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 




Mlawer, E. J., J. Mascio, D. D. Turner, V. Payne, C. Flynn, and R. Pincus, 2024. A more transparent water vapor window. Submitted to J. Geophys. Res. Atmos., Apr 2024. Preprint at doi:10.22541/essoar.171328603.35133326/v1

Roemer, F. E., S. A. Buehler, L. Kluft, and R. Pincus, 2023. Effect of uncertainty in water vapor continuum absorption on radiative forcing, longwave feedback, and climate sensitivity, Submitted to J. Adv. Model. Earth Syst., Dec 2023. Preprint at  doi:10.22541/essoar.168881869.96894704/v1

Veerman, M. A., Pincus, R., Mlawer, E. J., & van Heerwaarden, C. C., 2024. The impact of radiative transfer at reduced spectral resolution in large-eddy simulations of convective clouds. J. Adv. Modeling Earth Syst. 16, e2023MS003699. doi:10.1029/2023MS003699

Chen, X. et al., 2023: Ubiquitous sea surface temperature warm anomalies increase spatial heterogeneity of trade-wind cloudiness on daily timescales. J. Atmos. Sci., 80, 2969-2987, doi:10.1175/JAS-D-23-0075.1

Črnivec, N, G. Cesana, and R. Pincus, 2023. Evaluating the Representation of Tropical Stratocumulus and Shallow Cumulus Clouds As Well As Their Radiative Effects in CMIP6 Models Using Satellite Observations. J. Geophys. Res., 128, e2022JD038437, doi:10.1029/2022JD038437 

Czarnecki, P., L. M. Polvani, and R. Pincus, 2023. Sparse, empirically optimized quadrature for broadband spectral integration. J. Adv. Modeling Earth Syst., 15, e2023MS003819. doi:10.1029/2023MS003819

Pincus, R., P. A. Hubanks, S. A. Platnick, K. Meyer, R. E. Holz, D. Botambekov, and C. J. Wall, 2023: Updated observations of clouds by MODIS for global model assessment. Earth Syst. Sci. Data, 15, 2483–2497, doi:10.5194/essd-15-2483-2023.

Fildier, B., C. Muller, R. Pincus, and S. Fueglistaler, 2023: How moisture shapes low-level radiative cooling in subsidence regimes. AGU Advances, 4, e2023AV000880, doi:10.1029/2023AV000880

Cesana G.V., A.S. Ackerman, N. Črnivec, R. Pincus, and H. Chepfer, 2023: An observation-based method to assess tropical stratocumulus and shallow cumulus clouds and feedbacks in CMIP6 and CMIP5 models. Env. Res. Lett., 5, 045001, doi:10.1088/2515-7620/acc78a

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. Data, 13, 1759–1790, doi:10.5194/essd-13-1759-2021.

Albright, A. L. et al., 2021: Atmospheric Radiative Profiles during EUREC4A. Earth Syst. Sci. Data, 13, 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.