Mikhail D. Alexandrov

Organization

NASA Goddard Institute for Space Studies

Columbia University

Email

Contact person by email

Business Address

Department of Applied Physics and Applied Mathematics
2880 Broadway
New York, NY 10025
United States

Website

http://www.giss.nasa.gov/staff/malexandrov.ht

First Author Publications

Alexandrov, M.D., et al. (2022), Markovian Statistical Model of Cloud Optical Thickness. Part I: Theory and Examples, J. Atmos. Sci., 79, 3315-3332, doi:10.1175/JAS-D-22-0125.1.
Alexandrov, M.D., et al. (2020), Vertical profiles of droplet size distributions derived from cloud-side T observations by the research scanning polarimeter: Tests on simulated data ⁎, Atmos. Res., 239, 104924, doi:10.1016/j.atmosres.2020.104924.
Alexandrov, M.D., et al. (2018), Retrievals of cloud droplet size from the research scanning polarimeter data: T Validation using in situ measurements, Remote Sensing of Environment, 210, 76-95, doi:10.1016/j.rse.2018.03.005.
Alexandrov, M.D., and M.I. Mishchenko (2017), Information content of bistatic lidar observations of aerosols from space, Optics Express, 25, A134-A150.
Alexandrov, M.D., and A. Marshak (2017), Cellular Statistical Models of Broken Cloud Fields. Part III: Markovian Properties, J. Atmos. Sci., 74, 2921-2935, doi:10.1175/JAS-D-17-0075.1.
Alexandrov, M.D., et al. (2016), Polarized view of supercooled liquid water clouds, Remote Sensing of Environment, 181, 96-110, doi:10.1016/j.rse.2016.04.002.
Alexandrov, M.D., et al. (2016), Derivation of cumulus cloud dimensions and shape from the airborne measurements by the Research Scanning Polarimeter, Remote Sensing of Environment, 177, 144-152, doi:10.1016/j.rse.2016.02.032.
Alexandrov, M.D., et al. (2016), New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean*, J. Atmos. Sci., 73, 821-837, doi:10.1175/JAS-D-15-0130.1.
Alexandrov, M.D., et al. (2015), Liquid water cloud properties during the Polarimeter Definition Experiment (PODEX), Remote Sensing of Environment, 169, 20-36, doi:10.1016/j.rse.2015.07.029.
Alexandrov, M.D., et al. (2012), Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter, Remote Sensing of Environment, 125, 92-111, doi:10.1016/j.rse.2012.07.012.
Alexandrov, M.D., et al. (2012), Rainbow Fourier transform, J. Quant. Spectrosc. Radiat. Transfer, 113, 2521-2535, doi:10.1016/j.jqsrt.2012.03.025.
Alexandrov, M.D., et al. (2010), Cellular Statistical Models of Broken Cloud Fields. Part I: Theory, J. Atmos. Sci., 67, 2125-2151, doi:10.1175/2010JAS3364.1.
Alexandrov, M.D., et al. (2010), Cellular Statistical Models of Broken Cloud Fields. Part II: Comparison with a Dynamical Model and Statistics of Diverse Ensembles, J. Atmos. Sci., 67, 2152-2170, doi:10.1175/2010JAS3365.1.
Alexandrov, M.D., et al. (2009), Columnar water vapor retrievals from multifilter rotating shadowband radiometer data, J. Geophys. Res., 114, D02306, doi:10.1029/2008JD010543.
Alexandrov, M.D., et al. (2008), Characterization of atmospheric aerosols using MFRSR measurements, J. Geophys. Res., 113, D08204, doi:10.1029/2007JD009388.
Alexandrov, M.D., et al. (2007), Optical depth measurements by shadow-band radiometers and their uncertainties, Appl. Opt., 46, 8027-8038.
Alexandrov, M.D., et al. (2005), Separation of fine and coarse aerosol modes in MFRSR data sets, J. Geophys. Res., 110, D13204, doi:10.1029/2004JD005226.
Alexandrov, M.D., et al. (2004), Automated cloud screening algorithm for MFRSR data, Geophys. Res. Lett., 31, L04118, doi:10.1029/2003GL019105.
Alexandrov, M.D., et al. (2004), Scaling Properties of Aerosol Optical Thickness Retrieved from Ground-Based Measurements, J. Atmos. Sci., 61, 1024-1039.
Alexandrov, M.D., et al. (2002), Remote Sensing of Atmospheric Aerosols and Trace Gases by Means of Multifilter Rotating Shadowband Radiometer. Part II: Climatological Applications, J. Atmos. Sci., 59, 544-566.
Alexandrov, M.D., et al. (2002), Remote Sensing of Atmospheric Aerosols and Trace Gases by Means of Multifilter Rotating Shadowband Radiometer. Part I: Retrieval Algorithm, J. Atmos. Sci., 59, 524-543.
Alexandrov, M.D., and A. Lacis (2000), A new three-parameter cloud/aerosol particle size distribution based on the generalized inverse Gaussian density function, Applied Mathematics and Computation, 116, 153-165.

Note: Only publications that have been uploaded to the ESD Publications database are listed here.

Co-Authored Publications

Sorooshian, A., et al. (2023), Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset, Earth Syst. Sci. Data, 15, 3419-3472, doi:10.5194/essd-15-3419-2023.
Fu, D., et al. (2022), An evaluation of the liquid cloud droplet effective radius derived from MODIS, airborne remote sensing, and in situ measurements from CAMP2 Ex, Atmos. Chem. Phys., doi:10.5194/acp-22-8259-2022.
Sinclair, K.A., et al. (2021), Inference of Precipitation in Warm Stratiform Clouds Using Remotely Sensed Observations of the Cloud Top Droplet Size Distribution, Geophys. Res. Lett..
Miller, D.J., et al. (2020), Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm, Atmos. Meas. Tech., 13, 3447-3470, doi:10.5194/amt-13-3447-2020.
Sinclair, K.A., et al. (2020), Observations of Aerosol‐Cloud Interactions During the North Atlantic Aerosol and Marine Ecosystem Study, Geophys. Res. Lett., 47, 1-10, doi:10.1029/2019GL085851.
Sinclair, K.A., et al. (2019), Polarimetric retrievals of cloud droplet number concentrations T a,b,⁎ b,c b b,c, Remote Sensing of Environment, 228, 227-240, doi:10.1016/j.rse.2019.04.008.
Segal-Rozenhaimer, M., et al. (2018), Development of neural network retrievals of liquid cloud properties from multi-angle polarimetric observations, J. Quant. Spectrosc. Radiat. Transfer, 220, 39-51, doi:10.1016/j.jqsrt.2018.08.030.
Xu, F., et al. (2018), Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), J. Geophys. Res., 123, 3175-3204, doi:10.1002/2017JD027926.
Mishchenko, M.I., et al. (2016), Multistatic aerosol–cloud lidar in space: A theoretical perspective, J. Quant. Spectrosc. Radiat. Transfer, 184, 180-192, doi:10.1016/j.jqsrt.2016.07.015.
Geogdzhayev, I., et al. (2013), Statistical analysis of single-track instrument sampling in spaceborne aerosol remote sensing for climate research, J. Quant. Spectrosc. Radiat. Transfer, 121, 69-77, doi:10.1016/j.jqsrt.2013.02.003.
Knobelspiesse, K.D., et al. (2012), Analysis of fine-mode aerosol retrieval capabilities by different passive remote sensing instrument designs, Opt. Express, 20, 21457-21484.
Knobelspiesse, K.D., et al. (2012), Analysis of fine-mode aerosol retrieval capabilities by different passive remote sensing instrument designs , Optics Express, 20, 21457-21484.
Zaveri, R.A., et al. (2012), Overview of the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES), Atmos. Chem. Phys., 12, 7647-7687, doi:10.5194/acp-12-7647-2012.
Kassianov, E., et al. (2010), Retrieval of aerosol optical depth in vicinity of broken clouds from reflectance ratios: case study, Atmos. Meas. Tech., 3, 1333-1349, doi:10.5194/amt-3-1333-2010.

Note: Only publications that have been uploaded to the ESD Publications database are listed here.

Mikhail D. Alexandrov

National Aeronautics and Space Administration

National Aeronautics and
Space Administration