Robert Pincus: Scientific Publications
Titles below link to the article's on-line page as maintained by the journals; this is where you'll find the abstract. The copyright for most articles belongs to the organization publishing the journal, so further redistribution of reprints from this site is not allowed. (The journals Atmospheric Chemistry and Physics and J. Adv. Model Earth Syst. are exceptions.) Please contact me for reprints of any publications for which I haven't provided an electronic copy below.
Submitted, in press | 2011 - present | 2006 - 2010 | 2001 - 2005 | 2000 and before | Book chapters, etc.
Submitted and in press
Bozzo, A., R. Pincus, I. Sandu, and J.-J. Morcrette, 2014: Impact of a spectral sampling technique for radiation on ECMWF weather forecasts Submitted to J. Adv. Model. Earth Syst., Sep 2014. (Preprint, abstract.) Radiation transfer computations are one of the most expensive components of atmospheric models integrations. Methods generally applied to reduce their computational cost, include less frequent update of the radiative fluxes or coarser spatial grids than those used for the rest of the model. In the operational configuration of the Integrated Forecast System (IFS) used at the European Centre for Medium Range Weather Forecasts (ECMWF), radiation accounts for ∼ 10% of the total computer time, and the radiative fluxes are computed with both a reduced temporal and spatial resolution. In this study we show that these approximations have a negligible impact on the forecast errors when looking at the large scale circulation but they lead to biases in the surface temperature. These are linked to inconsistencies in the representation of surface properties or to poorly sampled temporal evolution of the radiative fluxes. Here we explore an alternative method to alleviate such errors, based on a recently developed technique that estimates radiative fluxes from randomly-chosen subsets of spectral points designed to minimise the surface flux error. This approach introduces substantial uncorrelated noise in the radiative fluxes at the surface and heating rates, but it reduces the cost associated to the spectral integration. Therefore it allows to update the radiative transfer computations more frequently and to perform them on a denser spatial grid. We evaluate how this approach applies to five-days weather forecasts by testing different combinations of temporal and spectral sampling at high spatial resolution. We assess the impact of each radiation configuration on the forecast, by comparing the near-surface temperatures to observations from synoptic stations. The results show that a combination of spectrally sparse but temporally and spatially dense radiation calculations has the potential to reduce the forecast errors, particularly those associated with under-resolved topography and stable nocturnal boundary layers, with affordable computational costs.
Articles from 2011 to the present
Pincus, R. and B. Stevens, 2013: Paths to accuracy for radiation parameterizations in atmospheric models. J. Adv. Model Earth Syst., 5, 225-233, doi:10.1002/jame.20027.
Stevens, B. and co-authors, 2013: The Atmospheric Component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model Earth Syst., 5, 146-172, doi:10.1002/jame.20015.
Klein, S. A., Y. Zhang, M. D. Zelinka, R. Pincus, J. Boyle, and P. J. Gleckler, 2013: Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator. J. Geophys. Res., 118, 1329-1342, doi:10.1002/jgrd.50141.
Schirber, S., D. Klocke, R. Pincus, J. Quaas, and J. L. Anderson, 2013: Parameter estimation using data assimilation in an atmospheric general circulation model: From a perfect towards the real world. J. Adv. Model Earth Syst., 5, 58-70, doi:10.1029/2012MS000167.
Zhang, Z., A. S. Ackerman, G. Feingold, S. Platnick, R. Pincus and H. Xue, 2012: Effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius remote sensing: Case study based on large-eddy simulations. J. Geophys. Res., 117, D19208. doi:10.1029/2012JD017655.
Raeder, K., J. L. Anderson, N. Collins, T. Hoar, J. E. Jay, P. H. Lauritzen, and R. Pincus, 2012: DART/CAM: An Ensemble Data Assimilation System for CESM Atmospheric Models. J. Climate, 25, 6304-6317. doi: 10.1175/JCLI-D-11-00395.1.
Mauritsen, T. et al., 2012: Tuning the climate of a global model. J. Adv. Model Earth Syst., 4, M00A01. doi:10.1029/2012MS000154.
Kay, J. E. et al., 2012: Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators. J. Climate, 25, 5190-5207. doi:10.1175/JCLI-D-11-00469.1.
Pincus, R., S. Platnick, S. A. Ackerman, R. S. Hemler, and R. J. P. Hofmann, 2012: Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators. J. Climate, 25, 4699-4720. doi:10.1175/JCLI-D-11-00267.1. (Reprint, abstract.) The properties of clouds that may be observed by satellite instruments, such as optical thickness and cloud top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between can be interpreted as model error. But simulators may themselves be restricted by limited information or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail data sets developed for comparison with global models using ISCCP and MODIS simulators. In nature MODIS observes less mid-level cloudiness than ISCCP, consistent with the different methods used to determine cloud top pressure; aspects of this difference are reproduced by the simulators. Differences in observed distributions of optical thickness, however, are not captured. The largest differences between can be traced to different approaches to partly-cloudy pixels, which MODIS excludes and ISCCP treats as homogeneous. These cover roughly 15% of the planet and account for most optically thinnest clouds. Instrument simulators can not reproduce these differences because there is no way to synthesize partly-cloudy pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by integrating over the robust subset of observations.
Klocke, D., R. Pincus and J. Quaas, 2011: On constraining estimates of climate sensitivity with present-day observations through model weighting. J. Climate, 24, 6092-6099. doi:10.1175/2011JCLI4193.1 (Reprint.)
L. J. Donner et al., 2011: The Dynamical Core, Physical Parameterizations, and Basic Simulation Characteristics of the Atmospheric Component AM3 of the GFDL Global Coupled Model CM3. J. Climate, 24, 3484-3519. doi:10.1175/2011JCLI3955.1.
R. Pincus, R. J. P. Hofmann, J. L. Anderson, K. Raeder, N. Collins, and J. S. Whitaker, 2011: Can fully accounting for clouds in data assimilation improve short-term forecasts? Mon. Wea. Rev., 139, 946-957. doi:10.1175/2010MWR3412.1 (Reprint.)
Articles from 2006-2010
Sandu, I., B. Stevens and R. Pincus, 2010: On the transitions in marine boundary layer cloudiness. Atmos. Chem. Phys., 10, 2377-2391. doi:10.5194/acp-10-2377-2010.
Pincus, R. and K. F. Evans, 2009: Computational cost and accuracy in calculating three-dimensional radiative transfer: Results for new implementations of Monte Carlo and SHDOM. J. Atmos. Sci., 66, 3131-3146. doi:10.1175/2009JAS3137.1. (Reprint, more information.) Here are links to the two radiative transfer codes described in this paper: the I3RC Community Monte Carlo model and SHDOM.
Henderson, P. W. and R. Pincus, 2009: Multiyear evaluations of a cloud model using ARM data. J. Atmos. Sci., 66, 2925-2936. doi:10.1175/2009jas2957.1. (Reprint.)
Pincus, R. and B. Stevens, 2009: Monte Carlo Spectral Integration: a consistent approximation for radiative transfer in large eddy simulations. J. Adv. Model Earth Syst., 1, 9. doi:10.3894/JAMES.2009.1.1. (Reprint.)
Pincus, R., C. P. Batstone, R. J. P. Hofmann, K. E. Taylor, and P. J. Glecker, 2008: Evaluating the present-day simulation of clouds, precipitation, and radiation in climate models. J. Geophys. Res. - Atmos., 113. doi:10.1029/2007jd009334. (Reprint.)
Morcrette, J. J., H. W. Barker, J. N. S. Cole, M. J. Iacono, and R. Pincus, 2008: Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System. Mon. Wea. Rev., 136, 4773-4798. doi:10.1175/2008mwr2363.1. (Reprint.)
Barker, H. W., J. N. S. Cole, J. J. Morcrette, R. Pincus, P. Räisäenen, K. von Salzen, and P. A. Vaillancourt, 2008: The Monte Carlo Independent Column Approximation: An assessment using several global atmospheric models. Q. J. Royal Met. Soc., 134, 1463-1478. doi:10.1002/qj.303. (Reprint.)
Pincus, R., R. Hemler, and S. A. Klein, 2006: Using stochastically generated subcolumns to represent cloud structure in a large-scale model. Mon. Wea. Rev., 134, 3644-3656. doi:10.1175/MWR3257.1. (Reprint.)
Articles from 2001 - 2005
Zhang, M. H. et al., 2005: Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. J. Geophys. Res. - Atmos., 110. doi:10.1029/2004jd005021. (Reprint.)
Pincus, R., C. Hannay, S. A. Klein, K. M. Xu, and R. Hemler, 2005: Overlap assumptions for assumed probability distribution function cloud schemes in large-scale models. J. Geophys. Res. - Atmos., 110. doi:10.1029/2004jd005100. (Reprint.)
Pincus, R., C. Hannay, and K. F. Evans, 2005: The accuracy of determining three-dimensional radiative transfer effects in cumulus clouds using ground-based profiling instruments. J. Atmos. Sci., 62, 2284-2293. doi:10.1175/JAS3464.1. (Reprint.)
Klein, S. A., R. Pincus, C. Hannay, and K. M. Xu, 2005: How might a statistical cloud scheme be coupled to a mass-flux convection scheme? J. Geophys. Res. - Atmos., 110. doi:10.1029/2004jd005017. (Reprint.)
Cahalan, R. F. and co-authors, 2005: The I3RC - Bringing together the most advanced radiative transfer tools for cloudy atmospheres. Bull. Amer. Met. Soc., 86, 1275-+. doi:10.1175/bams-86-9-1275. (Reprint.)
Jakob, C., R. Pincus, C. Hannay, and K. M. Xu, 2004: Use of cloud radar observations for model evaluation: A probabilistic approach. J. Geophys. Res. - Atmos., 109. doi:10.1029/2003jd003473. (Reprint.)
Pincus, R., 2003:
Wine, place, and identity in a changing climate.
3, 87-93. doi:10.1525/gfc.2003.3.2.87.
This article is anthologized in the
Gastronomcia Reader, scheduled to appear in February, 2010.
This journal does not allow redistribution of articles, but you may request a copy by email or purchase one online from the University of California Press.
This work was covered in the news media by The New York Times and (much less carefully) by Newsweek International.
Pincus, R., H. W. Barker, and J. J. Morcrette, 2003: A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields. J. Geophys. Res. - Atmos., 108. doi:10.1029/2002jd003322. (Reprint.)
King, M. D. and co-authors, 2003: Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS. IEEE Trans. Geosci. Rem. Sens., 41, 442-458. doi:10.1109/tgrs.2002.808226. (Reprint.)
Articles from 2000 and before
Pincus, R. and S. A. Klein, 2000: Unresolved spatial variability and microphysical process rates in large-scale models. J. Geophys. Res. - Atmos., 105, 27059-27065. doi:10.1029/2000JD900504. (Reprint.)
Pincus, R., S. A. McFarlane, and S. A. Klein, 1999: Albedo bias and the horizontal variability of clouds in subtropical marine boundary layers: Observations from ships and satellites. J. Geophys. Res. - Atmos., 104, 6183-6191. doi:10.1029/1998JD200125. (Reprint.)
Pincus, R., M. B. Baker, and C. S. Bretherton, 1997: What controls stratocumulus radiative properties? Lagrangian observations of cloud evolution. J. Atmos.Sci., 54, 2215-2236. doi:10.1175/1520-0469(1997)054<2215:WCSRPL>2.0.CO;2. (Reprint.)
Pincus, R., M. Szczodrak, J. J. Gu, and P. Austin, 1995: Uncertainty in cloud optical depth estimates made from satellite radiance measurements. J. Clim., 8, 1453-1462. doi:10.1175/1520-0442(1995)008<1453:UICODE>2.0.CO;2. (Reprint.)
Bretherton, C. S. and R. Pincus, 1995: Cloudiness and marine boundary-layer dynamics in the ASTEX Lagrangian experiments. 1. Synoptic setting and vertical structure. J. Atmos. Sci., 52, 2707-2723. doi:10.1175/1520-0469(1995)052<2707:CAMBLD>2.0.CO;2. (Reprint.)
Austin, P., Y. N. Wang, R. Pincus, and V. Kujala, 1995: Precipitation in stratocumulus clouds - observational and modeling results. J. Atmos. Sci., 52, 2329-2352. doi:10.1175/1520-0469(1995)052<2329:PISCOA>2.0.CO;2. (Reprint.)
Pincus, R. and M. B. Baker, 1994: Effect of precipitation on the albedo susceptibility of clouds in the marine boundary layer. Nature, 372, 250-252. doi:10.1038/372250a0. (More information.) This journal does not allow redistribution of articles, but you may request a copy by email.
Book chapters and the like
Pincus, R., 2013:
Radiation across spatial scales (and model resolutions)
In the Proceedings of the ECMWF Workshop on Parametrization of clouds and precipitation across model resolutions, 5-8 Nov 2012, pages 109-115. (Reprint.)
Pincus, R., 2011:
Radiation: Fast physics with slow consequences in an uncertain atmosphere.
In the Proceedings of the ECMWF/WGNE Workshop on Representing Model Uncertainty and Error in Numerical Weather and Climate Prediction Models, 20-24 June 2011, pages 65-76. (Reprint.)
Pincus, R., 2004:
Book review: A first course in atmospheric radiation, by Grant Petty
Eos, Trans., Amer. Geophys. Union, 85. doi:10.1029/2004EO360007. (Reprint.)
Pincus, R. and S. A. Ackerman, 2004: Radiation in the atmosphere: Foundations. Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Weather Systems, and Measurements T. D. Potter and B. Colman, Eds. John Wiley and Sons, 301-342.
Ackerman, S. A. and Pincus, R.: Radiation in the atmosphere: Observations and applications. Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Weather Systems, and Measurements T. D. Potter and B. Colman, Eds. John Wiley and Sons, 343-385.