Ph.D., 1997, University of Oklahoma
Climate modeling, high-resolution cloud modeling, cloud microphysics, super-parameterization, massively parallel super-computing, cloud parameterization
The main goal of my research is to better understand the role of clouds in the Earth climate system through high-resolution cloud modeling. The foci of modeling activities include microphysics processes, cloud mixing and entrainment, life-cycle of boundary layer clouds, drizzle, turbulence, shallow and deep convection, interactions of clouds with radiation and with atmospheric aerosol.
I have been interested in clouds and numerical modeling of clouds ever since my undergraduate and graduate student years at Moscow Institute of Physics and Technology in late 1980s, and my subsequent employment at the Central Aerological Observatory in Moscow. There, I got my first very valuable experience in cloud modeling. I have developed a numerical model of aircraft dry-ice seeding of orographic clouds applying the explicit or bin microphysics to model processes in artificially seeded clouds. I also developed my first 3-D cloud-resolving model with bulk microphysics.
During my Ph.D. studies at the University of Oklahoma, I developed one of the first Large-Eddy Simulation (LES) models with explicit/bin microphysics and applied it to study the evolution of drizzling marine stratocumulus clouds. Using the LES results, I developed a bulk microphysics parameterization for LES models. The expression for cloud water autoconversion-to-drizzle rate has been used in several regional models and even in a couple of General Circulation Models (GCMs).
After obtaining my Ph.D. degree in 1997, I redesigned my LES model to handle deep convective clouds and made it suitable to run on massively parallel computers. The new cloud-resolving model (CRM) named System for Atmospheric Modeling, or SAM, has been applied to various interesting convection problems, such as, for example, self similarity of deep convection. The easy-to-use-model philosophy and ability to run on hundreds of processors have made SAM quite popular among cloud modelers; in fact, SAM has been used by more than a dozen scientists in the United States and Canada and helped to generate quite a few publications. Here is an incomplete list of organizations whose scientists have been using SAM in their research: Colorado State University, Pacific Northwest National Laboratory, University of Washington, Harvard University, University of Miami, University of British Columbia, University of Oklahoma, NOAA, NASA Langley, University of Hawaii, University of Wisconsin, Scripps Institution of Oceanography.
I also have strong research interests in the area of climate modeling. Several years ago, I put together the first realistic GCM with cloud-resolving model in place of conventional sub-grid scale parameterizations. The resultent model has become known as the Multiscale Modeling Framework (MMF). The prototype MMF has thousands of CRM models running simultaneously; in each GCM grid cell, the CRM (a.k.a. ‘super-parameterization’) simulates the thermodynamic tendencies due to precipitating clouds evolving in response to GCM large-scale forcing and radiation heating rates computed independently in each CRM column. As the result, the MMF has much higher computational cost than a conventional GCM; however, since the ratio of the time that the MMF spends computing to the time spent for inter processor communication is much higher than the one for conventional GCMs, the MMF is vastly more scalable on parallel computers. In fact, it was demonstrated to run on 1024 processors of IBM SP supercomputer with 95% parallel efficiency. Due to its computational cost, the MMF is primerely used to conduct relatively short, 5-10-20 year long present climate simulations using the sea surface temperatures (SSTs), climatological or observed over the same period. The MMF has simulated many observed features of the modern climate rather well. For example, it has simulated a very robust and realistic Madden-Julian Oscillation (MJO) which has been quite a challanging phenomenon for most conventional GCMs to simulate. MMF has also been used to conduct idealized climate sensitivity experiments when the control simulations of the current climate are compared to the simulations of climate with prescribed warmer SSTs. As the next step, the MMF will be coupled with an ocean model to simulate future climate change.
Bretherton, C.S., and M. Khairoutdinov, 2015: Convective self-aggregation feedbacks in near-global cloud-resolving simulations of an aquaplanet. J. Adv. Model. Earth Syst., DOI: 10.1002/2015MS000499
Lee, J. K., and M. Khairoutdinov, 2015: Simplified Land Model (SLM) for use in cloud resolving models: Formulation and evaluation. J. Adv. Model. Earth Syst., 07, doi: 10.1002/2014MS000419
Alfaro, D. A., and M. Khairoutdinov, 2015: Thermodynamic constraints on the morphology of simulated midlatitude squall lines. J. Atmos. Sci., 72, 3116-3137.
Khairoutdinov, M. F., and K. A. Emanuel, 2013: Rotating radiative-convective equilibrium simulated by a cloud-resolving model, J. Adv. Model. Earth Syst., 5, doi:10.1002/2013MS000253.
Khairoutdinov, M. F., and C.-E. Yang, 2013: Cloud-Resolving Modeling of Aerosol Indirect Effects in Idealized Radiative-Convective Equilibrium with Interactive and Fixed Sea Surface Temperature. Atmos. Chem. Phys., 13, 4133-4144, doi:10.5194/acp-13-4133-2013
Goswami B.B, P. Mukhopadhyay, M. Khairoutdinov, B.N. Goswami, 2013: Simulation of Indian summer monsoon intraseasonal oscillations in a superparameterized coupled climate model: need to improve the embedded cloud resolving model. Climate Dynamics. 41, 5-6, 1497-1507.
Wyant, M. C., C. S. Bretherton, P. N. Blossey, and M. Khairoutdinov, 2012: Fast cloud adjustment to increasing CO2 in a superparameterized climate model. J. Adv. Model Earth Syst., VOL. 4, M05001, 14 pp., doi: 10.1029/2011MS000092.
Goswami, B. B., N. J. Mani, P. Mukhopadhyay, D. E. Waliser, J. J. Benedict, E. D. Maloney, M. Khairoutdinov, and B. N. Goswami (2011), Monsoon intraseasonal oscillations as simulated by the superparameterized Community Atmosphere Model, J. Geophys. Res., 116, D22104, doi:10.1029/2011JD015948.
Yamaguchi, T., D. A. Randall, and M. F. Khairoutdinov, 2011: Cloud Modeling Tests of the ULTIMATE-MACHO Scalar Advection Scheme. Monthly Weather Review, 139, pp.3248-3264
DeMott, C. A., C. Stan, D. A. Randall, J. L. Kinter III, and M. Khairoutdinov, 2011: The Asian Monsoon in the Super-Parameterized CCSM and its relation to tropical wave activity. J. Climate, 24, 5134-5156
vanZanten, M.C., B. B. Stevens, L. Nuijens, A. P. Siebesma, A. Ackerman, F. Burnet, A. Cheng, F. Couvreux, H. Jiang, M. Khairoutdinov, Y. Kogan, D. C. Lewellen, D. Mechem, K. Nakamura, A. Noda, B. J. Shipway, J. Slawinska, S. Wang and A. Wyszogrodzki. 2011. Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO. Journal of Advances in Modelling Earth Systems 3, M06001
Wang, M., S. Ghan, R. Easter, M. Ovchinnikov, X. Liu, E. Kassianov, Y. Qian, W. I. Gustafson Jr., V. E. Larson, D. P. Schanen, M. Khairoutdinov and H. Morrison. 2011. The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation.Geoscientific Model Development 4(1): 137-168.
Bogenschutz, P. A., S. K Krueger and Marat Khairoutdinov. 2010. Assumed probability density functions for shallow and deep convection. Journal of Advances in Modelling Earth Systems Vol. 2, Art. #10, 24 pp., doi:10.3894/JAMES.2010.2.10
DeMott, C. A., D. A. Randall and M. Khairoutdinov. 2010. Implied ocean heat transports in the standard and super-parameterized community atmospheric models. Journal of Climate 23: 1908-1928.
Stan, C., M. F. Khairoutdinov, C. A. DeMott, V. Krishnamurthy, D. M. Straus, D. A. Randall, J. L. Kinter, III and J. Shukla. 2010. An ocean-atmosphere climate simulation with an embedded cloud resolving model. Geophysical Research Letters 37, L01702, doi:10.1029/2009GL040822.
Moeng, C.-H., P. P. Sullivan, M. F. Khairoutdinov and D. A. Randall. 2010. A mixed scheme for subgrid-scale fluxes in cloud-resolving models. Journal of the Atmospheric Sciences 11: 3692-3705.
Khairoutdinov M. F., S. K. Krueger, C.-H. Moeng, P. A. Bogenschutz and D. A Randall. 2009. Large-eddy simulation of maritime deep tropical convection. Journal of Advances in Modelling Earth Systems Vol. 1, Art. #15, 13 pp., doi:10.3894/JAMES.2009.1.15
Moeng C. H., M. A. LeMone, M. F. Khairoutdinov, S. K. Krueger, P. A. Bogenschutz and D. A. Randall. 2009. The tropical marine boundary layer under a deep convection system: a large-eddy simulation study. Journal of Advances in Modelling Earth Systems. Vol 1, Art. #16, 13 pp., doi:10.3894/ JAMES.2009.1.16
Kim, D., K. Sperber, W. Stern, D. Waliser, I.-S. Kang, E. Maloney, W. Wang, K. Weickmann, J. Benedict, M. Khairoutdinov, M.-I. Lee, R. Neale, M. Suarez, K. Thayer-Calder and G. Zhang. 2009. Application of MJO simulation diagnostics to climate models. Journal of Climate 22: 6413-6436.
Ackerman, A. S., M. C. vanZanten, B. Stevens, V. Savic-Jovcic, C. S. Bretherton, A. Chlond, J.-C. Golaz, H. Jiang, M. Khairoutdinov, S. K. Krueger, D. C. Lewellen, A. Lock, C.-H. Moeng, K. Nakamura, M. D. Petters, J. R. Snider and M. Zulauf. 2009. Large-eddy simulations of a drizzling, stratocumulus-topped marine boundary layer. Monthly Weather Review 137: 1083-1110.
Tao, W. K., J.-D. Chern, R. Atlas, D. A. Randall, M. F. Khairoutdinov, J.-L. Li, D. E. Waliser, A. Hou, X. Lin, C. Peters-Lidard, W. Lau, J. Jiang and J. Simpson. 2009. A multi-scale modeling system: developments, applications and critical issues. Bulletin of the American Meteorological Society 90: 515-534.
Mapes, B., J. Bacmeister, M. Khairoutdinov, C. Hannay and M. Zhao. 2009. Virtual field campaigns on deep tropical convection in climate models. Journal of Climate 22: 244-257.
Khairoutdinov, M., C.A. Demott and D. A. Randall. 2008. Evaluation of the simulated interannual and subseasonal variability in an AMIP-style simulation using the CSU multi-scale modeling framework. Journal of Climate 21: 413-431.
DeMott, C. A., D. A. Randall, and M. Khairoutdinov, 2007: Convective precipitation variability as a tool for general circulation model analysis. J. Climate., 20, 91–112.
Blossey, P. N., C. S. Bretherton, J. Cetrone, and M. Khairoutdinov, 2007: Cloud-resolving model simulations of KWAJEX: Model sensitivities and comparisons with satellite and radar observations. J. Atmos. Sci., 64, 1488-1508.
Khairoutdinov, M. F., and D. A. Randall, 2006: High-resolution simulation of shallow-to-deep convection transition over land. J. Atmos. Sci., 63, 3421–3436.
Wyant, M. C., M. Khairoutdinov, and C. S. Bretherton, 2006: Climate sensitivity and cloud response of a GCM with a superparameterization. Geophys. Res. Lett., 33, L06714, doi:10.1029/2005GL025464.
Ovtchinnikov, M., T. P. Ackerman, R. T. Marchand, and M. F. Khairoutdinov, 2006: Evaluation of the Multi-scale Modeling Framework using data from the Atmospheric Radiation Measurement program, J. Climate, 19, 1716-1729.
Beare, R.J., M.K. MacVean, A.A.M. Holtslag, J. Cuxart, I. Esau, J.C. Golaz, M.A. Jimenez, M. Khairoudinov, B. Kosovic, D. Lewellen, T.S. Lund, J.K. Lundquist, A. McCabe, A.F. Moene, Y. Noh, S. Raasch, and P. Sullivan, 2004: An intercomparison of large eddy simulations of the stable boundary layer, Bound. Layer Meteor. 118(2), 247.
Bretherton, C. S., P. N. Blossey, and M. Khairoutdinov, 2005: An energy-balance analysis of deep convective self-aggregation above uniform SST. J. Atmos. Sci., 62, 4273-4292.
Grabowsky W. W., P. Bechtold, A. Cheng, R. Forbes, C. Halliwell, M. F. Khairoutdinov, S. Lang, T. Nasuno, J. Petch, W.-K. Tao, R. Wong, X. Wu, AND K.-M. Xu, 2005: Daytime convective development over land: a model intercomparison based on LBA observations.Q. J. Roy. Meteor. Soc., 132, 317-344.
Xu, K.-M., M. Zhang, Z. A. Eitzen, S. J. Ghan, S. A. Klein, X. Wu, S. Xie, M. Branson, A. D. Del Genio, S. F. Iacobellis, M. F. Khairoutdinov, W. Lin, U. Lohmann, D. A. Randall, R. C. J. Somerville, Y. C. Sud, G. K. Walker, A. Wolf, J. J. Yio, J. Zhang, 2005: Modeling Springtime Shallow Frontal Clouds with Cloud-resolving and Single-column Models, J. Geophys. Res., 110, D15S04, doi:10.1029/2004JD005153.
Li, J.-L., D. E. Waliser, J. H. Jiang, D. L. Wu, W. Read, J. W. Waters, A. M. Tompkins, L. J. Donner, J.-D. Chern, W.-K. Tao,R. Atlas, Y. Gu, K. N. Liou, A. Del Genio, M. Khairoutdinov, and A. Gettelman: Comparisons of EOS MLS cloud ice measurements with ECMWF
analyses and GCM simulations: Initial results. Geophys. Res. Lett., 32, L18710, doi:10.1029/2005GL023788.
Khairoutdinov, M. F., D.A. Randall, and C. DeMotte, 2005: Simulations of the atmospheric general circulation using a cloud-resolving model as a super-parameterization of physical processes. J. Atmos. Sci., 62, 2136-2154.
Cole J. N. S., H. W. Barker, D. A. Randall, M. F. Khairoutdinov, and E. E. Clothiaux, 2005: Global consequences of interactions between clouds and radiation at scales unresolved by global climate models. Geophys. Res. Lett., 32, L06703, doi: 10.1029/2004GL020945.
Stevens, B., C.-H. Moeng, A. S. Ackerman, C. S. Bretherton, A. Chlond, S. deRoode, J. Edwards, C. Golaz, H. Jiang, M. Khairoutdinov, M. Kirkpatrick, D. C. Lewellen, A. Lock, F. Mueller, D. E. Stevens, E. Whelan, and P. Zhu, 2005: Observations of nocturnal marine stratocumulus as represented by large eddy simulation, Mon. Wea. Rev., 133, 1443-1462.
Raisanen, P, H. W. Barker, M. F. Khairoutdinov, J. Li, and D. A. Randall, 2004: Stochastic generation of subgrid-scale cloudy columns for large-scale models, Q. J. Roy. Meteor. Soc., 130, 2047-2067.
Iorio, J. P., P. B. Duffy, B. Govindasamy, S. L. Thompson, M. F. Khairoutdinov, D. A. Randall, 2004: Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States, Climate Dynamics, 2004, 23, no. 3/4, pp. 243-258.
Oreopoulos L, Choub M.-D., M. Khairoutdinov, H. W. Barker, and R. F. Cahalan, 2004: Performance of Goddard Earth Observing System GCM Column Radiation Models under heterogeneous cloud conditions. Atmos. Research, 72, 365–382.
Randall, D. A., M. Khairoutdinov, A. Arakawa, and W. Grabowski, 2003: Breaking the cloud-parameterization deadlock. Bull. Amer. Meteor. Soc., 84, 1547-1564.
Khairoutdinov, M. F., and D.A. Randall, 2003: Cloud-resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties and sensitivities. J. Atmos. Sci., 60, 607-625.
Oreopoulos L., and M. Khairoutdinov, 2003: Overlap properties of clouds generated by a cloud-resolving model. J. Geoph. Res., 108(D15), 4479-
Siebesma, A.P., C. S. Bretherton, A.R. Brown, A. Chlond, J. Cuxart, P.G. Duynkerke, H. Jiang, M. Khairoutdinov, D.C. Lewellen, C-H. Moeng, E. Sanchez, B. Stevens, and D.E. Stevens, 2003: A large-eddy simulation intercomparison study of shallow cumulus convection. J. Atmos. Sci., 60, 1201-1219.
Brown, A. R., R. T. Cederwall, A. Chlond, P.G. Duynkerke, J-C. Golaz, M. Khairoutdinov, D. C. Lewellen, A. P. Lock, M. K. MacVean, C.-H. Moeng, R. A. J. Neggers, A. P. Siebesma and B. Stevens, 2002: Large-eddy simulation of the diurnal cycle of shallow cumulus convection over land. Quart. J. Roy. Meteor. Soc., 128, 1075-1093.
Khairoutdinov, M. F., and D.A. Randall, 2002: Similarity of deep continental cumulus convection as revealed by a three-dimensional cloud resolving model. J. Atmos. Sci., 59, 2550-2566.
Khairoutdinov, M. F., and D.A. Randall, 2001: A cloud resolving model as a cloud parameterization in the NCAR Community Climate System Model: Preliminary Results. Geophys. Res. Lett., 28, 3617-3620.
Khairoutdinov, M. F., and Y. L. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229-243
Bretherton, C. S., M. K. Mac Vean, P. Bechtold, A. Chlond, W. R. Cotton, J. Cuxart, H. Cuijpers, M. Khairoutdinov, B. Kosovic, D. Lewellen, C.-H. Moeng, P. Siebesma, B. Stevens, D. E. Stevens, I. Sykes, and M. C. Wyant, 1999: An intercomparison of radiatively-driven entrainment and turbulence in a smoke cloud, as simulated by different numerical models. Quart. J. Roy. Meteor. Soc., 125, 391-423.
Khairoutdinov, M. F., and Y. L. Kogan, 1999: A large-eddy simulation model with explicit microphysics: Validation against aircraft observations of a stratocumulus-topped boundary layer. J. Atmos. Sci., 56, 2115-2131.
Liu, Q., Kogan, Y. L., D. K. Lilly, M. F. Khairoutdinov, 1997: Variational Optimization Method for Calculation of Cloud Drop Growth in an Eulerian Drop-Size Framework. J. Atmos. Sci.: Vol. 54, No. 20, pp. 2493-2504.
Moeng, C.-H., Cotton, W.R., Stevens, B., Bretherton, C., Rand, H.A., Chlond, A., Khairoutdinov, M., Krueger, S., Lewellen, W.S., MacVean, M.K., Pasquier, J.R.M., Siebesma, A.P., Sykes, R.I.. 1996: Simulation of a Stratocumulus-Topped Planetary Boundary Layer: Intercomparison among Different Numerical Codes. Bull. Amer. Meteor. Soc., 77, 261-278.
Kogan, Y.L., M. Khairoutdinov, D. K. Lilly, Z. N. Kogan, Q. Liu, 1995: Modeling of Stratocumulus Cloud Layers in a Large Eddy Simulation Model with Explicit Microphysics. J. Atmos. Sci., 52, 2923-2940.
Fiedler, B. H., and M. Khairoutdinov, 1994: Cell broadening in three-dimensional thermal convection between poorly conducting boundaries: Large eddy simulations. Beitr. Phys. Atmos., 67, 235-241.
Khvorostyanov, V.I., and M. F. Khairoutdinov, 1990: Modeling aircraft seeding of orographic cloud over an extended mountainous area.Soviet Meteorology and Hydrology (Meteorologiya I Gidrologiya) (translated to English from Russian), 11, 34-41.
Khairoutdinov, M. F., and V. I. Khvorostyanov, 1988: Modeling an artificial increase of precipitation from orographic clouds with periodic seeding of dry ice from an airplane. Trudy TsAO (in Russian), No.175.