Oak Ridge National Laboratory Distributed Research Articles

Annual forest disturbance intensity mapped using Landsat time series and field inventory data for the conterminous United States (1986–2015)

Forest disturbances can have broad impact on the climate, local environment, and the regeneration of the forest ecosystem. The nature and magnitude of such impact is largely driven by disturbance intensity. In this study, by integrating field plot measurements collected by the Forest Inventory and Analysis program with time series Landsat observations, we produced the first set of annual forest disturbance intensity map products quantifying the percentage of basal area removal (PBAR) at the 30-m resolution for the conterminous United States (CONUS) from 1986 to 2015. The derived map products revealed that during the 30-year study period, the annual average PBAR values of all disturbed pixels across CONUS ranged from 66% to 70%, and the proportion of those pixels having stand-clearing disturbances ranged from 40% to 58%. High disturbance intensities were concentrated in the Southeastern states from Texas to Virginia and along the Pacific coast and the Cascades in the West. At the national scale, the annual mean PBAR and proportion of stand clearing area (PSCA) values both appeared to follow second order trajectories, with increasing trends at the beginning, decreasing trends towards the end, and turning points around 2003. Overall, there is a net increase of 2% in PBAR and 3% in PSCA from 1986 to 2015. The temporal trends of PBAR and PSCA were also investigated at state and ecoregion levels, with substantial differences found among many states and ecoregions. While states and ecoregions generally follow second order trajectories, the majority had increasing trends throughout much of the study period, reflecting higher disturbance intensities during the later years compared to earlier years. Large increase (>10%) in PBAR was seen in several states (e.g., Virginia, Arkansas, and Minnesota) and ecoregions (e.g., Northern Minnesota Wetlands); however, large decreases (>10%) in PBAR were not observed in any states, and were seen in only one ecoregion, the Blue Mountains in the southeast. The disturbance intensity maps are available from a web portal of the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) at https://doi.org/10.3334/ORNLDAAC/2059.

Biomass partitioning of C3- and C4-dominated grasslands in response to climatic variability and climate extremes

The rising temperature, altering precipitation, and increasing extreme events under climate warming affect the stability and sustainability of grassland ecosystems. The dynamics of above-ground biomass (AGB), below-ground biomass (BGB), and biomass partitioning (BGB:AGB ratio) of grasslands are of fundamental importance to understand their feedback to climate change. In this study, we used grassland productivity data extracted from the Oak Ridge National Laboratory Distributed Active Archive Center, Tennessee, USA, in which the AGB was collected within a 1.0 m × 0.25 m quadrat and the BGB was sampled within the center of the quadrat. Using multiple pairwise tests and Pearson’s correlation analysis, we assessed the variations of grassland productivity and examined the response of single-harvest and annual biomass partitioning of C3- and C4-dominated grasslands to the growing-season and annual climatic variability and climate extremes in seven sites belonging to four ecoregions (i.e. cold steppe, humid temperate, humid savanna, and savanna). The results show that the annual and single-harvest BGB:AGB ratio varied significantly across the plant types and ecoregions. Overall, the C3-dominated grasslands exhibited a higher BGB:AGB ratio than that of C4-dominated grasslands. Growing-season temperatures (GSTs) were found to be the key determinants in explaining the single-harvest BGB:AGB ratio rather than growing-season precipitation. For instance, the single-harvest BGB:AGB ratio of C4-dominated grasslands increased, while that of C3-dominated grasslands decreased with elevated GSTs. The growing-season extreme dry climates significantly increased the single-harvest BGB:AGB ratio of C4 plants by a large reduction of AGB, potentially affecting the ecosystem functioning and stability. The C3-dominated grasslands in the cold steppe ecoregion are at great threat of drought-induced stress, as we observed that growing-season extreme dry climates reduced, albeit insignificantly, both the single-harvest AGB and BGB. This study provides key insights into factors influencing the biomass partitioning of C3- and C4-dominated grasslands and has important implications for assessing the grassland functioning and stability under increasing climate extremes.

The Vulcan Version 3.0 High-Resolution Fossil Fuel CO2 Emissions for the United States.

Estimates of high‐resolution greenhouse gas (GHG) emissions have become a critical component of climate change research and an aid to decision makers considering GHG mitigation opportunities. The “Vulcan Project” is an effort to estimate bottom‐up carbon dioxide emissions from fossil fuel combustion and cement production (FFCO2) for the U.S. landscape at space and time scales that satisfy both scientific and policy needs. Here, we report on the Vulcan version 3.0 which quantifies emissions at a resolution of 1 km2/hr for the 2010–2015 time period. We estimate 2011 FFCO2 emissions of 1,589.9 TgC with a 95% confidence interval of 1,367/1,853 TgC (−14.0%/+16.6%), implying a one‐sigma uncertainty of ~ ±8%. Per capita emissions are larger in states dominated by electricity production and industrial activity and smaller where onroad and building emissions dominate. The U.S. FFCO2 emissions center of mass (CoM) is located in the state of Missouri with mean seasonality that moves on a near‐elliptical NE/SW path. Comparison to ODIAC, a global gridded FFCO2 emissions estimate, shows large total emissions differences (100.4 TgC for year 2011), a spatial correlation of 0.68 (R2), and a mean absolute relative difference at the 1 km2 scale of 104.3%. The Vulcan data product offers a high‐resolution estimate of FFCO2 emissions in every U.S. city, obviating costly development of self‐reported urban inventories. The Vulcan v3.0 annual gridded emissions data product can be downloaded from the Oak Ridge National Laboratory Distributed Active Archive Center (Gurney, Liang, et al., 2019, https://doi.org/10.3334/ORNLDAAC/1741).

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi‐objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides Microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimization (MOO) and decision analysis is put forward to address this model. First, a powerful heuristic optimization algorithm, called the {\theta}-dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. And thereby, the best compromise solutions (BCSs) are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Vista-LA: Mapping methane-emitting infrastructure in the Los Angeles megacity

Abstract. Methane (CH4) is a potent greenhouse gas (GHG) and a critical target of climate mitigation efforts. However, actionable emission reduction efforts are complicated by large uncertainties in the methane budget on relevant scales. Here, we present Vista, a Geographic Information System (GIS)-based approach to map potential methane emissions sources in the South Coast Air Basin (SoCAB) that encompasses Los Angeles, an area with a dense, complex mixture of methane sources. The goal of this work is to provide a database that, together with atmospheric observations, improves methane emissions estimates in urban areas with complex infrastructure. We aggregated methane source location information into three sectors (energy, agriculture, and waste) following the frameworks used by the State of California GHG Inventory and the Intergovernmental Panel on Climate Change (IPCC) Guidelines for GHG Reporting. Geospatial modeling was applied to publicly available datasets to precisely geolocate facilities and infrastructure comprising major anthropogenic methane source sectors. The final database, Vista-Los Angeles (Vista-LA), is presented as maps of infrastructure known or expected to emit CH4. Vista-LA contains over 33 000 features concentrated on < 1 % of land area in the region. Currently, Vista-LA is used as a planning and analysis tool for atmospheric measurement surveys of methane sources, particularly for airborne remote sensing, and methane hotspot detection using regional observations. This study represents a first step towards developing an accurate, spatially resolved methane flux estimate for point sources in SoCAB, with the potential to address discrepancies between bottom–up and top–down methane emissions accounting in this region. The Vista-LA datasets and associated metadata are available from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (ORNL DAAC; https://doi.org/10.3334/ORNLDAAC/1525).

Development of Landsat-based annual US forest disturbance history maps (1986–2010) in support of the North American Carbon Program (NACP)

In Phase III of the North American Forest Dynamics (NAFD) study an automatic workflow has been developed for evaluating forest disturbance history using Landsat observations. It has four major components: an automated approach for image selection and preprocessing, the vegetation change tracker (VCT) forest disturbance analysis, postprocessing, and validation. This approach has been applied to the conterminous US (CONUS) to produce a comprehensive analysis of US forest disturbance history using the NASA Earth Exchange (NEX) cloud computing system. The resultant NAFD-NEX product includes 25 annual forest disturbance maps for 1986–2010 and two time-integrated maps to provide spatial-temporal synoptic view of disturbances over this time period. These maps were derived based on 24,000+ scenes selected from 350,000+ available Landsat images at 30-m resolution, and were validated using a visual assessment of Landsat time-series images in combination with high-resolution and other ancillary data sources over samples selected using a probability based sampling method. The validation revealed no major biases in the NAFD-NEX maps for disturbance events that resulted in at least 20% canopy cover loss. The average user's and producer's accuracies for the disturbance class were 53.6% and 53.3%, respectively, with the individual year's user's accuracy varying from 42.8% to 73.6% and producer's accuracy from 39.0% to 84.8% over the 25-year period. The NAFD-NEX disturbance maps are available from a web portal of the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) at https://doi.org/10.3334/ORNLDAAC/1290.

Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe

Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwide, playing an important role in global carbon cycling. Therefore, studying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppe, an important part of global grasslands, is the largest and relatively well preserved grassland in the world. In this study, we analyzed the spatial pattern of aboveground biomass (AGB), and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources (literature, global NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL), some data provided by other researchers). Our results demonstrated that: (1) as for the Eurasian steppe overall, the spatial variation in AGB exhibited significant horizontal and vertical zonality. In detail, AGB showed an inverted parabola curve with the latitude and with the elevation, while a parabola curve with the longitude. In addition, the spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregion, while horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion. (2) Of the examined environmental variables, the spatial variation of AGB was related to mean annual precipitation (MAP), mean annual temperature (MAT), mean annual solar radiation (MAR), soil Gravel content, soil pH and soil organic content (SOC) at the depth of 0–30 cm. Nevertheless, MAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions. (3) A Gaussian function was found between AGB and MAP in the Eurasian steppe overall, which was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion (elevation < 3000 m), the Mongolian Plateau steppe subregion (elevation < 3000 m) and the surface (elevation ≥ 4800 m) of the Tibetan Plateau. Nevertheless, the spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins (elevation < 4800 m) of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grassland, the Tibetan Plateau alpine grassland, etc.

In situ air temperature and humidity measurements over diverse land covers in Greenbelt, Maryland, November 2013–November 2015

Abstract. As our climate changes through time there is an ever-increasing need to quantify how and where it is changing so that mitigation strategies can be implemented. Urban areas have a disproportionate amount of warming due, in part, to the conductive properties of concrete and asphalt surfaces, surface albedo, heat capacity, lack of water, etc. that make up an urban environment. The NASA Climate Adaptation Science Investigation working group at Goddard Space Flight Center in Greenbelt, MD, conducted a study to collect temperature and humidity data at 15 min intervals from 12 sites at the center. These sites represent the major surface types at the center: asphalt, building roof, grass field, forest, and rain garden. The data show a strong distinction in the thermal properties of these surfaces at the center and the difference between the average values for the center compared to a local meteorological station. The data have been submitted to Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) for archival in comma separated value (csv) file format (Carroll et al., 2016) and can be found by following this link: http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1319.

A Semi-Automated Workflow Solution for Data Set Publication

To address the need for published data, considerable effort has gone into formalizing the process of data publication. From funding agencies to publishers, data publication has rapidly become a requirement. Digital Object Identifiers (DOI) and data citations have enhanced the integration and availability of data. The challenge facing data publishers now is to deal with the increased number of publishable data products and most importantly the difficulties of publishing diverse data products into an online archive. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-funded data center, faces these challenges as it deals with data products created by individual investigators. This paper summarizes the challenges of curating data and provides a summary of a workflow solution that ORNL DAAC researcher and technical staffs have created to deal with publication of the diverse data products. The workflow solution presented here is generic and can be applied to data from any scientific domain and data located at any data center.

Implementation of data citations and persistent identifiers at the ORNL DAAC

A requirement of data archives is that data holdings can be easily discovered, accessed, and used. One approach to improving data discovery and access is through data citations coupled with Digital Object Identifiers (DOI). The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) since 1998 has issued data citations that have been accepted and used in peer-reviewed journals. Citation elements established by the ORNL DAAC are similar to those used for journal articles (authors, year, product title, and information to locate), and beginning in 2007 included a DOI that is persistent, actionable, specific, and complete. The approach used at the ORNL DAAC also allows for referring to subsets of the data, by including within the citation the temporal and spatial extent, and parameters used. Data citations allow readers to find data and reproduce the results of the research article, and also use those data to test new hypotheses, design new sample collections, or construct or evaluate models. The ORNL DAAC uses a manual method to compile data citations and has developed a database that links research articles and their use of specific ORNL DAAC data products. Automation of the data citation compilation process, as is the case for articles, will enable data citations to become a more common practice. In addition to enhancing discovery and access of the data used in a research article, the citation gives credit to data generators, data centers and their funders, and, through citation indices, determine the scientific impact of a data set.

The North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project – Part 2: Environmental driver data

Abstract. Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model–model and model–observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.

Empirical Orthogonal Function analysis of the palmer drought indices

The aim of the paper is to employ Empirical Orthogonal Function (EOF) analysis to drought indices including Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Palmer Moisture Anomaly (Z) Index (Z-Index), Weighted Palmer Drought Severity Index (WPDSI), and Water Deficit ( P– PET) Index and to compare their resultant spatial patterns across Turkey. In this respect, the PDSI, PHDI, Z, WPDSI, Aridity Index ( AI) and P– PET Index values are calculated based on observed monthly temperature and precipitation values of the 96 Turkish meteorological stations for the 1929–2009 period, and gridded available water holding capacities (AWHC) in 1-m soil depth are extracted from the soil data sets of the Oak Ridge National Laboratory Distributed Active Archive Centre (ORNL DAAC). By considering the strong match among the PDSI, PHDI, and WPDSI based on the results of the patterns of the first EOFs (EOF1) with the highest eigenvalue, we suggest that using and applying one of these drought indices could be adequate for a drought analysis in Turkey. On the other hand, it is evident that the significant results from the EOF2, EOF3 and EOF4 loadings of the PHDI and WPDSI indices have a similar pattern across Turkey. Therefore, with respect to the geographical autocorrelation and magnitudes of the loading values, it is explained that the PDSI and WPDSI in particular could have originated from the same physical process, and one may have a preference for the effective usage of a combination of PDSI, PHDI and Z-Index. Consequently, in a multi-purpose medium- and long-term drought management plan for Turkey or in any country having similar climatic and physical geographical conditions, using one of the three drought indices along with the Z-Index could be acceptable for successful applications.

Remote sensing of suspended sediment concentration, flow velocity, and lake recharge in the Peace‐Athabasca Delta, Canada

The transport of fine sediment, carried in suspension by water, is central to the hydrology, geomorphology, and ecological functioning of river floodplains and deltas. An extensive new field data set for the Peace‐Athabasca Delta (PAD), Canada quantifies robust positive relationships between in situ suspended sediment concentration (SSC) and remotely sensed visible/near‐infrared reflectance. These relationships are exploited using SPOT and ASTER satellite images to map suspended sediment concentrations across the PAD for four days in 2006 and 2007, revealing strong variations in water sources and flow patterns, including flow reversals in major distributaries. Near‐daily monitoring with 276 MODIS satellite images tracks hydrologic recharge of floodplain lakes, as revealed by episodic infusions of sediment‐rich water from the Athabasca River. The timing and magnitude of lake recharge are linked to springtime water level on the Athabasca River, suggesting a system sensitive to changes in river flow regime. Moreover, recharge timing differentiates lakes that are frequently and extensively recharged from those recharged more rarely. Finally, we present a first estimation of river flow velocity based on remotely sensed SSC, though saturation may occur at velocities &gt;0.6 m/s. Viewed collectively, the different remote sensing methodologies presented here suggest strong value for visible/near‐infrared remote sensing of suspended sediment to assess hydrologic and sediment transport processes in complex flow environments. Field observations including nephelometric turbidity, specific conductivity, water temperature, Secchi disk depth, suspended sediment concentration, and water level are archived at the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (available at http://daac.ornl.gov//HYDROCLIMATOLOGY/guides/PAD.html).

Terrestrial net primary productivity – A brief history and a new worldwide database

Consistent data on terrestrial net primary productivity (NPP) are urgently needed to constrain model estimates of carbon fluxes and hence to refine our understanding of ecosystem responses to climate change. The NPP data have been collected in a coordinated manner for the past 30 years, but comprehensive summaries are rare. We report on the development and availability of a global NPP database that is suitable for modeling of the terrestrial carbon cycle at global and regional scales, for validation of remote sensing data, and for other applications. These data were obtained from the literature on ecophysiological field work and from detailed consultation with the scientific community. Data on NPP, biomass, and associated environmental variables are now publicly available for 53 detailed study sites, of which more than half have data for belowground biomass or biomass dynamics. Aboveground NPP ranges from 35 to 2320 g m–2a–1 (dry matter) and total NPP from 182 to 3538 g m–2a–1. Well-known but previously unobtainable compilations of data, such as the "Osnabrück Data Set" and the International Biological Program (IBP) Woodlands Data Set, are also incorporated in this database. Preliminary exploration of relationships between NPP and mean annual precipitation and temperature suggests that the new 53-site data collection, as well as the Osnabrück and IBP data, are all consistent with the historic "Miami" statistical model. These data are available from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics (see http://www.daac.ornl.gov/NPP/).Key words: net primary productivity, grasslands, forests, biogeochemical dynamics, global carbon cycle, model validation.

OSNABRÜCK NET PRIMARY PRODUCTIVITY DATA SET

An extensive compilation of nearly 700 field estimates of net primary productivity of natural and agricultural ecosystems worldwide was synthesized in Germany in the 1970s and early 1980s. The literature cited dates from 1869 to 1982, with the majority of references from the 1960s and 1970s. Although the Osnabruck data set has not been updated since the 1980s, it represents a wealth of information for use in model development and validation. This data paper documents the development of this data set, its contents, and its recent availability on the Internet, both in Ecological Archives on the Ecological Society of America's web site, and in a “mirror” copy at the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. The version presented here (version 2.0) incorporates amendments suggested by data users over the past two years. Caution is advised in using these data, which necessarily include assumptions that may not be universally applicable to all study sites and records. Nevertheless, we consider these “Class III” data to be useful, even though they may not meet the “Gold Standards” which are being developed for this type of data (mainly because the documentation may be incomplete, not because the numbers themselves are of poor quality).