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Cook, Robert B

Publications and source records attributed to Cook, Robert B.

Big data for ecologists: Highlighting the ORNL DAAC

Ecologists are increasingly confronted by questions that can be addressed only by integrating data from numerous sources, often across large geographic areas and broad time periods. The supply of ecological big data is increasing at a rapid pace as researchers are publishing their data sets and large, public science and data infrastructures (such as NEON, DataONE, LTER, & NCEAS) are producing and curating extensive volumes of complex data and metadata. While supply of, and demand for, ecological data is on the rise, many ecologists now face a new challenge in locating and synthesizing the data relevant for their particular question. Here we highlight selected popular big data products applicable to ecological research available from the NASA Distributed Active Archive Center (DAAC) located at Oak Ridge National Laboratory (ORNL).

Boyer, Alison G↗

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a spreadsheet or other data analysis software. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. A multiple extractor script is freely available to download at http://daymet.ornl.gov/files/daymet.zip. The ORNL DAAC s THREDDS data server (TDS) provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. The ORNL DAAC TDS also exposes Daymet metadata through its ncISO service to facilitate harvesting Daymet metadata records into 3rd party catalogs. References: [1] Thornton, P.E., M.M. Thornton, B.W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R.B. Cook. 2014. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available on-line [http://daymet.ornl.go/singlepixel.html]. [3] Wei Y., et al. 2014. Daymet: Thematic Real-time Environmental Data Services. Available on-line [http://daymet.ornl.gov/thredds_tiles.html].

Thornton, Peter E↗

The Unified North American Soil Map and Its Implication on the Soil Organic Carbon Stock in North America

The Unified North American Soil Map (UNASM) was developed to provide more accurate regional soil information for terrestrial biosphere modeling. The UNASM combines information from state-of-the-art U.S. STATSGO2 and Soil Landscape of Canada (SLCs) databases. The area not covered by these datasets is filled with the Harmonized World Soil Database version 1.1 (HWSD1.1). The UNASM contains maximum soil depth derived from the data source as well as seven soil attributes (including sand, silt, and clay content, gravel content, organic carbon content, pH, and bulk density) for the top soil layer (0-30 cm) and the sub soil layer (30-100 cm) respectively, of the spatial resolution of 0.25 degrees in latitude and longitude. There are pronounced differences in the spatial distributions of soil properties and soil organic carbon between UNASM and HWSD, but the UNASM overall provides more detailed and higher-quality information particularly in Alaska and central Canada. To provide more accurate and up-to-date estimate of soil organic carbon stock in North America, we incorporated Northern Circumpolar Soil Carbon Database (NCSCD) into the UNASM. The estimate of total soil organic carbon mass in the upper 100 cm soil profile based on the improved UNASM is 347.70 Pg, of which 24.7% is under trees, 14.2% is under shrubs, and 1.3% is under grasses and 3.8% under crops. This UNASM data will provide a resource for use in land surface and terrestrial biogeochemistry modeling both for input of soil characteristics and for benchmarking model output.

Liu, Shishi↗

North American Carbon Project (NACP) Regional Interim Synthesis: Terrestrial Biospheric Model Intercomparison

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.

54 ENVIRONMENTAL SCIENCES↗

Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions and a new approach for estimating net ecosystem exchange from inventory-based data

While fossil fuel emissions are calculated with relatively high precision, understanding the fate of those emissions with respect to sequestration in terrestrial ecosystems requires data and methods that can reduce uncertainties in the diagnosis of land-based CO2 sinks. The wide range in the land surface flux estimates is related to a number of factors, but most generally because of the different methodologies used to develop estimates of carbon stocks and flux, and the uncertainties inherent in each approach. The alternative approaches to estimating continental scale carbon fluxes that we explored here can be broadly classified as applying a top-down or bottom-up perspective. Top-down approaches calculate land-atmosphere carbon fluxes based on atmospheric budgets and inverse modeling. Bottom-up approaches rely primarily on measurements of carbon stock changes (the inventory approach) or on spatially distributed simulations of carbon stocks and/or fluxes using process-based modeling (the forward modelapproach).

Hayes, D J↗

Database Maintenance, Data Sharing Policy, Collaboration

Scientific questions of today are now more global than ever before. The answers to these questions are buried within multiple disciplines and across a diverse range of scientists and institutions. The expanse and complexity of data required by researchers often exceed the means of a single scientist. Data sharing in the form of its distributed collection and analysis is increasingly common. Collective research now takes place in what may be called 'collaboratories' or in 'centers without walls' (Clery 2006). Creating effective artifacts, which enable scientists to collaborate on data analyses, continues to be a significant challenge for today's science activities. It is rare that providing a file system abstraction on distributed data enables acceleration of scientific discoveries. By explicitly identifying and addressing the different requirements for data contributors, data curators, and data consumers, we can create a data management architecture which enables the creation of datasets that evolve over time with growing and changing data, data annotations, participants, and use rules. This involves also a crucial contribution by the teams and people collecting the data, that in addition to carefully acquire and process the measurements and to be ready to share their measurements within the scientific community, need to follow general rules that help to make their data well documented and safely stored and to maximize visibility to their works and sites. In this chapter, we provide examples of the types of functions and capabilities typically provided within the data management systems, focusing in particular on databases structures and characteristics, data practices, and data user services. Finally, the importance and advantages of collective efforts like data sharing for synthesis activities and the relative data policy options are discussed and analyzed.

99 GENERAL AND MISCELLANEOUS↗