S. R. Alam, J. A. Kuehn, R. F. Barrett, J. M. Larkin, M. R. Fahey, R. Sankaran, and P. H. Worley. Cray XT4: an early evaluation for petascale scientific simulation. In Verastegui:sc07:2007 [Verastegui:sc07:2007], pages 1–12. General Chair-Verastegui, Becky. [ bib | DOI | www: | .pdf ]

The scientific simulation capabilities of next generation high-end computing technology will depend on striking a balance among memory, processor, I/O, and local and global network performance across the breadth of the scientific simulation space. The Cray XT4 combines commodity AMD dual core Opteron processor technology with the second generation of Cray's custom communication accelerator in a system design whose balance is claimed to be driven by the demands of scientific simulation. This paper presents an evaluation of the Cray XT4 using micro-benchmarks to develop a controlled understanding of individual system components, providing the context for analyzing and comprehending the performance of several petascale-ready applications. Results gathered from several strategic application domains are compared with observations on the previous generation Cray XT3 and other high-end computing systems, demonstrating performance improvements across a wide variety of application benchmark problems.

G. Allen, J. Nabrzyski, E. Seidel, G. D. van Albada, J. Dongarra, and P. M. A. Sloot, editors. Computational Science - ICCS 2009, volume 5545/2009 of Lecture Notes in Computer Science. Springer Berlin / Heidelberg, May 2009. [ bib | DOI | www: ]

M. E. Angeles, J. E. Gonzalez, D. J. Erickson III, and J. L. Hernández. Predictions of future climate change in the Caribbean region using global circulation models. Int. J. Climatol., 27(5):555–569, 2007. [ bib | DOI | www: ]

Since the 1800s the global average CO₂ mixing ratio has increased and has been related to increases in surface air temperature (0.6 ± 0.2 ^oC) and variations in precipitation patterns among other weather and climatic variables. The Small Island Developing States (SIDS), according to the 2001 report of the Intergovernmental Panel on Climate Change (IPCC), are likely to be among the most seriously impacted regions on Earth by global climate changes. In this work, three climate change scenarios are investigated using the Parallel Climate Model (PCM) to study the impact of the global anthropogenic CO₂ concentration increases on the Caribbean climate. A climatological analysis of the Caribbean seasonal climate variation was conducted employing the National Center for Environmental Prediction (NCEP) reanalysis data, the Xie-Arkin precipitation and the Reynolds-Smith Sea Surface Temperature (SST) observed data. The PCM is first evaluated to determine its ability to predict the present time Caribbean climatology. The PCM tends to under predict the SSTs, which along with the cold advection controls the rainfall variability. This seems to be a main source of bias considering the low model performance to predict rainfall activity over the Central and southern Caribbean. Future predictions indicate that feedback processes involving evolution of SST, cloud formation, and solar radiative interactions affect the rainfall annual variability simulated by PCM from 1996 to 2098. At the same time two large-scale indices, the Southern Oscillation Index (SOI) and the North Atlantic Oscillation (NAO) are strongly related with this rainfall annual variability. A future climatology from 2041 to 2058 is selected to observe the future Caribbean condition simulated by the PCM. It shows, during this climatology range, a future warming of approximately 1 ^oC (SSTs) along with an increase in the rain production during the Caribbean wet seasons (early and late rainfall seasons). Although the vertical wind shear is strengthened, it typically remains lower than 8 m/s, which along with SST > 26.5 ^oC provides favorable conditions for possible future increases in tropical storm frequency. Copyright ©2006 Royal Meteorological Society

D. A. Bader, editor. Petascale Computing: Algorithms and Applications, volume 1 of Chapman & Hall CRC Computational Science Series. Chapman & Hall CRC Press, Taylor and Francis Group, Dec. 2007. [ bib | http ]

S. E. Bauer, D. L. Wright, D. Koch, E. R. Lewis, R. McGraw, L.-S. Chang, S. E. Schwartz, and R. Ruedy. MATRIX (Multiconfiguration Aerosol TRacker of mIXing state): an aerosol microphysical module for global atmospheric models. Atmos. Chem. Phys., 8(20):6003–6035, 2008. [ bib | http | .pdf ]

A new aerosol microphysical module MATRIX, the Multiconfiguration Aerosol TRacker of mIXing state, and its application in the Goddard Institute for Space Studies (GISS) climate model (ModelE) are described. This module, which is based on the quadrature method of moments (QMOM), represents nucleation, condensation, coagulation, internal and external mixing, and cloud-drop activation and provides aerosol particle mass and number concentration and particle size information for up to 16 mixed-mode aerosol populations. Internal and external mixing among aerosol components sulfate, nitrate, ammonium, carbonaceous aerosols, dust and sea-salt particles are represented. The solubility of each aerosol population, which is explicitly calculated based on its soluble and insoluble components, enables calculation of the dependence of cloud drop activation on the microphysical characterization of multiple soluble aerosol populations.

A detailed model description and results of box-model simulations of various aerosol population configurations are presented. The box model experiments demonstrate the dependence of cloud activating aerosol number concentration on the aerosol population configuration; comparisons to sectional models are quite favorable. MATRIX is incorporated into the GISS climate model and simulations are carried out primarily to assess its performance/efficiency for global-scale atmospheric model application. Simulation results were compared with aircraft and station measurements of aerosol mass and number concentration and particle size to assess the ability of the new method to yield data suitable for such comparison. The model accurately captures the observed size distributions in the Aitken and accumulation modes up to particle diameter 1 μm, in which sulfate, nitrate, black and organic carbon are predominantly located; however the model underestimates coarse-mode number concentration and size, especially in the marine environment. This is more likely due to oversimplifications of the representation of sea salt emissions – sea salt emissions are only calculated for two size classes – than to inherent limitations of MATRIX.

M. L. Branstetter and D. J. Erickson, III. Hydrology in the CCSM3. Presentation, June 2008. 13th Annual CCSM Workshop. [ bib ]

M. L. Branstetter, D. J. Erickson, III, A. Ganguly, S. Khan, G. Kuhn, G. Ostrouchov, and C. T. Fuller. Extreme hydrologic events from an ensemble of CCSM3 climate change simulations. Poster, Jan. 2007. 87th Annual Meeting of the American Meteorological Society. [ bib | http ]

One of the key questions is whether the extremes in weather phenomena such as floods and droughts will increase in the future along with increasing global average temperatures. Daily and monthly results from a set of ensemble simulations from the Community Climate System Model (CCSM3) were analyzed to detect extreme highs and lows over a hundred year period from 2000-2100. The ensemble of simulations was from an IPCC A2 climate change scenario. The number of extreme highs in daily precipitation was significantly higher during the latter part of the simulation period in some regions. This period also showed a significant change in runoff during the later years, wetter some places and drier other places.

M. L. Branstetter, D. J. Erickson, III, A. Ganguly, G. Kuhn, S. Khan, and C. T. Fuller. Extreme hydrologic events in CCSM3. Poster, June 2007. 12th Annual CCSM Workshop. [ bib | .pdf ]

One of the key questions is whether the extremes in weather phenomena such as floods and droughts will increase in the future along with increasing global average temperatures. Daily and monthly results from a set of ensemble simulations from the Community Climate System Model (CCSM3) were analyzed to detect extreme highs and lows over a hundred year period from 2000-2100. The ensemble of simulations was from an IPCC A2 climate change scenario. The number of extreme highs in daily precipitation was significantly higher during the latter part of the simulation period in some regions. This period also showed a significant change in runoff during the later years, wetter some places and drier other places. When combined with population data, the human impact of the precipitation extremes becomes more clear. Highlights of such a study for South America point out certain regions of the continent that could experience particular problems. Preliminary results for the Darfur region of Sudan point out the variation in rainfall and extremes within the region.

M. L. Branstetter, D. J. Erickson, III, J. Hernandez, and R. J. Oglesby. Spatial resolution and precipitation impacts on the magnitude and variability of river discharge in the CCSM3 control simulation. J. Hydrol., 2007. Submitted. [ bib ]

M. L. Branstetter et al. Hydrology in the IPCC simulations. Presentation, June 2006. 11th Annual CCSM Workshop. [ bib ]

P. Cameron-Smith, S. Elliott, C. Chuang, and D. Bergmann. Towards an Earth system model: Validating interactive DMS emissions and the importance of making atmospheric-chemistry interactive. Presentation, 2007 Climate Change Prediction Program (CCPP) Meeting, Sept. 2007. [ bib ]

P. J. Cameron-Smith, P. Connell, C. Chuang, and C. Atherton. SciDAC chem-climate at LLNL. Presentation, June 2007. 12th Annual CCSM Workshop. [ bib ]

S. Chu and S. Elliott. Global sulfur cycle simulation in the Parallel Ocean Program, chapter 5. Volume 3 of Zannetti et al. [Zannetti:esec:2007], 2007. [ bib ]

S. Chu, S. Elliott, and D. Erickson. Basin-scale carbon monoxide distributions in the Parallel Ocean Program. Earth Interact., 11(22):1–30, Jan. 2008. [ bib | DOI | www: ]

As a primary photochemical constituent in upper-ocean and tropospheric geocycling, carbon monoxide is of interest to a variety of global change research communities. Dynamic three-dimensional simulations of its marine concentration patterns, emphasizing Pacific surface waters, are presented. Calculations were driven by nitrogen/iron ecodynamics within the Parallel Ocean Program (POP) transport framework. Photoproduction was estimated following broadband transfer of ultraviolet A radiation down to and penetrating the mixed layer. Quantum efficiency, absorption, the chromophoric fraction of dissolved organics, and related microchemical parameters were all varied, in some cases collectively. Bacterial uptake was parameterized through stages of refinement ranging from a single global average time constant to the application of steady-state zooplanktonic grazing pressure. Major features of basin-spanning ship track data can be reproduced including tropical to gyre and temperate frontal ratios. Evidence for ecosystem structural influence upon the removal kinetics is reviewed and investigated. Polar waters exhibit unique processing modes and the periphery of the ocean requires specialized handling of organic and bacterial behavior. Large-scale budgets are consistent with recent independent determinations both with respect to internal turnover and flux to the atmosphere. A parsimonious mechanism involving optimized yield is recommended for early system model efforts. Areas awaiting improvement include resolution of UV and the segregation of both light-interacting carbon compounds and microbial populations as tracers.

S. Chu, S. M. Elliott, and D. J. Erickson. Carbon monoxide in the Parallel Ocean Program. Eos Trans. AGU, 87(36):Ocean Sci. Meet. Suppl., Abstract OS45B–01, 2006. [ bib | .txt ]

We have developed a module for the incorporation of dissolved trace gases into the Parallel Ocean Program (POP), the marine component of CCSM. Although tested initially on greenhouse and aerosol influencing species such as N2O and DMS, a logical extension of the coding is to carbon monoxide. Its fluxes into the marine troposphere may influence hydroxyl radical levels over large portions of the open ocean. We describe the design, insertion and testing of CO schemes in POP. During photochemical production the dissolved organics act as both major absorbers and as the source of organic functionality. Removal of carbon monoxide seems to be mediated by bacteria but taxa and metabolic requirements are not well characterized. We thus test several distinct loss mechanisms -global average linear terms, Q10 temperature dependence and steady state microbial ecology. The latter involves recognition that the microbes responsible for CO uptake may be under zooplanktonic grazing control. While removal forms are treated as variable between runs, within any one simulation the uncertainty in quantum yield is explored via a replicate strategy. Ten tracers identical except in photolytic release proportionality are carried simultaneously. Validation is conducted for the Pacific Basin because unified ship track data are available (PMEL). We focus comparisons on the longest north/south experiments. It is found that Q10 removal mechanisms may be slightly superior, but grazing controlled bacteria hold advantages as well. There is some indication moving across the basin from east to west that photoproduction slows. This may indicate a decrease in quantum yield associated with dissolved organic aging and/or photobleaching.

Cray User Group. Proceedings of the 49th Cray User Group Conference, Seattle, WA, May 2007. [ bib ]

B. R. de Supinski, J. K. Hollingworth, S. Moore, and P. H. Worley. Results of the PERI survey of SciDAC applications. J. Phys.: Conf. Ser., 78:012027 (5pp), 2007. [ bib | DOI | www: | http | .pdf ]

The Performance Engineering Research Institute (PERI) project focuses on achieving superior performance for Scientific Discovery through Advanced Computing (SciDAC) applications on leadership class machines through cutting-edge research in performance modeling and automated performance tuning. This focus requires coordinated activities to engage SciDAC application teams. The initial application engagement activity was a survey of these teams to determine their performance goals, the criticality of those goals, current performance of their applications, application characteristics relevant to performance and their plans for future optimization. Using a web-based questionnaire, PERI researchers have worked with application developers to provide this information for over twenty-five applications. This paper describes the initial analysis of the application characteristics and performance goals, as well as current and future application engagement activities driven by these results. While the survey was conducted primarily to meet PERI needs, the results represent a snapshot of the state of SciDAC code development and may be of use to the DOE community at large. Overall, the results show that SciDAC application teams are engaged in significant new code development, which will require flexible performance optimization techniques that can improve performance as the applications evolve.

C. Deal, S. Elliott, M. Jin, E. H. Hunke, and M. Maltrud. Large scale modeling of sea ice algal distributions. In Lessons from continuity and change: an international polar year symposium [lccipys:2009]. In Press. [ bib ]

R. E. Dickinson, K. W. Oleson, G. Bonan, P. Thornton, M. Vertenstein, F. Hoffman, Z.-L. Yang, and X. Zeng. The Community Land Model and its climate statistics as a component of the Community Climate System Model. J. Clim., 19(11):2302–2324, June 2006. Special Issue: Community Climate System Model (CCSM). [ bib | DOI | www: ]

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.

J. Drake and P. Jones. Developing models for predictive climate science. SciDAC Rev., 3:44–56, 2007. [ bib | .html | .pdf ]

J. B. Drake. A vertical grid module for baroclinic models of the atmosphere. Technical Report ORNL/TM-2008/085, Oak Ridge National Laboratory, 2008. [ bib ]

The vertical grid of an atmospheric model assigns dynamic and thermodynamic variables to grid locations. The vertical coordinate is typically not height but one of a class of meterological variables that vary with atmospheric conditions. The grid system is chosen to further numerical approximations of the boundary conditions so that the system is terrain following at the surface. Lagrangian vertical coordinates are useful in reducing the numerical errors from advection processes. That the choices will effect the numercial properties and accuracy is explored in this report. A MATLAB class for Lorentz vertical grids is described and applied to the vertical structure equation and baroclinic atmospheric circulation. A generalized meteorolgoical coordinate system is developed which can support σ, isentropic θ vertical coordinate, or Lagrangian vertical coordinates. The vertical atmospheric column is a MATLAB class that includes the kinematic and thermodynamic variables along with methods for computing geopoentials and terms relevant to a 3D baroclinc atmospheric model.

J. B. Drake, P. W. Jones, M. Vertenstein, J. B. White III, and P. H. Worley. Petascale Computing: Algorithms and Applications, chapter Software design for petascale climate science. Volume 1 of Bader [Bader:pcaa:2007], Dec. 2007. [ bib ]

J. B. Drake, P. Worley, and E. D'Azevedo. Spherical harmonic transform algorithms. ACM Trans. Math. Softw., 35(3):1–23, 2008. [ bib | DOI | www: ]

J. K. Dukowicz, S. F. Price, and W. H. Lipscomb. Consistent approximation of ice sheet dynamics from a principle of least action. J. Glaciol., 2009. Submitted. [ bib ]

C. Ehlschlaeger, J. Westervelt, H. Balbach, H. R. Akcakaya, T. Hoctor, C. Goodison, W. W. Hargrove, F. M. Hoffman, W. Rose, and R. C. Lozar. Habitat fragmentation handbook for installation planners: status and options. Technical Report ERDC/CERL TR-06-36, U. S. Army Corps of Engineers, Engineer Research and Development Center, Dec. 2006. [ bib | .pdf ]

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:

⋅ TES habitat background survey

⋅ Army TES Life histories and potential supporting data types

⋅ Description of major Fragmentation initiatives

⋅ Survey of the major Fragmentation modeling techniques

⋅ Evaluation of Data Quality

⋅ Potential inputs for a long term TES monitoring capability

⋅ Recommendations for future directions.

S. Elliott. Marine systems simulation in the Anthropocene, chapter 4. Volume 3 of Zannetti et al. [Zannetti:esec:2007], 2007. [ bib ]

S. Elliott. Photochemistry Research Progress, chapter Marine photochemistry in earth system models, pages 465–477. In Sánchez and Gutierrez [Sanchez:prp:2008], 2008. [ bib ]

S. Elliott. Dependence of DMS global sea-air flux distribution on transfer velocity and concentration field type. J. Geophys. Res., 114:G02001, Apr. 2009. [ bib | DOI | www: | .html ]

Large-scale transport of marine reduced sulfur to the troposphere is a key to climate and global change, due to the influence of dimethyl sulfide (DMS) on aerosol/condensation nucleus fields. The sensitivity of DMS fluxes to sea-air transfer scheme has previously been studied using established climatologies or local simulations. However, planetary level sulfur cycle models are now coming on line, and roughly coincident, eddy correlation measurements indicate that interfacial behavior of the compound may be distinct from less soluble gases. Variation of the overall sulfur flux distribution is explored here for an historical sampling of piston velocities expressed as functions of the reference height wind, plus a composite reflecting the new transfer estimates. Dissolved concentrations are derived alternately from a current generation biogeochemistry model or the standard compilation. Comparisons of simulation and data-driven fields show that both have advantages. Modeling captures fine resolution features along frontal systems and provides a natural, biogeographic extrapolation across the general circulation. Climatology is free from physical or biotic computational biases and also is relatively strongly supported by coastal measurements. Contrast among the piston formulas includes integrated mass transfer differences as large as a factor of two. Working from the composite scheme, potential is demonstrated for improvements to shift marine DMS outputs from the Southern Ocean toward the equator. Complexities deriving from atmospheric stability, bubble enhancement, and surfactant chemistry may temper these results. Global budgets fall within the envelope of earlier work, 15 to 35 Tg S a^-1.

S. Elliott, S. Chu, C. Dean, and D. Erickson. TRACEGAS_MOD: geochemical processing for low concentration volatiles in the CCSM ocean, chapter 8. Volume 3 of Zannetti et al. [Zannetti:esec:2007], 2007. [ bib ]

S. Elliott, S. Chu, and D. Erickson. Contours of simulated marine dimethyl sulfide distributions under variation in a Gabric mechanism. Environmental Modeling and Software, 22(3):349–358, 2007. [ bib | DOI | www: ]

Biogeochemical tracer bins and transformations from an established reduced sulfur cycle mechanism were introduced into the oceanic component of the Community Climate System Model. The resulting global dimethyl sulfide simulation framework was then subjected to variation in plant cell precursor content and the kinetic form of removal terms. Chi square type merit minima were computed analytically along a release rate axis over global, low latitude and localized domains. A band of width 60 degrees centered on the equator proved to be the most effective optimization area because it greatly exceeded resolution of the validation data set but avoided fronts where the driver ecodynamics module overpredicts chlorophyll. Loss terms involving bacterial consumption formulated as bimolecular kinetics and photochemical decay sensitized by dissolved organic matter independently provided superior agreement with data by modulating peaks along the equatorial divergence. Factor of ten reductions in the sulfur precursor content of diatoms or small noncalcite secretors respectively flattened and exaggerated the same features, but intermediate compositions were not tested. The parameter suite of constant intracellular sulfur, second order osmotrophy (microbial uptake) and photochemistry set proportional to photosynthetic radiation is recommended and packaged as a startup mechanism. This particular combination optimizes large-scale reduced sulfur fields across well-understood ecosystems while simultaneously maintaining parsimony. Visualizations from the inverse procedure are offered for multiple mechanisms, as mappings of both normalized deviation and concentration. The value of the rate constant for injection from plant and animal material was often determined to be of the order weeks, consistent with emission via grazing or aging/mortality. Refinement of the model will require linkage to the ecological flows associated with cell disruption, accounting of elemental metabolic stresses which in part govern reduced sulfur storage, addition of true microbial ecology, further studies of open ocean sulfur photochemistry and longer duration/more detailed optimization exercises. A stepwise strategy is outlined for moving through this task list. In next-generation experiments it may prove expedient to fix sulfur content ratios within taxonomic classes while varying the maximum cell content.

S. Elliott, S. Chu, M. Maltrud, and D. Erickson. Sulfur cycling in the Parallel Ocean Program. Presentation, May 2006. 4th international symposium on biological and environmental chemistry of DMS(P) and related compounds, School of Environmental Sciences, University of East Anglia. [ bib | .pdf ]

The Parallel Ocean Program (POP) serves as the marine component of the U.S. Community Climate System Model (CCSM). Ecodynamics and biogeochemistry capabilities have recently been under intense development within POP. Here we describe efforts to include a surface ocean reduced sulfur cycle. Most simulations have been based upon a Gabric-type bins and time constants mechanism, with driver ecological quantities pulled in from a standard carbon/nitrogen/iron biogeochemistry module. Refinements include parameterization of consumer bacterial densities, expression of nitrate/dissolved organic dependence for photolytic dimethyl sulfide loss, apportionment of specialized source species such as the diatoms, coccolithophorids, cyanobacteria, diazotrophs and phaeocystis. Runs have been conducted over the global domain 1) at resolutions ranging from one fifth to three degrees latitude/longitude, 2) for periods of up to one hundred years, 3) in ocean-only mode adopting reanalyzed winds from1950-2000, and 4.) in a coupled-climate version with DMS passing into CCSM atmospheric chemistry modules to influence tropospheric sulfate distributions. A selection of these POP sulfur processing results will be presented for inspection.

D. Erickson, T. J. Blasing, R. T. Mills, F. M. Hoffman, M. T. Devries, Z. Zhu, and S. R. Kawa. Monthly global emissions of anthropogenic CO₂: atmospheric CO₂ transport calculations based on NASA data assimilation. Eos Trans. AGU, 87(52):Fall Meet. Suppl., Abstract A41C–0044, Dec. 2006. [ bib | .txt ]

We present monthly estimates of the global emissions of anthropogenic CO₂. We posit that high temporal estimates of anthropogenic CO₂ fluxes will impact the seasonal cycle of atmospheric CO₂ concentrations and will impact inversion calculations. Implementing a dual harmonic numerical treatment as a function of latitude the annual fluxes are decomposed into monthly flux estimates. Using these monthly flux estimates we then use the NASA PCTM to transport the annual and monthly fluxes in the atmosphere. We find that the use of monthly fluxes makes a significant difference in the seasonal cycle of atmospheric CO₂ in and near those regions where anthropogenic CO₂ is released to the atmosphere. Local variations of 2–6 ppm CO₂ in the seasonal cycle amplitude are simulated. We also find that in the mid latitudes near the sources synoptic scale atmospheric circulations are important in the winter and that boundary layer venting and rectifier effects are more important in the summer. These finding have implications for inverse models that attempt to estimate surface source/sink regions especially when the surface sinks are co-located with regions of strong anthropogenic CO₂ emissions.

D. Erickson and J. Gunson. Comprehensive earth system modeling: Air-sea flux treatments and climate impacts. Presentation, Mar. 2007. Surface Ocean-Lower Atmosphere Study (SOLAS) Open Science Meeting, Xiamen, China. [ bib | .pdf ]

Several new climate, carbon and biogeochemical modelling efforts that require multi-Tera flop computational resources will be discussed within the context of SOLAS related climate science and high performance computing. This session seeks contributions that evaluate and describe next generation Earth system models especially those that include specific biogeochemical processes and feedbacks in the air-sea climate system. Fully-coupled Earth system models –in both the biogeochemical and physical sense– that specifically track particle and trace gas exchange between the ocean and atmosphere, are critical in understanding and predicting future Earth climate. As part of the Climate Modelling in US SOLAS (CLIMIS) projecct and in the UK and EU SOLAS projects we encourage contributions from the the modelling fields of ocean physics, ocean ecosystems, air-sea fluxes and atmosphereic chemistry, radiation and physics. In particular, oceanic ecosystem models that describe and predict the carbon cycle and several other biogeochemical tracers that impact atmospheric chemistry and climate variability are encouraged to be described in this session.

D. J. Erickson, M. L. Branstetter, T. J. Wilbanks, A. R. Ganguly, F. M. Hoffman, A. W. King, L. Buja, and T. S. Panwar. Global climate simulations with the A1FI scenario for 2000-2010: Meltwater temperature and river flow impacts in India. Eos Trans. AGU, 89(23):Jt. Assem. Suppl., Abstract U33C–01, May 2008. [ bib | .txt ]

Climate simulations based on the assumptions implicit in the SRES A1FI scenario for the period 2000-2100 using CCSM3 are analyzed. We find temperature increases of 3-9^oC over Northern India by the end of this century. We will discuss the implications and resulting alterations of the hydrologic cycle as the climate evolves from 2000-2100. In particular, we will assess the changes in the surface latent and sensible heat energy budget, the Indian regional water budgets including trends in the timing and duration of the Indian monsoon and the resulting impacts on mean river flow and hydroelectric power generation potential. These analyses will also be examined within the context of heat index, droughts, floods and related estimates of societal robustness and resiliency. We will compare our new insights with the existing literature. Climate simulations based on the SRES A2 and B1 scenarios forced with land cover have indicated increased cloud cover and precipitation, resulting in decreased incident radiation and higher latent heat fluxes, in India during June, July and August by 2050 (Feddema et al., 2005). Analyses of historical records in the context of the Indian Monsoon Rainfall (IMR) have suggested an evolving relation of IMR with natural climate variability caused by El Nino events (Krishna Kumar et al., 2006), studied the combined effects of natural climate variability and global warming (Kripalini et al., 2003) on IMR, as well as demonstrated an increasing trend of extreme rain events in a warming environment (Goswami et al., 2006). In addition, the vulnerability of the Indian agriculture sector to climate change was analyzed and mapped at district-levels by combining with multiple global stressors (O'Brien et al., 2004). [[References::: (1) Feddema, J.J., Oleson, K.W., Bonan, G.B., Mearns, L.O., Buja, L.E., Meehl, G.A., and W.M. Washington (2005): The importance of land-cover change in simulating future climates, Science, 310 (5754): 1674-1678, 9 December.... (2) Goswami, B.N., Venugopal, V., Sengupta, D., Madhusoodanan, and P.K. Xavier (2006): Increasing trend of extreme rain events over India in a warming environment, Science, 314 (5804): 1442-1445, 1 December.... (3) Kripalini, R.H., Kulkarni, A., Sabade, S.S., and M.L. Khandekar (2003): Indian monsoon variability in a global warming scenario, Natural Hazards, 29: 189-206.... (4) Krishna Kumar, M., Rajagolapan, B., Hoerling, M., Bates, G., and M. Cane (2006): Unraveling the mystery of Indian Monsoon failure during El Nino, Science, 314 (5796): 115-119, 6 October.... (5) O'Brien, K., Leichenko, R., Kelkar, U., Venema, H., Aandhal, G., Tompkins, H., Javed, A., Bhadwal, S., Barg, S., Nygaard, L., and J. West (2004): Mapping vulnerability to multiple stressors: climate change and globalization in India, Global Environmental Change, 14: 303-313.]]

D. J. Erickson, A. Ganguly, K. Steinhaeuser, M. Branstetter, R. Oglesby, F. Hoffman, and L. Buja. Extreme climate event trends: the data mining and evaluation of the A1FI scenario for 2000–2010. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract H12B–03 INVITED, Dec. 2008. [ bib | .txt ]

We will discuss the implications and resulting alterations of the hydrologic cycle as Earth climate evolves from 2000-2100. Climate simulations based on the assumptions implicit in the A1FI scenario for the period 2000- 2100 using CCSM3 are analyzed. In particular, we will assess the changes in the surface latent and sensible heat energy budget, the Indian regional water budgets including trends in the timing and duration of the Indian monsoon and the resulting impacts on mean river flow and hydroelectric power generation potential. These analyses will also be examined within the context of heat index, droughts, floods and related estimates of societal robustness and resiliency. We will interpret these new A1FI results within the context of the previous climate simulations based on the SRES A2 and B1 scenarios forced with land cover and atmospheric CO₂. Analyses of historical records in the context of the Indian Monsoon Rainfall (IMR) have suggested an evolving relation of IMR with natural climate variability caused by El Nino events. We will report on the combined effects of natural climate variability and global warming on IMR and assess the trend of extreme rain and temperature events in a warming environment.

D. J. Erickson, III, R. T. Mills, J. Gregg, T. J. Blasing, F. M. Hoffman, R. J. Andres, M. Devries, Z. Zhu, and S. R. Kawa. An estimate of monthly global emissions of anthropogenic CO₂: Impact on the seasonal cycle of atmospheric CO₂. J. Geophys. Res., 113:G01023, Mar. 2008. [ bib | DOI | www: | http ]

Monthly estimates of the global emissions of anthropogenic CO₂ are presented. Approximating the seasonal CO₂ 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 CO₂ flux estimates are then used to model atmospheric CO₂ 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 CO₂ in and near those regions where anthropogenic CO₂ is released to the atmosphere. Local variations of 2–6 ppmv CO₂ 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 CO₂ emissions.

D. J. Erickson, III, R. T. Mills, J. S. Gregg, T. J. Blasing, F. M. Hoffman, R. J. Andres, M. Devries, Z. Zhu, and S. R. Kawa. Estimated monthly global emissions of anthropogenic CO₂ and their impact on calculated atmospheric CO₂. Presentation, May 2007. 2007 ESRL/NOAA Global Monitoring Annual Conference. [ bib | .pdf ]

Estimates of monthly fossil-fuel carbon emissions for each 1-degree gridsquare of the earth's surface are used in the context of meteorological fields from the NASA GEOS-4 data assimilation system to investigate the influence of seasonal emissions cycles on atmospheric concentrations and transport of CO₂. We find that the use of monthly resolved fluxes makes a significant difference in the seasonal cycle of atmospheric CO₂ in and near those regions where anthropogenic CO₂ is released to the atmosphere. Local variations of 2–6 ppmv CO₂ in the seasonal cycle amplitude are simulated, and 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 mid latitudes 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 to estimate surface source/sink regions especially when the surface sinks are colocated with regions of strong anthropogenic CO₂ emissions.

D. J. Erickson, III, R. J. Oglesby, S. Elliott, and F. M. Hoffman. Peta-scale climate modeling: Biogeochemical and financial feedbacks. In Voinov et al. [Voinov:iEMSs:2006]. Available on CD-ROM. [ bib | http ]

Several new climate, carbon and biogeochemical modeling results that require multi-Tera flop computational resources will be discussed within the context of climate science and high performance computing. A new fully coupled Earth system model, in both the biogeochemical and physical sense, that specifically tracks CO₂ and dimethyl sulfide exchange between the ocean, land and atmosphere systems will be described. As an example of the utility of next generation Earth system models, a series of specific biogeochemical processes and feedbacks in the climate system are examined. A multi-variate clustering algorithm to assess terrestrial ecosystem niche evolution in a warming greenhouse world will be presented. Essentially, the spatial distribution of concurrent changes in temperature, precipitation, radiation and soil moisture drive ecosystem niche evolution in complex and interactive ways. Using climate prediction simulations for 1870-2100, ecosystem niche evolution at mid-high latitudes will be presented. Oceanic applications of this new clustering technique will be explored. Consistent with the theme of fully coupled, comprehensive Earth system model creation, a highly detailed numerical model of energy usage is grafted to a GCM. This energy use and resource allocation model is driven with GCM simulated climate variables from 2000-2025 so as to predict the financial impacts and feedbacks of global warming.

D. J. Erickson III. Climate/biogeochemical implications of sea-air gas transfer: background and computational testing, chapter 11. Volume 3 of Zannetti et al. [Zannetti:esec:2007], 2007. [ bib ]

D. J. Erickson III, T. J. Blasing, R. T. Mills, F. M. Hoffman, M. T. Devries, Z. Zhu, and S. R. Kawa. Monthly global emissions of anthropogenic CO₂: the impact on a NASA transport model. Presentation, June 2008. 13th Annual CCSM Workshop. [ bib ]

D. J. Erickson III, T. J. Blasing, R. T. Mills, F. M., M. T. Devries, Z. Zhu, and S. R. Kawa. Monthly global emissions of anthropogenic CO₂: atmospheric CO₂ transport calculations based on NASA data assimilation. Poster, Joint Workshop on NASA Biodiversity, Terrestrial Ecology, and Related Applied Sciences, Adelphi, MD, Aug. 2006. [ bib | .pdf ]

We present monthly estimates of the global emissions of anthropogenic CO₂. We posit that high temporal estimates of anthropogenic CO₂ fluxes will impact the seasonal cycle of atmospheric CO₂ concentrations and will impact inversion calculations. Implementing a dual harmonic numerical treatment as a function of latitude the annual fluxes are decomposed into monthly flux estimates. Using these monthly flux estimates we then use the NASA PCTM to transport the annual and monthly fluxes in the atmosphere. We find that the use of monthly fluxes makes a significant difference in the seasonal cycle of atmospheric CO₂ in and near those regions where anthropogenic CO₂ is released to the atmosphere. Local variations of 2–6 ppm CO₂ in the seasonal cycle amplitude are simulated. We also find that in the mid latitudes near the sources synoptic scale atmospheric circulations are important in the winter and that boundary layer venting and rectifier effects are more important in the summer. There are clear transitions over the seasonal cycle between these two modes of boundary layer mixing. These findings have implications for inverse models that attempt to estimate surface source/sink regions especially when the surface sinks are co-located with regions of strong anthropogenic CO₂ emissions.

D. J. Erickson III et al. A coupled biogeochemistry – physical climate simulation. Presentation, June 2006. 11th Annual CCSM Workshop. [ bib ]

D. J. Erickson III, J. Foley, F. M. Hoffman, A. W. King, and A. Mirin. Global coupled climate-carbon models: CCSM3 coupled with the Integrated Biosphere Simulator (IBIS). Presentation, Feb. 2006. Association for the Advancement of Science (AAAS) Annual Meeting, St. Louis, MO. [ bib | http ]

C. T. Fuller, A. Sabesan, S. Khan, A. R. Ganguly, D. J. Erickson, and G. Ostrouchov. Quantification and visualization of the human impacts of anticipated precipitation extremes in South America. Eos Trans. AGU, 87(52):Fall Meet. Suppl., Abstract GC44A–03, Dec. 2006. [ bib | .txt ]

The research described here quantifies and visualizes the human impacts of extreme events, which in turn can lead to enhanced disaster readiness levels as well as response or mitigation strategies. Specifically, we investigate the space-time impact of anticipated precipitation extremes on human population in South America. The research attempts to integrate two recent and ongoing lines of research. In the first study (Sabesan et al., 2006; Abercrombie et al, 2006) LandScan ™high-resolution population data sets were used to develop threat metrics in space and time. In the second study (Khan et al, 2006; Kuhn and Ganguly, 2006), grid-based observations of precipitation time series in South America were utilized to quantify the probability of precipitation extremes in space and time and define a geo-referenced "extremes volatility ratio" (EVR) for unanticipated, or the "truly unusual", extremes. Here we define an "extremes volatility index" (EVI) which scales from zero to unity and provides an anticipated measure of surprise corresponding to the truly unusual extremes. An EVI of zero indicates no possibility of surprise with the truly unusual extremes statistically identical to the "typical extremes", or the extremes considered, for example, in engineering design. We investigate the EVI in conjunction with maps for ambient population in South America obtained from a high- resolution global population database called LandScan ™to produce a "human risk index" (HRI) in space and time. The EVI is roughly interpreted as a probability number which is multiplied with the population at each grid in space and time to obtain a measure of risk. Future research needs to explore measures of risk that consider other costs of disasters, for example impacts on critical infrastructures. A geo-referenced index, the "disaster impact index" (DII) is proposed. The DII at each grid is computed by dividing the HRI with the Gross Domestic Product (GDP) for each country. The GDP is utilized for each country as a proxy for the ability of a country to respond to disasters. Future research needs to develop more robust measures for disaster response which include the availability of disaster warning and management systems, economic development and other geo-political considerations. The research methodologies developed here can be generalized to develop threat profiles for extreme events in other disciplines.

A. R. Ganguly, M. L. Branstetter, K. J. Steinhaeuser, D. J. Erickson, III, E. S. Parish, and N. Singh. Global warming impacts on regional hydrology and water resources. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract H21E–0870, Dec. 2008. [ bib | .txt ]

The Community Climate System Model version 3 (CCSM3) outputs for temperature, precipitation, land surface wetness (precipitation less evapotranspiration) and stream flow are analyzed at regional and decadal scales to determine the plausible impacts of global warming on regional hydrology and water resources. Precipitation events and stream flow are analyzed to investigate anticipated changes in the intensity, duration and frequency of extreme events, while land surface wetness is analyzed in conjunction with other variables to anticipate extreme water-related stresses. In particular, changes in projected global population and water availability are compared at high space-time precisions to develop hotspots for water scarcity. Uncertainties in temperature and precipitation are assessed by comparing the CCSM3 model outputs with reanalysis data, which are in turn based on observations and available from the National Centers for Environmental Prediction (NCEP). The possibility of developing uncertainty characterizations for projected stream flow is explored.

A. R. Ganguly, S. Khan, G. Kuhn, Y. Fang, D. J. Erickson III, M. L. Branstetter, and G. Ostrouchov. Climate change, rainfall extremes, and population at risk. Presentation at 22nd Conference on Hydrology, 88th Annual Meeting of AMS, Jan. 2008. [ bib | http ]

The hypothesis that climate change may enhance the intensity, duration, and frequency of precipitation extremes needs to be carefully studied for future adaptation policies or flood disaster mitigation strategies. Several aspects of this hypothesis are examined here in the context of precipitation extremes in South America. The volatility of precipitation extremes is quantified from observations to obtain the natural variability and geospatial-temporal trends of the extremes. The geospatial-temporal extremes dependence structures estimated from observed data and climate model simulations are compared with each other to develop an understanding of the ability of the climate models to simulate precipitation extremes. The ability to utilize the statistical properties of the precipitation extremes, in conjunction with precise estimates of population counts, to obtain objective and high resolution risk maps at continental scales for disasters potentially caused by the precipitation extremes, is illustrated. The limitations of this study and the outstanding challenges are discussed. New opportunities for future research are suggested, with a particular emphasis on novel and emerging tools in high-performance computing and knowledge discovery from massive geographic data. The results presented here are based on prior and ongoing work at the Computational Sciences and Engineering Division of the Oak Ridge National Laboratory.

A. R. Ganguly, E. S. Parish, N. Singh, K. Steinhaeuser, D. J. Erickson III, M. Branstetter, A. W. King, and E. J. Middleton. Regional and decadal analysis of climate change induced extreme hydro-meteorological stresses informs adaptation and mitigation policies. Presentation at 21st Conference on Climate Variability and Change, 89th Annual Meeting of the American Meteorological Society, Jan. 2009. [ bib | http | .pdf ]

Climate change projections corresponding to the IPCC SRES A1FI scenario obtained from the integrated CCSM3 earth systems model were analyzed at regional and decadal scales to develop projections of extreme hydro-meteorological stresses. The extreme stresses considered in this study include major decadal or regional changes in temperatures or precipitation patterns, regional co-occurrence of increased temperature and reduced precipitation, reduction in soil moisture and stream flows, as well as increase in the intensity, duration or frequency of extreme events like heat waves, severe droughts, rainfall extremes, significant storms and possible floods. The analyses consider population projections from the A1FI scenario and produce anticipatory insights which are expected to be relevant for impacts on water resources, natural hazards, critical infrastructures, agriculture and nutritional resources, energy usage and regional tensions. While precise projections were developed for the entire globe, the focus was on detailed analyses of specific regions which represent either the top emitters of greenhouse gases or are among the most vulnerable to climate change impacts. The analysis was developed for the entire 21st century; however, the focus was on an adaptation scenario based on the state of the world in 2050 and a mitigation scenario based on the state of the world in 2100. The study led to both confirmation and refinement of existing knowledge and development of new insights. The methodologies used for the analysis were drawn from the geographic information sciences, extreme value theory, and geospatial-temporal data mining.

One part of our analyses considered grid-based decadal monthly averages. Thus, for each CCSM3 model output grid, we considered the average value for an entire month like January or July for each decade (e.g., "current" decade from 2000 to 2009, or "2050" decade from 2045-2055, or "2100" decade from 2090-2099) and then calculated the difference of the future decadal averages compared to the current decadal average. The globally average temperature for January increased by 2.29 degrees Celsius with a standard deviation of 2.2 in 2050 and by 5.7 degrees with a standard deviation of 5.9 in 2100. The corresponding numbers for July were 2 degrees average and 1 degree standard deviation in 2050 and 4 degrees average and 2 degree standard deviation in 2100. In the northern hemisphere, the mean summer (July) and winter (January) temperatures for the study regions (e.g., US, Europe, China and India) showed significant increase. In China, the average temperatures in the Tibetan plateau appears to rise above freezing, which may have serious implications in terms of de-glaciation and drastic longer-term reductions in the headwaters of the rivers that eventually cause the mega-deltas of the Indian sub-continent and eastern China. The average wetness of the land decreases by about 4 cm in July in East China and about 7 cm in eastern China. These may lead to extreme stresses on water and food resources and agriculture in the populated and cultivated regions of eastern China. Winter temperatures in most of the European Union appear to grow milder. However, extreme stresses in Europe, especially in the south, are likely from increased summer temperatures of 8 to 9 degrees Celsius in the heart of the European Union, specifically Austria, Balkans and Italian Alps, and about 6 to 7 degrees in Spain and most of France and Germany, in the 2100s. These levels of temperature increase imply tropical or sub-tropical summers in large parts of Europe as well as an intensification of heat waves, which agree with prior projections (Meehl and Tebaldi, 2004: Science, 305, 5686). The entire European Union appears to become drier on the average, with reduced summer precipitation, reduced soil moisture in the summer and reduced annual stream flows. The significant heating combined with drying may lead to additional stresses on water, vegetation and agriculture. In addition to hazards related to heat waves, significant stress on the energy sector due to air-conditioner use is likely. In the western United States (nearly a third to a half of the continental US), summer (July) temperatures are expected to rise by 4 to 5 degree Celsius in July on the average by 2050 and 6 to 8 degrees by 2100. The average summer precipitation reduces significantly in the western United States in roughly the same region where the increase in temperature occurs. The annual summer stream flow and the soil moistures reduce significantly in the summer across the continental US. Extreme water-related stress is expected in the Western United States, which confirms recent insights (Barnett et al., 2008: Science, 319, 5866). In the Indian sub-continent, winter (January) temperatures increase much more significantly than summer (July). However, the more extreme stresses will likely be caused by the significant warming in the north and northwest parts of India as well as in the Himalayas and the Tibetan plateau. Enhanced snowmelt may cause additional stream flow initially but de-glaciation would likely reduce runoff significantly in the long run. The monsoon rainfall amount in July shows an average increase in the eastern part of South India, Bay of Bengal and east central portions but a significant decrease in the Arabian Sea on the north-western part of the southern Deccan peninsula. Extreme storms increase in several parts of India. Overall, the insights appear to corroborate and/or complement the insights obtained from observations by previous researchers, specifically, decrease in total monsoon rainfall but increase in extremes (Goswami et al., 2006: Science, 314, 5804).

The regional and decadal changes in climate will be mostly felt on the regional water resources as well as water-related infrastructures. In addition, agriculture and food sectors will be impacted, as well as energy consumption and management. Natural hazards will cause strains on humanitarian relief infrastructures while water-related regional tensions will likely increase. Adaptation and mitigation decisions need to consider the impacts of regional climate change on projected population and demographic distributions as well as future technological and economic change which may significantly impact vulnerabilities and resilience. The guidance developed from these analyses was used in a climate change wargame organized by the Center for a New American Security (CNAS) in July 2008.

A. Gettelman, H. Morrison, and S. J. Ghan. A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, version 3 (CAM3). Part II: single-column and global results. J. Clim., 21(15):3660–3679, Aug. 2008. [ bib | DOI | www: ]

The global performance of a new two-moment cloud microphysics scheme for a general circulation model (GCM) is presented and evaluated relative to observations. The scheme produces reasonable representations of cloud particle size and number concentration when compared to observations, and it represents expected and observed spatial variations in cloud microphysical quantities. The scheme has smaller particles and higher number concentrations over land than the standard bulk microphysics in the GCM and is able to balance the top-of-atmosphere radiation budget with 60% the liquid water of the standard scheme, in better agreement with retrieved values. The new scheme diagnostically treats both the mixing ratio and number concentration of rain and snow, and it is therefore able to differentiate the two key regimes, consisting of drizzle in shallow, warm clouds and larger rain drops in deeper cloud systems. The modeled rain and snow size distributions are consistent with observations.

S. J. Ghan and R. C. Easter. Impact of cloud-borne aerosol representation on aerosol direct and indirect effects. Atmos. Chem. Phys., 6(12):4163–4174, 2006. [ bib | http | .pdf ]

Aerosol particles attached to cloud droplets are much more likely to be removed from the atmosphere and are much less efficient at scattering sunlight than if unattached. Models used to estimate direct and indirect effects of aerosols employ a variety of representations of such cloud-borne particles. Here we use a global aerosol model with a relatively complete treatment of cloud-borne particles to estimate the sensitivity of simulated aerosol, cloud and radiation fields to various approximations to the representation of cloud-borne particles. We find that neglecting transport of cloud-borne particles introduces little error, but that diagnosing cloud-borne particles produces global mean biases of 20% and local errors of up to 40% for aerosol, droplet number, and direct and indirect radiative forcing. Aerosol number, aerosol optical depth and droplet number are significantly underestimated in regions and seasons where and when wet removal is primarily by stratiform rather than convective clouds (polar regions during winter), but direct and indirect effects are less biased because of the limited sunlight there and then. A treatment that predicts the total mass concentration of cloud-borne particles for each mode yields smaller errors and runs 20% faster than the complete treatment. The errors are much smaller than current estimates of uncertainty in direct and indirect effects of aerosols, which suggests that the treatment of cloud-borne aerosol is not a significant source of uncertainty in estimates of direct and indirect effects.

S. J. Ghan and R. A. Zaveri. Parameterization of optical properties for hydrated internally mixed aerosol. J. Geophys. Res., 112:D10201, May 2007. [ bib | DOI | www: | http ]

The optical properties of an internally mixed aerosol with a lognormal size distribution can be approximated in terms of analytic functions of the wet surface mode radius with coefficients that can be related to the wet refractive index. The wet radius is calculated from the dry radius and relative humidity using either the Köhler theory or the MOSAIC thermodynamic model. The hydration state of the aerosol in the hysteresis region between the crystallization and deliquescence relative humidities is diagnosed by comparing the aerosol water from the previous time step with the current water content of the hydrated aerosol. The wet refractive index is estimated from the volume fractions and refractive indices of all components of the aerosol, including water, using volume mixing for soluble components and an effective medium approximation for the insoluble components. The parameterization is evaluated by comparing with Mie solutions for ammonium sulfate, black carbon, and a 50:50 mixture for a wide range in size distributions and relative humidity. Errors are usually less than 20% and are less then 30% for all conditions except when absolute values are small. The parameterization is suitable for any aerosol model that uses lognormal size distributions composed of internal mixtures of multiple aerosol components.

S. W. Hadley, D. J. Erickson III, C. T. Broniak, and T. J. Blasing. Responses of energy use to climate change: A climate modeling study. Eos Trans. AGU, 87(52):Fall Meet. Suppl., Abstract B53E–08, Dec. 2006. [ bib | .txt ]

Using a general-circulation climate model to drive an energy-use model, we projected changes in USA energy-use and in corresponding fossil-fuel CO₂ emissions through year 2025 for a low (1.2^oC) and a high (3.4^oC) temperature response to CO₂ doubling. The low-ΔT scenario had a cumulative (2003-2025) energy increase of 1.09 quadrillion Btu (quads) for cooling/heating demand. Northeastern states had net energy reductions for cooling/heating over the entire period, but in most other regions energy increases for cooling outweighed energy decreases for heating. The high-ΔT scenario had significantly increased warming, especially in winter, so decreased heating needs led to a cumulative (2003-2025) heating/cooling energy decrease of 0.82 quads. In both scenarios, CO₂ emissions increases from electricity generation outweighed CO₂ emissions decreases from reduced heating needs. The results reveal the intricate energy-economy structure that must be considered in projecting consequences of climate warming for energy, economics, and fossil-fuel carbon emissions.

S. W. Hadley, D. J. Erickson III, J. L. Hernandez, C. T. Broniak, and T. J. Blasing. Responses of energy use to climate change: A climate modeling study. Geophys. Res. Lett., 33:L17703, Sept. 2006. [ bib | DOI | www: | http ]

Using a general-circulation climate model to drive an energy-use model, we projected changes in USA energy-use and in corresponding fossil-fuel CO₂ emissions through year 2025 for a low (1.2^circC) and a high (3.4^oC) temperature response to CO₂ doubling. The low-ΔT scenario had a cumulative (2003–2025) energy increase of 1.09 quadrillion Btu (quads) for cooling/heating demand. Northeastern states had net energy reductions for cooling/heating over the entire period, but in most other regions energy increases for cooling outweighed energy decreases for heating. The high-ΔT scenario had significantly increased warming, especially in winter, so decreased heating needs led to a cumulative (2003–2025) heating/cooling energy decrease of 0.82 quads. In both scenarios, CO₂ emissions increases from electricity generation outweighed CO₂ emissions decreases from reduced heating needs. The results reveal the intricate energy-economy structure that must be considered in projecting consequences of climate warming for energy, economics, and fossil-fuel carbon emissions.

W. W. Hargrove and F. M. Hoffman. Multivariate geographic clustering as a basis for ecoregionalization in the environmental sciences. Eos Trans. AGU, 87(52):Fall Meet. Suppl., Abstract IN41C–02 INVITED, Dec. 2006. [ bib | .txt ]

Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics, and solar inputs has been used to produce sets of quantitative ecoregion maps for the conterminous United States and the world at several levels of division. The coarse ecoregion divisions accurately capture intuitively-understood regional environmental differences, whereas the finer divisions highlight local condition gradients and ecotones. Such statistically-generated ecoregions can be produced based on user-selected continuous variables, allowing customized regions to be delineated for any specific problem. For example, 20 geographic domains having a similar climate were identified for the National Ecological Observatory Network (NEON), based on nine ecologically relevant climatic variables, including temperature, precipitation, solar radiation, and plant-available soil moisture at 1 sq km resolution. Because the ecoregion classification is quantitative, it can provide a basis for additional types of analyses. A red-green-blue visualization based on the first three Principal Component axes of ecoregion centroids indicates with color the relative combination of environmental conditions found within each ecoregion. Colors show the similarity of environmental conditions across regions. 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.

W. W. Hargrove, J. Spruce, G. Gasser, F. M. Hoffman, and D. Lee. A new national MODIS-derived phenology data set every 16 days, 2002 through 2006. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract B51B–0373, Dec. 2008. [ bib | .txt ]

A new national phenology data set has been developed, comprised of a series of seamless 231m national maps, every 16 days from 2001 through 2006. The data set was developed jointly by the Eastern Forest Environmental Threat Assessment Center (EFETAC) of the USDA Forest Service, and contractors of the NASA Stennis Space Center. The data are available now for dissemination and use. The first half of the National Phenology Data Set is the cumulative area under the NDVI curve since Jan 1, and increases monotonically every 16 days until the end of the year. These cumulative data values "latch" in the event of clouds or snow, remaining at the value when we last saw this cell. The second half is a set of diagnostic parameters fit to the annual NDVI function. The spring minimum, the 20% rise, the 80% rise, the leaf-on maximum, the 80% fall, the 20% fall, and the trailing fall minimum are determined for each map cell. For each parameter, we produce both a national map of the NDVI value, and a map of the day-of-year when that NDVI value was reached. Length of growing season, as the difference between the spring and fall 20% DOYs, and date of middle of growing season can be mapped as well. The new dataset has permitted the development of a set of national phonological ecoregions, and has also proven useful for mapping Gypsy Moth defoliation, simultaneously delineating the aftermath of three Gulf Coast hurricanes, and quantifying suburban/ex-urban development surrounding metro Atlanta.

J. L. Hernandez, J. Srikishen, D. J. Erickson III, R. Oglesby, and D. Irwin. A regional climate study of Central America using the MM5 modeling system: results and comparison to observations. Int. J. Climatol., 26(15):2161–2179, July 2006. [ bib | DOI | www: | http ]

The Mesoscale Modeling system, version 3.6 (MM5) regional modeling system has been applied to Central America and has been evaluated against National Oceanic and Atmospheric Administration/National Climatic Data Center (NOAA/NCDC) daily observations and the Global Precipitation Climatology Project (GPCP) precipitation data. We compare model results and observations for 1997 and evaluate various climate parameters (temperature, wind speed, precipitation and water vapor mixing ratio), emphasizing the differences within the context of the station dependent geographical features and the land use (LU) categories. At 9 of the 16 analyzed stations the modeled temperature, wind speed and vapor mixing ratio are in agreement with observations with average model-observation differences consistently lower than 25%. MM5 has better performance at stations strongly impacted by monsoon systems, regions typified by low topography in coastal areas and areas characterized by evergreen, broad-leaf and shrub land vegetation types. At four stations the model precipitation is about a factor of 3-5 higher than the observations, while the simulated wind is roughly twice what is observed. These stations include two inland stations characterized by croplands close to water bodies; one coastal station in El Salvador adjacent to a mountain-based cropland area and one station at sea-level. This suggests that the model does not adequately represent the influence of topographic features and water bodies close to these stations. In general, the model agrees reasonably well with measurements and therefore provides an acceptable description of regional climate. The simulations in this study use only two seasonal maps of land cover. The main model discrepancies are likely attributable to the actual annual cycle of land-atmosphere vapor and energy exchange that has a temporal scale of days to weeks. These fluxes are impacted by surface moisture availability, albedo and thermal inertia parameters. Copyright ©2006 Royal Meteorological Society.

F. Hoffman. The future of HPC. Linux Magazine, 8(10):46–48, Oct. 2006. [ bib | http ]

F. Hoffman. The global arrays toolkit. Linux Magazine, 8(7):42–44, July 2006. [ bib | http ]

F. Hoffman. Global arrays toolkit, part three. Linux Magazine, 8(9):40–43, 53, Sept. 2006. [ bib | http ]

F. Hoffman. Global arrays toolkit, part two. Linux Magazine, 8(8):48–51, 59, Aug. 2006. [ bib | http ]

F. Hoffman, I. Fung, J. Randerson, P. Thornton, J. Foley, C. Covey, J. John, S. Levis, W. M. Post, M. Vertenstein, R. C. Stöockli, S. Running, F. A. Heinsch, D. Erickson, and J. Drake. Terrestrial biogeochemistry in the community climate system model (CCSM). J. Phys.: Conf. Ser., 46:363–369, 2006. [ bib | DOI | www: | http | .pdf ]

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 (C⁴MIP) 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, Principal Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory.

F. M. Hoffman. Terrestrial biogeochemistry in CCSM. Presentation, June 2006. 11th Annual CCSM Workshop. [ bib ]

F. M. Hoffman, C. C. Covey, I. Y. Fung, J. T. Randerson, P. E. Thornton, Y.-H. Lee, N. A. Rosenbloom, R. C. Stöckli, S. W. Running, D. E. Bernholdt, and D. N. Williams. Results from the Carbon-Land Model Intercomparison Project (C-LAMP) and availability of the data on the Earth System Grid (ESG). J. Phys.: Conf. Ser., 78:012026, (8pp), 2007. [ bib | DOI | www: | http ]

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.

F. M. Hoffman, I. Fung, J. Randerson, P. Thornton, R. Stöckli, F. Heinsch, S. Running, K. Hibbard, J. John, C. Covey, J. Foley, W. M. Post, W. W. Hargrove, D. J. Erickson III, and N. Mahowald. Preliminary results from the CCSM Carbon-Land Model Intercomparison Project (C-LAMP). Eos Trans. AGU, 87(52):Fall Meet. Suppl., Abstract B51C–0316, Dec. 2006. [ bib | .txt ]

The Biogeochemistry Working Group for the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) has initiated an intercomparison of terrestrial biosphere models running within the CCSM framework. Called the CCSM Carbon-Land Model Intercomparison Project (C-LAMP), its purpose is to allow the U.S. scientific community to evaluate the performance of biogeochemical cycling models within CCSM and to identify the most important processes for inclusion in a biosphere model participating in simulations supporting the IPCC Fifth Assessment Report (AR5). Three terrestrial biogeochemistry modules coupled to CCSM—CLM3-CASA', CLM3-CN, and LSX-IBIS—will be evaluated following a set of carefully crafted experiments that build upon the C⁴MIP Phase 1 protocol. In Experiment 1, the models will be forced with an improved NCAR/NCAR reanalysis data set, while in Experiment 2, the models will be coupled to the Community Atmosphere Model Version 3 (CAM3) with carbon, water, and energy exchanges over the 20th century. In order to quickly verify and validate the performance of these biogeochemistry models against high quality observations, a set of offline runs for Fluxnet tower sites have been performed using observed meteorology. Certain biogeochemical, hydrological, physiological, and radiation fields have been saved hourly for intercomparison across models and with high frequency tower measurements. An analysis of the offline flux tower runs will be presented along with preliminary results from the global experiments run within the CCSM framework. Model results will be made available by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) via the Earth System Grid (ESG), and this presentation will include an invitation for community participation in the analysis and evaluation of the model results. C-LAMP is a subproject of the Computational Climate Science End Station headed by Dr. Warren Washington, using computing resources at the National Center for Computational Sciences (NCCS).

F. M. Hoffman, I. Y. Fung, W. M. Post, and D. J. Erickson III. Recent results from coupled climate/carbon-cycle models in CCSM3. In Voinov et al. [Voinov:iEMSs:2006]. Available on CD-ROM. [ bib | http ]

Two terrestrial biogeochemistry modules (CN by Thornton and CASA' by Fung, et al.) have been coupled to the Community Land Model Version 3 (CLM3), the land component model contained in the Community Climate System Model Version 3 (CCSM3). A third terrestrial biogeochemistry module called IBIS (the Integrated Biosphere Simulator) by Foley, et al., has also been coupled to CCSM3 by Mirin, et al., and will be used to further explore land-atmosphere interactions specific to the global carbon cycle within the CCSM framework. A detailed model intercomparison project has been undertaken by the CCSM Biogeochemistry Working Group to elucidate the differences among these biogeochemistry modules in an effort to understand the terrestrial processes important to modeling the carbon cycle in a fully coupled Earth system model. It is expected that this project will result in a terrestrial model for use in future IPCC simulations. Presented will be early results from offline and partially coupled simulations of these terrestrial biogeochemistry modules with and without land cover change, fossil fuel emissions, and ocean carbon flux forcings over the 19th and 20th centuries.

F. M. Hoffman, W. W. Hargrove, R. T. Mills, S. Mahajan, D. J. Erickson, and R. J. Oglesby. Multivariate spatio-temporal clustering (MSTC) as a data mining tool for environmental applications. In Sànchez-Marrè et al. [Sanchez-Marre:iEMSs:2008], pages 1774–1781. [ bib ]

F. M. Hoffman, J. T. Randerson, I. Fung, P. Thornton, C. Covey, G. Bonan, S. Running, and R. Norby. Comparison of global model results from the Carbon-Land Model Intercomparison Project (C-LAMP) with Free-Air Carbon dioxide Enrichment (FACE) manipulation experiments. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract B51E–0447, Dec. 2008. [ bib | .txt ]

Free-Air CO₂ Enrichment (FACE) manipulation experiments have been carried out at a handful of sites to gauge the response of the biosphere to significant increases in atmospheric [CO₂]. Early synthesis results from four temperate forest sites suggest that the response of net primary productivity (NPP) is conserved across a broad range of productivity with a stimulation at the median of 23 ± 2% when the surrounding air [CO₂] was raised to 550 ppm. As a part of the Carbon-Land Model Intercomparison Project (C-LAMP), a community-based model-data comparison activity, the authors have performed a global FACE modeling experiment using two terrestrial biogeochemistry modules, CLM3-CASA' and CLM3-CN, coupled to the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). The two models were forced with an improved NCEP/NCAR reanalysis data set and reconstructed atmospheric [CO₂] and N deposition data through 1997. At the beginning of 1997 in the transient simulations, global atmospheric [CO₂] was abruptly raised to 550 ppm, the target value used at the FACE sites. In the control runs, [CO₂] continued to rise following observations until 2004, after which it was held constant out to year 2100. In both simulations, the last 25 years of reanalysis forcing and a constant N deposition were applied after year 2004. Across all forest biomes, the NPP responses from both models are weaker than those reported for the four FACE sites. Moreover, model responses vary widely geographically with a decreasing trend of NPP increases from 40^oN to 70^oN. For CLM3- CASA', the largest responses occur in arid regions of western North America and central Asia, suggesting that responses are most strongly influenced by increased water use efficiency for this model. CLM3-CN exhibits consistently weaker responses than CLM3-CASA' with the strongest responses in central Asia, but significantly constrained by N limitation. C-LAMP is a sub-project of the Computational Climate Science End Station led by Dr. Warren Washington, using computing resources at the U.S. Department of Energy's National Center for Computational Sciences (NCCS).

F. M. Hoffman, J. T. Randerson, I. Fung, P. Thornton, J. Lee, G. Bonan, S. Running, D. J. Erickson III, and J. Drake. The Carbon-Land Model Intercomparison Project: A protocol and metrics for global biosphere models. Poster, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop, Apr. 2008. [ bib ]

The Carbon-Land Model Intercomparison Project (C-LAMP) began as a project to intercompare terrestrial biogeochemistry models in the Community Climate System Model (CCSM) framework. A collaboration between the CCSM Biogeochemsitry Working Group the U.S. Dept. of Energy Scientific Discovery through Advanced Computing (SciDAC) initiative, C-LAMP has evolved into an international protocol and set of metrics for grading the scientific performance of models by comparison with best-available observational datasets, from satellite to leaf-scale measurements. In the first set of experiments, the models are forced with an improved NCEP/NCAR reanalysis climate data set to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to examine the influence of climate variability, prescribed atmospheric CO₂ and nitrogen deposition on terrestrial carbon fluxes during the 20th century. An active atmosphere model is used in the second set of experiments with prescribed atmospheric CO₂ concentrations. The objective of these simulations is to examine the effect of a coupled biosphere-atmosphere for carbon fluxes and climate during the 20th century. Presented will be preliminary results from offline and partially coupled experiments using two models, CLM3-CASA' and CLM3-CN, in the CCSM framework. Metadata standards developed to support archival and distribution of model output via the Earth System Grid (ESG) will also be presented.

F. M. Hoffman, J. T. Randerson, I. Fung, P. Thornton, J. Lee, C. Covey, D. Erickson, G. Bonan, and S. Running. The Carbon-Land Model Intercomparison Project: A protocol and metrics for global model-data comparison. Presentation, June 2008. 13th Annual CCSM Workshop. [ bib ]

F. M. Hoffman, J. T. Randerson, I. Fung, P. Thornton, Y. J. Lee, and C. C. Covey. Results from the CCSM Carbon-Land Model Intercomparison Project (C-LAMP). Eos Trans. AGU, 88(52):Fall Meet. Suppl., Abstract B31B–0324, Dec. 2007. [ bib | .txt ]

The National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) Biogeochemistry Working Group has initiated an intercomparison of terrestrial biosphere models running within the CCSM framework. Called the CCSM Carbon-Land Model Intercomparison Project (C-LAMP), its purpose is to allow the U.S. scientific community to evaluate the performance of biogeochemical cycling models within CCSM and to identify the most important processes for inclusion in future versions of CCSM. Two terrestrial biogeochemistry modules coupled to CCSM—CLM3-CASA' and CLM3-CN—have been evaluated following a set of carefully crafted experiments that build upon the C⁴MIP Phase 1 protocol. In Experiment 1, the models were forced with an improved NCEP/NCAR reanalysis data set, while in Experiment 2, the models were coupled to the Community Atmosphere Model Version 3 (CAM3) with carbon, water, and energy exchanges over the 20th century. Unlike with most model intercomparisons, for C-LAMP a model performance methodology based on comparison against best-available observational data sets has been developed. Scalar metrics for each model are derived from comparisons against measurements of net primary production, leaf area index, the seasonal cycle of CO₂, carbon stocks, and energy. Results from both experiments for CLM3- CASA' and CLM3-CN will be presented, along with recommendations for future evaluations of terrestrial models. C-LAMP model output will be made available by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) via the Earth System Grid (ESG). C-LAMP is a sub-project of the Computational Climate Science End Station headed by Dr. Warren Washington, using computing resources at the U.S. Department of Energy's National Center for Computational Sciences (NCCS).

F. M. Hoffman, J. T. Randerson, I. Y. Fung, P. E. Thornton, Y.-H. J. Lee, C. C. Covey, G. B. Bonan, and S. W. Running. (C-LAMP): A protocol and evaluation metrics for global terrestrial biogeochemistry models. In Sànchez-Marrè et al. [Sanchez-Marre:iEMSs:2008], pages 1039–1046. [ bib ]

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.

J. Huang, M. Glatter, W. Kendall, B. Langley, J. New, R. Sisneros, F. Hoffman, and D. Erickson. Time-varying multivariate visualization for understanding the climate science of the terrestrial biosphere. Poster, 13th annual CCSM workshop, June 2008. [ bib ]

Inland Northwest Research Alliance and University of Alaska Fairbanks. Lessons from continuity and change: an international polar year symposium, 2009. In Press. [ bib ]

S. R. Kawa, G. J. Collatz, A. S. Denning, and D. J. Erickson III. Progress in modeling global atmospheric CO₂ fluxes and transport. Poster, U. S. North American Carbon Program NACP Investigators Meeting, Jan. 2007. [ bib | http | .pdf ]

Progress in better determining CO₂ sources and sinks will almost certainly rely on utilization of more extensive and intensive CO₂ and related observations including those from satellite remote sensing. Use of advanced data requires improved modeling and analysis capability. Under NASA Carbon Cycle Science support we seek to develop and integrate improved formulations for 1) atmospheric transport, 2) terrestrial uptake and release, 3) biomass and 4) fossil fuel burning, and 5) observational data analysis including inverse calculations. The transport modeling is based on meteorological data assimilation analysis from the Goddard Modeling and Assimilation Office. Use of assimilated met data enables model comparison to CO₂ and other observations across a wide range of scales of variability. In this presentation we focus on the short end of the temporal variability spectrum: hourly to synoptic to seasonal. Using CO₂ fluxes at varying temporal resolution from the SiB 2 and CASA biosphere models, we examine the model's ability to simulate CO₂ variability in comparison to observations at different times, locations, and altitudes. We find that the model can resolve much of the variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The influence of key process representations is inferred. The high degree of fidelity in these simulations leads us to anticipate incorporation of real-time, highly resolved observations into a multiscale carbon cycle analysis system that will begin to bridge the gap between top-down and bottom-up flux estimation, which is a primary focus of NACP.

S. R. Kawa, G. J. Collatz, D. J. Erickson III, A. S. Denning, S. C. Wofsy, and A. E. Andrews. Evaluating the capacity of global CO₂ flux and atmospheric transport models to incorporate new satellite observations. Eos Trans. AGU, 88(52):Fall Meet. Suppl., Abstract A13D–1516, Dec. 2007. [ bib | .txt ]

As we enter the new era of satellite remote sensing for CO₂ and other carbon cycle-related quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO₂ surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO₂ data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO₂ fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO₂ data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO₂ flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO₂ sink and revolutionize our understanding of the key processes controlling atmospheric CO₂ and its evolution with time.

S. R. Kawa, A. S. Denning, G. J. Collatz, and D. J. Erickson. Progress in modeling global atmospheric CO₂ fluxes and transport. Poster, Joint Workshop on NASA Biodiversity, Terrestrial Ecology, and Related Applied Sciences, Aug. 2006. [ bib | .pdf ]

Progress in better determining CO₂ sources and sinks will almost certainly rely on utilization of more extensive and intensive CO₂ and related observations including those from satellite remote sensing. Use of advanced data requires improved modeling and analysis capability. Here we seek to develop and integrate improved formulations for 1) atmospheric transport, 2) terrestrial uptake and release, 3) biomass and 4) fossil fuel burning, and 5) observational data analysis including inverse calculations. The transport modeling is based on meteorological data assimilation analysis from the Goddard Modeling and Assimilation Office. Use of assimilated met data enables model comparison to CO₂ and other observations across wide range of scales of variability. In this presentation we focus on the short end of the temporal variability spectrum: hourly to synoptic to seasonal. Using CO₂ fluxes at varying temporal resolution from the Transcom-C model intercomparison exercise, we examine the model's ability to simulate CO₂ variability in comparison to observations at different times, locations, and altitudes. We find that the model can resolve much of the variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The influence of key process representations is inferred. The high degree of fidelity in these simulations leads us to anticipate incorporation of real-time, highly resolved observations into a multidisciplinary carbon cycle data assimilation system that will reduce uncertainty in the terrestrial CO₂ sink and lead toward credible, tested predictive models of climate and carbon needed for informed policy decisions.

M. Keller, D. S. Schimel, W. W. Hargrove, and F. M. Hoffman. A continental strategy for the National Ecological Observatory Network. Front. Ecol. Environ., 6(5):282–284, 2008. Special Issue on Continental-Scale Ecology. [ bib | DOI | www: ]

W. Kendall, M. Glatter, J. Huang, F. Hoffman, and D. E. Bernholdt. Web enabled collaborative climate visualization in the Earth System Grid. In Proceedings of the International Symposium on Collaborative Technologies and Systems (CTS'08), Irvine, California, USA, May 2008. [ bib ]

S. Khan, S. Bandyopadhyay, A. R. Ganguly, S. Saigal, D. J. Erickson III, V. Protopopescu, and G. Ostrouchov. Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data. Phys. Rev. E, 76:026209, 2007. [ bib | DOI | www: ]

Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall's, cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), k-nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the XY plane. However, outstanding gaps in the current literature have precluded the ability to effectively automate these methods, which, in turn, have caused limited adoptions by the application communities. This study attempts to address a key gap in the literature–specifically, the evaluation of the above methods to choose the best method, particularly in terms of their robustness for short and noisy data, based on comparisons with the theoretical MI estimates, which can be computed analytically, as well with linear correlation and Kendall's . Here we consider smaller data sizes, such as 50, 100, and 1000, and within this study we characterize 50 and 100 data points as very short and 1000 as short. We consider a broader class of functions, specifically linear, quadratic, periodic, and chaotic, contaminated with artificial noise with varying noise-to-signal ratios. Our results indicate KDEs as the best choice for very short data at relatively high noise-to-signal levels whereas the performance of KNNs is the best for very short data at relatively low noise levels as well as for short data consistently across noise levels. In addition, the optimal smoothing parameter of a Gaussian kernel appears to be the best choice for KDEs while three nearest neighbors appear optimal for KNNs. Thus, in situations where the approximate data sizes are known in advance and exploratory data analysis and/or domain knowledge can be used to provide a priori insights into the noise-to-signal ratios, the results in the paper point to a way forward for automating the process of MI estimation.

S. Khan, A. R. Ganguly, S. Bandyopadhyay, S. Saigal, D. J. Erickson III, V. Protopopescu, and G. Ostrouchov. Nonlinear statistics reveals stronger ties between ENSO and tropical hydrological cycle. Geophys. Res. Lett., 33:L24402, 2006. [ bib | DOI | www: | http ]

Cross-spectrum analysis based on linear correlations in the time domain suggested a coupling between large river flows and the El Niño-Southern Oscillation (ENSO) cycle. A nonlinear measure based on mutual information (MI) reveals extrabasinal connections between ENSO and river flows in the tropics and subtropics, that are 20-70% higher than those suggested so far by linear correlations. The enhanced dependence observed for the Nile, Amazon, Congo, Paraná, and Ganges rivers, which affect large, densely populated regions of the world, has significant impacts on inter-annual river flow predictabilities and, hence, on water resources and agricultural planning.

S. Khan, G. Kuhn, A. R. Ganguly, D. J. Erickson III, and G. Ostrouchov. Spatio-temporal variability of daily and weekly precipitation extremes in South America. Water Resour. Res., 43:W11424, 2006. [ bib | DOI | www: | http ]

Spatial and temporal variability of precipitation extremes are investigated by utilizing daily observations available at 2.5^o gridded fields in South America for the period 1940–2004. All 65 a of data from 1940–2004 are analyzed for spatial variability. The temporal variability is investigated at each spatial grid by utilizing 25-a moving windows from 1965–2004 and visualized through plots of the slope of the regression line in addition to its quality measure (R²). The Poisson-generalized Pareto (Poisson-GP) model, which is a peaks over threshold (POT) approach, is applied to weekly precipitation maxima residuals based on the 95%-quantile threshold, while daily data are utilized to analyze the number of consecutive daily extremes and daily extremes in a month based on the 99%-quantile threshold. Using the Poisson-GP model, we compute parameters of the GP distribution, return levels (RL) and a new measure called the precipitation extremes volatility index (PEVI). The PEVI measures the variability of extremes and is expressed as a ratio of return levels. From 1965–2004, the PEVI shows increasing trends in the Amazon basin except eastern parts, few parts of the Brazilian highlands, north-west Venezuela including Caracas, north Argentina, Uruguay, Rio De Janeiro, São Paulo, Asuncion, and Cayenne. Catingas, few parts of the Brazilian highlands, São Paulo and Cayenne experience increasing number of consecutive 2- and 3-days extremes from 1965–2004. The number of daily extremes, computed for each month, suggest that local extremes occur mostly from December to April with July to October being relatively quiet periods.

S.-J. Kim, T. J. Crowley, D. J. Erickson III, , B. Govindasamy, P. B. Duffy, and B. Y. Lee. High-resolution climate simulation of the last glacial maximum. Clim. Dyn., 31(1):1–16, July 2008. [ bib | DOI | www: ]

The climate of the last glacial maximum (LGM) is simulated with a high-resolution atmospheric general circulation model, the NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. The purpose of the study is to assess whether there are significant benefits from the higher resolution simulation compared to the lower resolution simulation associated with the role of topography. The LGM simulations were forced with modified CLIMAP sea ice distribution and sea surface temperatures (SST) reduced by 1^oC, ice sheet topography, reduced CO₂, and 21,000 BP orbital parameters. The high-resolution model captures modern climate reasonably well, in particular the distribution of heavy precipitation in the tropical Pacific. For the ice age case, surface temperature simulated by the high-resolution model agrees better with those of proxy estimates than does the low-resolution model. Despite the fact that tropical SSTs were only 2.1^oC less than the control run, there are many lowland tropical land areas 4–6^oC colder than present. Comparison of T170 model results with the best constrained proxy temperature estimates (noble gas concentrations in groundwater) now yield no significant differences between model and observations. There are also significant upland temperature changes in the best resolved tropical mountain belt (the Andes). We provisionally attribute this result in part as resulting from decreased lateral mixing between ocean and land in a model with more model grid cells. A longstanding model-data discrepancy therefore appears to be resolved without invoking any unusual model physics. The response of the Asian summer monsoon can also be more clearly linked to local geography in the high-resolution model than in the low-resolution model; this distinction should enable more confident validation of climate proxy data with the high-resolution model. Elsewhere, an inferred salinity increase in the subtropical North Atlantic may have significant implications for ocean circulation changes during the LGM. A large part of the Amazon and Congo Basins are simulated to be substantially drier in the ice age–consistent with many (but not all) paleo data. These results suggest that there are considerable benefits derived from high-resolution model regarding regional climate responses, and that observationalists can now compare their results with models that resolve geography at a resolution comparable to that which the proxy data represent.

G. Kuhn, S. Khan, A. R. Ganguly, and M. L. Branstetter. Geospatial-temporal dependence among weekly precipitation extremes with applications to observations and climate model simulations in south america. Adv. Water Resour., 30(12):2401 – 2423, 2007. [ bib | DOI | www: ]

J.-F. Lamarque, D. E. Kinnison, P. G. Hess, and F. M. Vitt. Simulated lower stratospheric trends between 1970 and 2005: identifying the role of climate. J. Geophys. Res., 113:D12301, June 2008. [ bib | DOI | www: | http ]

We have analyzed a set of simulations aimed at understanding the mechanisms that drive observed trends in the lower stratosphere after 1970. The simulations were performed using a version of the Community Atmosphere Model version 3 (CAM3) updated with interactive tropospheric and stratospheric chemistry. Even with a relatively low model top (40 km), this model shows good ability at reproducing a variety of large-scale changes in climate and chemical composition in the stratosphere when forced with the observed sea-surface temperatures and surface concentrations of long-lived trace gases and ozone-depleting substances. We then used the same model framework to differentiate the role of chemically active composition (ozone, methane, and chlorofluorocarbons) and CO₂ changes on observed trends in the stratosphere. Among the sensitivity factors analyzed, our simulations indicate that changes in CO₂ over the simulated period do not lead to significantly different total ozone trend; however, changes in CO₂ lead to important differences in ozone in the upper part of the model. On the other hand, changes in surface methane concentration are shown to play a significant role in driving changes in the globally averaged total ozone column, through a combination of changes in tropospheric and stratospheric ozone columns. We also show that the correlation between a change in tropical mean age of air and in vertical velocity breaks down above 20 hPa, in association with increased isentropic mixing above that level. Finally, we show that our model is capable of reproducing trends in the tropical age of air that were found in other studies; our simulations also indicate a significant impact of keeping methane and ozone-depleting substances at their 1970 levels, indicating the potentially important role of controlling methane emissions.

J. W. Larson, A. P. Craig, J. B. Drake, D. J. Erickson III, M. L. Branstetter, and M. W. Ham. A massively parallel dynamical core for continental- to global-scale river transport. In Oxley and Kulsiri [Oxley:modsim:2007], pages 532–538. [ bib | .pdf ]

R. M. Law, W. Peters, C. Rödenbeck, C. Aulagnier, I. Baker, D. J. Bergmann, P. Bousquet, J. Brandt, L. Bruhwiler, P. J. Cameron-Smith, J. H. Christensen, F. Delage, A. S. Denning, S. Fan, C. Geels, S. Houweling, R. Imasu, U. Karstens, S. R. Kawa, J. Kleist, M. C. Krol, S.-J. Lin, R. Lokupitiya, T. Maki, S. Maksyutov, Y. Niwa, R. Onishi, N. Parazoo, P. K. Patra, G. Pieterse, L. Rivier, M. Satoh, S. Serrar, S. Taguchi, M. Takigawa, R. Vautard, A. T. Vermeulen, and Z. Zhu. TransCom model simulations of hourly atmospheric CO₂: Experimental overview and diurnal cycle results for 2002. Glob. Biogeochem. Cycles, 22:GB3009, 2008. [ bib | DOI | www: | http ]

W. Lipscomb, R. Bindschadler, E. Bueler, D. Holland, J. Johnson, and S. Price. A community ice sheet model for sea level prediction. Eos Trans. AGU, 90(3), 2009. [ bib | DOI | www: | http ]

X. Liu, S. G. Ghan, R. Easter, R. Zaveri, A. Gettelman, P. Rasch, H. Morrison, J.-F. Lamarque, A. Conley, F. Vitt, C. Chuang, P. Cameron-Smith, K. Grant, P. Hess, N. Mahowald, and A. Ekman. Indirect effect in NCAR CAM: sensitivity to aerosol-cloud parameterizations. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract A32A–03 INVITED, Dec. 2008. [ bib | .txt ]

There are still large uncertainties in the estimate of aerosol indirect effect in global models which result not only from different treatments of aerosol (e.g., composition, size distribution and mixing states), but also from different treatments of aerosol-cloud interactions (aerosol activation and droplet autoconversion). In this presentation a modal aerosol treatment which predicts both aerosol mass and number, and internal mixing between aerosol components in the NCAR Community Atmospheric Model (CAM) will be used to estimate aerosol indirect effects. Sensitivities to different activation parameterizations (Abdul-Razzak and Ghan, 2002; Nenes and Seinfeld, 2003) and to different autoconversion parameterizations (Khairoutdinov-Kogan, 2000; Manton-Cotton, 1977; Liu-Daum, 2004; Beheng, 1994) will be investigated and discussed. The uncertainty range of indirect effect to aerosol-cloud interactions will also be compared to that from the NCAR CAM with a bulk aerosol treatment (i.e., only aerosol mass is predicted).

Z. Liu, B. Otto-Bliesner, F. He, E. Brady, P. Clark, A. Carlson, D. J. Erickson III, and R. Jacob. Transient simulation of climate evolution over the last 21,000 years. Invited presentation, PAGES Global Monsoon Symposium: Global Monsoon and Low-Latitude Processes: Evolution and Variability, Oct. 2008. [ bib ]

M. Long, W. C. Keene, and D. J. Erickson III. An inter-comparison of marine aerosol production parameterizations in CAM 3.5. Poster, June 2008. 13th Annual CCSM Workshop. [ bib ]

R. Loy, A. A. Mirin, and P. H. Worley. Performance engineering for the next generation Community Climate System Model. Poster, ACSR Computer Science Research Principal Investigators Meeting, Mar. 2008. [ bib | .pdf ]

S. Mahajan, F. M. Hoffman, W. W. Hargrove, S. W. Christensen, and R. T. Mills. A cluster analysis approach to comparing atmospheric radiation measurement (ARM) observations with global climate model (GCM) results. Eos Trans. AGU, 88(52):Fall Meet. Suppl., Abstract A41A–0010, Dec. 2007. [ bib | .txt ]

Continued validation of General Circulation Models (GCMs) is essential for their improvement, and pin-pointing their biases and systematic deviations might be of service to climate modelers. The availability of abundant multi-variate atmospheric data from the Dept. of Energy's Atmospheric Radiation Measurement (ARM) Program sites allows for comparison of atmospheric column observations to GCM simulations at high temporal resolutions at those locations. This study focuses on using a multi-variate cluster analysis approach to compare ARM observations of tropospheric vertical temperature, humidity, wind speed profiles, and surface pressure at the Southern Great Plains (SGP) site with corresponding output from an integration of the Community Climate System Model (CCSM) for the same location, highlighting observed discrepancies in the GCM results. Cluster analysis is a technique for classifying multi-variate data into distinct regimes based on Euclidean distance in phase space. A parallel clustering algorithm, designed for analyzing very large datasets, was applied to developing various atmospheric column regimes at the SGP site from the observations and, separately, from the CCSM model results. A comparison of the atmospheric regimes derived from the observations against the CCSM output proves to be useful in distinguishing their individual nature and identifying singular behavior. Some atmospheric regimes are found to be poorly represented in the CCSM. For example, while ARM SGP observations show hot humid lower tropospheric conditions are usually associated with low shear conditions, such conditions in CCSM output are associated with stronger shear. Low shear conditions in CCSM usually occur in a hot, moderately humid lower troposphere. These distinct regimes in CCSM, as compared to ARM observations, suggest misrepresentation of atmospheric states in CCSM over the SGP site, which could have ramifications on the formation of clouds in CCSM simulations, affecting the local radiation budget. In addition, the multi-variance of CCSM is lower than that of ARM observations suggesting that estimates of extremes based on GCM simulations are probably conservative.

R. McGraw. Numerical advection of correlated tracers: preserving particle size/composition moment sequences during transport of aerosol mixtures. J. Phys.: Conf. Ser., 78:012045 (5pp), 2007. [ bib | http | .pdf ]

Nonlinear transport algorithms designed to reduce numerical diffusion fail to preserve correlations between moments, isotope abundances, etc. when these scalar densities are transported in models as separate tracers. In case of the particle size/composition coordinates of an aerosol, such loss can give rise to unphysical moment sets. New statistical approaches to aerosol dynamics, which involve tracking moments directly, offer highly efficient alternatives to sectional and modal methods for representing aerosols in climate models, but it is essential that moment set integrity be preserved throughout a simulation. In this paper we review the problem and weaknesses of previous attempts at solution, including vector transport - a scheme in which the moments, as internal aerosol coordinates, are transported together with a single lead tracer such as number or mass. A non-negative least squares (NNLS) solution that finally eliminates the problem without requiring modification of the transport algorithm itself is presented. Following each transport step, new moment sets are resolved into sums of previously validated sets with non-negative coefficients using NNLS Transport errors are removed and the now guaranteed-to-be-valid moment sets are ready for passage to the aerosol dynamics module. In addition to moment set validation, the new scheme reduces numerical diffusion during transport and provides greater accuracy for the source apportionment of aerosol mixtures. The method is not limited to moment transport - similar improvements in accuracy are expected using NNLS in conjunction with modal and sectional methods.

R. McGraw, L. Leng, W. Zhu, N. Riemer, and M. West. Aerosol dynamics using the quadrature method of moments: comparing several quadrature schemes with particle-resolved simulation. J. Phys.: Conf. Ser., 125:012020 (5pp), 2008. [ bib | http | .pdf ]

The method of moments (MOM) is a statistically based alternative to sectional and modal methods for aerosol simulation. The MOM is highly efficient as the aerosol distribution is represented by its lower-order moments and only these, not the full distribution itself, are tracked during simulation. Quadrature is introduced to close the moment equations under very general growth laws and to compute aerosol physical and optical properties directly from moments. In this paper the quadrature method of moments (QMOM) is used in a bivariate test tracking of aerosol mixing state. Two aerosol populations, one enriched in soot and the other in sulfate, are allowed to interact through coagulation to form a generally-mixed third particle population. Quadratures of varying complexity (including two candidate schemes for use in climate models) are described and compared with benchmark results obtained by using particle-resolved simulation. Low-order quadratures are found to be highly accurate, and Gauss and Gauss-Radau quadratures appear to give nested lower and upper bounds, respectively, to aerosol mixing rate. These results suggest that the QMOM makes it feasible to represent the generallymixed states of aerosols and track their evolution in climate models.

A. Mirin and P. Worley. Extending scalability of the Community Atmosphere Model. Presentation, June 2007. 12th Annual CCSM Workshop. [ bib | .pdf ]

The parallel implementation of the Community Atmosphere Model (CAM) employs a number of different domain decompositions. Currently, each decomposition must utilize the same number of MPI processes, limiting the scalability of CAM to that of the least scalable decomposition. This limitation becomes unacceptably restrictive when including additional physical processes such as atmospheric chemistry or cloud resolving physics. We are generalizing CAM to allow the number of active MPI processes to vary between domain decompositions. We are also introducing new domain decompositions to address new physics scenarios. We report on our progress to date.

A. Mirin and P. Worley. Extending scalability of the community atmosphere model. J. Phys.: Conf. Ser., 78:012082 (7pp), 2007. [ bib | http | .pdf ]

The Community Atmosphere Model (CAM) is the atmosphere component of the Community Climate System Model (CCSM), and is the largest consumer of computing resources in typical CCSM simulations. The parallel implementation of the Community Atmosphere Model (CAM) employs a number of different domain decompositions. Currently, each decomposition must utilize the same number of MPI processes, limiting the scalability of CAM to that of the least scalable decomposition. This limitation becomes unacceptably restrictive when including additional physical processes such as atmospheric chemistry or cloud-resolving physics. This paper reports on current efforts to improve CAM scalability by allowing the number of active MPI processes to vary between domain decompositions.

A. Mirin and P. Worley. Improvements in CAM throughput at scale. Presentation, CCSM Atmosphere Model Working Group Meeting, Mar. 2009. [ bib | .pdf ]

A. A. Mirin and P. H. Worley. Extending scalability of the Community Atmosphere Model. Presentation, Climate Change Prediction Program Meeting, Sept. 2007. [ bib | .pdf ]

A. A. Mirin and P. H. Worley. Enabling highly-scalable ultra-high resolution climate simulations using the Community Climate System Model. Presentation, SIAM Conference on Parallel Processing for Scientific Computing (PP08), Mar. 2008. [ bib | http | .pdf ]

A. A. Mirin and P. H. Worley. Recent improvements to the scalability of the Community Atmosphere Model. Presentation, Joint Chemistry Climate and Atmosphere Model Working Group Meeting, Feb. 2008. [ bib | .pdf ]

A. A. Mirin and P. H. Worley. Scalability improvements in the Community Atmosphere Model. Poster, June 2008. 13th Annual CCSM Workshop. [ bib | .pdf ]

R. J. Norby, J. M. Warren, C. M. Iversen, B. E. Medlyn, R. E. McMurtrie, and F. M. Hoffman. Nitrogen limitation is reducing the enhancement of NPP by elevated CO₂ in a deciduous forest. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract B32B–05 INVITED, Dec. 2008. [ bib | .txt ]

Accurate model representation of the long-term response of forested ecosystems to elevated atmospheric CO₂ concentrations (eCO2) is important for predictions of future concentrations of CO₂. For biogeochemical models that predict the response of net primary productivity (NPP) to eCO2, free-air CO₂ enrichment (FACE) experiments provide the only source of data for comparison. A synthesis of forest FACE experiments reported a 23% increase in NPP in eCO2, and this result has been used as a model benchmark. Here, we provide new evidence from a FACE experiment in a deciduous forest in Tennessee that N limitation has significantly reduced the stimulation of NPP by eCO2, consistent with predictions from ecosystem and global models that incorporate N feedbacks. The Liquidambar styraciflua stand has been exposed to current ambient atmospheric CO₂ or air enriched with CO₂ to 550 ppm since 1998. Results from the first 6 years of the experiment indicated that NPP was significantly enhanced by eCO2 and that this was a consistent and sustained response. Now, with 10 years of data, our analysis must be revised. The response of NPP to eCO2 has declined from 24% in 2001-2003 to 9% in 2007. The diminishing response to eCO2 since 2004 coincides with declining NPP in ambient CO₂ plots. Productivity of this forest stand is limited by N availability, and the steady decline in forest NPP is closely related to changes in the N economy, as evidenced by declining foliar N concentrations. There is a strong linear relationship between foliar [N] and NPP, and the steeper slope in eCO2 indicates that the NPP response to eCO2 should diminish as foliar N declines. Increased fine-root production and root proliferation deeper in the soil have sustained N uptake, but not to an extent sufficient to benefit aboveground production. The mechanistic basis of the N effect on NPP resides in the photosynthetic machinery. The linear relationships between Jmax and Vcmax with foliar [N] did not change from 1998 to 2008 or in response to eCO2; hence, lower foliar [N] resulted in significant reductions in Jmax, Vcmax, and photosynthesis over time and in eCO2. It is not yet clear whether foliar [N] and NPP will continue to decline or have reached a new steady state indicative of long-term forest response to eCO2. These results are consistent with ecosystem models, which suggest that the NPP response to eCO2 will include a transient increase in NPP followed by a decline to a lower level when fast C and N pools reach quasi-equilibrium at eCO2. Our results also are consistent with optimization models of carbon-water-nitrogen economy, which suggest eCO2 leads to increased fine-root production, declining foliar [N], and diminishing enhancement of aboveground production. At a larger scale, a model incorporating N feedbacks (CLM3-CN) predicts a much smaller enhancement of NPP in eCO2 than the CLM3-CASA' model without such a feedback. When applied across the terrestrial biosphere, the smaller CO₂ fertilization effect has important implications for the pace of climate change.

R. Oglesby, D. Erickson, D. Irwin, and T. Sever. Human-induced land use changes: What can Earth system models tell us about climate implications? In Voinov et al. [Voinov:iEMSs:2006]. Available on CD-ROM. [ bib | http ]

Changes to the landscape have long been thought to have substantial effects on climate, with climatic changes also having impacts on landscapes, For example, changes in climate can lead to changes in vegetation, which in turn induce further changes in climate, and so forth. In addition to these natural processes, however, human-induced changes in land use can also have substantial impacts on climate. A key point here is that the original anthropogenic change may have had nothing whatsoever to do with climate, yet still induce a change in climate that may be detrimental in many ways, and lead to additional changes, both human and natural, in the nature of the landscape. Earth system models, both global and regional, have become valuable tools in understanding and predicting the consequences of specific land use changes on climate. In this paper, Mesoamerica (Central America plus southern Mexico) will be used as a case study. Explored will be the role of the almost complete deforestation in the demise of the Maya civilization about 850 AD, as well as the possible effects on droughts and floods of the present-day extensive deforestation occurring in this region.

R. Oglesby, C. Rowe, and D. Erickson. Transitioning from corn to switchgrass in the US Great Plains: Implications for climate and water resources. Geophys. Res. Abstr., 10(EGU2008-A-05722), Apr. 2008. General Assembly. [ bib | .pdf ]

R. J. Oglesby, C. M. Rowe, and D. J. Erickson III. Transitioning from corn to switchgrass in the US Great Plains: Implications for climate and water resources. Eos Trans. AGU, 88(52):Fall Meet. Suppl., Abstract B44B–05, Dec. 2007. [ bib | .txt ]

Much attention has been paid to the use of corn as a biofuel, in large part because corn is already grown throughout much of the US and technology is in place to convert it to ethanol. Increasingly, however, it is recognized that other types of vegetation are likely to be more efficient producers of biofuel. In particular, switchgrass (the primary component of prairie long grass) may be a very efficient producer in the Great Plains (as well as portions of the Midwest and Southeast), where it is an indigenous species. The dominant agricultural planting in the Great Plains at present is corn. A transition from corn to switchgrass may have numerous benefits, both because it may be a better source of biofuels, and because in the water-scarce Great Plains it would likely make better use of available water resources. In addition to these positive benefits, however, there may be effects on the climate of this region that can be deleterious. While switchgrass, with its deep and extensive root system may be less subject to drought, and less needing of irrigation, than corn, it also cycles much less water during its growing season. This reduction in water input to the atmosphere means less water available for local and regional precipitation, and also dramatically affects the surface energy balance, resulting in more sensible and longwave heating of the atmosphere. This may cause a significant increase in surface air temperature and stabilization of the atmosphere, leading to a reduction in precipitation as well as increased evaporative potential (both of which would help negate any increased water efficiency of switchgrass). We use the MM5 and WRF regional climate models to investigate these effects over the Great Plains. Simulations were made assuming all corn ('irrigated cropland') and all switchgrass ('grassland') and compared to a control using present-day land use types that is largely a mix of the two. Model runs are being made for three years with normal precipitation, plus years with precipitation above and below normal (as based on observations). The high-resolution North American Regional Reanalysis provides lateral and initial conditions for the model simulations. Preliminary results suggest that a transition from corn to switchgrass can increase daily maximum temperatures by up to 4 C, with smaller increases in daily minimums. Precipitation decreases by 15-25%. Overall, the tendency is for warmer and drier conditions. These results also suggest that effects due to global warming may be exacerbated by a large-scale change to switchgrass.

B. L. Otto-Bliesner, Z. Liu, F. He, E. Brady, P. Clark, A. Carlson, R. Tomas, D. J. Erickson III, and R. Jacob. Transient simulation of climate evolution over the last 21,000 years (TraCE-21,000): First results. Eos Trans. AGU, 89(53):Fall Meet. Suppl., Abstract PP51E–02 INVITED, Dec. 2008. [ bib | .txt ]

This is a report of the first transient simulation of global climate change from the Last Glacial Maximum to 14 kyr BP employing the synchronously coupled NCAR CCSM3. Forced by realistic orbital influences, greenhouse gas concentrations, continental ice sheets, as well as a reasonable characterization of melting water forcing, CCSM3 is able to simulate many major features of the deglaciation climate evolution and abrupt climate changes. Most notably, the Heinrich 1 event, the Bolling-Allerod (BA) warming, and the associated changes of the Atlantic thermohaline circulation are replicated in our simulation. The numerical results suggest that the abrupt climate change towards the BA is induced by the rebounding of the thermohaline circulation and the associated high latitude climate feedbacks in response to the demise of the North Atlantic meltwater forcing. This is in contrast to other theories involving hysteresis of the thermohaline circulation. Our analysis also suggests that the abrupt change in the North Atlantic region has a significant impact on low latitude climate and monsoon systems through atmospheric and oceanic teleconnections.

L. Oxley and D. Kulsiri, editors. MODSIM 2007 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, Dec. 2007. [ bib ]

P. K. Patra, R. M. Law, W. Peters, C. Rödenbeck, M. Takigawa, C. Aulagnier, I. Baker, D. J. Bergmann, P. Bousquet, J. Brandt, L. Bruhwiler, P. J. Cameron-Smith, J. H. Christensen, F. Delage, A. S. Denning, S. Fan, C. Geels, S. Houweling, B. Imasu, U. Karstens, S. R. Kawa, J. Kleist, M. C. Krol, S.-J. Lin, R. Lokupitiya, T. Maki, S. Maksyutov, Y. Niwa, R. Onishi, N. Parazoo, G. Pieterse, L. Rivier, M. Satoh, S. Serrar, S. Taguchi, B. Vautard, A. T. Vermeulen, and Z. Zhu. TransCom model simulations of hourly atmospheric CO₂: Analysis of synoptic-scale variations for the period 2002-2003. Glob. Biogeochem. Cycles, 22:GB4013, 2008. [ bib | DOI | www: | http ]

The ability to reliably estimate CO₂ fluxes from current in situ atmospheric CO₂ measurements and future satellite CO₂ measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO₂) at 280 locations. We extracted synoptic-scale variability from daily averaged CO₂ time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO₂ variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

J. V. Pittman, E. M. Weinstock, R. J. Oglesby, D. S. Sayres, J. B. Smith, J. G. Anderson, O. R. Cooper, S. C. Wofsy, I. Xueref, C. Gerbig, B. C. Daube, E. C. Richard, B. A. Ridley, A. J. Weinheimer, M. Loewenstein, H.-J. Jost, J. P. Lopez, M. J. Mahoney, T. L. Thompson, W. W. Hargrove, and F. M. Hoffman. Transport in the subtropical lowermost stratosphere during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment. J. Geophys. Res., 112:D08304, Apr. 2007. [ bib | DOI | www: | http ]

We use in situ measurements of water vapor (H₂O), ozone (O₃), carbon dioxide (CO₂), 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.

A. Roberts, L. Hinzman, J. E. Walsh, M. Holland, J. Cassano, R. Döscher, H. Mitsudera, A. S. (lead authors), U. Bhatt, C. Deal, S. Elliot, M. Follows, H. Lantuit, D. Lawrence, W. Maslowski, A. D. McGuire, P. P. Overduin, I. Overeem, and V. R. (major contributors). Science plan for Arctic system modeling: A report by the arctic research community for the National Science Foundation Office of Polar Programs. Draft, International Arctic Research Center, University of Alaska at Fairbanks, 2008. Arctic System Model Workshop. [ bib | http ]

N. F. Samatova, M. Branstetter, A. R. Ganguly, R. Hettich, S. Khan, G. Kora, J. Li, X. Ma, C. Pan, A. Shoshani, and S. Yoginath. High performance statistical computing with parallel R: applications to biology and climate modelling. J. Phys.: Conf. Ser., 46:505–509, 2006. [ bib | http | .pdf ]

Ultrascale computing and high-throughput experimental technologies have enabled the production of scientific data about complex natural phenomena. With this opportunity, comes a new problem - the massive quantities of data so produced. Answers to fundamental questions about the nature of those phenomena remain largely hidden in the produced data. The goal of this work is to provide a scalable high performance statistical data analysis framework to help scientists perform interactive analyses of these raw data to extract knowledge. Towards this goal we have been developing an open source parallel statistical analysis package, called Parallel R, that lets scientists employ a wide range of statistical analysis routines on high performance shared and distributed memory architectures without having to deal with the intricacies of parallelizing these routines.

A. Sánchez and S. J. Gutierrez, editors. Photochemistry Research Progress. Nova Science Publishers, 2008. [ bib | http ]

M. Sànchez-Marrè, J. Béjar, J. Comas, A. E. Rizzoli, and G. Guariso, editors. Proceedings of the iEMSs Fourth Biennial Meeting: International Congress on Environmental Modelling and Software (iEMSs 2008), Barcelona, Catalonia, Spain, July 2008. International Environmental Modelling and Software Society. [ bib ]

D. Schimel, W. Hargrove, F. Hoffman, and J. MacMahon. NEON: A hierarchically designed national ecological network. Front. Ecol. Environ., 5(2):59, Mar. 2007. Guest Editorial. [ bib | DOI | www: ]

R. Sisneros, M. Glatter, B. Langley, J. Huang, F. Hoffman, and D. J. Erickson III. Time-varying multivariate visualization for understanding terrestrial biogeochemistry. J. Phys.: Conf. Ser., 125:012093 (6pp), 2008. [ bib | DOI | www: ]

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.

M. A. Taylor, J. Edwards, and A. St-Cyr. Petascale atmospheric models for the Community Climate System Model: new developments and evaluation of scalable dynamical cores. J. Phys.: Conf. Ser., 125:012023 (10pp), 2008. [ bib | http | .pdf ]

We present results from the integration and evaluation of the spectral finite-element method into the atmospheric component of the Community Climate System Model (CCSM). This method overcomes the atmospheric scalability bottleneck by allowing the use of a true two-dimensional domain decomposition for the first time in the CCSM. Scalability is demonstrated out to 86,200 processors with an average grid spacing of 0.25deg (25 km). We present initial evaluations results using a standardized test problem with the full suite of CCSM atmospheric model forcings and subgrid parametrizations but without the CCSM land, ice, or ocean models. For this realistic setting, the true solution is unknown. Even convergence under mesh refinement is not expected, so we cannot rely on high-resolution reference solutions. Instead we focus on intermodel comparisons and use the Williamson equivalent resolution methodology to evaluate the results.

M. A. Taylor, J. Edwards, S. Thomas, and R. Nair. A mass and energy conserving spectral element atmospheric dynamical core on the cubed-sphere grid. J. Phys.: Conf. Ser., 78:012074 (5pp), 2007. [ bib | http | .pdf ]

We present results from a conservative formulation of the spectral element method applied to global atmospheric circulation modeling. Exact local conservation of both mass and energy is obtained via a new compatible formulation of the spectral element method. Compatibility insures that the key integral property of the divergence and gradient operators required to show conservation also hold in discrete form. The spectral element method is used on a cubed-sphere grid to discretize the horizontal directions on the sphere. It can be coupled to any conservative vertical/radial discretization. The accuracy and conservation properties of the method are illustrated using a baroclinic instability test case.

M. A. Taylor, A. St-Cyr, and A. Fournier. Computational Science - ICCS 2009, chapter A non-oscillatory advection operator for the compatible spectral element method. Volume 5545/2009 of Allen et al. [Allen:iccs:2009], May 2009. [ bib | DOI | www: ]

The spectral element method is well known as an efficient way to obtain high-order numerical solutions on unstructured finite element grids. However, the oscillatory nature of the method's advection operator makes it unsuitable for many applications. One popular way to address this problem is with high-order discontinuous-Galerkin methods. In this work, an alternative solution which fits within the continuous Galerkin formulation of the spectral element method is proposed. Making use of a compatible formulation of spectral elements, a natural way to implement conservative non-oscillatory reconstructions for spectral element advection is shown. The reconstructions are local to the element and thus preserve the parallel efficiency of the method. Numerical results from a low-order quasi-monotone reconstruction and a higher-order sign-preserving reconstruction are presented.

U. [UNEP]. Environmental effects of ozone depletion and its interactions with climate change: Progress report, 2007. Photochem. Photobiol. Sci., 7(1):15–27, 2008. Contributing authors in alphabetical order: A. Andrady and P. J. Aucamp and A. F. Bais and C. L. Ballaré and L. O. Björn and J. F. Bornman and M. Caldwell and A. P. Cullen and Erickson, III, D. J. and F. R. de Gruijl and D.-P. Häder and M. Ilyas and G. Kulandaivelu and H. D. Kumar and J. Longstreth and R. L. McKenzie and M. Norval and H. H. Redhwi and R. C. Smith and K. R. Soloman and B. Sulzberger and Y. Takizawa and X. Tang and A. H. Teramura and A. Torikai and J. C. van der Leun and S. R. Wilson and R. C. Worrest and R. G. Zepp. [ bib | DOI | www: ]

This year the Montreal Protocol celebrates its 20th Anniversary. In September 1987, 24 countries signed the Montreal Protocol on Substances that Deplete the Ozone Layer. Today 191 countries have signed and have met strict commitments on phasing out of ozone depleting substances with the result that a 95% reduction of these substances has been achieved. The Montreal Protocol has also contributed to slowing the rate of global climate change, since most of the ozone depleting substances are also effective greenhouse gases. Even though much has been achieved, the future of the stratospheric ozone layer relies on full compliance of the Montreal Protocol by all countries for the remaining substances, including methyl bromide, as well as strict monitoring of potential risks from the production of substitute chemicals. Also the ozone depleting substances existing in banks and equipment need special attention to prevent their release to the stratosphere. Since many of the ozone depleting substances already in the atmosphere are long-lived, recovery cannot be immediate and present projections estimate a return to pre-1980 levels by 2050 to 2075. It has also been predicted that the interactions of the effects of the ozone layer and that of other climate change factors will become increasingly important.

SC '07: Proceedings of the 2007 ACM/IEEE conference on Supercomputing, New York, NY, USA, 2007. ACM. General Chair-Verastegui, Becky. [ bib | DOI | www: ]

A. Voinov, A. J. Jakeman, and A. E. Rizzoli, editors. Proceedings of the iEMSs 3rd Biennial Meeting: Summit on Environmental Modelling and Software}, Burlington, VT, July 2006. International Environmental Modelling and Software Society. Available on CD-ROM. [ bib | .html ]

W. M. Washington, J. Drake, L. Buja, D. Anderson, D. Bader, R. Dickinson, D. Erickson, P. Gent, S. Ghan, P. Jones, and R. Jacob. The use of the Climate-science Computational End Station (CCES) development and grand challenge team for the next IPCC assessment: an operational plan. J. Phys.: Conf. Ser., 125:012024 (5pp), 2008. [ bib | http | .pdf ]

The grand challenge of climate change science is to predict future climates based on scenarios of anthropogenic emissions and other changes resulting from options in energy and development policies. Addressing this challenge requires a Climate Science Computational End Station consisting of a sustained climate model research, development, and application program combined with world-class DOE leadership computing resources to enable advanced computational simulation of the Earth system. This project provides the primary computer allocations for the DOE SciDAC and Climate Change Prediction Program. It builds on the successful interagency collaboration of the National Science and the U.S. Department of Energy in developing and applying the Community Climate System Model (CCSM) for climate change science. It also includes collaboration with the National Aeronautics and Space Administration in carbon data assimilation and university partners with expertise in high-end computational climate research.

P. Worley and A. Mirin. Performance results for the new CAM benchmark suite. Presentation, June 2008. 13th Annual CCSM Workshop. [ bib | .pdf ]

P. Worley, A. Mirin, J. Drake, and W. Sawyer. Performance engineering in the Community Atmosphere Model. J. Phys.: Conf. Ser., 46:356–362, 2006. [ bib | http | .pdf ]

The Community Atmosphere Model (CAM) is the atmospheric component of the Community Climate System Model (CCSM) and is the primary consumer of computer resources in typical CCSM simulations. Performance engineering has been an important aspect of CAM development throughout its existence. This paper briefly summarizes these efforts and their impacts over the past five years.

P. H. Worley. Comparison of Cray XT3 and XT4 scalability. In Proceedings of the 49th Cray User Group Conference [cug:2007]. [ bib | .pdf ]

P. H. Worley and A. A. Mirin. Performance and performance scalability of the Community Atmosphere Model. Presentation, 13th SIAM Conference on Parallel Processing for Scientific Computing (PP08), Mar. 2008. [ bib | http | .pdf ]

P. Zannetti, S. Elliott, and D. Rouson, editors. Environmental Sciences and Environmental Computing, volume 3. FiatLux Publications, 2007. [ bib | http ]

R. G. Zepp, D. J. Erickson, III, N. D. Paul, and B. Sulzberger. Interactive effects of solar UV radiation and climate change on biogeochemical cycling. Photochem. Photobiol. Sci., 6(3):286–300, Mar. 2007. UNEP Special Issue. [ bib | DOI | www: ]

This report assesses research on the interactions of UV radiation (280-400 nm) and global climate change with global biogeochemical cycles at the Earth's surface. The effects of UV-B (280-315 nm), which are dependent on the stratospheric ozone layer, on biogeochemical cycles are often linked to concurrent exposure to UV-A radiation (315-400 nm), which is influenced by global climate change. These interactions involving UV radiation (the combination of UV-B and UV-A) are central to the prediction and evaluation of future Earth environmental conditions. There is increasing evidence that elevated UV-B radiation has significant effects on the terrestrial biosphere with implications for the cycling of carbon, nitrogen and other elements. The cycling of carbon and inorganic nutrients such as nitrogen can be affected by UV-B-mediated changes in communities of soil organisms, probably due to the effects of UV-B radiation on plant root exudation and/or the chemistry of dead plant material falling to the soil. In arid environments direct photodegradation can play a major role in the decay of plant litter, and UV-B radiation is responsible for a significant part of this photodegradation. UV-B radiation strongly influences aquatic carbon, nitrogen, sulfur and metals cycling that affect a wide range of life processes. UV-B radiation changes the biological availability of dissolved organic matter to microorganisms, and accelerates its transformation into dissolved inorganic carbon and nitrogen, including carbon dioxide and ammonium. The coloured part of dissolved organic matter (CDOM) controls the penetration of UV radiation into water bodies, but CDOM is also photodegraded by solar UV radiation. Changes in CDOM influence the penetration of UV radiation into water bodies with major consequences for aquatic biogeochemical processes. Changes in aquatic primary productivity and decomposition due to climate-related changes in circulation and nutrient supply occur concurrently with exposure to increased UV-B radiation, and have synergistic effects on the penetration of light into aquatic ecosystems. Future changes in climate will enhance stratification of lakes and the ocean, which will intensify photodegradation of CDOM by UV radiation. The resultant increase in the transparency of water bodies may increase UV-B effects on aquatic biogeochemistry in the surface layer. Changing solar UV radiation and climate also interact to influence exchanges of trace gases, such as halocarbons (e.g., methyl bromide) which influence ozone depletion, and sulfur gases (e.g., dimethylsulfide) that oxidize to produce sulfate aerosols that cool the marine atmosphere. UV radiation affects the biological availability of iron, copper and other trace metals in aquatic environments thus potentially affecting metal toxicity and the growth of phytoplankton and other microorganisms that are involved in carbon and nitrogen cycling. Future changes in ecosystem distribution due to alterations in the physical and chemical climate interact with ozone-modulated changes in UV-B radiation. These interactions between the effects of climate change and UV-B radiation on biogeochemical cycles in terrestrial and aquatic systems may partially offset the beneficial effects of an ozone recovery.

T. Zhang, W. Zhu, and R. McGraw. Joint cluster and non-negative least squares analysis for aerosol mass spectrum data. J. Phys.: Conf. Ser., 125:012026 (11pp), 2008. Full paper in J. Agri. Bio. and Environment. Stat. in press 2009. [ bib | DOI | www: | http | .pdf ]

Aerosol mass spectrum (AMS) data contain hundreds of mass to charge ratios and their corresponding intensities from air collected through the mass spectrometer. The observations are usually taken sequentially in time to monitor the air composition, quality and temporal change in an area of interest. An important goal of AMS data analysis is to reduce the dimensionality of the original data yielding a small set of representing tracers for various atmospheric and climatic models. In this work, we present an approach to jointly apply the cluster analysis and the non-negative least squares method towards this goal. Application to a relevant study demonstrates the effectiveness of this new approach. Comparisons are made to other relevant multivariate statistical techniques including the principal component analysis and the positive matrix factorization method, and guidelines are provided.

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