Sciences and Exploration Directorate

Peter M Norris

(RESEARCH SCIENTIST)

 peter.m.norris@nasa.gov

Org Code: 610.1

NASA/GSFC
Mail Code: 610.1
Greenbelt, MD 20771

Employer: UNIVERSITY OF MARYLAND BALTIMORE CO

Brief Bio


Dr. Peter M. Norris received a BS and MS from the University of Auckland, New Zealand, in 1986 and 1989, and a Ph.D. in Oceanography in 1996 from Scripps Institution of Oceanography (SIO), University of California, San Diego, where his major research interest was numerical modeling of the stratocumulus-topped marine boundary layer. He continued this research in 1996 as a Research Oceanographer in the Marine Meteorology Research Group at SIO, and in 1997-1998 as a New Zealand Postdoctoral Fellow at the National Institute for Water and Atmospheric Research. In 1999 he joined the GSFC Center for Excellence in Space Data and Information Science (USRA/CESDIS) as a Staff Scientist working on cloud parameterization. In 2000 he joined the Goddard Earth Science & Technology Center (UMBC/GEST) as an Assistant Research Scientist, working at the NASA Data Assimilation Office (DAO), now the Global Modeling and Assimilation Office (GMAO), on cloud modeling and assimilation. This work continued under USRA/GESTAR from 2011-2021 and from 2021 onwards under UMBC/GESTARII as a Senior Research Scientist, with his focus transitioning in 2018 to radiative transfer in GMAO's GEOS-5 system.

Dr. Norris' research has addressed methods to improve cloud properties in numerical weather prediction and global climate models, and in particular GMAO's GEOS-5 system. This includes improved cloud parameterizations and simulations using subcolumn statistical approaches (see Norris et al., 2008, QJRMS, v. 134, Oreopoulos & Norris, 2011, ACP, v. 11, and Wind et al., GMD, 2016, v. 9 & 2022, v. 15), and cloud data assimilation of high-resolution satellite cloud data via Bayesian cloud parameter estimation (see Norris and da Silva, 2016, QJRMS, v. 142, Parts 1 & 2). Dr. Norris' current research focuses on advanced radiative transfer methods for GCMs, including proper treatment of cloud subgrid-scale variability.

Dr. Norris has also participated in numerous atmospheric field experiments, including the FIRE Cirrus II, Kansas, 1991, FIRE ASTEX, Azores, 1992, and TOGA-COARE, Solomon Islands, 1993, taking roles in data collection, aircraft flight direction, and data analysis.

Positions/Employment


Senior Research Scientist

Goddard Earth Sciences Technology and Research II (GESTAR2), University of Maryland, Baltimore County (UMBC), Global Modeling and Assimilation Office - NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771

December 2021 - Present


Sr. Scientist, Earth Sciences

Goddard Earth Sciences Technology and Research (GESTAR), University Space Research Association (USRA) - Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771

October 2018 - November 2021


Scientist III

Goddard Earth Sciences Technology and Research (GESTAR), University Space Research Association (USRA) - Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771

2011 - September 2018


Assistant Research Scientist

Goddard Earth Science and Technology Center (GEST), University of Maryland, Baltimore County (UMBC) - Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771

2000 - 2011


Staff Scientist

Center of Excellence in Space Data and Information Science (CESDIS), University Space Research Association (USRA) - Earth and Space Data Computing Division, NASA Goddard Space Flight Center, Code 930, Greenbelt, MD 20771

1999 - 2000


New Zealand Foundation for Research, Sci. and Tech. Postdoctoral Fellow

National Institute of Water and Atmospheric Research (NIWA) - Wellington, New Zealand

1997 - 1999


Post-Graduate Research Oceanographer

Marine Meteorology Research Group, Scripps Institution of Oceanography, University of California, San Diego - San Diego, CA

1996 - 1997

Education


1996, Ph.D., Oceanography, University of California, San Diego (UCSD), Scripps Institution of Oceanography, Dissertation: Radiatively driven convection in marine stratocumulus clouds.
1989, M.Sc., Physics (1st Class Honors), University of Auckland, New Zealand
1986, B.Sc., Physics, University of Auckland, New Zealand

Awards


GMAO Outstanding Performance Award, for implementation of the COSP simulators to support the GEOS-5 submission to CFMIP, January 2012.

Other Professional Information


Selected Publications


Refereed

Wind, G., A. M. da Silva, K. G. Meyer, S. Platnick, and P. M. Norris. 2022. Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS Geoscientific Model Development 15 (1): 1-14 [10.5194/gmd-15-1-2022]

Bian, H., E. Lee, R. D. Koster, et al. D. Barahona, M. Chin, P. R. Colarco, A. Darmenov, S. Mahanama, M. Manyin, P. Norris, J. Shilling, H. Yu, and F. Zeng. 2021. The response of the Amazon ecosystem to the photosynthetically active radiation fields: integrating impacts of biomass burning aerosol and clouds in the NASA GEOS Earth system model Atmospheric Chemistry and Physics 21 (18): 14177-14197 [10.5194/acp-21-14177-2021]

Wind, G., A. M. da Silva, P. M. Norris, et al. S. Platnick, S. Mattoo, and R. C. Levy. 2016. Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters – Part 2: Aerosols Geosci. Model Dev. 9 (7): 2377-2389 [10.5194/gmd-9-2377-2016]

Norris, P. M., and A. M. da Silva. 2016. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results Q.J.R. Meteorol. Soc. 142 (699): 2528-2540 [10.1002/qj.2844]

Norris, P. M., and A. M. da Silva. 2016. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method Q.J.R. Meteorol. Soc. 142 (699): 2505-2527 [10.1002/qj.2843]

Tao, W.-K., S. E. Lang, X. Zeng, et al. X. Li, T. Matsui, K. I. Mohr, D. Posselt, J.-D. Chern, C. D. Peters-Lidard, P. M. Norris, I.-S. Kang, I. Choi, A. Hou, W. K. Lau, and Y.-M. Yang. 2014. The Goddard Cumulus Ensemble model (GCE): Improvements and applications for studying precipitation processes Atmospheric Research 143 392-424 [10.1016/j.atmosres.2014.03.005]

Wind, G., A. M. Da Silva, P. M. Norris, and S. E. Platnick. 2013. Multi-sensor cloud retrieval simulator and remote sensing from model parameters – Part 1: Synthetic sensor radiance formulation Geosci. Model Dev. 6 (6): 2049-2062 [10.5194/gmd-6-2049-2013]

Oreopoulos, L., and P. Norris. 2011. An analysis of cloud overlap at a midlatitude atmospheric observation facility Atmos. Chem. Phys. 11 (12): 5557-5567 [10.5194/acp-11-5557-2011]

Norris, P. M., L. Oreopoulos, A. Y. Hou, W. K. Tao, and X. Zeng. 2008. Representation of 3D heterogeneous cloud fields using copulas: Theory for water clouds Q. J. R. Meteorol. Soc. 1843-1864 10.1002/qj.321

Norris, P. M., and A. M. da Silva. 2007. Assimilation of Satellite Cloud Data into the GMAO Finite-Volume Data Assimilation System Using a Parameter Estimation Method. Part I: Motivation and Algorithm Description J. Atmos. Sci. 64 (11): 3880-3895 [10.1175/2006JAS2046.1]

Rogers, D. P., X. Yang, P. M. Norris, et al. D. W. Johnson, G. M. Martin, C. A. Friehe, and B. W. Berger. 1995. Diurnal evolution of the cloud-topped marine boundary layer. Part I: Nocturnal stratocumulus development J. Atmos. Sci. 52 (16): 2953--2966

Randall, D. A., R. D. Cess, J. P. Blanchet, et al. S. Chalita, R. Colman, D. A. Dazlich, A. D. Del Genio, E. Keup, A. Lacis, H. Le Treut, X. Z. Liang, B. J. McAvaney, J. F. Mahfouf, V. P. Meleshko, J. J. Morcrette, P. M. Norris, G. L. Potter, L. Rikus, E. Roeckner, J. F. Royer, U. Schlese, D. A. Sheinin, A. P. Sokolov, K. E. Taylor, R. T. Wetherald, I. Yagai, and M. H. Zhang. 1994. Analysis of snow feedbacks in 14 general circulation models J Geophys Res 99 (D10): 20,757-20,771 [10.1029/94JD01633]

Cess, R. D., G. L. Potter, M. H. Zhang, et al. J. P. Blanchet, S. Chalita, R. Colman, D. A. Dazlich, A. D. Del Genio, V. Dymnikov, V. Galin, D. Jerrett, E. Keup, A. A. Lacis, H. Le Treut, X. Z. Liang, J. F. Mahfouf, B. J. McAvaney, V. P. Meleshko, J. F. Mitchell, J. J. Morcrette, P. M. Norris, D. A. Randall, L. Rikus, E. Roeckner, J. F. Royer, U. Schlese, D. A. Sheinin, J. M. Slingo, A. P. Sokolov, K. E. Taylor, W. M. Washington, R. T. Wetherald, and I. Yagai. 1991. Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models Science 253 (5022): 888-892 [10.1126/science.253.5022.888]

Non-Refereed

Norris, P. M., L. L. Takacs, W. M. Putman, et al. L. Coy, S. Pawson, E. Mlawer, and M. Iacono. 2020. Transition to the RRTMG Shortwave Radiation Code in GEOS Models Goddard Modeling and Assimilation Office (GMAO) Research Brief

Bosilovich, M. G., S. R. Akella, L. Coy, et al. R. I. Cullather, C. S. Draper, R. Gelaro, R. M. Kovach, Q. Liu, A. M. Molod, P. M. Norris, K. Wargan, C. Yang, R. H. Reichle, L. L. Takacs, Y. V. Vikhliaev, S. C. Bloom, A. Collow, S. Firth, G. J. Labow, G. S. Partyka, S. Pawson, O. Reale, S. D. Schubert, and M. J. Suarez. 2015. MERRA-2: Initial Evaluation of the Climate NASA Technical Report Series on Global Modeling and Data Assimilation 43 (NASA/TM–2015–10) 139 pp.

Gelaro, R., W. M. Putman, S. Pawson, et al. C. S. Draper, A. M. Molod, P. M. Norris, L. E. Ott, N. C. Privé, O. Reale, D. Achuthavarier, M. G. Bosilovich, V. J. Buchard, W. C. Chao, L. Coy, R. I. Cullather, A. M. Da Silva, A. S. Darmenov, R. M. Errico, M. Fuentes, M.-J. Kim, R. D. Koster, W. R. Mccarty, J. Nattala, G. S. Partyka, S. D. Schubert, G. R. Vernieres, Y. V. Vikhliaev, and K. Wargan. 2015. Evaluation of the 7-km GEOS-5 Nature Run NASA Technical Report Series on Global Modeling and Data Assimilation 36 (NASA/TM-2014-104606):