peerreviewed_2010.bib

@inproceedings{Hoffman2010,
  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 United States},
  booktitle = {Proceedings of the 2010 IEEE International Geoscience and Remote
	Sensing Symposium (IGARSS 2010), Honolulu, Hawaii (Invited)},
  year = {2010},
  month = {July 25-30 2010},
  doi = {10.1109/IGARSS.2010.5653935},
  file = {pubs/Hoffman_IGARSS_20100725.pdf},
  owner = {jkumar},
  timestamp = {2010.08.21}
}
@conference{Kumar2010,
  author = {Jitendra Kumar and E. Downey Brill and G. Mahinthakumar and Ranji
	Ranjithan},
  title = {Identification of Reactive Contaminant Sources in a Water Distribution
	System under the Conditions of Data Uncertainties},
  booktitle = {World Environmental and Water Resources Congress 2010, Providence,
	Rhode Island},
  year = {2010},
  editor = {Richard N. Palmer},
  volume = {371},
  number = {41114},
  pages = {442-442},
  publisher = {ASCE},
  doi = {10.1061/41114(371)442},
  keywords = {Water distribution systems; Data analysis; Uncertainty principles;
	Water pollution},
  location = {Providence, Rhode Island},
  owner = {jkumar},
  timestamp = {2010.08.21},
  url = {http://link.aip.org/link/?ASC/371/442/1}
}
@conference{Kumar2010a,
  author = {Jitendra Kumar and Sarat Sreepathi and E. Downey Brill and Ranji
	Ranjithan and G. Mahinthakumar},
  title = {Detection of Leaks in Water Distribution System Using Routine Water
	Quality Measurements},
  booktitle = {World Environmental and Water Resources Congress 2010, Providence,
	Rhode Island},
  year = {2010},
  editor = {Richard N. Palmer},
  volume = {371},
  number = {41114},
  pages = {426-426},
  publisher = {ASCE},
  doi = {10.1061/41114(371)426},
  keywords = {Leakage; Water distribution systems; Water quality; Measurement},
  location = {Providence, Rhode Island},
  owner = {jkumar},
  timestamp = {2010.08.21},
  url = {http://link.aip.org/link/?ASC/371/426/1}
}
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@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.}
}
@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 20$^\textnormal{th}$ 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.}
}
@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 20$^\textnormal{th}$ 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.}
}