high potential hydrothermal areas where critical data are needed. This analysis was updated in FY2013 and the resulting datasets are represented by this metadata. Themore » original process was published in FY 2012 and is available here: Though there are many types of data that can be used for hydrothermal exploration, five types of exploration data were targeted for this analysis. These data types were selected for their regional reconnaissance potential, and include many of the primary exploration techniques currently used by the geothermal industry. The data types include: 1. well data 2. geologic maps 3. fault maps 4. geochemistry data 5. geophysical data To determine data coverage, metadata for exploration data (including data type, data status, and coverage information) were collected and catalogued from nodes on the National Geothermal Data System (NGDS). It is the intention of this analysis that the data be updated from this source in a semi-automated fashion as new datasets are added to the NGDS nodes. In addition to this upload, an online tool was developed to allow all geothermal data providers to access this assessment and to directly add metadata themselves and view the results of the analysis via maps of data coverage in Geothermal Prospector ( A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the five data types. Using these five data coverage maps and the USGS Resource Potential Map, sites were identified for future data collection efforts. These sites signify both that the USGS has indicated high favorability of occurrence of geothermal resources and that data gaps exist. The uploaded data are contained in two data files for each data category. The first file contains the grid and is in the SHP file format (shape file.) Each populated grid cell represents a 10k area within which data is known to exist. The second file is a CSV (comma separated value) file that contains all of the individual layers that intersected with the grid. This CSV can be joined with the map to retrieve a list of datasets that are available at any given site. The attributes in the CSV include: 1. grid_id : The id of the grid cell that the data intersects with 2. title: This represents the name of the WFS service that intersected with this grid cell 3. abstract: This represents the description of the WFS service that intersected with this grid cell 4. gap_type: This represents the category of data availability that these data fall within. As the current processing is pulling data from NGDS, this category universally represents data that are available in the NGDS and are ready for acquisition for analytic purposes. 5. proprietary_type: Whether the data are considered proprietary 6. service_type: The type of service 7. base_url: The service URL « less
  4. The stations in this dataset are considered by RIHMI to comprise one of the best networks suitable for temperature and precipitation monitoring over the the former-USSR. Factors involved in choosing these 223 stations included length or record, amount of missing data, and achieving reasonably goodmore » geographic coverage. There are indeed many more stations with daily data over this part of the world, and hundreds more station records are available through NOAA's Global Historical Climatology Network - Daily (GHCND) database. The 223 stations comprising this database are included in GHCND, but different data processing, updating, and quality assurance methods/checks mean that the agreement between records will vary depending on the station. The relative quality and accuracy of the common station records in the two databases also cannot be easily assessed. As of this writing, most of the common stations contained in the GHCND have more recent records, but not necessarily records starting as early as the records available here. This database contains four variables: daily mean, minimum, and maximum temperature, and daily total precipitation (liquid equivalent). Temperature were taken three times a day from 1881-1935, four times a day from 1936-65, and eight times a day since 1966. Daily mean temperature is defined as the average of all observations for each calendar day. Daily maximum/minimum temperatures are derived from maximum/minimum thermometer measurements. See the measurement description file for further details. Daily precipitation totals are also available (to the nearest tenth of a millimeter) for each station. Throughout the record, daily precipitation is defined as the total amount of precipitation recorded during a 24-h period, snowfall being converted to a liquid total by melting the snow in the gauge. From 1936 on, rain gauges were checked several times each day; the cumulative total of all observations during a calendar day was presumably used as the daily total. Again, see the measurement description file for further details. « less
  5. This report is the third in a series of reports sponsored by the U.S. Department of Energy Geothermal Technologies Program in which a range of water-related issues surrounding geothermal power production are evaluated. The first report made an initial attempt at quantifying the life cyclemore » fresh water requirements of geothermal power-generating systems and explored operational and environmental concerns related to the geochemical composition of geothermal fluids. The initial analysis of life cycle fresh water consumption of geothermal power-generating systems identified that operational water requirements consumed the vast majority of water across the life cycle. However, it relied upon limited operational water consumption data and did not account for belowground operational losses for enhanced geothermal systems (EGSs). A second report presented an initial assessment of fresh water demand for future growth in utility-scale geothermal power generation. The current analysis builds upon this work to improve life cycle fresh water consumption estimates and incorporates regional water availability into the resource assessment to improve the identification of areas where future growth in geothermal electricity generation may encounter water challenges. « less