peerreviewed_2009.bib

@conference{Kumar2009,
  author = {Jitendra Kumar and E. Downey Brill and G Mahinthakumar and Ranji
	Ranjithan},
  title = {Characterizing Reactive Contaminant Sources in a Water Distribution
	System},
  booktitle = {World Environmental and Water Resources Congress 2009, Kansas City,
	Missouri},
  year = {2009},
  editor = {Steve Starrett},
  volume = {342},
  number = {41036},
  pages = {65-65},
  publisher = {ASCE},
  doi = {10.1061/41036(342)65},
  file = {:Publications/Kumar2009.pdf:PDF},
  keywords = {Water pollution; Water distribution systems; Drinking water; Public
	health},
  location = {Kansas City, Missouri},
  owner = {jkumar},
  timestamp = {2009.09.19},
  url = {http://link.aip.org/link/?ASC/342/65/1}
}

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@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
}

@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.}
}

@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.}
}

@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. }
}

@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).}
}