@Article{Alexandrov_EMS_20110301, author = {G. A. Alexandrov and D. Ames and G. Bellocchi and M. Bruen and N. Crout and M. Erechtchoukova and A. Hildebrandt and F. Hoffman and C. Jackisch and P. Khaiter and G. Mannina and T. Matsunaga and S. T. Purucker and M. Rivington and L. Samaniego}, title = {Technical Assessment and Evaluation of Environmental Models and Software: Letter to the Editor}, journal = EMS, volume = 26, number = 3, note = {Thematic issue on the assessment and evaluation of environmental models and software}, pages = {328--336}, doi = {10.1016/j.envsoft.2010.08.004}, day = 1, month = mar, year = 2011, abstract = {This letter details the collective views of a number of independent researchers on the technical assessment and evaluation of environmental models and software. The purpose is to stimulate debate and initiate action that leads to an improved quality of model development and evaluation, so increasing the capacity for models to have positive outcomes from their use. As such, we emphasize the relationship between the model evaluation process and credibility with stakeholders (including funding agencies) with a view to ensure continued support for modelling efforts. Many journals, including EM\&S, publish the results of environmental modelling studies and must judge the work and the submitted papers based solely on the material that the authors have chosen to present and on how they present it. There is considerable variation in how this is done with the consequent risk of considerable variation in the quality and usefulness of the resulting publication. Part of the problem is that the review process is reactive, responding to the submitted manuscript. In this letter, we attempt to be proactive and give guidelines for researchers, authors and reviewers as to what constitutes best practice in presenting environmental modelling results. This is a unique contribution to the organisation and practice of model-based research and the communication of its results that will benefit the entire environmental modelling community. For a start, our view is that the community of environmental modellers should have a common vision of minimum standards that an environmental model must meet. A common vision of what a good model should be is expressed in various guidelines on Good Modelling Practice. The guidelines prompt modellers to codify their practice and to be more rigorous in their model testing. Our statement within this letter deals with another aspect of the issue---it prompts professional journals to codify the peer-review process. Introducing a more formalized approach to peer-review may discourage reviewers from accepting invitations to review given the additional time and labour requirements. The burden of proving model credibility is thus shifted to the authors. Here we discuss how to reduce this burden by selecting realistic evaluation criteria and conclude by advocating the use of standardized evaluation tools as this is a key issue that needs to be tackled.} } @Misc{Allen_AGU_20101216, author = {M. R. Allen and D. J. Erickson and R. J. Andres and F. M. Hoffman and M. L. Branstetter}, title = {Monthly Anthropogenic {CO$_2$} Fluxes: Impacts on the Atmospheric {CO$_2$} Seasonal Cycle and Implications for Models of the Terrestrial Biosphere}, howpublished = {Abstract B41G-0391 presented at 2010 Fall Meeting, American Geophysical Union (AGU), San Francisco, California, USA}, day = 16, month = dec, year = 2010 } @InProceedings{Baker:US-IALE:2006, author = {Barry Baker and William W. Hargrove and Forrest M. Hoffman and Mike Heiner}, title = {Use of Multivariate Cluster and Climate Classification Techniques to Characterize Future Climate Scenarios in {P}eoples {R}epublic of {C}hina}, booktitle = {Proceedings of the 21st Annual Symposium of the International Association for Landscape Ecology, United States Regional Association (US-IALE)}, address = {San Diego, California, USA}, day = 31, month = mar, year = 2006 } @Article{Baker_ClimChange_20100101, author = {Barry Baker and Henry Diaz and William Hargrove and Forrest Hoffman}, title = {Use of the {K}\"oppen-{T}rewartha Climate Classification to Evaluate Climatic Refugia in Statistically Derived Ecoregions for the {P}eople's {R}epublic of {C}hina}, journal = ClimChange, volume = 98, number = 1, pages = {113--131}, doi = {10.1007/s10584-009-9622-2}, issn = {0165-0009}, day = 1, month = jan, year = 2010, abstract = {Changes in climate as projected by state-of-the-art climate models are likely to result in novel combinations of climate and topo-edaphic factors that will have substantial impacts on the distribution and persistence of natural vegetation and animal species. We have used multivariate techniques to quantify some of these changes; the method employed was the Multivariate Spatio-Temporal Clustering (MSTC) algorithm. We used the MSTC to quantitatively define ecoregions for the People's Republic of China for historical and projected future climates. Using the K\"oppen-Trewartha classification system we were able to quantify some of the temperature and precipitation relationships of the ecoregions. We then tested the hypothesis that impacts to environments will be lower for ecoregions that retain their approximate geographic locations. Our results showed that climate in 2050, as projected from anthropogenic forcings using the Hadley Centre HadCM3 general circulation model, were sufficient to create novel environmental conditions even where ecoregions remained spatially stable; cluster number was found to be of paramount importance in detecting novelty. Continental-scale analyses are generally able to locate potentially static ecoregions but they may be insufficient to define the position of those reserves at a grid cell-by-grid cell basis.} } @TechReport{Barnes_ORNL-TM-13139_19951101, author = {K. D. Barnes and J. M. Donato and D. M. Flanagan and N. W. Grady and J. A. Green and F. M. Hoffman and J. A. Kohl and M. R. Leuze and P. M. Papadopoulos and R. F. Sincovec}, title = {The {F}inancial Automated {M}anagement {O}n-line {U}ser {S}ystem ({F}a{MOUS}): A Prototype Interactive Hypertext-based Financial Planning and Reporting System}, type = {Technical Memorandum}, number = {ORNL/TM-13139}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, day = 1, month = nov, year = 1995, abstract = {It is critical in every government, research, and industrial organization that accurate and timely financial information be made available at all levels so that project and business decisions can be made within funding constraints. The FaMOUS prototype implemented at Oak Ridge National Laboratory extracts financial data from a legacy system, builds easy-to-understand reports and graphs, and presents them on-line so that people at all levels in an organization can assess the financial status of individual projects or entire organizations. Reports are presented in hypertext and graphical formats that can be read with popular World Wide Web browsers such as NCSA Mosaic or Netscape. All reports are hyper-linked in a natural way to simplify navigation and inormation retrieval. To protect potentially sensitive information, FaMOUS provides access control so that individuals can retrieve only the information that is required for them to carry out their financial duties. In addtiion to the reports and graphs, FaMOUS includes budget buidling tools to provide for financial planning. Another primary feature is that the prototype utilizes equipment that already exists on the user's desktop. The overall goal of the FaMOUS system is to provide users with precise and meaningful information on the financial status of an organization or project at a glance.} } @Article{Brooks_AGU_20091218, author = {Bj{\o}rn J. Brooks and Forrest M. Hoffman and Richard T. Mills and David J. Erickson and T. J. Blasing}, title = {The Effect of Anthropogenic Emissions Corrections on the Seasonal Cycle of Atmospheric {CO}$_2$}, journal = Eos, volume = 90, number = 52, note = {Fall Meet. Suppl., Abstract A51A-0108}, day = 18, month = dec, year = 2009 } @InProceedings{Carr_CUG_20050516, author = {George R. Carr and Matthew J. Cordery and John B. Drake and Michael W. Ham and Forrest M. Hoffman and Patrick H. Worley}, title = {Porting and Performance of the {C}ommunity {C}limate {S}ystem {M}odel ({CCSM3}) on the {C}ray {X1}}, booktitle = {Proceedings of the 2005 {C}ray {U}sers {G}roup ({CUG}) Conference}, dates = {16--19 May 2005}, location = {Albuquerque, New Mexico, USA}, day = 16, month = may, year = 2005, abstract = {The Community Climate System Model (CCSM3) is the primary model for global climate research in the United States and is supported on a variety of computer systems. We present some of our porting experiences and describe the current performance of the CCSM3 on the Cray X1. We include the status of work in progress on other systems in the Cray product line.} } @Article{Dickinson_JClim_20060601, author = {Robert E. Dickinson and Keith W. Oleson and Gordon Bonan and Forrest Hoffman and Peter Thornton and Mariana Vertenstein and Zong-Liang Yang and Xubin Zeng}, title = {The {C}ommunity {L}and {M}odel and Its Climate Statistics as a Component of the {C}ommunity {C}limate {S}ystem {M}odel}, journal = JClim, volume = 19, number = 11, pages = {2302--2324}, doi = {10.1175/JCLI3742.1}, day = 1, month = jun, year = 2006, abstract = {Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on the simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.} } @TechReport{Ehlschlaeger_ERDC-CERL-TR-06-36_20061201, author = {Charles Ehlschlaeger and James Westervelt and Harold Balbach and H. Resit Akcakaya and Tom Hoctor and Crystal Goodison and William W. Hargrove and Forrest M. Hoffman and Winifred Rose and Robert C. Lozar}, institution = {U.S. Army Corps of Engineers, Engineer Research and Development Center}, title = {Habitat Fragmentation Handbook for Installation Planners}, editor = {Robert C. Lozar}, type = {Technical Report}, number = {ERDC/CERL TR-06-36}, day = 1, month = dec, year = 2006, abstract = {The primary objective of this work is to provide military installation planners with a sourcebook on the state of the art in how to analyze the probability and risks of habitat fragmentation for animal Threatened and Endangered Species (TES). The document provides a review of habitat fragmentation issues, focusing on those of highest concern to Army Military Installation Land Managers. It has been designed to capture information developed during the 4-year ERDC research project called: Quantify Effects of Fragmentation and Approaches to Mitigate. Major components include: \begin{itemize} \item TES habitat background survey \item Army TES Life histories and potential supporting data types \item Description of major Fragmentation initiatives \item Survey of the major Fragmentation modeling techniques \item Evaluation of Data Quality \item Potential inputs for a long term TES monitoring capability \item Recommendations for future directions. \end{itemize} } } @InProceedings{Erickson:iEMSs:2006, author = {David Erickson and Robert Oglesby and Scott Elliott and Forrest Hoffman}, title = {Peta-scale Climate Modeling: Biogeochemical and Financial Feedbacks}, booktitle = {Proceedings of the {iEMSs} {T}hird {B}iennial {M}eeting: {I}nternational {C}ongress on {E}nvironmental {M}odelling and {S}oftware {S}ociety ({iEMSs} 2006), Summit on Environmental Modelling and Software}, address = {Burlington, Vermont, USA}, day = {9--13}, month = jul, year = 2006 } @Article{Erickson:AGU:2006, author = {David J. Erickson and T. J. Blasing and Forrest M. Hoffman and Richard T. Mills and Z. Zhu and Stephan R. Kawa}, title = {Monthly Global Emissions of Anthropogenic {CO}$_2$: Atmospheric {CO}$_2$ Transport Calculations Based on {NASA} Data Assimilation}, journal = Eos, volume = 87, number = 52, note = {Fall Meet. Suppl., Abstract A41C-0044}, month = dec, year = 2006 } @Article{Erickson_JGR_20080315, author = {David J. {Erickson III} and Richard T. Mills and Jay Gregg and T. J. Blasing and Forrest M. Hoffman and Robert J. Andres and Matthew Devries and Z. Zhu and S. R. Kawa}, title = {An Estimate of Monthly Global Emissions of Anthropogenic {CO$_2$}: Impact on the Seasonal Cycle of Atmospheric {CO$_2$}}, journal = JGR, volume = 113, number = {G1}, pages = {G01023}, doi = {10.1029/2007JG000435}, day = 15, month = mar, year = 2008, abstract = {Monthly estimates of the global emissions of anthropogenic CO$_2$ are presented. Approximating the seasonal CO$_2$ emission cycle using a 2-harmonic Fourier series with coefficients as a function of latitude, the annual fluxes are decomposed into monthly flux estimates based on data for the United States and applied globally. These monthly anthropogenic CO$_2$ flux estimates are then used to model atmospheric CO$_2$ concentrations using meteorological fields from the NASA GEOS-4 data assimilation system. We find that the use of monthly resolved fluxes makes a significant difference in the seasonal cycle of atmospheric CO$_2$ in and near those regions where anthropogenic CO$_2$ is released to the atmosphere. Local variations of 2--6~ppmv CO$_2$ in the seasonal cycle amplitude are simulated; larger variations would be expected if smaller source-receptor distances could be more precisely specified using a more refined spatial resolution. We also find that in the midlatitudes near the sources, synoptic scale atmospheric circulations are important in the winter and that boundary layer venting and diurnal rectifier effects are more important in the summer. These findings have implications for inverse-modeling efforts that attempt to estimate surface source/sink regions especially when the surface sinks are colocated with regions of strong anthropogenic CO$_2$ emissions.} } @Article{Erickson:AGU:2008, author = {David J. Erickson and Auroop Ganguly and Karsten Steinhaeuser and Marcia Branstetter and Robert J. Oglesby and Forrest M. Hoffman and Lawrence Buja}, title = {Extreme Climate Event Trends: The Data Mining and Evaluation of the {A1FI} Scenario for 2000--2100}, journal = Eos, volume = 89, number = 53, note = {Fall Meet. Suppl., Abstract H12B-03, Invited}, month = dec, year = 2008 } @Article{Erickson_AGU_20091218, author = {David J. Erickson and Steven Pawson and Jamison Daniel and Melissa Allen and L. E. Ott and Auroop Ganguly and E. Nielsen and Forrest M. Hoffman}, title = {Atmospheric {CO}$_2$ Simulation inside {GEOS}-5: Data Mining, Evaluation and Treaty Verification}, journal = Eos, volume = 90, number = 52, note = {Fall Meet. Suppl., Abstract A51A-0078}, day = 18, month = dec, year = 2009 } @InProceedings{Gwo_HPC2000_20000416, author = {Jin-Ping Gwo and Forrest M. Hoffman and William W. Hargrove}, title = {Mechanistic-Based Genetic Algorithm Search on a {B}eowulf Cluster of {L}inux {PC}s}, booktitle = {Proceedings of the High Performance Computing 2000 ({HPC}2000) Conference}, dates = {16--20 April 2000}, location = {Washington, DC}, day = 16, month = apr, year = 2000, abstract = {A simple genetic algorithm (SGA) was implemented on a cluster of Linux PCs to search for the most likely fracture networks in a soil column. The objective is to evaluate the performance of SGAs in a distributed computing environment that is widely and inexpensively available to environmental researchers and engineers. The Beowulf computer was built out of surplus personal computers at Oak Ridge National Laboratory by scientists in the Environmental Sciences Division (http://www.esd.ornl.gov). The communication on the Beowulf is via ordinary Ethernet connection private among the processors, with a peak bandwidth of 10 Mbit/s. The CPUs are mostly Intel 486DX-2/66 and Pentiums, with 16--32 MB of memory. Most of the software on the Beowulf is from the public domain. Using the PVM message passing library and a manager-worker paradigm, we seek to maximize the loads on CPUs of dissimilar speed and memory size. SGA is an inductive search algorithm that bases upon a few simple operators such as reproduction, crossover, and mutation. The underlying mechanisms of flow and transport phenomena in structured soils with discrete fractures are simulated by the computer code FRACTRAN. In a generation of SGA, hundreds of FRACTRAN simulations are required, which consume the majority of the CPU time needed by the SGA search process. For an entire SGA search, tens of millions of such simulations, often referred to as function evaluation in genetic algorithms literature, are performed. The minimal communication between the manager and workers, passing fracture networks represented in bit strings to the workers and bit string fitness back to the manager, suggests that small communication bandwidth is adequate to achieve high performance. The manager-worker paradigm is also highly effective in achieving load balance on heterogeneous, networked computers such as the Beowulf. In addition to reporting the performance of the implementation, we also explore the aspect of SGA related to information constraints. SGA may be trapped in local optima and genetic drifting may ensue. With additional information the SGA may be steered away from local optima and the uncertainty of the identified fracture networks may be reduced. Because multiple runs of the SGA search algorithm are necessary to determine the least uncertain fracture networks, a distributed computing environment proves to be highly effective.} } @Article{Gwo_ComputGeosci_20011201, author = {Jin-Ping Gwo and Eduardo F. D'Azevedo and Hartmut Frenzel and Melaine Mayes and Gour-Tsyh Yeh and Philip M. Jardine and Karen M. Salvage and Forrest M. Hoffman}, title = {{HBGC123D}: A High Performance Computer Model of Coupled Hydrogeological and Biogeochemical Processes}, journal = ComputGeosci, volume = 27, number = 10, pages = {1231--1242}, doi = {10.1016/S0098-3004(01)00027-9}, day = 1, month = dec, year = 2001, abstract = {Groundwater flow and transport models have been used to assist management of subsurface water resources and water quality. The needs of more efficient use of technical and financial resources have recently motivated the development of more effective remediation techniques and complex models of coupled hydrogeological and biogeochemical processes. We present a high-performance computer model of the coupled processes, HBGC123D. The model uses a hybrid Eulerian-Lagrangian finite element method to solve the solute transport equation and a Newton's method to solve the system of nonlinear, mixed kinetics and equilibrium reaction equations. Application of the model to a laboratory soil column with multispecies tracer injection suggests that one may use the model to derive important parameters of subsurface solute fate and transport. These parameters may be used for predictive purpose in similar field problems. To this end, we present a three-dimensional, hypothetical bioremediation simulation on an aquifer contaminated by CoNTA. The simulation suggests that, using oxygen alone to stimulate the biodegradation of the contaminant, one may reduce the waste to 40\% in 10 years. Using a refined mesh of this three-dimensional model, we also conduct a performance study of HBGC123D on an array of SGI Origin 2000 distributed shared-memory processors. Both the computational kernels and the entire model show very good performance up to 32 processors. The CPU time is essentially reduced by 20-fold using 64 processors. This result suggests that HBGC123D may be a useful tool in assisting environmental restoration efforts such as waste site characterization and remediation.} } @InProceedings{Hargrove_GIS95_19950328, author = {William W. Hargrove and Forrest M. Hoffman and Daniel A. Levine}, title = {Interpolation of Bottom Bathymetry and Potential Erosion in a Large {T}ennessee Reservoir System Using {GRASS}}, booktitle = {Proceedings of the Ninth Annual Symposium on Geographic Information Systems}, dates = {28 March--2 April 1995}, location = {Vancouver, British Columbia, Canada}, pages = {552--557}, day = 28, month = mar, year = 1995 } @Article{Hargrove_ComputSciEng_19990701, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Using Multivariate Clustering to Characterize Ecoregion Borders}, journal = ComputSciEng, volume = 1, number = 4, pages = {18--25}, doi = {10.1109/5992.774837}, day = 1, month = jul, year = 1999, abstract = {The authors present a geographic clustering technique which unambiguously locates, characterizes, and visualizes ecoregions and their borders. When coded with similarity colors, it can produce planar map views with sharpness contours that are visually rich in ecological information and represent integrated visualizations of complex and massive environmental data sets.} } @InProceedings{Hargrove_GIS-EM4_20000902, author = {William W. Hargrove and Forrest M. Hoffman}, title = {An Analytical Assessment Tool for Predicting Changes in a Species Distribution Map Following Changes in Environmental Conditions}, booktitle = {Proceedings of the Fourth International Conference on Integrating GIS and Environmental Modeling ({GIS}/{EM}4): Problems, Prospects and Research Needs}, editor = {B. O. Parks and K. M. Clarke and M. P. Crane}, publisher = {University of Colorado, Cooperative Institute for Research in Environmental Sciences (CIRES)}, address = {Boulder, Colorado}, dates = {2--8 September 2000}, location = {The Banff Centre, Banff, (AB) Canada}, ISBN = {0-9743307-0-1}, url = {http://www.colorado.edu/research/cires/banff/pubpapers/104/}, day = 2, month = sep, year = 2000, abstract = {We have developed a GIS-based statistical technique which empirically predicts changes in the spatial distribution of habitat for a plant or animal species over a geographic area that has undergone a scenario of change in specified environmental conditions. The technique is illustrated with \textit{Pinus taeda} L., loblolly pine, and \textit{Acer saccharum} Marsh., sugar maple, under two future climate change scenarios for the continental U.S. We use a new Multivariate Spatio-Temporal Clustering (MSTC) approach that we developed for application on raster data within a GIS. MSTC employs non-hierarchical clustering on the individual pixels in a digital map from a GIS for the purpose of classifying the cells into types or categories. Our technique uses the standardized values of each environmental condition (e.g., temperature, rainfall, soil) for every raster cell in the map as a set of coordinates that together specify a position for that raster cell in a data space having a dimension for each of the included environmental characteristics. Two raster cells from anywhere in the map that have similar combinations of environmental characteristics will be located near each other in this data space. Their proximity and relative positions in data space will quantitatively reflect their environmental similarities, allowing these cells to be classified into environmentally similar groups. MSTC combines aspects of traditional GIS and statistical clustering techniques. Using the classification abilities of MSTC, we compared and grouped map cells by selected environmental conditions found within the present continental U.S. with conditions predicted to occur here according to two alternative future climate scenarios. Environments were specified in terms of 25 condition characteristics. We obtained high-resolution simulation forecasts for conditions within the continental U.S. in the year 2099 according to two global climate simulation models that are recognized by the U.S. National Assessment: the Canadian Climate Centre model, and the Hadley UKMO model. The VEMAP program has made yearly data sets for these models available for the period between 1994 and 2099 at 0.5 degree resolution for the continental United States. From these models, we obtained the simulated forecasts for monthly minimum and maximum temperature, monthly solar irradiance, and monthly precipitation. We calculated differences between present and future conditions predicted in the year 2099 by each of the two models. Difference layers were applied to our high resolution maps of current conditions within the United States in order to obtain predicted conditions. Thus, sixteen of the 25 environmental conditions were altered to represent the conditions forecast to occur within the continental U.S. in the year 2099 by each model. A variant of the MSTC procedure can be used to generate a model of the environmental envelope or niche of a particular species. We use the current distribution of \textit{Pinus} and \textit{Acer} to define their respective niches, then alter the map, and use the niche definition to classify map pixels and delineate the new distribution of habitat suitable for these tree species within the map. This technique is significant for assessing predicted effects of changes in environmental conditions (i.e., global warming) on the potential distribution of suitable habitat for both plants and animals. Making a special prediction of the current geographic range of a species allows us to test the robustness and adequacy of the niche model. Conditions present within the current U.S. are used to predict a current geographic range for the species, which can be compared with the known actual geographic distribution. When the fitness prediction obtained for each species when the current conditions within the United States are tested against the hypervolume definitions, the predicted distributions strongly resemble the known current distributions for both of these tree species. The niche model-based geographic predictions are somewhat more extensive in terms of the outer, low-fitness peripheral areas, but still strongly resemble the original geographic ranges which were used as input to the model development process. Predictions for a simple uniform climate warming scenario are surprising. Habitat distributions for the tested tree species generally dissapate and evaporate, without visible northward migration. We speculate that environmental conditions in many cells of the new maps may represent new combinations never seen in the present U.S. The performance of species cannot be predicted inside such cells, since the cells have left the inference space of the training data set. Methods for identifying such unpredictable cells, and speculation about their abundance and distribution are discussed.} } @Article{Hargrove_SciAm_20010801, author = {William W. Hargrove and Forrest M. Hoffman and Thomas Sterling}, title = {The Do-It-Yourself Supercomputer}, journal = SciAm, volume = 265, number = 2, pages = {72--79}, url = {http://www.sciam.com/article.cfm?articleID=000E238B-33EC-1C6F-84A9809EC588EF21}, day = 1, month = aug, year = 2001, abstract = {Scientists have found a cheaper way to solve tremendously difficult computational problems: connect ordinary PCs so that they can work together.} } @Article{Hargrove_ConservEcol_20020213, author = {William W. Hargrove and Forrest M. Hoffman and Paul M. Schwartz}, title = {A Fractal Landscape Realizer for Generating Synthetic Maps}, journal = ConservEcol, volume = 6, number = 1, pages = 2, url = {http://www.consecol.org/vol6/iss1/art2/}, note = {Part of Special Feature on Ralf Yorque Memorial Competition 2001}, day = 13, month = feb, year = 2002, abstract = {A fractal landscape realizer has been developed that generates synthetic landscape maps to user specifications. The alternative landscape realizations are not identical to the actual maps after which they are patterned, but are similar statistically (i.e., the areas and fractal character of each category are replicated). A fractal or self-affine pattern generator is used to provide a spatial probability surface for each category in the synthetic map. The Fractal Realizer arbitrates contentions among categories in a way that makes it possible to preserve the fractal patterns of all the categories in the resulting synthetic landscape. Each synthetic landscape is one equally likely realization from among an infinite ensemble of possible fractal landscape combinations. Synthetic landscapes produced by the Fractal Realizer have been tested using a variant of the Turing Test. More than 100 map experts were presented with a series of 20 selections of paired maps, and asked to distinguish the real map from the synthetic realization. The resulting population of scores was not significantly different from a random binomial, suggesting that the experts were unable to discern the synthetic maps from the actual ones. Statistical landscape indices computed for 25 different synthetic realizations are compared with the values computed for the actual maps. The Fractal Realizer can be used as a stochastic generator of synthetic input maps to a spatially explicit simulation model to test the effects of landscape rearrangement on the uncertainty of model parameter estimates. The sensitivity of stochastic spatial simulations to prescribed input landscapes can be evaluated by supplying them with a series of synthetic maps that obey particular statistical characteristics and by monitoring changes in selected output responses. Statistically similar input landscapes with different spatial arrangements can be generated and supplied to spatial models as a hedge against pseudoreplication.} } @Article{Hargrove_Eos_20031202, author = {William W. Hargrove and Forrest M. Hoffman and Beverly E. Law}, title = {New Analysis Reveals Representativeness of the {A}meri{F}lux {N}etwork}, journal = Eos, volume = 84, number = 48, pages = {529, 535}, doi = {10.1029/2003EO480001}, day = 2, month = dec, year = 2003 } @InProceedings{Hargrove:US-IALE:2004, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Developing a Practical Map-analysis Tool for Corridor Detection}, booktitle = {Proceedings of the 19th Annual Symposium of the International Association for Landscape Ecology, United States Regional Association (US-IALE)}, address = {Las Vegas, Nevada}, pages = {93--94}, month = mar, year = 2004 } @TechReport{Hargrove_ORNL-TM-2004-112_20040528, author = {William W. Hargrove and Forrest M. Hoffman}, title = {A Flux Atlas for Representativeness and Statistical Extrapolation of the {A}meri{F}lux Network}, type = {Technical Memorandum}, number = {ORNL/TM-2004/112}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, url = {http://www.geobabble.org/flux-ecoregions/}, day = 28, month = apr, year = 2004 } @Article{Hargrove_EnvironManage_20040401, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Potential of Multivariate Quantitative Methods for Delineation and Visualization of Ecoregions}, journal = EnvironManage, volume = 34, number = {Supplement 1}, pages = {S39--S60}, doi = {10.1007/s00267-003-1084-0}, day = 1, month = apr, year = 2004, abstract = {Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics, and solar inputs has been used at several specified levels of division to produce a spectrum of quantitative ecoregion maps for the conterminous United States. The coarse ecoregion divisions accurately capture intuitively-understood regional environmental differences, whereas the finer divisions highlight local condition gradients, ecotones, and clines. Such statistically generated ecoregions can be produced based on user-selected continuous variables, allowing customized regions to be delineated for any specific problem. By creating an objective ecoregion classification, the ecoregion concept is removed from the limitations of human subjectivity, making possible a new array of ecologically useful derivative products. A red-green-blue visualization based on principal components analysis of ecoregion centroids indicates with color the relative combination of environmental conditions found within each ecoregion. Multiple geographic areas can be classified into a single common set of quantitative ecoregions to provide a basis for comparison, or maps of a single area through time can be classified to portray climatic or environmental changes geographically in terms of current conditions. Quantified representativeness can characterize borders between ecoregions as gradual, sharp, or of changing character along their length. Similarity of any ecoregion to all other ecoregions can be quantified and displayed as a representativeness map. The representativeness of an existing spatial array of sample locations or study sites can be mapped relative to a set of quantitative ecoregions, suggesting locations for additional samples or sites. In addition, the shape of Hutchinsonian niches in environment space can be defined if a multivariate range map of species occurrence is available.} } @Article{Hargrove_LandscapeEcol_20050501, author = {William W. Hargrove and Forrest M. Hoffman and Rebecca A. Efroymson}, title = {A Practical Map-Analysis Tool for Detecting Potential Dispersal Corridors}, journal = LandscapeEcol, volume = 20, number = 4, pages = {361--373}, doi = {10.1007/s10980-004-3162-y}, day = 1, month = may, year = 2005, abstract = {We describe the Pathway Analysis Through Habitat (PATH) tool, which can predict the location of potential corridors of animal movement between patches of habitat within any map. The algorithm works by launching virtual entities that we call `walkers' from each patch of habitat in the map, simulating their travel as they journey through land cover types in the intervening matrix, and finally arrive at a different habitat `island.' Each walker is imbued with a set of user-specified habitat preferences that make its walking behavior resemble a particular animal species. Because the tool operates in parallel on a supercomputer, large numbers of walkers can be efficiently simulated. The importance of each habitat patch as a source or a sink for a species is calculated, consistent with existing concepts in the metapopulation literature. The manipulation of a series of contrived artificial landscapes demonstrates that the location of potential dispersal corridors and relative source and sink importance among patches can be purposefully altered in expected ways. Finally, potential dispersal corridors are predicted among remnant woodlots within three actual landscape maps.} } @Article{Hargrove:AGU-Ameriflux:2005, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Quantifying Representativeness Importance Values for {A}meri{F}lux Sites}, journal = Eos, volume = 86, number = 52, note = {Fall Meet. Suppl., Abstract B51C-0219}, month = dec, year = 2005 } @Article{Hargrove:AGU-NEON:2005, author = {William W. Hargrove and Forrest M. Hoffman and Bruce P. Hayden and Dean L. Urban and J. A. MacMahon and J. F. Franklin}, title = {Development of a Domain Map for Nodes of the {N}ational {E}cological {O}bservatory {N}etwork ({NEON})}, journal = Eos, volume = 86, number = 52, note = {Fall Meet. Suppl., Abstract H33H-02}, month = dec, year = 2005 } @InProceedings{Hargrove:iLEAPS:2006, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Quantifying Representativeness Importance Values for AmeriFlux Tower Locations}, booktitle = {Proceedings of the 1st Integrated Land Ecosystem-Atmsophere Processes Study (iLEAPS) Science Conference, Boulder, Colorado}, editor = {Anni Reissel and Asbj{\o}rn Aarflot}, series = {Report Series in Aerosol Science}, number = 79, address = {Helsinki, Finland}, note = {ISSN 0784-3496}, ISSN = {0784-3496}, ISBN = {952-5027-66-X}, pages = {252}, month = jan, year = 2006 } @InProceedings{Hargrove:US-IALE:2006, author = {William W. Hargrove and Bruce Hayden and Dean Urban and James MacMahon and Jerry Franklin and Forrest M. Hoffman}, title = {Development of a Domain Map for Nodes of the {N}ational {E}cological {O}bservatory {N}etwork ({NEON})}, booktitle = {Proceedings of the 21st Annual Symposium of the International Association for Landscape Ecology, United States Regional Association (US-IALE)}, address = {San Diego, California, USA}, day = 31, month = mar, year = 2006 } @Article{Hargrove_JGS_20060701, author = {William W. Hargrove and Forrest M. Hoffman and Paul F. Hessburg}, title = {Mapcurves: A Quantitative Method for Comparing Categorical Maps}, journal = JGS, volume = 8, number = 2, pages = {187--208}, doi = {10.1007/s10109-006-0025-x}, day = 1, month = jul, year = 2006, abstract = {We present Mapcurves, a quantitative goodness-of-fit (GOF) method that unambiguously shows the degree of spatial concordance between two or more categorical maps. Mapcurves graphically and quantitatively evaluate the degree of fit among any number of maps and quantify a GOF for each polygon, as well as the entire map. The Mapcurve method indicates a perfect fit even if all polygons in one map are comprised of unique sets of the polygons in another map, if the coincidence among map categories is absolute. It is not necessary to interpret (or even know) legend descriptors for the categories in the maps to be compared, since the degree of fit in the spatial overlay alone forms the basis for the comparison. This feature makes Mapcurves ideal for comparing maps derived from remotely sensed images. A translation table is provided for the categories in each map as an output. Since the comparison is category-based rather than cell-based, the GOF is resolution-independent. Mapcurves can be applied either to entire map categories or to individual raster patches or vector polygons. Mapcurves also have applications for quantifying the spatial uncertainty of particular map features.} } @Article{Hargrove:AGU:2006, author = {William W. Hargrove and Forrest M. Hoffman}, title = {Multivariate Geographic Clustering as a Basis for Ecoregionalization in the Environmental Sciences}, journal = Eos, volume = 87, number = 52, note = {Fall Meet. Suppl., Abstract IN41C-02, Invited}, month = dec, year = 2006 } @Article{Hargrove:AGU:2008, author = {William W. Hargrove and Joe Spruce and Gerry Gasser and Forrest M. Hoffman and Danny Lee}, title = {A New National {MODIS}-Derived Phenology Data Set Every 16 Days, 2002 through 2006}, journal = Eos, volume = 89, number = 53, note = {Fall Meet. Suppl., Abstract B51B-0373}, month = dec, year = 2008 } @Article{Hargrove_PERS_20091001, author = {William W. Hargrove and Joseph P. Spruce and Gerald E. Gasser and Forrest M. Hoffman}, title = {Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Phenology}, journal = PERS, volume = 75, number = 10, pages = {1150--1156}, day = 1, month = oct, year = 2009 } @Article{Hargrove_AGU_20091217, author = {William W. Hargrove and Joseph P. Spruce and Gerald E. Gasser and Forrest M. Hoffman}, title = {Toward A National Early Warning System for Forest Disturbances Using Remotely Sensed Land Surface Phenology}, journal = Eos, volume = 90, number = 52, note = {Fall Meet. Suppl., Abstract B42B-06}, day = 17, month = dec, year = 2009 } @InProceedings{Hessburg:US-IALE:2006, author = {Paul Hessburg and William W. Hargrove and Forrest M. Hoffman}, title = {A Quantitative Method for Comparing Categorical Maps}, booktitle = {Proceedings of the 21st Annual Symposium of the International Association for Landscape Ecology, United States Regional Association (US-IALE)}, address = {San Diego, California, USA}, day = 31, month = mar, year = 2006 } @TechReport{Hoffman_ORNL-TM-12190_19920901, author = {Forrest M. Hoffman}, title = {A {U}nix Print Filter for Controlling an {HP} {L}aserjet Printer}, type = {Technical Memorandum}, number = {ORNL/TM-12190}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, day = 1, month = sep, year = 1992, abstract = {This report describes a Unix print filter designed to control an Hewlett Packard Lasterjet or other printer that uses hewlett Packard's Printer Control Language (HP-PCL). The filter gives users the ability to control print pitch, orientation, and indentation by using standard flags to the Unix \texttt{lpr} command or multiple entries in the \texttt{/etc/printcap} file and allows both ascii and binary (i.e., graphics and downloadable fonts) files to be printed. Additionally, the filter provides some accounting capability. The supported print pitch and orientation options are described, as are the different configuration options. The code for the filter in included in Appendix A and sample entries for the \texttt{/etc/printcap} file are included in Appendix B and C.} } @Article{Hoffman_ComputGeosci_19930101, author = {Forrest M. Hoffman and Vijay S. Tripathi}, title = {A Geochemical Expert System Prototype Using Object-oriented Knowledge Representation and a Production Rule System}, journal = ComputGeosci, volume = 19, number = 1, pages = {53--60}, doi = {10.1016/0098-3004(93)90042-4}, day = 1, month = jan, year = 1993, abstract = {This paper presents the design and development of a Geochemical Expert System prototype (GES) for analyzing solution---mineral interactions in nature. The emphasis is placed on expert system design and knowledge representation. One of the most challenging and research-intensive steps was the identification of the key geochemical characteristics that would enable the expert system to identify salient features of any user-defined geochemical composition. Moreover, developing a system to create geochemical interpretations similar to those written by expert geochemists proved to be difficult. Important geochemical characteristics and their interrelationships which were ``discovered'' during knowledge acquisition and conceptualization are presented. These characteristics have been organized and documented within the expert system to emulate the skills of an expert geochemist. Examples of expert system-generated analyses are presented.} } @InProceedings{Hoffman:WATTec:1994, author = {Forrest M. Hoffman}, title = {How Do {I} Connect to the {I}nternet? Let Me Count the Ways}, booktitle = {Proceedings of WATTec '94}, address = {Knoxville, Tennessee}, month = feb, year = 1994 } @InProceedings{Hoffman:PCOC:1994, author = {Forrest M. Hoffman}, title = {Converting Hard Copy Document for Electronic Dissemination}, booktitle = {Proceedings of the 18th Annual Practical Conference on Communication ({PCOC})}, address = {Oak Ridge, Tennessee}, month = nov, year = 1994 } @InProceedings{Hoffman:WATTec:1995, author = {Forrest M. Hoffman}, title = {Deployment of {I}nternet Technologies at {O}ak {R}idge {N}ational {L}aboratory}, booktitle = {Proceedings of WATTec '95}, address = {Knoxville, Tennessee}, month = feb, year = 1995 } @Article{Hoffman:Troubleshooting:1998, author = {Forrest M. Hoffman and William W. Hargrove}, title = {Making Soup from Stones}, journal = {Troubleshooting Professional}, volume = 2, number = 5, month = may, year = 1998 } @InProceedings{Hoffman_PDPTA99_19990628, author = {Forrest M. Hoffman and William W. Hargrove}, title = {Multivariate Geographic Clustering Using a {B}eowulf-style Parallel Computer}, editor = {Hamid R. Arabnia}, booktitle = {Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications ({PDPTA} '99)}, volume = {III}, dates = {28 June--1 July 1999}, location = {Las Vegas, Nevada}, publisher = {CSREA Press}, pages = {1292--1298}, ISBN = {1-892512-11-4}, day = 28, month = jun, year = 1999, abstract = {The authors present an application of multivariate non-hierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity called ecoregions. Nine input variables thought to affect the growth of vegetation are clustered at a resolution of one square kilometer. These data represent over 7.8 million map cells in a 9-dimensional data space. For the analysis, the authors built a 126-node heterogeneous cluster--aptly named the Stone SouperComputer--out of surplus PCs. The authors developed a parallel iterative statistical clustering algorithm which uses the MPI message passing routines, employs a classical master/slave single program multiple data (SPMD) organization, performs dynamic load balancing, and provides fault tolerance. In addition to being run on the Stone SouperComputer, the parallel algorithm was tested on other parallel platforms without code modification. Finally, the results of the geographic clustering are presented.} } @Article{Hoffman_Crossroads_19990901, author = {Forrest M. Hoffman and William W. Hargrove}, title = {Parallel Computing with {L}inux}, journal = {Crossroads}, volume = 6, number = 1, pages = {23--27}, doi = {10.1145/331636.331643}, day = 1, month = sep, year = 1999 } @Article{Hoffman:OSDJ:2000, author = {Forrest M. Hoffman and William W. Hargrove}, title = {High Performance Computing: An Introduction to Parallel Programming With {B}eowulf}, journal = {Open Source Developers Journal}, volume = 1, number = 1, pages = {24--31}, year = 2000 } @Article{Hoffman:AGU:2002, author = {Forrest M. Hoffman and Robert J. Oglesby and William W. Hargrove and David J. Erickson}, title = {Using Clustering to Establish Climate Regimes from {PCM} Output}, journal = Eos, volume = 83, number = 47, note = {Fall Meet. Suppl., Abstract A61C-0090}, month = dec, year = 2002 } @InProceedings{Hoffman:AMS:2003, author = {Forrest M. Hoffman and William W. Hargrove and David J. Erickson and Robert J. Oglesby}, title = {Using Clustered Climate Regimes for Understanding Water Cycle Variability}, booktitle = {Proceedings of the American Meteorological Society 83rd Annual Meeting}, volume = {69}, address = {Long Beach, California}, note = {Abstract 9.4}, month = feb, year = 2003 } @InProceedings{Hoffman:ARM:2003, author = {Forrest M. Hoffman and William W. Hargrove and Anthony D. Del Genio}, title = {Multivariate Spatio-Temporal Clustering of Time-Series Data: An Approach for Diagnosing Cloud Properties and Understanding {ARM} Site Representativeness}, booktitle = {Proceedings of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program Science Team Meeting}, address = {Broomfield, Colorado}, note = {Extended Abstract}, month = apr, year = 2003 } @Article{Hoffman:AGU:2003, author = {Forrest M. Hoffman and William W. Hargrove and David J. Erickson and Robert J. Oglesby}, title = {A Novel Method for Analyzing and Interpreting {GCM} Results Using Clustered Climate Regimes}, journal = Eos, volume = 84, number = 46, note = {Fall Meet. Suppl., Abstract GC12A-0155}, month = dec, year = 2003 } @InProceedings{Hoffman_CUG_20040517, author = {Forrest M. Hoffman and Mariana Vertenstein and Hideyuki Kitabata and James B. White and Patrick Worley and John Drake and Matthew Cordery}, title = {Adventures in Vectorizing the {C}ommunity {L}and {M}odel}, booktitle = {Proceedings of the 2004 {C}ray {U}sers {G}roup ({CUG}) Conference}, dates = {17--21 May 2004}, location = {Knoxville, Tennessee}, day = 17, month = may, year = 2004, abstract = {Described here are the extensive efforts of the authors to modify the Community Land Model for vectorization on the Earth Simulator in Japan and the Cray X1 at Oak Ridge National Laboratory. This paper follows experimental results presented at the Cray Users Group (CUG) Meeting in 2003 (White, 2003). Presented here are the technical details of the old and new internal data structures, the required code reorganization, and the resulting performance improvements. Additionally, performance and scaling of the final Community Land Model Version 3 (CLM3) on the IBM Power4, the Earth Simulator, and the Cray X1 are compared.} } @TechReport{Hoffman_ORNL-TM-2004-119_20040601, author = {Forrest Hoffman and Mariana Vertenstein and Peter Thornton and Keith Oleson and Samuel Levis}, title = {{C}ommunity {L}and {M}odel Version 3.0 ({CLM3.0}) Developer's Guide}, type = {Technical Memorandum}, number = {ORNL/TM-2004/119}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, url = {http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/DevelopersGuide/doc/CodeReference/DevGuideAndReference.pdf}, day = 1, month = jun, year = 2004 } @MastersThesis{Hoffman_MS-UTK-Physics_20041104, author = {Forrest M. Hoffman}, title = {Analysis of Reflected Spectral Signatures and Detection of Geophysical Disturbance Using Hyperspectral Imagery}, school = {University of Tennessee, Department of Physics and Astronomy}, address = {Knoxville, Tennessee, USA}, day = 4, month = nov, year = 2004, abstract = {Geophysical disturbances resulting from human activities often have significant consequences for plants and animals, and even for entire ecosystems. Disturbances resulting from petroleum exploration and production activities can have long term impacts on soils, watersheds, rivers and lakes, vegetation, wildlife, and humans. These anthropogenic disturbances are frequently the result of hydrocarbon (oil) or produced water (brine) spills. Brine is usually produced simultaneously with oil or gas. The ability to detect brine spills with remote sensing techniques would be valuable to petroleum companies and industry regulators. The objectives of this research were to 1) determine if brine spills could be detected spectroscopically, 2) determine if spectral analysis could be performed using a statistical method to identify surface features quickly and easily from large imaging spectroscopy data sets without modeling and removing atmospheric effects or performing detailed spectral unmixing, 3) develop a spectral signature for brine spills which could be applied at other locations, and 4) determine if brine spills could be detected using substantially fewer spectral bands so that a smaller and cheaper instrument could be applied to detect these disturbances. Using hyperspectral image cubes acquired by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over Osage County, Oklahoma, a multivariate statistical clustering technique successfully discerned well-documented brine disturbances on the Tallgrass Prairie Preserve, and the resulting brine spectral signature was applied to locate similar brine disturbances in surrounding image scenes. While validating the prediction results by visiting the site was outside the scope of this project, high resolution aerial photographs were used to assess the success of the predictions and attribute at least 40 of the 87 prediction regions to petroleum activities. While a number of false positives resulted from the analysis, many of these are easily discounted based on objects in the aerial photographs or explained by mineral/salt accumulation. In addition, four bands from the 224-band hyperspectral imagery were used to predict brine disturbances in one of the image cubes. Approximately 90\% of the prediction regions detected in the original analysis---which used 187 of the 224 bands---were again detected using only four spectral bands.} } @Article{Hoffman:AGU:2004, author = {Forrest M. Hoffman and William W. Hargrove}, title = {Quantitative Flux Ecoregions for {A}meri{F}lux Using {MODIS}}, journal = Eos, volume = 85, number = 47, note = {Fall Meet. Suppl., Abstract B23B-07}, month = dec, year = 2004 } @Article{Hoffman_EI_20050803, author = {Forrest M. Hoffman and William W. Hargrove and David J. Erickson and Robert J. Oglesby}, title = {Using Clustered Climate Regimes to Analyze and Compare Predictions from Fully Coupled General Circulation Models}, journal = EI, volume = 9, number = 10, pages = {1--27}, doi = {10.1175/EI110.1}, day = 3, month = aug, year = 2005, abstract = {Changes in Earth's climate in response to atmospheric greenhouse gas buildup impact the health of terrestrial ecosystems and the hydrologic cycle. The environmental conditions influential to plant and animal life are often mapped as ecoregions, which are land areas having similar combinations of environmental characteristics. This idea is extended to establish regions of similarity with respect to climatic characteristics that evolve through time using a quantitative statistical clustering technique called Multivariate Spatio-Temporal Clustering (MSTC). MSTC was applied to the monthly time series output from a fully coupled general circulation model (GCM) called the Parallel Climate Model (PCM). Results from an ensemble of five 99-yr Business-As-Usual (BAU) transient simulations from 2000 to 2098 were analyzed. MSTC establishes an exhaustive set of recurring climate regimes that form a ``skeleton'' through the ``observations'' (model output) throughout the occupied portion of the climate phase space formed by the characteristics being considered. MSTC facilitates direct comparison of ensemble members and ensemble and temporal averages since the derived climate regimes provide a basis for comparison. Moreover, by mapping all land cells to discrete climate states, the dynamic behavior of any part of the system can be studied by its time-varying sequence of climate state occupancy. MSTC is a powerful tool for model developers and environmental decision makers who wish to understand long, complex time series predictions of models. Strong predicted interannual trends were revealed in this analysis, including an increase in global desertification; a decrease in the cold, dry high-latitude conditions typical of North American and Asian winters; and significant warming in Antarctica and western Greenland.} } @Article{Hoffman_IJHPCA_20050801, author = {Forrest M. Hoffman and Mariana Vertenstein and Hideyuki Kitabata and James B. {White III}}, title = {Vectorizing the {C}ommunity {L}and {M}odel ({CLM})}, journal = IJHPCA, volume = 19, number = 3, pages = {247--260}, doi = {10.1177/1094342005056113}, day = 1, month = aug, year = 2005, abstract = {In this paper we describe our extensive efforts to rewrite the Community Land Model (CLM) so that it provides good vector performance on the Earth Simulator in Japan and the Cray X1 at Oak Ridge National Laboratory. We present the technical details of the old and new internal data structures, the required code reorganization, and the resulting performance improvements. We describe and compare the performance and scaling of the final CLM Version 3.0 (CLM3.0) on the IBM Power4, the Earth Simulator, and the Cray X1. At 64 processors, the performance of the model is similar on the IBM Power4, the Earth Simulator, and the Cray X1. However, the Cray X1 offers the best performance of all three platforms tested from 4 to 64 processors when OpenMP is used. Moreover, at low processor counts (16 or fewer), the model performs significantly better on the Cray X1 than on the other platforms. The vectorized version of CLM was publicly released by the National Center for Atmospheric Research as the standalone CLM3.0, as a part of the new Community Atmosphere Model Version 3.0 (CAM3.0), and as a component of the Community Climate System Model Version 3.0 (CCSM3.0) on June 23, 2004.} } @Article{Hoffman:AGU:2005, author = {Forrest M. Hoffman and Inez Fung and Jasmin John}, title = {Preliminary Results from the {C$^4$MIP} {P}hase 1 Simulations Using the {CCSM3-CLM3-CASA$'$} Coupled Model}, journal = Eos, volume = 86, number = 52, note = {Fall Meet. Suppl., Abstract B33G-07}, month = dec, year = 2005 } @InProceedings{Hoffman:iLEAPS:2006, author = {Forrest M. Hoffman and Peter Thornton and Inez Fung and W. Mac Post}, title = {Land-Atmosphere Interactions Exhibited By Coupled Carbon-Cycle Climate Models}, booktitle = {Proceedings of the 1st Integrated Land Ecosystem-Atmsophere Processes Study (iLEAPS) Science Conference, Boulder, Colorado}, editor = {Anni Reissel and Asbj{\o}rn Aarflot}, series = {Report Series in Aerosol Science}, number = 79, address = {Helsinki, Finland}, note = {ISSN 0784-3496}, ISSN = {0784-3496}, ISBN = {952-5027-66-X}, pages = {341}, month = jan, year = 2006 } @InProceedings{Hoffman:US-IALE:2006, author = {Forrest M. Hoffman and William W. Hargrove}, title = {Applying Quantitative Ecoregionalization to Network Analysis: Quantifying Representativeness and Determining Importance Values for {A}meri{F}lux Sites}, booktitle = {Proceedings of the 21st Annual Symposium of the International Association for Landscape Ecology, United States Regional Association (US-IALE)}, address = {San Diego, California, USA}, day = 31, month = mar, year = 2006 } @InProceedings{Hoffman:iEMSs:2006, author = {Forrest M. Hoffman and Inez Fung and W. Mac Post and David Erickson}, title = {Recent Results From Coupled Climate/Carbon-Cycle Models in {CCSM}3}, booktitle = {Proceedings of the {iEMSs} {T}hird {B}iennial {M}eeting: {I}nternational {C}ongress on {E}nvironmental {M}odelling and {S}oftware {S}ociety ({iEMSs} 2006), Summit on Environmental Modelling and Software}, address = {Burlington, Vermont, USA}, day = {9--13}, month = jul, year = 2006 } @Article{Hoffman_JPConf_20060901, author = {Forrest M. Hoffman and Inez Fung and Jim Randerson and Peter Thornton and Jon Foley and Curtis Covey and Jasmin John and Samuel Levis and W. Mac Post and Mariana Vertenstein and Reto St\"ockli and Steve Running and Faith Ann Heinsch and David Erickson and John Drake}, title = {Terrestrial Biogeochemistry in the {C}ommunity {C}limate {S}ystem {M}odel ({CCSM})}, journal = JPConf, volume = 46, number = 1, pages = {363--369}, doi = {10.1088/1742-6596/46/1/051}, day = 1, month = sep, year = 2006, abstract = {Described here is the formulation of the CASA' biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C$^4$MIP) Phase 1 experiments. In addition, CASA' is one of three models---in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.)---that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory.} } @Article{Hoffman:AGU:2006, author = {Forrest M. Hoffman and Inez Y. Fung and James T. Randerson and Peter E. Thornton and Reto St\"ockli and Faith Ann Heinsch and Steve Running and Kathy Hibbard and Jasmin John and Curt Covey and Jon Foley and W. Mac Post and William W. Hargrove and David J. Erickson and Natalie Mahowald}, title = {Preliminary Results from the {CCSM} {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP})}, journal = Eos, volume = 87, number = 52, note = {Fall Meet. Suppl., Abstract B51C-0316}, month = dec, year = 2006 } @Article{Hoffman_JPConf_20071201, author = {Forrest M. Hoffman and Curtis C. Covey and Inez Y. Fung and James T. Randerson and Peter E. Thornton and Yen-Huei Lee and Nan A. Rosenbloom and Reto C. St\"ockli and Steven W. Running and David E. Bernholdt and Dean N. Williams}, title = {Results from the {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP}) and Availability of the Data on the {E}arth {S}ystem {G}rid ({ESG})}, journal = JPConf, volume = 78, number = 1, pages = {012026}, doi = {10.1088/1742-6596/78/1/012026}, day = 1, month = dec, year = 2007, abstract = {This paper describes the Carbon-Land Model Intercomparison Project (C-LAMP) being carried out through a collaboration between the Community Climate System Model (CCSM) Biogeochemistry Working Group, a DOE SciDAC-2 project, and the DOE Program for Climate Model Diagnosis and Intercomparison (PCMDI). The goal of the project is to intercompare terrestrial biogeochemistry models running within the CCSM framework to determine the best set of processes to include in future versions of CCSM. As a part of the project, observational datasets are being collected and used to score the scientific performance of these models following a well-defined set of metrics. In addition, metadata standards for terrestrial biosphere models are being developed to support archival and distribution of the C-LAMP model output via the Earth System Grid (ESG). Progress toward completion of this project and preliminary results from the first set of experiments are reported.} } @Article{Hoffman:AGU:2007, author = {Forrest M. Hoffman and James T. Randerson and Inez Y. Fung and Peter E. Thornton and Jeff Lee and Curt Covey}, title = {Results from the {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP})}, journal = Eos, volume = 88, number = 52, note = {Fall Meet. Suppl., Abstract B31C-0324}, month = dec, year = 2007 } @InProceedings{Hoffman_iEMSs-MSTC_20080707, author = {Forrest M. Hoffman and William W. Hargrove and Richard T. Mills and Salil Mahajan and David J. Erickson and Robert J. Oglesby}, title = {{M}ultivariate {S}patio-{T}emporal {C}lustering ({MSTC}) as a Data Mining Tool for Environmental Applications}, booktitle = {Proceedings of the {iEMSs} {F}ourth {B}iennial {M}eeting: {I}nternational {C}ongress on {E}nvironmental {M}odelling and {S}oftware {S}ociety ({iEMSs} 2008)}, editor = {Miquel S\`anchez-Marr\`e and Javier B\'ejar and Joaquim Comas and Andrea E. Rizzoli and Giorgio Guariso}, dates = {7--10 July 2008}, location = {Barcelona, Catalonia, Spain}, pages = {1774--1781}, ISBN = {978-84-7653-074-0}, day = 7, month = jul, year = 2008, abstract = {The authors have applied multivariate cluster analysis to a variety of environmental science domains, including ecological regionalization; environmental monitoring network design; analysis of satellite-, airborne-, and ground-based remote sensing, and climate model-model and model-measurement intercomparison. The clustering methodology employs a $k$-means statistical clustering algorithm that has been implemented in a highly scalable, parallel high performance computing (HPC) application. Because of its efficiency and use of HPC platforms, the clustering code may be applied as a data mining tool to analyze and compare very large data sets of high dimensionality, such as very long or high frequency/resolution time series measurements or model output. The method was originally applied across geographic space and called Multivariate Geographic Clustering (MGC). Now applied across space and through time, the environmental data mining method is called Multivariate Spatio-Temporal Clustering (MSTC). Described here are the clustering algorithm, recent code improvements that significantly reduce the time-to-solution, and a new parallel principal components analysis (PCA) tool that can analyze very large data sets. Finally, a sampling of the authors' applications of MGC and MSTC to problems in the environmental sciences are presented.} } @InProceedings{Hoffman_iEMSs-C-LAMP_20080707, author = {Forrest M. Hoffman and James T. Randerson and Inez Y. Fung and Peter E. Thornton and Yen-Huei ``Jeff'' Lee and Curtis C. Covey and Gordon B. Bonan and Steven W. Running}, title = {The {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP}): A Protocol and Evaluation Metrics for Global Terrestrial Biogeochemistry Models}, booktitle = {Proceedings of the {iEMSs} {F}ourth {B}iennial {M}eeting: {I}nternational {C}ongress on {E}nvironmental {M}odelling and {S}oftware {S}ociety ({iEMSs} 2008)}, editor = {Miquel S\`anchez-Marr\`e and Javier B\'ejar and Joaquim Comas and Andrea E. Rizzoli and Giorgio Guariso}, dates = {7--10 July 2008}, location = {Barcelona, Catalonia, Spain}, pages = {1039--1046}, ISBN = {978-84-7653-074-0}, day = 7, month = jul, year = 2008, abstract = {Described here is a protocol and accompanying metrics for evaluation of scientific model performance of global terrestrial biogeochemistry models. Developed under the guise of the NCAR Community Climate System Model (CCSM) Biogeochemistry Working Group, the Carbon-Land Model Intercomparison Project (C-LAMP) experimental protocol improves and expands upon the Coupled Carbon Cycle-Climate Model Intercomparison Project (C4MIP) Phase 1 protocol. However, unlike traditional model intercomparisons, C-LAMP has established scientific model performance metrics based upon comparison against best-available satellite- and ground-based measurements. Moreover, C-LAMP has partnered with the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison (PCMDI) to collect, archive, and distribute---via the Earth System Grid (ESG)---model results from C-LAMP experiments performed by international modeling groups in the same fashion as was done for the model results used in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In addition, because future IPCC Assessment Reports are expected to be based on results from integrated Earth System Models (ESMs), C-LAMP is helping to establish the metadata standards for model output from terrestrial biogeochemistry components of ESMs. Proposed as an extension to the netCDF Climate and Forecast (CF) 1.1 Convention, these metadata standards will facilitate future model-model and model-measurement intercomparisons. A prototype diagnostics tool has been developed for C-LAMP that summarizes model results, produce graphical representations of these results as compared with observational data sets, and score models on their scientific performance.} } @Article{Hoffman:AGU:2008, author = {Forrest M. Hoffman and James T. Randerson and Inez Y. Fung and Peter Thornton and Curtis Covey and Gordon Bonan and Steven Running and Richard Norby}, title = {Comparison of Global Model Results from the {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP}) with {F}ree-{A}ir {C}arbon {D}ioxide {E}nrichment ({FACE}) Manipulation Experiments}, journal = Eos, volume = 89, number = 53, note = {Fall Meet. Suppl., Abstract B51E-0447}, month = dec, year = 2008 } @Article{Hoffman_iLEAPS-Newsletter_20090601, author = {Forrest M. Hoffman and Martial Mancip}, title = {Working Group Report on Terrestrial Biosphere Model Evaluation}, journal = {Integrated Land Ecosystem-Atmosphere Processes Study (iLEAPS) Newsletter}, ISSN = {1796-0363}, volume = 7, pages = 64, day = 1, month = jun, year = 2009 } @InProceedings{Hoffman:iLEAPS:2009, author = {Forrest M. Hoffman and James T. Randerson and Inez Y. Fung and Peter E. Thornton and Natalie M. Mahowald and Gordon B. Bonan and Steven W. Running}, title = {The {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP}): A Prototype for Coupled Biosphere-Atmosphere Model Benchmarking for the {IPCC} {F}ifth {A}ssessment {R}eport ({AR5})}, booktitle = {Water in a Changing Climate --- Progress in Land-Atmosphere Interactions and Energy/Water Cycle Research}, editor = {Anni Reissell and Marjut Nyman and Miia Vesala and Tyyne Viisanen}, series = {Proceedings of the 6th International Scientific Conference on the Global Energy and Water Cycle (GEWEX) and 2nd International Land Ecosystem-Atmosphere Processes Study (iLEAPS) Science Conference}, address = {Melbourne, Australia}, volume = 1, isbn = {978-952-5855-01-2}, pages = {126--127}, month = aug, year = 2009 } @InProceedings{Hoffman:ICDC8:2009, author = {Forrest M. Hoffman and James T. Randerson and Peter E. Thornton and Natalie M. Mahowald and Gordon B. Bonan and Steven W. Running and Inez Y. Fung}, title = {The {C}arbon-{L}and {M}odel {I}ntercomparison {P}roject ({C-LAMP}): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models}, booktitle = {Proceedings of the 8th International Carbon Dioxide Conference}, address = {Jena, Germany}, month = sep, year = 2009 } @Article{Hoffman_AGU_20091215, author = {Forrest M. Hoffman and James T. Randerson and Peter E. Thornton and Gordon B. Bonan and Bj{\o}rn J. Brooks and Inez Y. Fung}, title = {An International Land-Biosphere Model Benchmarking Activity for the {IPCC} {F}ifth {A}ssessment {R}eport ({AR5})}, journal = Eos, volume = 90, number = 52, note = {Fall Meet. Suppl., Abstract B23G-08}, day = 15, month = dec, year = 2009 } @InProceedings{Hoffman_IGARSS_20100725, author = {Forrest M. Hoffman and Richard T. Mills and Jitendra Kumar and Srinivasa S. Vulli and William W. Hargrove}, title = {Geospatiotemporal Data Mining in an Early Warning System for Forest Threats in the {U}nited {S}tates}, booktitle = {Proceedings of the 2010 {IEEE} {I}nternational {G}eoscience and {R}emote {S}ensing {S}ymposium ({IGARSS} 2010)}, dates = {25--30 July 2010}, location = {Honolulu, Hawaii, USA}, pages = {170--173}, doi = {10.1109/IGARSS.2010.5653935}, issn = {2153-6996}, isbn = {978-1-4244-9566-5}, note = {Invited}, day = 25, month = jul, year = 2010, abstract = {We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250~m Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study) for the conterminous United States as part of an early warning system to identify threats to forest ecosystems. Cluster analysis of this massive data set, using high-performance computing, provides a basis for several possible approaches to defining the bounds of ``normal'' phenological patterns, indicating healthy vegetation in a given geographic location. We demonstrate the applicability of such an approach, using it to identify areas in Colorado, USA, where an ongoing mountain pine beetle outbreak has caused significant tree mortality.} } @Misc{Hoffman_AGU_20101216, author = {F. M. Hoffman and J. T. Randerson}, title = {The Impact of the Temperature Sensitivity of Ecosystem Respiration on the Climate-Carbon Cycle Feedback Strength}, howpublished = {Abstract B44A-02 presented at 2010 Fall Meeting, American Geophysical Union (AGU), San Francisco, California, USA}, day = 16, month = dec, year = 2010 } @InProceedings{Hoffman_ICCS_20110601, author = {Forrest M. Hoffman and J. Walter Larson and Richard Tran Mills and Bj{\o}rn-Gustaf J. Brooks and Auroop R. Ganguly and William W. Hargrove and Jian Huang and Jitendra Kumar and Ranga R. Vatsavai}, title = {{D}ata {M}ining in {E}arth {S}ystem {S}cience ({DMESS} 2011)}, booktitle = {Proceedings of the International Conference on Computational Science ({ICCS} 2011)}, editor = {Mitsuhisa Sato and Satoshi Matsuoka and Peter M. Sloot and G. Dick {van Albada} and Jack Dongarra}, publisher = {Elsevier}, address = {Amsterdam}, series = PCS, dates = {1--3 June 2011}, location = {Nanyang Technological University, Singapore}, volume = 4, pages = {1450--1455}, doi = {10.1016/j.procs.2011.04.157}, issn = {1877-0509}, day = 1, month = jun, year = 2011, abstract = {From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques---such as cluster analysis, singular value decomposition, block entropy, Fourier and wavelet analysis, phase-space reconstruction, and artificial neural networks---are being applied to problems of segmentation, feature extraction, change detection, model-data comparison, and model validation. The size and complexity of Earth science data exceed the limits of most analysis tools and the capacities of desktop computers. New scalable analysis and visualization tools, running on parallel cluster computers and supercomputers, are required to analyze data of this magnitude. This workshop will demonstrate how data mining techniques are applied in the Earth sciences and describe innovative computer science methods that support analysis and discovery in the Earth sciences.} } @InProceedings{Johnson_LNCS_20090527, author = {C. Ryan Johnson and Markus Glatter and Wesley Kendall and Jian Huang and Forrest M. Hoffman}, title = {Querying for Feature Extraction and Visualization in Climate Modeling}, booktitle = {Proceedings of the 9th International Conference on Computational Science ({ICCS 2009})}, editor = {Gabrielle Allen and Jaros{\l}aw Nabrzyski and Edward Seidel and Geert Dick van Albada and Jack Dongarra and Peter M.A. Sloot}, publisher = {Springer-Verlag}, address = {Heidelberg}, series = {Lecture Notes in Computer Science ({LNCS})}, dates = {25--27 May 2009}, location = {Baton Rogue, Louisiana, USA}, volume = 5545, pages = {416--425}, doi = {10.1007/978-3-642-01973-9\_46}, isbn = {978-3-642-01972-2}, day = 27, month = may, year = 2009, abstract = {The ultimate goal of data visualization is to clearly portray features relevant to the problem being studied. This goal can be realized only if users can effectively communicate to the visualization software what features are of interest. To this end, we describe in this paper two query languages used by scientists to locate and visually emphasize relevant data in both space and time. These languages offer descriptive feedback and interactive refinement of query parameters, which are essential in any framework supporting queries of arbitrary complexity. We apply these languages to extract features of interest from climate model results and describe how they support rapid feature extraction from large datasets.} } @Article{Keller_FrontEcolEnviron_20080601, author = {Michael Keller and David Schimel and William Hargrove and Forrest Hoffman}, title = {A Continental Strategy for the {N}ational {E}cological {O}bservatory {N}etwork}, journal = FrontEcolEnviron, note = {Special Issue on Continental-Scale Ecology}, volume = 6, number = 5, pages = {282--284}, doi = {10.1890/1540-9295(2008)6[282:ACSFTN]2.0.CO;2}, day = 1, month = jun, year = 2008 } @InProceedings{Kendall_CTS_20080519, author = {Wesley Kendall and Markus Glatter and Jian Huang and Forrest Hoffman and David E. Bernholdt}, title = {Web Enabled Collaborative Climate Visualization in the Earth System Grid}, booktitle = {Proceedings of the International Symposium on Collaborative Technologies and Systems 2008 ({CTS} 2008)}, dates = {19--23 May 2008}, location = {Irvine, California, USA}, pages = {212--220}, doi = {10.1109/CTS.2008.4543934}, isbn = {978-1-4244-2248-7}, day = 19, month = may, year = 2008, abstract = {The recent advances in high performance computing, storage and networking technologies have enabled fundamental changes in current climate research. While sharing datasets and results is already common practice in climate modeling, direct sharing of the analysis and visualization process is also becoming feasible. We report our efforts to develop a capability, coupled with the Earth system grid (ESG), for sharing an entire executable workspace of visualization among collaborators. Evolutionary history of visualizations of research findings can also be captured and shared. The data intensive nature of the visualization system requires using several advanced techniques of visualization and parallel computing. With visualization clients implemented through standard Web browsers, however, the ensuing complexity is made transparent to end-users. We demonstrate the efficacy of our system using cutting edge climate datasets.} } @Article{Kloster_Biogeosci_20100611, author = {Silvia Kloster and Natalie M. Mahowald and James T. Randerson and Peter E. Thornton and Forrest M. Hoffman and Samuel Levis and Peter J. Lawrence and Johan J. Feddema and Keith W. Oleson and David M. Lawrence}, title = {Fire Dynamics During the 20th Century Simulated by the {C}ommunity {L}and {M}odel}, journal = Biogeosci, volume = 7, number = 6, pages = {1877--1902}, doi = {10.5194/bg-7-1877-2010}, day = 11, month = jun, year = 2010, abstract = {Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4~Pg~C/year for the period 1997--2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2~Pg~C/year with 11\% stemming from deforestation fires. During 2000--2004 this flux decreased to 0.85~Pg~C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.} } @InProceedings{Kumar_ICCS_20110601, author = {Jitendra Kumar and Richard Tran Mills and Forrest M. Hoffman and William W. Hargrove}, title = {Parallel $k$-Means Clustering for Quantitative Ecoregion Delineation Using Large Data Sets}, booktitle = {Proceedings of the International Conference on Computational Science ({ICCS} 2011)}, editor = {Mitsuhisa Sato and Satoshi Matsuoka and Peter M. Sloot and G. Dick {van Albada} and Jack Dongarra}, publisher = {Elsevier}, address = {Amsterdam}, series = PCS, dates = {1--3 June 2011}, location = {Nanyang Technological University, Singapore}, volume = 4, pages = {1602--1611}, doi = {10.1016/j.procs.2011.04.173}, issn = {1877-0509}, day = 1, month = jun, year = 2011, abstract = {Identification of geographic ecoregions has long been of interest to environmental scientists and ecologists for identifying regions of similar ecological and environmental conditions. Such classifications are important for predicting suitable species ranges, for stratification of ecological samples, and to help prioritize habitat preservation and remediation efforts. Hargrove and Hoffman [1] and [2] have developed geographical spatio-temporal clustering algorithms and codes and have successfully applied them to a variety of environmental science domains, including ecological regionalization; environmental monitoring network design; analysis of satellite-, airborne-, and ground-based remote sensing, and climate model-model and model-measurement intercomparison. With the advances in state-of-the-art satellite remote sensing and climate models, observations and model outputs are available at increasingly high spatial and temporal resolutions. Long time series of these high resolution datasets are extremely large in size and growing. Analysis and knowledge extraction from these large datasets are not just algorithmic and ecological problems, but also pose a complex computational problem. This paper focuses on the development of a massively parallel multivariate geographical spatio-temporal clustering code for analysis of very large datasets using tens of thousands processors on one of the fastest supercomputers in the world.} } @TechReport{Lee_ORNL-TM-12401_19930801, author = {S. Y. Lee and Mark Elless and Forrest M. Hoffman}, title = {Solubility Measurement of {U}ranium in {U}ranium-Contaminated Soils}, type = {Technical Memorandum}, number = {ORNL/TM-12401}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, day = 1, month = aug, year = 1993, abstract = {A short-term equilibration study involving two uranium-contaminated soils at the Department of Energy’s Fernald Environmental Management Program (FEMP) site was conducted as part of the In Situ Remediation Integrated Program. The goal of this study is to predict the behavior of uranium during on-site remediation of these soils. Geochemical modeling was performed on the aqueous species dissolved from these soils following the equilibration study to predict the on-site uranium leaching and transport processes. Results showed that the soluble levels of the major components (total uranium, calcium, magnesium, and carbonate) increased continually for the first four weeks. After the first four weeks, these components either reached a steady-state equilibrium (in those components having solubilities approaching that of the controlling solid phase for that component) or continued linearity throughout the study (in those components having low solubilities). Other major components, such as aluminum, potassium, and iron, reached a steady-state concentration within three days. Silica levels approximated the predicted solubility of quartz throughout the study. A much higher level of dissolved uranium was observed in the soil contaminated from spillage of uranium-laden solvents and process effluents than in the soil contaminated from settling of airborne uranium particles ejected from the nearby incinerator. The high levels observed for soluble calcium, magnesium, and bicarbonate are probably the result of magnesium and/or calcium carbonate minerals dissolving in these soils. The increase in the total uranium levels with increasing carbonate levels is due to the complexation of uranium with carbonate species. Geochemical modeling confirms that the uranyl-carbonate complexes are the most stable and dominant in these solutions. The implication of this work is that the use of carbonate minerals on these soils for erosion control and road construction activities contributes to the leaching of uranium from contaminated soil particles. Dissolved carbonates promote uranium solubility, forming highly mobile anionic species. Mobile uranium species are contaminating the groundwater underlying these soils. Therefore, the development of a site-specific remediation technology is urgently needed for the FEMP site.} } @InProceedings{Levine_GIS95_19950328, author = {Daniel A. Levine and William W. Hargrove and Forrest M. Hoffman}, title = {Characterization of Sediments in the {C}linch {R}iver, {T}ennessee, Using Remote Sensing and Multi-Dimensional {GIS} Techniques}, booktitle = {Proceedings of the Ninth Annual Symposium on Geographic Information Systems}, dates = {28 March--2 April 1995}, location = {Vancouver, British Columbia, Canada}, pages = {548--551}, day = 28, month = mar, year = 1995 } @InCollection{Levine_GISWorld_19950801, author = {Daniel A. Levine and William W. Hargrove and Forrest M. Hoffman}, title = {Characterization of Sediments in the {C}linch {R}iver, {T}ennessee, Using Remote Sensing and Multi-Dimensional {GIS} Techniques}, booktitle = {GIS Applications in Natural Resources 2}, editor = {Michael Heit and H. Dennison Parker and Art Shortreid}, publisher = {GIS World, Inc.}, address = {Fort Collins, Colorado}, ISBN = {1-882610-17-2}, day = 1, month = aug, year = 1995 } @TechReport{Lozar_ERDC-CERL-TR-05-23_20050901, author = {Robert C. Lozar and William Hargrove and Forrest Hoffman}, institution = {U.S. Army Corps of Engineers, Engineer Research and Development Center}, title = {Use of the {C}orridor {T}ool in Support of Threatened and Endangered Species Habitat Fragmentation}, type = {Technical Report}, number = {ERDC/CERL TR-05-23}, day = 1, month = sep, year = 2005, abstract = {Researchers at the Engineer Research and Development Center, Construction Engineering Research Laboratory (ERDC-CERL), Champaign, IL, determined that a ``Corridor Tool'' developed by the Oak Ridge National Laboratory (ORNL) could serve to further focus ongoing ``habitat'' research on habitat fragmentation at the landscape scale. This work tested the ORNL Corridor Tool on data related to Red-cockaded Woodpecker habitat fragmentation in the southeastern United States using widely available data to run the Corridor Tool, and to develop a general corridor analysis.} } @Article{Mahajan_AGU_20071213, author = {Salil Mahajan and Forrest M. Hoffman and William W. Hargrove and Sigurd W. Christensen and Richard T. Mills}, title = {A Cluster Analysis Approach to Comparing {A}tmospheric {R}adiation {M}easurement ({ARM}) Observations with Global Climate Model ({GCM}) Results}, journal = Eos, volume = 88, number = 52, note = {Fall Meet. Suppl., Abstract A41A-0010}, day = 13, month = dec, year = 2007 } @InProceedings{Mahinthakumar_SC99_19991113, author = {Gnanamanika Mahinthakumar and Forrest M. Hoffman and William W. Hargrove and Nicolas T. Karonis}, title = {Multivariate Geographic Clustering in a Metacomputing Environment Using {G}lobus}, booktitle = {Supercomputing '99: Proceedings of the 1999 {ACM/IEEE} conference on Supercomputing ({CDROM})}, series = {Supercomputing '99}, isbn = {1-58113-091-0}, doi = {10.1145/331532.331537}, dates = {13--19 November 1999}, location = {Portland, Oregon, United States}, publisher = {ACM Press}, address = {New York, NY, USA}, day = 13, month = nov, year = 1999, abstract = {The authors present a metacomputing application of multivariate, nonhierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity, called \textit{ecoregions}. These maps represent finer scale regionalizations than do those generated by the traditional technique: an expert with a marker pen. Several variables (e.g., temperature, organic matter, rainfall etc.) thought to affect the growth of vegetation are clustered at resolutions as fine as one square kilometer (1~km$^2$). These data can represent over 7.8 million map cells in an $n$-dimensional ($n = 9$ to $25$) data space. A parallel version of the iterative statistical clustering algorithm is developed by the authors using the MPI (Message Passing Interface) message passing routines. The parallel algorithm uses a classical, self-scheduling, single-program, multiple data (SPMD) organization; performs dynamic load balancing for reasonable performance in heterogeneous metacomputing environments; and provides fault tolerance by saving intermediate results for easy restarts in case of hardware failure. The parallel algorithm was tested on various geographically distributed heterogeneous metacomputing configurations involving an IBM SP3, an IBM SP2, and two SGI Origin 2000’s. The tests were performed with minimal code modification, and were made possible by Globus, (a metacomputing software toolkit) and the Globus-enabled version of MPI (MPICH-G). Our performance tests indicate that while the algorithm works reasonably well under the metacomputing environment for a moderate number of processors, the communication overhead can become prohibitive for large processor configurations.} } @Article{Mahowald_ACP_20101119, author = {N. M. Mahowald and S. Kloster and S. Engelstaedter and J. K. Moore and S. Mukhopadhyay and J. R. McConnell and S. Albani and S. C. Doney and A. Bhattacharya and M. A. J. Curran and M. G. Flanner and F. M. Hoffman and D. M. Lawrence and K. Lindsay and P. A. Mayewski and J. Neff and D. Rothenberg and E. Thomas and P. E. Thornton and C. S. Zender}, title = {Observed 20th Century Desert Dust Variability: Impact on Climate and Biogeochemistry}, journal = ACP, volume = 10, number = 22, pages = {10875--10893}, doi = {10.5194/acp-10-10875-2010}, day = 19, month = nov, year = 2010, abstract = {Desert dust perturbs climate by directly and indirectly interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were increasing or decreasing desert dust in the global average. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates of desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be $-0.14 \pm 0.11$~W/m$^2$ (1990--1999 vs. 1905--1914). The estimated radiative change due to dust is especially strong between the heavily loaded 1980--1989 and the less heavily loaded 1955--1964 time periods ($-0.57 \pm 0.46$~W/m$^2$), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11$^\circ$C. Model simulations also indicate strong regional shifts in precipitation and temperature from desert dust changes, causing 6~ppm (12~PgC) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6\% over the 20th century, drawing down an additional 4~ppm (8~PgC) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our understanding of these changes and their impacts should continue to be refined.} } @Misc{Mahowald_AGU_20101213, author = {N. M. Mahowald and S. Kloster and S. Engelstaedter and J. K. Moore and S. Mukhopadhyay and J. R. McConnell and S. Albani and S. C. Doney and A. Bhattacharya and M. A. J. Curran and M. G. Flanner and F. M. Hoffman and D. M. Lawrence and K. Lindsay and P. A. Mayewski and J. Neff and D. Rothenberg and E. Thomas and P. E. Thornton}, title = {Observed 20th Century Desert Dust Variability: Impact on Climate and Biogeochemistry}, howpublished = {Abstract A11K-02 presented at 2010 Fall Meeting, American Geophysical Union (AGU), San Francisco, California, USA}, day = 13, month = dec, year = 2010 } @InProceedings{Mills_CUG_20090506, author = {Richard T. Mills and Forrest M. Hoffman and Patrick H. Worley and Kalyan S. Perumalla and Art Mirin and Glenn E. Hammond and Barry F. Smith}, title = {Coping at the User-Level with Resource Limitations in the {C}ray {M}essage {P}assing {T}oolkit {MPI} at Scale: How Not to Spend Your Summer Vacation}, booktitle = {Proceedings of the 2009 {C}ray {U}ser {G}roup ({CUG}) Conference}, dates = {4--7 May 2009}, location = {Atlanta, Georgia, United States}, day = 6, month = may, year = 2009, abstract = {As the number of processor cores available in Cray XT series computers has rapidly grown, users have increasingly encountered instances where an MPI code that has previously worked for years unexpectedly fails at high core counts (``at scale'') due to resource limitations being exceeded within the MPI implementation. Here, we examine several examples drawn from user experiences and discuss strategies for working around these difficulties at the user level.} } @Misc{Mills_AGU_20101214, author = {R. T. Mills and F. M. Hoffman and J. Kumar and S. S. Vulli and W. W. Hargrove and J. Spruce}, title = {Geospatiotemporal Data Mining of Remotely Sensed Phenology for Unsupervised Forest Threat Detection}, howpublished = {Abstract B23G-0462 presented at 2010 Fall Meeting, American Geophysical Union (AGU), San Francisco, California, USA}, day = 14, month = dec, year = 2010 } @InProceedings{Mills_ICCS_20110601, author = {Richard Tran Mills and Forrest M. Hoffman and Jitendra Kumar and William W. Hargrove}, title = {Cluster Analysis-Based Approaches for Geospatiotemporal Data Mining of Massive Data Sets for Identification of Forest Threats}, booktitle = {Proceedings of the International Conference on Computational Science ({ICCS} 2011)}, editor = {Mitsuhisa Sato and Satoshi Matsuoka and Peter M. Sloot and G. Dick {van Albada} and Jack Dongarra}, publisher = {Elsevier}, address = {Amsterdam}, series = PCS, dates = {1--3 June 2011}, location = {Nanyang Technological University, Singapore}, volume = 4, pages = {1612--1621}, doi = {10.1016/j.procs.2011.04.174}, issn = {1877-0509}, day = 1, month = jun, year = 2011, abstract = {We investigate methods for geospatiotemporal data mining of multi-year land surface phenology data (250 m$^2$ Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectrometer (MODIS) in this study) for the conterminous United States (CONUS) as part of an early warning system for detecting threats to forest ecosystems. The approaches explored here are based on $k$-means cluster analysis of this massive data set, which provides a basis for defining the bounds of the expected or ``normal'' phenological patterns that indicate healthy vegetation at a given geographic location. We briefly describe the computational approaches we have used to make cluster analysis of such massive data sets feasible, describe approaches we have explored for distinguishing between normal and abnormal phenology, and present some examples in which we have applied these approaches to identify various forest disturbances in the CONUS.} } @Article{Norby:AGU:2008, author = {Richard J. Norby and J. M. Warren and C. M. Iversen and B. E. Medlyn and R. E. McMurtrie and Forrest M. Hoffman}, title = {Nitrogen Limitation is Reducing the Enhancement of {NPP} by Elevated {CO}$_2$ in a Deciduous Forest}, journal = Eos, volume = 89, number = 53, note = {Fall Meet. Suppl., Abstract B32B-05, Invited}, month = dec, year = 2008 } @TechReport{Oleson_NCAR-TN-478+STR_20100301, author = {Keith W. Oleson and David M. Lawrence and Gordon B. Bonan and Mark G. Flanner and Erik Kluzek and Peter J. Lawrence and Samuel Levis and Sean C. Swenson and Peter E. Thornton and Aiguo Dai and Mark Decker and Robert Dickinson and Johannes Feddema and Colette Heald and Forrest Hoffman and Jean-Fran\c{c}ois Lamarque and Natalie Mahowald and Guo-Yue Niu and Taotao Qian and James Randerson and Steve Running and Koichi Sakaguchi and Andrew Slater and Reto St\"{o}ckli and Aihui Wang and Zong-Liang Yang and Xiaodong Zeng and Xubin Zeng}, title = {Technical Description of Version 4.0 of the {C}ommunity {L}and {M}odel ({CLM})}, type = {Technical Note}, number = {NCAR/TN-478+STR}, institution = {National Center for Atmospheric Research}, address = {Boulder, Colorado, USA}, url = {http://www.cesm.ucar.edu/models/cesm1.0/clm/CLM4_Tech_Note.pdf}, day = 1, month = mar, year = 2010 } @TechReport{Oleson_NCAR-TN-461+STR_20040501, author = {Keith W. Oleson and Yongjiu Dai and Gordon Bonan and Mike Bosilovich and Robert Dickinson and Paul Dirmeyer and Forrest Hoffman and Paul Houser and Samuel Levis and Guo-Yue Niu and Peter Thornton and Mariana Vertenstein and Zong-Liang Yange and Xubin Zeng}, title = {Technical Description of the {C}ommunity {L}and {M}odel}, type = {Technical Note}, number = {NCAR/TN-461+STR}, institution = {National Center for Atmospheric Research}, address = {Boulder, Colorado, USA}, url = {http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/TechNote/CLM_Tech_Note.pdf}, day = 1, month = may, year = 2004 } @Article{Pittman_JGR_20070420, author = {Jasna V. Pittman and Elliot M. Weinstock and Robert J. Oglesby and David S. Sayres and Jessica B. Smith and James G. Anderson and Owen R. Cooper and Steven C. Wofsy and Irene Xueref and Cristoph Gerbig and Bruce C. Daube and Erik C. Richard and Brian A. Ridley and Andrew J. Weinheimer and Max Loewenstein and Hans-Jurg Jost and Jimena P. Lopez and Michael J. Mahoney and Thomas L. Thompson and William W. Hargrove and Forrest M. Hoffman}, title = {Transport in the Subtropical Lowermost Stratosphere during the {C}irrus {R}egional {S}tudy of {T}ropical {A}nvils and {C}irrus {L}ayers-{F}lorida {A}rea {C}irrus {E}xperiment}, journal = JGR, volume = 112, number = {D8}, pages = {D08304}, doi = {10.1029/2006JD007851}, day = 20, month = apr, year = 2007, abstract = {We use in situ measurements of water vapor (H$_2$O), ozone (O$_3$), carbon dioxide (CO$_2$), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NO$_y$) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and last by the extent of convective influence, potentially related to the latitude of convective injection (Dessler and Sherwood, 2004). We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and nonlocal events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.} } @Article{Post_DOE-Research-Summary_19970624, author = {Wilfred M. Post and Anthony W. King and Stan D. Wullschleger and Forrest M. Hoffman}, title = {Historical Variations in Terrestrial Biospheric Carbon Storage}, journal = {DOE Research Summary}, number = 34, url = {http://cdiac.esd.ornl.gov/pns/doers/doer34/doer34.htm}, day = 24, month = jun, year = 1997 } @Article{Randerson_GCB_20091001, author = {James T. Randerson and Forrest M. Hoffman and Peter E. Thornton and Natalie M. Mahowald and Keith Lindsay and Yen-Huei Lee and Cynthia D. Nevison and Scott C. Doney and Gordon Bonan and Reto St\"ockli and Curtis Covey and Steven W. Running and Inez Y. Fung}, title = {Systematic Assessment of Terrestrial Biogeochemistry in Coupled Climate-Carbon Models}, journal = GCB, volume = 15, number = 10, pages = {2462--2484}, doi = {10.1111/j.1365-2486.2009.01912.x}, issn = {1365-2486}, day = 1, month = oct, year = 2009, abstract = {With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon-LAnd Model Intercomparison Project (C-LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) --- Carnegie-Ames-Stanford Approach$'$ (CASA$'$) and carbon-nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO$_2$ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1--3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO$_2$ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr$^{-1}$ for CASA$'$ vs. 1.2 Pg C yr$^{-1}$ for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988--2004 based on comparison with atmospheric inversion results from TRANSCOM ($r=0.66$ for CASA$'$ and $r=0.73$ for CN). Adding (CASA$'$) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C-LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community-wide platform for model-data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C-LAMP are publicly available on the Earth System Grid. } } @Article{Saxon_EcolLett_20050101, author = {Earl Saxon and Barry Baker and William Hargrove and Forrest Hoffman and Chris Zganjar}, title = {Mapping Environments at Risk Under Different Global Climate Change Scenarios}, journal = EcolLett, volume = 8, number = 1, pages = {53--60}, doi = {10.1111/j.1461-0248.2004.00694.x}, day = 1, month = jan, year = 2005, abstract = {All global circulation models based on Intergovernmental Panel on Climate Change (IPCC) scenarios project profound changes, but there is no consensus on how to map their environmental consequences. Our multivariate representation of environmental space combines stable topographic and edaphic attributes with dynamic climatic attributes. We divide that environmental space into 500 unique domains and map their current locations and their projected locations in 2100 under contrasting emissions scenarios. The environmental domains found across half the study area today disappear under the higher emissions scenario, but persist somewhere in it under the lower emissions scenario. Locations affected least and those affected most under each scenario are mapped. This provides an explicit framework for designing conservation networks to include both areas at least risk (potential refugia) and areas at greatest risk, where novel communities may form and where sentinel ecosystems can be monitored for signs of stress.} } @Article{Schimel_FrontEcolEnviron_20070301, author = {David Schimel and William Hargrove and Forrest Hoffman and James McMahon}, title = {{NEON}: A Hierarchically Designed National Ecological Network}, journal = FrontEcolEnviron, volume = 5, number = 2, pages = 59, doi = {10.1890/1540-9295(2007)5[59:NAHDNE]2.0.CO;2}, day = 1, month = mar, year = 2007 } @Misc{Shi_AGU_20101216, author = {X. Shi and J. Mao and P. E. Thornton and F. M. Hoffman}, title = {The Impact of Climate, {CO$_2$}, Nitrogen Deposition and Land Use Change on Contemporary Global River Flow}, howpublished = {Abstract B41G-0401 presented at 2010 Fall Meeting, American Geophysical Union (AGU), San Francisco, California, USA}, day = 16, month = dec, year = 2010 } @Article{Sisneros_JPConf_20081201, author = {Robert Sisneros and Markus Glatter and Brandon Langley and Jian Huang and Forrest Hoffman and David J. {Erickson III}}, title = {Time-Varying Multivariate Visualization for Understanding Terrestrial Biogeochemistry}, journal = JPConf, volume = 125, number = 1, pages = {012093}, doi = {10.1088/1742-6596/125/1/012093}, day = 1, month = dec, year = 2008, abstract = {Petascale computing has brought forth a transformational way of doing science. To the global effort on studying climate change, this shift has enabled not only tools more functional and more powerful than before but also a scientific exploration more comprehensive than before. In this work, we report our efforts to employ recent ultrascale visualization technologies (SciDAC Ultravis) to study model comparison in terrestrial biogeochemistry datasets produced by computation (SciDAC C-LAMP). While many of the current efforts are specific to climate modeling research, our method of location-specific summarizing visualization of extreme and normal relative distribution patterns is generally applicable to other fields of computational sciences.} } @InProceedings{Sisneros_ICCS_20110601, author = {Robert Sisneros and Jian Huang and George Ostrouchov and Forrest Hoffman}, title = {Visualizing Life Zone Boundary Sensitivities Across Climate Models and Temporal Spans}, booktitle = {Proceedings of the International Conference on Computational Science ({ICCS} 2011)}, editor = {Mitsuhisa Sato and Satoshi Matsuoka and Peter M. Sloot and G. Dick {van Albada} and Jack Dongarra}, publisher = {Elsevier}, address = {Amsterdam}, series = PCS, dates = {1--3 June 2011}, location = {Nanyang Technological University, Singapore}, volume = 4, pages = {1582--1591}, doi = {10.1016/j.procs.2011.04.171}, issn = {1877-0509}, day = 1, month = jun, year = 2011, abstract = {Life zones are a convenient and quantifiable method for delineating areas with similar plant and animal communities based on bioclimatic conditions. Such ecoregionalization techniques have proved useful for defining habitats and for studying how these habitats may shift due to environmental change. The ecological impacts of climate change are of particular interest. Here we show that visualizations of the geographic projection of life zones may be applied to the investigation of potential ecological impacts of climate change using the results of global climate model simulations. Using a multi-factor classification scheme, we show how life zones change over time based on quantitative model results into the next century. Using two straightforward metrics, we identify regions of high sensitivity to climate changes from two global climate simulations under two different greenhouse gas emissions scenarios. Finally, we identify how preferred human habitats may shift under these scenarios. We apply visualization methods developed for the purpose of displaying multivariate relationships within data, especially for situations that involve a large number of concurrent relationships. Our method is based on the concept of multivariate classification, and is implemented directly in VisIt, a production quality visualization package.} } @Article{Thornton_AGU_20091215, author = {Peter E. Thornton and Forrest M. Hoffman and George C. Hurtt}, title = {Influence of Dynamic Land Use and Land Cover Change on Simulated Global Terrestrial Carbon and Nitrogen Cycles, Climate-carbon Cycle Feedbacks, and Interactions with Rising {CO}$_2$ and Anthropogenic Nitrogen Deposition}, journal = Eos, volume = 90, number = 52, note = {Fall Meet. Suppl., Abstract B24B-06}, day = 15, month = dec, year = 2009 } @TechReport{Unseren_ORNL-TM-12176_19930101, author = {Michael A. Unseren and Forrest M. Hoffman}, title = {Errata Report on {H}erbert {G}oldstein's \textit{Classical Mechanics}, Second Edition}, type = {Technical Memorandum}, number = {ORNL/TM-12176}, institution = {Oak Ridge National Laboratory}, address = {Oak Ridge, Tennessee, USA}, day = 1, month = jan, year = 1993, abstract = {This report describes errors in Herbert Goldstein's textbook \textit{Classical Mechanics}, Second Edition (Copyright 1980, ISBN 0-201-02918-9). Some of the errors in current printings of the text were corrected in the second printing; however, after communicating with Addison Wesley, the publisher for \textit{Classical Mechanics}, it was discovered that the corrected galley proofs had been lost by the printer and that no one had complained of any errors in the eleven years since the second printing. The errata sheet corrects errors from all printings of the second edition.} } @TechReport{Vertenstein_NCAR-CLM3_20040621, author = {Mariana Vertenstein and Keith Oleson and Sam Levis and Forrest Hoffman}, title = {{C}ommunity {L}and {M}odel Version 3.0 ({CLM3.0}) User's Guide}, institution = {National Center for Atmospheric Research}, address = {Boulder, Colorado, USA}, url = {http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/UsersGuide/UsersGuide.pdf}, day = 21, month = jun, year = 2004 } @Article{White:AGU:2004, author = {Michael A. White and Forrest M. Hoffman and William W. Hargrove}, title = {A Strategy for Global Phenological Observatories}, journal = Eos, volume = 85, number = 47, note = {Fall Meet. Suppl., Abstract B44A-02}, month = dec, year = 2004 } @Article{White_GRL_20050218, author = {Michael A. White and Forrest Hoffman and William W. Hargrove and Ramakrishna R. Nemani}, title = {A Global Framework for Monitoring Phenological Responses to Climate Change}, journal = GRL, volume = 32, number = 4, pages = {L04705}, doi = {10.1029/2004GL021961}, day = 18, month = feb, year = 2005, abstract = {Remote sensing of vegetation phenology is an important method with which to monitor terrestrial responses to climate change, but most approaches include signals from multiple forcings, such as mixed phenological signals from multiple biomes, urbanization, political changes, shifts in agricultural practices, and disturbances. Consequently, it is difficult to extract a clear signal from the usually assumed forcing: climate change. Here, using global 8~km 1982 to 1999 Normalized Difference Vegetation Index (NDVI) data and an eight-element monthly climatology, we identified pixels whose wavelet power spectrum was consistently dominated by annual cycles and then created phenologically and climatically self-similar clusters, which we term phenoregions. We then ranked and screened each phenoregion as a function of landcover homogeneity and consistency, evidence of human impacts, and political diversity. Remaining phenoregions represented areas with a minimized probability of non-climatic forcings and form elemental units for long-term phenological monitoring.} } @InProceedings{Xue_LNCS_20090526, author = {Yong Xue and Forrest M. Hoffman and Dingsheng Liu}, title = {{G}eo{C}omputation 2009}, booktitle = {Proceedings of the 9th International Conference on Computational Science ({ICCS 2009})}, editor = {Gabrielle Allen and Jaros{\l}aw Nabrzyski and Edward Seidel and Geert Dick van Albada and Jack Dongarra and Peter M.A. Sloot}, publisher = {Springer-Verlag}, address = {Heidelberg}, series = {Lecture Notes in Computer Science ({LNCS})}, dates = {25--27 May 2009}, location = {Baton Rogue, Louisiana, USA}, volume = 5545, pages = {345--348}, doi = {10.1007/978-3-642-01973-9\_38}, isbn = {978-3-642-01972-2}, day = 26, month = may, year = 2009, abstract = {The tremendous computing requirements of today's algorithms and the high costs of high-performance supercomputers drive us to share computing resources. The emerging computational Grid technologies are expected to make feasible the creation of a computational environment handling many PetaBytes of distributed data, tens of thousands of heterogeneous computing resources, and thousands of simultaneous users from multiple research institutions (Giovanni et al. 2003).} }