Robert Pincus

Principal Investigator

I'm an atmospheric physicist interested in how clouds and radiation -- sunshine and earthlight -- sculpt the circulation of the atmosphere and the thermal and hydrological climate.


PhD. in Geophysics, University of of Washington, 1994

B.S. in Physics, University of Washington, 1987

2021 - Lamont Research Professor, Lamont Doherty Earth Observatory, Columbia University

2001 - 2021 Cooperative Institute for Research in Environmental Sciences, University of Colorado, with a joint appointment at the NOAA Physical Sciences Lab and its predecessors 

1998 - 2001 Visiting Professor, Department of Atmospheric and Oceanic Sciences, and Research Scientist, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin Madison 

1997 - 1998 Assistant Research Professor, Joint Center for Earth System Technology, University of Maryland Baltimore County

1995 - 1997 National Research Council Research Associate, NASA/Goddard Space Flight Center

Member, Coupled Model Intercomparision Project (CMIP) Panel (2020-)

Editor-in-Chief, Journal of Advances in Modeling Earth Systems (2015-2020; Associate Editor 2013-2014)

Lead coordinator, Radiative Forcing Model Intercomparison Project (RFMIP; 2014-)

Leader, Initiative on Leveraging the Past Record, WCRP Grand Challenge on Clouds, Circulation, and Climate Sensitivity (2013-)

Member, Science Advisory Board, Developmental Testbed Center (2018-2020)

Member, Science Advisory Board, HD(CP)2 (High Definition Clouds & Precipitation for Climate Prediction, Germany, 2013-2016)

Member, AMS Panel on Atmospheric Radiation (2013-2018)

Member, GEWEX Global Atmospheric System Studies (GASS) scientific steering committee (2011-2018)

My profile at Columbia's Climate School 




Pincus, R., P. A. Hubanks, S. A. Platnick, K. Meyer, R. E. Holz, D. Botambekov, and C. J. Wall, 2022: Updated observations of clouds by MODIS for global model assessment. Under open review at Earth System. Sci. Data, doi:10.5194/essd-2022-282


Buehler, S. A. et al., 2022: A new halocarbon absorption model based on HITRAN cross-section data and new estimates of halocarbon instantaneous clear-sky radiative forcing. J. Adv. Modeling Earth Syst., 14, e2022MS003239, doi:10.1029/2022MS003239

Chen, T.-C., S. G. Penny, J. S. Whitaker, S. Frolov, R. Pincus, and S. Tulich, 2022: Correcting systematic and state-dependent errors in the NOAA FV3-GFS using neural networks. J. Adv. Modeling Earth Syst., 14, e2022MS003309, doi:10.1029/2022MS003309

Giorgetta, M. A. et al., 2022: The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514), Geosci. Model Dev., 15, 6985–7016, doi:10.5194/gmd-15-6985-2022

George, G. et al., 2021: JOANNE: Joint dropsonde Observations of the Atmosphere in tropical North atlaNtic meso-scale Environments, Earth Syst. Sci. Data, 13, 5253–5272, doi:10.5194/essd-13-5253-2021.

Stevens, B., S. Bony, D. Farrell et al., 2021: EUREC4A, Earth Syst. Sci. Data, 13, 4067–4119, doi:10.5194/essd-13-4067-2021

Pincus, R. et a., 2021: Observations from the NOAA P-3 aircraft during ATOMIC, Earth Syst. Sci. Data, 13, 3281–3296, doi:10.5194/essd-13-3281-2021.

Quinn, P. K. et al., 2021: Measurements from the RV Ronald H. Brown and related platforms as part of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). Earth Syst. Sci. Data13, 1759–1790, doi:10.5194/essd-13-1759-2021.

Albright, A. L. et al., 2021: Atmospheric Radiative Profiles during EUREC4A. Earth Syst. Sci. Data13, 617–630, doi:10.5194/essd-13-617-2021

Veerman, M. A. et al., 2021: Predicting atmospheric optical properties for radiative transfer computations using neural networks. Phil. Trans. Royal Soc. A.379, 20200095, doi:10.1098/rsta.2020.0095

Pincus, R. et al., 2020: Benchmark calculations of radiative forcing by greenhouse gases. J. Geophys. Res. - Atmos.125, e2020JD033483, doi:10.1029/2020JD033483

Ukkonen, P., R. Pincus, R. J. Hogan, K. P. Nielsen, and E. Kaas, 2020: Accelerating radiation computations for dynamical models with targeted machine learning and code optimization. J. Adv. Modeling Earth Syst.12, e2020MS002226, doi:10.1029/2020MS002226

Smith, C. J. et al., 2020: Effective radiative forcing and adjustments in CMIP6 models. Atmos. Chem. Phys.20, 9591–9618, doi:10.5194/acp-20-9591-2020

Pincus, R., Eli J. Mlawer and Jennifer S. Delemere, 2019: Balancing accuracy, efficiency, and flexibility in radiation calculations for dynamical models. J. Adv. Modeling Earth Syst.11, 3074-3089, doi:10.1029/2019MS001621

Randall, D. A. et al., 2019: 100 years of model development. Meteor. Monographs, 59, 12.1-12.66, doi:10.1175/AMSMONOGRAPHS-D-18-0018.1

Mauritsen, T. et al., 2019: Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM 1.2) and its response to increasing CO2J. Adv. Modeling Earth Syst., 11, 998– 1038, doi:10.1029/2018MS001400

Abramowitz, G. et al., 2019: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing. Earth Syst. Dyn., 10, 91-105, doi:10.5194/esd-10-91-2019

Eyring, V. et al., 2019: Taking climate model evaluation to the next level. Nature Clim. Change, 9, 102-110, doi:10.1038/s41558-018-0355-y. (Read via Readcube)

Marvel, K., R. Pincus, G. Schmidt, and R. L Miller, 2018: Internal variability and disequilibrium confound estimates of climate sensitivity from observations. Geophys. Res. Lett., 45, 1595–1601, doi:10.1002/2017GL076468

Swales, D. J., R. Pincus, and A. Bodas-Salcedo, 2018: The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2. Geosci. Model Dev., 11, 77-81, doi:10.5194/10.5194/gmd-11-77-2018

Clement, V. et al., 2018: The CLAW DSL: Abstractions for Performance Portable Weather and Climate Models. Proc. Platform Adv. Sci. Computing, 2, 1-10, doi:10.1145/3218176.3218226

Jones, A. L. et al., 2017: A new paradigm for diagnosing contributions to model aerosol forcing error. Geophys. Res. Lett.44, 12004–12012, doi:10.1002/2017GL075933

Pincus, R. et al., 2017: The representation of tropospheric water vapor over low-latitude oceans in (re-)analysis: Errors, impacts, and the ability to exploit current and prospective observations. Surv. Geophys., 38, 1399-1423, doi:10.1007/s10712-017-9437-z.

Klein, S. A., A. Hall, J. R. Norris, and R. Pincus, 2017: Low-cloud feedbacks from cloud-controlling factors: A review. Surv. Geophys., 38, 1307-1329, doi:10.1007/s10712-017-9433-3

Lebsock, M., T. S. L'Ecuyer, and R. Pincus, 2017: An observational view of relationships between moisture aggregation, cloud, and radiative heating profiles. Surv. Geophys., 38, 1237-1254, doi:10.1007/s10712-017-9443-1

Mauritsen, T. and R. Pincus, 2017: Committed warming inferred from observations. Nature Clim. Change7, 652-655, doi:10.1038/nclimate3357. (Read Cube version.)

Voigt, A. et al., 2017: Fast and slow shifts of the zonal-mean intertropical convergence zone in response to an idealized anthropogenic aerosol. J. Adv. Modeling Earth Sys.9, 870-892, doi:10.1002/2016MS000902

Forster, P. M. et al., 2016: Recommendations for diagnosing effective radiative forcing from climate models for CMIP6 J. Geophys. Res. - Atmos.121, 12460-12475, doi:10.1002/2016JD025320

Pincus, R., P. M. Forster, and B. Stevens, 2016: The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6. Geosci. Model Dev., 9, 3447-3460, doi:10.5194/gmd-9-3447-2016

Mlawer, E. J., M. J. Iacono, R. Pincus, H. W. Barker, L. Oeropoulos, D. L. Mitchell, 2016: Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications. Meteor. Monographs57 15.1-15.19. doi:10.1175/AMSMONOGRAPHS-D-15-0041.1

Seifert, A., T. Heus, R. Pincus, and B. Stevens, 2015: Large-eddy simulation of the transient and near-equilibrium behavior of precipitating shallow convection. J. Adv. Model. Earth Syst., 7, 1918-1937, doi:10.1002/2015MS000489.

Pincus, R. et al., 2015: Radiative flux and forcing parameterization error in clear, clean skies. Geophys. Res. Let.42, 5485–5492, doi:10.1002/2015GL064291.

Bony, S., et al., 2015: Clouds, circulation, and climate sensitivity. Nature Geosci.8, 261–268, doi:10.1038/ngeo2398

Bozzo, A., R. Pincus, I. Sandu, and J.-J. Morcrette, 2014: Impact of a spectral sampling technique for radiation on ECMWF weather forecasts. J. Adv. Model. Earth Syst.6, 1288–1300, doi:10.1002/2014MS000386

Feldman, D., W. D. Collins, R. Pincus, X. Huang, and X. Chen, 2014: Far-infrared surface emissivity and climate.  Proc. Nat. Acad. Sci.111, 16297-16302, doi:10.1073/pnas.1413640111.

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. - Atmos.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. - Atmos.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. Climate25, 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. Climate25, 4699-4720. doi:10.1175/JCLI-D-11-00267.1.

Klocke, D., R. Pincus and J. Quaas, 2011: On constraining estimates of climate sensitivity with present-day observations through model weighting. J. Climate24, 6092-6099. doi:10.1175/2011JCLI4193.1

Bodas-Salcedo, A. et al, 2011: COSP: Satellite simulation software for model assessment. Bull. Amer. Met. Soc.92, 1023-1043. doi:10.1175/2011BAMS2856.1

Donner, L. J. 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. Climate24, 3484-3519. doi:10.1175/2011JCLI3955.1.

Pincus, R, 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

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. (more information.

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.

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, 1. doi:10.3894/JAMES.2009.1.1.

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.

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.

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.

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. 

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.

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. 

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. 

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. 

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. 

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.

Pincus, R., 2003: Wine, place, and identity in a changing climate. Gastronomica3, 87-93. doi:10.1525/gfc.2003.3.2.87.

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, 4376. doi: 10.1029/2002jd003322.

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.

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.

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.

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.

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.

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. 

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.

Pincus, R. and M. B. Baker, 1994: Effect of precipitation on the albedo susceptibility of clouds in the marine boundary layer. Nature372, 250-252. doi: 10.1038/372250a0. 

Pincus, R. and H. Chepfer, 2020: Clouds as light. In Clouds and climate: Climate Science's greatest challenge. A. P. Siebesma, S. Bony, C. Jakob, and B. Stevens, Eds. Cambridge University Press, 99-122. doi:10.1017/9781107447738.005

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.

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.