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Michael F. Wehner Selected Publications


Stone, D. A., H. Krishnan, R. Lance, S. Sippel, and M. F. Wehner, "The First and Second Hackathons of the International CLIVAR C20C+ Detection and Attribution Project", CLIVAR Exchanges, 2017,

Timmermans, B., D. Stone, M. Wehner, and H. Krishnan, "Impact of tropical cyclones on modeled wind-wave climate", Geophysical Research Letters, 2017, 44:1393-1401, doi: 10.1002/2016GL071681

Mitchell, D., K. AchutaRao, M. Allen, I. Bethke, U. Beyerle, A. Ciavarella, P. M. Forster, J. Fuglestvedt, N. Gillett, K. Haustein, W. Ingram, T. Iverson, V. Kharin, N. Klingaman, N. Massey, E. Fischer, C.-F. Schleussner, J. Scinocca, O. Seland, H. Shiogama, E. Shuckburgh, S. Sparrow, D. Stone, P. Uhe, D. Wallom, M. Wehner, and R. Zaaboul, "Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design", Geoscientific Model Development, 2017, 10:571-583, doi: 10.5194/gmd-10-571-2017

Angélil, O., D. Stone, M. Wehner, C. J. Paciorek, H. Krishnan, W. Collins, "An independent assessment of anthropogenic attribution statements for recent extreme temperature and rainfall events", Journal of Climate, 2017, 30:5-16, doi: 10.1175/JCLI-D-16-0077.1


M. Wehner, D. Stone, H. Krishnan, K. AchutaRao, F. Castillo, "The deadly combination of heat and humidity in India and Pakistan in summer 201", Bulletin of the American Meteorological Society, 2016, 97:S81-S86, doi: 10.1175/BAMS-D-16-0145.2

K. A. Lawal, A. A. Abatan, O. Ang\'elil, E. Olaniyan, V. H. Olusoji, P. G. Oguntunde, B. Lamptey, B. J. Abiodun, H. Shiogama, M. F. Wehner, D. A. Stone, "The late onset of the 2015 wet season in Nigeria", Bulletin of the American Meteorological Society, 2016, 97:S63-S69, doi: 10.1175/BAMS-D-16-0131.2


Stone, D., H. Shiogama, P. Wolski, O. Angélil, S. Cholias, N. Christidis, A. Dittus, C. Folland, A. King, J. Kinter, H. Krishnan, S.-K. Min, M. Wehner, "The C20C+ Detection and Attribution Project", Fall Meeting of the American Geophysical Union, 2015,

Wehner, M., Prabhat, K. A. Reed, D. Stone, W. D. Collins, and J. Bacmeister, "Resolution dependence of future tropical cyclone projections of CAM5.1 in the US CLIVAR Hurricane Working Group idealized configurations", Journal of Climate, 2015, 28:3905-3925, doi: 10.1175/JCLI-D-14-00311.1


Dáithí Stone, Michael Wehner, Shreyas Cholia, Harinarayan Krishnan, Piotr Wolski, Mark Tadross, Chris Folland, Nikos Christidis, Hideo Shiogama, "The C20C+ Detection and Attribution Project", Integrated Climate Modeling Principal Investigator Meeting 2014, 2014,

O. Angélil, D. A. Stone, M. Tadross, F. Tummon, M. Wehner, R. Knutti, "Attribution of extreme weather to anthropogenic greenhouse gas emissions: sensitivity to spatial and temporal scales", Geophysical Research Letters, 2014, 41:2150-2155, doi: 10.1002/2014GL059234


E. Wes Bethel, Prabhat, Suren Byna, Oliver Rübel, K. John Wu, and Michael Wehner, "Why High Performance Visual Data Analytics is both Relevant and Difficult", Proceedings of Visualization and Data Analysis 2013, IS&T/SPIE Electronic Imaging 2013, San Francisco, CA, USA, SPIE, February 2013, LBNL LBNL-6063E,

Seasonal extreme daily precipitation is analyzed in the ensemble of NARCAPP regional climate models. Significant variation in these models’ abilities to reproduce observed precipitation extremes over the contiguous United States is found. Model performance metrics are introduced to characterize overall biases, seasonality, spatial extent and the shape of the precipitation distribution. Comparison of the models to gridded observations that include an elevation correction is found to be better than to gridded observations without this correction. A complicated model weighting scheme based on model performance in simulating observations is found to cause significant improvements in ensemble mean skill only if some of the models are poorly performing outliers. The effect of lateral boundary conditions are explored by comparing the integrations driven by reanalysis to those driven by global climate models. Projected mid-century future changes in seasonal precipitation means and extremes are presented and discussions of the sources of uncertainty and the mechanisms causing these changes are presented.

D. A. Stone, C. J. Paciorek, Prabhat, P. Pall, M. F. Wehner, "Inferring the anthropogenic contribution to local temperature extremes", Proceedings of the National Academy of Sciences, 2013, 110:E1543, doi: 10.1073/pnas.1221461110


Seung-Ki Min, Xuebin Zhang, Francis Zwiers, Hideo Shiogama, Yu-Shiang Tung, and Michael Wehner, "Multi-Model Detection and Attribution of Extreme Temperature Changes", Journal of Climate (submitted), 2012,

Donald Wuebbles, Gerald Meehl, Katharine Hayhoe, Thomas R. Karl, Kenneth Kunkel, Benjamin Santer, Michael Wehner, Brian Colle, Erich M. Fischer, Rong Fu, Alex Goodman, Emily Janssen, Huikyo Lee, Wenhong Li, Lindsey N. Long, Seth Olsen, Anji Seth, Justin Sheffield, Liqiang Sun, "CMIP5 Climate Model Analyses: Climate Extremes in the United States", Bulletin of the American Meteorological Society (submitted), 2012,

Santer, B.D., J. Painter, C. Mears, C. Doutriaux, P. Caldwell, J.M. Arblaster, P. Cameron-Smith, N.P. Gillett, P.J. Gleckler, J.R. Lanzante, J. Perlwitz, S. Solomon, P.A. Stott, K.E. Taylor, L. Terray, P.W. Thorne, M.F. Wehner, F.J. Wentz, T.M.L. Wigley, L. Wilcox and C.-Z. Zou, "Identifying Human Influences on Atmospheric Temperature: Are Results Robust to Uncertainties?", Proceedings of the National Academy of Sciences, June 22, 2012,

Prabhat, Oliver Rübel, Surendra Byna, Kesheng Wu, Fuyu Li, Michael Wehner and E. Wes Bethel, "TECA: A Parallel Toolkit for Extreme Climate Analysis", Procedia Computer Science, Proceedings of the International Conference on Computational Science, ICCS 2012, Presented at Third Worskhop on Data Mining in Earth System Science (DMESS 2012), Omaha, Nebraska, June 2012, 9:866–876, LBNL 5352E, doi: 10.1016/j.procs.2012.04.093

We present TECA, a parallel toolkit for detecting extreme events in large climate datasets. Modern climate datasets expose parallelism across a number of dimensions: spatial locations, timesteps and ensemble members. We design TECA to exploit these modes of parallelism and demonstrate a prototype implementation for detecting and tracking three classes of extreme events: tropical cyclones, extra-tropical cyclones and atmospheric rivers. We process a modern TB-sized CAM5 simulation dataset with TECA, and demonstrate good runtime performance for the three case studies.

Fuyu Li, Daniele Rosa, William D. Collins, and Michael F. Wehner, "“Super-parameterization”: A better way to simulate regional extreme precipitation?", Journal of Advances in Modeling Earth Systems, April 4, 2012, 4, doi: 10.1029/2011MS000106

Extreme precipitation is generally underestimated by current climate models relative to observations of present-day rainfall distributions. Possible causes of this systematic error include the convective parameterization in these models that have been designed to reproduce measurements of climatological mean precipitation. One possible approach to improve the interaction of subgrid-scale physical processes and large-scale climate is to replace the conventional convective parameterizations with a high-resolution cloud-system resolving model. A “super-parameterized” Community Atmosphere Model (SP-CAM) utilizing this approach is used in this study to investigate the distribution of extreme precipitation in the United States. Results show that SP-CAM better simulates the distributions of both light and intense precipitation compared to the standard version of CAM based upon conventional parameterizations. The improvements are mostly seen in regions dominated by convective precipitation, suggesting that super-parameterization provides a better representation of subgrid convective processes.

V. V. Kharin, F. W. Zwiers, X. Zhang, M. Wehner, "Changes in temperature and precipitation extremes in the CMIP5 ensemble", Climatic Change, 2012,

John C. H. Chiang, C. Y. Chang and M.F. Wehner, "Long-term trends of the Atlantic Interhemispheric SST Gradient in the CMIP5 Historical Simulations", J. Climate, 2012,

Wehner book chapter

Michael F. Wehner, "Methods of Projecting Future Changes in Extremes", Extremes in a Changing Climate: Detection, Analysis and Uncertainty, edited by A. AghaKouchak et al., (Springer: 2012) doi: 10.1007/978-94-007-4479-0_8

This chapter examines some selected methods of projecting changes in extreme weather and climate statistics. Indices of extreme temperature and precipitation provide measures of moderately rare weather events that are straightforward to calculate. Drought indices provide measures of both agricultural and hydrological drought that are especially suitable for constructing multi-model ensemble projections of future change. Extreme value statistical theories are surveyed and provide methodologies for projecting the changes in frequency and severity of very rare temperature and precipitation events.

Future changes in the average climate virtually guarantee that changes in extreme weather events will follow. Such rare events are best described statistically as it is difficult, but perhaps not impossible, to directly link individual disasters to human-induced climate change. Examples of extreme weather events with severe consequences to society that are amenable to projection include heat waves, cold spells, floods, droughts and tropical cyclones. Confidence in projections of future changes in the severity and frequency of such events is increased if the mechanisms of change can be identified and understood. Equally important, however, is the rigorous quantification of the uncertainties in these projections. These uncertainties include the inherent natural variability of the climate system as well as limitations in both the climate models’ fidelity and the statistical methods used to analyze their output.

The discussions about future changes in extreme events in recent climate change assessment reports (including the IPCC 4th Assessment Report and the US national assessments) did not generally focus on sophisticated statistical analyses. Rather, extremes were presented in these documents by a series of “extreme indices”. Introduced first by Frich et al. (2002), they are often referred to as the Frich indices. While many of these represent significant departures from the mean climate, they are by no means descriptive of rare events or the far tails of the temperature or precipitation distributions. The fundamental difference between these index based treatments and formal Extreme Value Theory descriptions of rare events illustrates the difficulties in nomenclature when discussing climate and weather extremes. What constitutes “extreme” varies greatly in the literature and depends highly on the application of the final results. This chapter will survey some of these methods of projecting changes in climate and weather.


T.C. Peterson, R. Heim, R. Hirsch, D. Kaiser, H. Brooks, N.S. Diffenbaugh, R. Dole, J. Giovannettone, K. Guiguis, T.R. Karl, R.W. Katz, K. Kunkel, D. Lettenmaier, G. J. McCabe, C.J. Paciorek, K.Ryberg, S.Schubert, V.B.S. Silva, B. Stewart, A.V. Vecchia, G. Villarini, R.S. Vose, J. Walsh, M.Wehner, D. Wolock, K. Wolter, C.A. Woodhouse and D. Wuebbles, "Monitoring and Understanding Trends in Extreme Storms: State of Knowledge", Bulletin of the American Meteorological Society, 2012, doi: 10.1175/BAMS-D-11-00262.1

The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hail storms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make the use of the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally-averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical linkages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multi-decadal trends in the areal percentage of the contiguous U.S. impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the U.S. as a whole since 1950.

E. W. Bethel, Surendra Byna, Jerry Chou, Cormier-Michel, Cameron G. R. Geddes, Howison, Fuyu Li, Prabhat, Ji Qiang, R\ ubel, Rob D. Ryne, Michael Wehner, Wu, "Big Data Analysis and Visualization: What Do LINACS Tropical Storms Have In Common?", 11th International Computational Accelerator Physics ICAP 2012, Germany, 2012,

Russell S. Vose, Scott Applequist, Mark A. Bourassa, Sara C. Pryor, Rebecca J. Barthelmie, Brian Blanton, Peter D. Bromirski, Harold E. Brooks, Arthur T. DeGaetano, Randall M. Dole, David R. Easterling, Robert E. Jensen, Thomas R. Karl, Katherine Klink, Richard W. Katz, Michael C. Kruk, Kenneth E. Kunkel, Michael C. MacCracken, Thomas C. Peterson, Bridget R. Thomas, Xiaolan L. Wang, John E. Walsh, Michael F. Wehner, Donald J. Wuebbles, and Robert S. Young, "Monitoring and Understanding Changes in Extremes: Extratropical Storms, Winds, and Waves", Bulletin of the American Meteorological Society (submitted), 2012,

T.C. Peterson, R. Heim, R. Hirsch, D. Kaiser, H. Brooks, N.S. Diffenbaugh, R. Dole, J. Giovannettone, K. Guiguis, T.R. Karl, R.W. Katz, K. Kunkel, D. Lettenmaier, G. J. McCabe, C.J. Paciorek, K.Ryberg, S.Schubert, V.B.S. Silva, B. Stewart, A.V. Vecchia, G. Villarini, R.S. Vose, J. Walsh, M.Wehner, D. Wolock, K. Wolter, C.A. Woodhouse and D. Wuebbles, "Monitoring and Understanding Changes in Heatwaves, Coldwaves, Floods and Droughts in the United States: State of Knowledge", Bulletin of the American Meteorological Society (accepted), 2012,

Fuyu Li, William D. Collins, Michael F. Wehner, Ruby L. Leung, "Hurricanes in an Aquaplanet World: Implications of the Impacts of External Forcing and Model Horizontal Resolution", Journal of Advances in Modeling Earth Systems, 2012,


Suren Byna, Prabhat, Michael F. Wehner and Kesheng Wu, "Detecting Atmospheric Rivers in Large Climate Datasets", Proceedings of the 2nd International Workshop on Petascale Data Analytics: Challenges, and Opportunities (PDAC-11/ Supercomputing11/ ACM/IEEE), November 14, 2011, Seattle, Washington, 2011, doi: 10.1145/2110205.2110208

Extreme precipitation events on the western coast of North America are often traced to an unusual weather phenomenon known as atmospheric rivers. Although these storms may provide a significant fraction of the total water to the highly managed western US hydrological system, the resulting intense weather poses severe risks to the human and natural infrastructure through severe flooding and wind damage. To aid the understanding of this phenomenon, we have developed an efficient detection algorithm suitable for analyzing large amounts of data. In addition to detecting actual events in the recent observed historical record, this detection algorithm can be applied to global climate model output providing a new model validation methodology. Comparing the statistical behavior of simulated atmospheric river events in models to observations will enhance confidence in projections of future extreme storms. Our detection algorithm is based on a thresholding condition on the total column integrated water vapor established by Ralph et al. (2004) followed by a connected component labeling procedure to group the mesh points into connected regions in space. We develop an efficient parallel implementation of the algorithm and demonstrate good weak and strong scaling. We process a 30-year simulation output on 10,000 cores in under 3 seconds.

B.D. Santer, Carl Mears , Charles Doutriaux , Peter Gleckler , Tom Wigley , Nathan Gillett , Detelina Ivanova , Thomas Karl , John Lanzante , Gerald Meehl , Peter Stott , Karl Taylor , Peter Thorne , Michael Wehner, and Frank Wentz, "Separating signal and noise in atmospheric temperature changes: The importance of timescale", Journal of Geophysical Research-Atmospheres, November 2011, 116, D22, doi: 10.1029/2011JD016263

Prabhat, Suren Byna. Chris Paciorek, Gunther Weber, Kesheng Wu, Thomas Yopes, Michael Wehner, William Collins, George Ostrouchov, Richard Strelitz, E. Wes Bethel, "Pattern Detection and Extreme Value Analysis on Large Climate Data", DOE/BER Climate and Earth System Modeling PI Meeting, September 2011,

Christopher Paciorek, Michael Wehner, and Prabhat, "Computationally-efficient Spatial Analysis of Precipitation Extremes Using Local Likelihood", Statistical and Applied Mathematical Sciences Institute Uncertainty Quantification program, Climate Modeling Opening Workshop, August 2011,

Michael Wehner, David R. Easterling, Jay H. Lawrimore, Richard R. Heim Jr., Russell S. Vose, and Benjamin Santer, "Projections of Future Drought in the Continental United States and Mexico", Journal of Hydrometerology, 2011, 12:1359–1377, doi: 10.1175/2011JHM1351.1

Using the Palmer drought severity index, the ability of 19 state-of-the-art climate models to reproduce observed statistics of drought over North America is examined. It is found that correction of substantial biases in the models’ surface air temperature and precipitation fields is necessary. However, even after a bias correction, there are significant differences in the models’ ability to reproduce observations. Using metrics based on the ability to reproduce observed temporal and spatial patterns of drought, the relationship between model performance in simulating present-day drought characteristics and their differences in projections of future drought changes is investigated. It is found that all models project increases in future drought frequency and severity. However, using the metrics presented here to increase confidence in the multimodel projection is complicated by a correlation between models’ drought metric skill and climate sensitivity. The effect of this sampling error can be removed by changing how the projection is presented, from a projection based on a specific time interval to a projection based on a specified temperature change. This modified class of projections has reduced intermodel uncertainty and could be suitable for a wide range of climate change impacts projections.

M. Wehner, L. Oliker, J. Shalf, D. Donofrio, L. Drummond, et al., "Hardware/Software Co-design of Global Cloud System Resolving Models", Journal of Advances in Modeling Earth Systems (JAMES), 2011, 3, M1000:22, doi: 10.1029/2011MS000073

Current climate models produce quite heterogeneous projections for the responses of precipitation extremes to future climate change. To help understand the range of projections from multimodel ensembles, a series of idealized ‘aquaplanet’ Atmospheric General Circulation Model (AGCM) runs have been performed with the Community Atmosphere Model CAM3. These runs have been analysed to identify the effects of horizontal resolution on precipitation extreme projections under two simple global warming scenarios. We adopt the aquaplanet framework for our simulations to remove any sensitivity to the spatial resolution of external inputs and to focus on the roles of model physics and dynamics. Results show that a uniform increase of sea surface temperature (SST) and an increase of low-to-high latitude SST gradient both lead to increase of precipitation and precipitation extremes for most latitudes. The perturbed SSTs generally have stronger impacts on precipitation extremes than on mean precipitation. Horizontal model resolution strongly affects the global warming signals in the extreme precipitation in tropical and subtropical regions but not in high latitude regions. This study illustrates that the effects of horizontal resolution have to be taken into account to develop more robust projections of precipitation extremes.

Fuyu Li, William Collins, Michael Wehner, David Williamson, Jerry Olson, and Christopher Algieri, "Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of Community Atmospheric Model (CAM3)", Tellus, 2011, 63, No. :884-823, doi: 10.1111/j.1600-0870.2011.00544.x

One key question regarding current climate models is whether the projection of climate extremes converges to a realistic representation as the spatial and temporal resolutions of the model are increased. Ideally the model extreme statistics should approach a fixed distribution once the resolutions are commensurate with the characteristic length and time scales of the processes governing the formation of the extreme phenomena of interest. In this study, a series of AGCM runs with idealized ‘aquaplanet-steady-state’ boundary conditions have been performed with the Community Atmosphere Model CAM3 to investigate the effect of horizontal resolution on climate extreme simulations. The use of the aquaplanet framework highlights the roles of model physics and dynamics and removes any apparent convergence in extreme statistics due to better resolution of surface boundary conditions and other external inputs. Assessed at a same large spatial scale, the results show that the horizontal resolution and time step have strong effects on the simulations of precipitation extremes. The horizontal resolution has a much stronger impact on precipitation extremes than on mean precipitation. Updrafts are strongly correlated with extreme precipitation at tropics at all the resolutions, while positive low-tropospheric temperature anomalies are associated with extreme precipitation at mid-latitudes.

Chang, C.-Y., J. C. H. Chiang, M. F. Wehner, A. R. Friedman, R. Ruedy, "Sulfate Aerosol Control of Tropical Atlantic Climate over the Twentieth Century", Journal of Climate, 2011, 24:2540–2555, doi: 10.1175/2010JCLI4065.1

The tropical Atlantic interhemispheric gradient in sea surface temperature significantly influences the rainfall climate of the tropical Atlantic sector, including droughts over West Africa and Northeast Brazil. This gradient exhibits a secular trend from the beginning of the twentieth century until the 1980s, with stronger warming in the south relative to the north. This trend behavior is on top of a multidecadal variation associated with the Atlantic multidecadal oscillation. A similar long-term forced trend is found in a multimodel ensemble of forced twentieth-century climate simulations. Through examining the distribution of the trend slopes in the multimodel twentieth-century and preindustrial models, the authors conclude that the observed trend in the gradient is unlikely to arise purely from natural variations; this study suggests that at least half the observed trend is a forced response to twentieth-century climate forcings. Further analysis using twentieth-century single-forcing runs indicates that sulfate aerosol forcing is the predominant cause of the multimodel trend. The authors conclude that anthropogenic sulfate aerosol emissions, originating predominantly from the Northern Hemisphere, may have significantly altered the tropical Atlantic rainfall climate over the twentieth century.


D. Hasenkamp, A. Sim, M. Wehner and K. Wu, "Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis", Proceedings of the 2nd IEEE International Conference on Cloud Computing Technology and Science, Nov. 30-Dec. 3, 2010, Indianapolis, Indiana, 2010, LBNL 4218E,



Wehner, M.F. ,R. Smith, P. Duffy, G. Bala, "The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model.", Climate Dynamics, 2010, 32:241-247, doi: 10.1007/s00382-009-0656-y

We investigate the ability of a global atmospheric general circulation model (AGCM) to reproduce observed 20 year return values of the annual maximum daily precipitation totals over the continental United States as a function of horizontal resolution. We find that at the high resolutions enabled by contemporary supercomputers, the AGCM can produce values of comparable magnitude to high quality observations. However, at the resolutions typical of the coupled general circulation models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, the precipitation return values are severely underestimated.


John Shalf, Donofrio, Rowen, Oliker, Michael F. Wehner, "Green Flash: Climate Machine (LBNL)", Encyclopedia of Parallel Computing, (Springer: 2010) Pages: 809-819

Green Flash is a research project focused on an application-driven manycore chip design that leverages commodity-embedded circuit designs and hardware/software codesign processes to create a highly programmable and energy-efficient HPC design. The project demonstrates how a multidisciplinary hardware/software codesign process that facilitates close interactions between applications scientists, computer scientists, and hardware engineers can be used to develop a system tailored for the requirements of scientific computing.

Michael F. Wehner, G. Bala, Phillip Duffy, Arthur A. Mirin, and Raquel Romano, "Towards Direct Simulation of Future Tropical Cyclone Statistics in a High-Resolution Global Atmospheric Model", Advances in Meteorology, 2010, 2010:Article ID, doi: 10.1155/2010/915303

Wehner, M.F., "Sources of uncertainty in the extreme value statistics of climate data", Extremes, 2010, 13:205-217, doi: 10.1007/s10687-010-0105-7

We investigate three sources of uncertainty in the calculation of extreme
value statistics for observed and modeled climate data. Inter-model differences in
formulation, unforced internal variability and choice of statistical model all contribute
to uncertainty. Using fits to the GEV distribution to obtain 20 year return
values, we quantify these uncertainties for the annual maximum daily mean surface
air temperatures of pre-industrial control runs from 15 climate models in the CMIP3


J. Shalf, M. Wehner, L. Oliker, "The Challenge of Energy-Efficient HPC", SCIDAC Review, Fall, 2009,

M. Wehner, L. Oliker., and J. Shalf, "Low Power Supercomputers", IEEE Spectrum, October 2009,

High-performance computing for such things as climate modeling is not going to advance at anything like the pace it has during the last two decades unless we apply fundamentally new ideas. Here we describe one possible approach. Rather than constructing supercomputers from the kinds of microprocessors found in fast desktop computers or servers, we propose adopting designs and design principles drawn, oddly enough, from the portable-electronics marketplace.

Easterling, D. R., and M. F. Wehner, "Is the climate warming or cooling?", Geophys. Res. Lett., April 2009, 36, L087, doi: 10.1029/2009GL037810

 Numerous websites, blogs and articles in the media have claimed that the climate is no longer warming, and is now cooling. Here we show that periods of no trend or even cooling of the globally averaged surface air temperature are found in the last 34 years of the observed record, and in climate model simulations of the 20th and 21st century forced with increasing greenhouse gases. We show that the climate over the 21st century can and likely will produce periods of a decade or two where the globally averaged surface air temperature shows no trend or even slight cooling in the presence of longer-term warming.


This report was produced by an advisory committee chartered under the Federal Advisory Committee Act, for the Subcommittee on Global Change Research, and at the request of the U.S. Government. Michael F. Wehner was one of its authors.

B.D. Santer, K.E. Taylor, P.J. Gleckler, C. Bonfils, T.P. Barnett, D.W. Pierce, T.M.L. Wigley, C. Mears, F.J. Wentz, W. Brueggemann, N.P. Gillett, S.A. Klein, S. Solomon, P.A. Stott, and M.F. Wehner, "Incorporating Model Quality Information in Climate Change Detection and Attribution Studies.", Proceeding of the National Academy of Sciences, 2009,

In a recent multimodel detection and attribution (D&A) study using the pooled results from 22 different climate models, the simulated “fingerprint” pattern of anthropogenically caused changes in water vapor was identifiable with high statistical confidence in satellite data. Each model received equal weight in the D&A analysis, despite large differences in the skill with which they simulate key aspects of observed climate. Here, we examine whether water vapor D&A results are sensitive to model quality. The “top 10” and “bottom 10” models are selected with three different sets of skill measures and two different ranking approaches. The entire D&A analysis is then repeated with each of these different sets of more or less skillful models. Our performance metrics include the ability to simulate the mean state, the annual cycle, and the variability associated with El Niño. We find that estimates of an anthropogenic water vapor fingerprint are insensitive to current model uncertainties, and are governed by basic physical processes that are well-represented in climate models. Because the fingerprint is both robust to current model uncertainties and dissimilar to the dominant noise patterns, our ability to identify an anthropogenic influence on observed multidecadal changes in water vapor is not affected by “screening” based on model quality.


David Donofrio, Oliker, Shalf, F. Wehner, Rowen, Krueger, Kamil, Marghoob Mohiyuddin, "Energy-Efficient Computing for Extreme-Scale Science", IEEE Computer, January 2009, 42:62-71, doi: 10.1109/MC.2009.35




M. Wehner, L. Oliker, J. Shalf, "Performance Characterization of the World's Most Powerful Supercomputers", Internation Journal of High Performance Computing Applications (IJHPCA), April 2008,

M. Wehner, L. Oliker, J. Shalf, Ultra-Efficient Exascale Scientific Computing, 2008,

N. P. Gillett, D. A. Stone, P. A. Stott, T. Nozawa, A. Yu. Karpechko, G. C. Hegerl, M. F. Wehner, P. D. Jones, "Attribution of polar warming to human influence", Nat. Geosci., 2008, 1:750--754,,

William T.C. Kramer, John M. Shalf, E. Wes Bethel, D. Agarwal, Michael Banda, John Hules, Juan C. Meza, Leonid Oliker, Horst Simon, David Skinner, Francesca Verdier, Howard Walter, Michael Wehner, and Katherine Yelick, "HPC in 2016: A View Point from NERSC", Proceedings of the Cray User Group Conference, Helsinki, Finland, 2008,

Michael F. Wehner, L. Oliker, John Shalf, "Towards Ultra-High Resolution Models of Climate and Weather", Internation Journal of High Performance Computing Applications (IJHPCA), January 2008, 22:149-165,


L. Oliker, J. Shalf, M. Wehner, Climate Modeling at the Petaflop Scale using Semi-Custom Computing, SIAM Conference on Computational Science and Engineering, 2007,


L. Oliker, J. Carter, M. Wehner, A. Canning, S. Ethier, A. Mirin, G. Bala, D. Parks, P. Worley, S. Kitawaki, Y. Tsuda, "Scientific Application Performance on Leading Scalar and Vector Supercomputing Platforms", International Journal of High Performance Computing Applications (IJHPCA), 2006,


Leonid Oliker, Jonathan Carter, Michael Wehner, Andrew Canning, Stephane Ethier, Art Mirin, David Parks, Patrick Worley, Shigemune Kitawaki, Yoshinori Tsuda, "Leading Computational Methods on Scalar and Vector HEC Platforms", SC 05, Washington, DC, USA, IEEE Computer Society, 2005, 62, doi: 10.1109/SC.2005.41

Horst Simon, William Kramer, William Saphir, John Shalf, David Bailey, Leonid Oliker, Michael Banda, C. William McCurdy, John Hules, Andrew Canning, Marc Day, Philip Colella, David Serafini, Michael Wehner, Peter Nugent, "Science-Driven System Architecture: A New Process for Leadership Class Computing", Journal of the Earth Simulator, Volume 2., 2005, LBNL 56545,


Simon, H., Kramer, W., Saphir, W., Shalf, J., Bailey, D., Oliker, L., Banda, M., McCurdy, C.W., Hules, J., Canning, A., Day, M., Colella, P., Serafini, D., Wehner, M., Nugent, P., "National Facility for Advanced Computational ScienceL A Sustainable Path to Scientific Discovery", April 2004, LBNL 5500,

L. Oliker, M. Wehner, D. Parks, W.S. Wang, High Resolution Atmospheric General Circulation Model Simulations on Vector and Cache-based Architectures, SIAM Conference on Parallel Processing for Scientific Computing, 2004,