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IMPACTS

Andrew S. Ackerman

Organization:

NASA Goddard Institute for Space Studies

Email:

Contact person by email

Business Phone:

(212) 678-5675

Business Address:

NASA GISS

2880 Broadway

New York, NY 10025

United States

First Author Publications:

Ackerman, A. S., et al. (2015), High ice water content at low radar reflectivity near deep convection – Part 2: Evaluation of microphysical pathways in updraft parcel simulations, Atmos. Chem. Phys., 15, 11729-11751, doi:10.5194/acp-15-11729-2015.
Ackerman, A. S., et al. (2009), Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer, Mon. Wea. Rev., 137, 1083-1110, doi:10.1175/2008MWR2582.1.
Ackerman, A. S., et al. (2004), The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014-1017, doi:10.1038/nature03174.
Ackerman, A. S., et al. (2003), Enhancement of cloud cover and suppression of nocturnal drizzle in stratocumulus polluted by haze, Geophys. Res. Lett., 30, 1381, doi:10.1029/2002GL016634.
Ackerman, A. S., and M. S. Marley (2001), Precipatating condensation clouds in substellar atmospheres, Astrophysical Journal, 556, 872-884.
Ackerman, A. S., et al. (2000), Reduction of Tropical Cloudiness by Soot, Science, 288, 1042-1047, doi:10.1126/science.288.5468.1042.
Ackerman, A. S., et al. (2000), Effects of aerosols on cloud albedo: Evaluation of Twomey's parameterization of cloud susceptibility using measurements of ship tracks, J. Atmos. Sci., 57, 2684-2695.

Co-Authored Publications:

Cesana, G., et al. (2023), An observation-based method to assess tropical stratocumulus and shallow cumulus clouds and feedbacks in CMIP6 and CMIP5 models, Environmental Research Communications, 5, 045001, doi:10.1088/2515-7620/acc78a.
Diamond, M., et al. (2023), Cloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transition, Atmos. Chem. Phys., doi:10.5194/acp-22-12113-2022.
Marshak, A., et al. (2023), Aerosol Properties in Cloudy Environments from Remote Sensing Observations, Bull. Am. Meteorol. Soc., 102, E2177-E2197, doi:10.1175/BAMS-D-20-0225.1.
Painemal, D., et al. (2023), Wintertime Synoptic Patterns of Midlatitude Boundary Layer Clouds Over the Western North Atlantic: Climatology and Insights From In Situ ACTIVATE Observations, J. Geophys. Res., 128, e2022JD037725, doi:10.1029/2022JD037725.
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.
Silber, I., et al. (2022), The Earth Model Column Collaboratory (EMC2) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models, Geosci. Model. Dev., 15, 901-927, doi:10.5194/gmd-15-901-2022.
Tornow, F., et al. (2022), Dilution of Boundary Layer Cloud Condensation Nucleus Concentrations by Free Tropospheric Entrainment During Marine Cold Air Outbreaks, Geophys. Res. Lett., 49, e2022GL09844, doi:10.1029/2022GL098444.
Cesana, G., et al. (2021), Snow Reconciles Observed and Simulated Phase Partitioning and Increases Cloud Feedback, Geophys. Res. Lett., 48, e2021GL094876, doi:10.1029/2021GL094876.
Kelley, M., et al. (2021), GISS‐E2.1: Configurations and Climatology, J. Adv. Modeling Earth Syst..
Lee, H., A. M. Fridlind, and A. S. Ackerman (2021), An Evaluation of Size-Resolved Cloud Microphysics Scheme Numerics for Use with Radar Observations. Part II: Condensation and Evaporation, J. Atmos. Sci., 78, 1629-1645, doi:10.1175/JAS-D-20-0213.1.
Miller, R. L., et al. (2021), CMIP6 Historical Simulations (1850–2014) With GISS-E2.1, J. Adv. Modeling Earth Syst., ) with GISS-E2.1. Jo, 1850-2014.
Redemann, J., et al. (2021), An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin, Atmos. Chem. Phys., 21, 1507-1563, doi:10.5194/acp-21-1507-2021.
Silber, I., et al. (2021), The prevalence of precipitation from polar supercooled clouds, Atmos. Chem. Phys., 21, 3949-3971, doi:10.5194/acp-21-3949-2021.
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.
Cheng, Y., et al. (2020), A Second-Order Closure Turbulence Model: New Heat Flux Equations and No Critical Richardson Number, J. Atmos. Sci., 77, 2743-2759, doi:10.1175/JAS-D-19-0240.1.
Korolev, A., et al. (2020), A new look at the environmental conditions favorable to secondary ice production, Atmos. Chem. Phys., 20, 1391-1429, doi:10.5194/acp-20-1391-2020.
Silber, I., et al. (2020), Nonturbulent Liquid‐Bearing Polar Clouds: Observed Frequency of Occurrence and Simulated Sensitivity to Gravity Waves, Geophys. Res. Lett..
van Diedenhoven, B., et al. (2020), Global Statistics of Ice Microphysical and Optical Properties at Tops of Optically Thick Ice Clouds, J. Geophys. Res., 125, doi:10.1029/2019JD031811.
Cesana, G., et al. (2019), Evaluating models’ response of tropical low clouds to SST forcings using CALIPSO observations, Atmos. Chem. Phys., 19, 2813-2832, doi:10.5194/acp-19-2813-2019.
de Roode, S. R., et al. (2019), Turbulent Transport in the Gray Zone: A Large Eddy Model Intercomparison Study of the CONSTRAIN Cold Air Outbreak Case, J. Adv. Modeling Earth Syst., 11, 597-623, doi:10.1029/2018MS001443.
Fridlind, A. M., and A. S. Ackerman (2019), Simulations of Arctic Mixed-Phase Boundary Layer Clouds: Advances in Understanding and Outstanding Questions, Mixed-Phase Clouds: Observations and Modeling, 153-183, doi:10.1016/B978-0-12-810549-8.00007-6.
Lee, H., A. M. Fridlind, and A. S. Ackerman (2019), An Evaluation of Size-Resolved Cloud Microphysics Scheme Numerics for Use with Radar Observations. Part I: Collision–Coalescence, J. Atmos. Sci., 76, 247-263, doi:10.1175/JAS-D-18-0174.1.
Silber, I., et al. (2019), Persistent Supercooled Drizzle at Temperatures Below −25 °C Observed at McMurdo Station, Antarctica, J. Geophys. Res., 124, 10,878-10,895, doi:10.1029/2019JD030882.
Chen, Y.-S., et al. (2018), On the Forward Modeling of Radar Doppler Spectrum Width From LES: Implications for Model Evaluation, J. Geophys. Res., 123, 7444-7461, doi:10.1029/2017JD028104.
Lamer, K., et al. (2018), (GO)2-SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase, Geosci. Model. Dev., 11, 4195-4214, doi:10.5194/gmd-11-4195-2018.
Miller, D. J., et al. (2018), Comparisons of bispectral and polarimetric retrievals of marine boundary layer cloud microphysics: case studies using a LES–satellite retrieval simulator, Atmos. Meas. Tech., 11, 3689-3715, doi:10.5194/amt-11-3689-2018.
Zhou, X., et al. (2018), Simulation of Mesoscale Cellular Convection in Marine Stratocumulus. Part I: Drizzling Conditions, J. Atmos. Sci., 75, 257-274, doi:10.1175/JAS-D-17-0070.1.
Fridlind, A. M., et al. (2017), Derivation of aerosol profiles for MC3E convection studies and use in simulations of the 20 May squall line case, Atmos. Chem. Phys., 17, 5947-5972, doi:10.5194/acp-17-5947-2017.
Ladino, L. A., et al. (2017), On the role of ice-nucleating aerosol in the formation of ice particles in tropical mesoscale convective systems, Geophys. Res. Lett., 44, 1574-1582, doi:10.1002/2016GL072455.
Neggers, R. A. J., et al. (2017), Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions, J. Adv. Modeling Earth Syst., 9, 2385-2412, doi:10.1002/2017MS001064.
Rémillard, J., et al. (2017), Use of Cloud Radar Doppler Spectra to Evaluate Stratocumulus Drizzle Size Distributions in Large-Eddy Simulations with Size-Resolved Microphysics, J. Appl. Meteor. Climat., 56, 3263-3283, doi:10.1175/JAMC-D-17-0100.1.
Zhou, X., et al. (2017), Impacts of solar-absorbing aerosol layers on the transition of stratocumulus to trade cumulus clouds, Atmos. Chem. Phys., 17, 12725-12742, doi:10.5194/acp-17-12725-2017.
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.
De Roode, S. R., et al. (2016), Large-Eddy Simulations of EUCLIPSE–GASS Lagrangian Stratocumulus-to-Cumulus Transitions: Mean State, Turbulence, and Decoupling, J. Atmos. Sci., 73, 2485-2508, doi:10.1175/JAS-D-15-0215.1.
Fridlind, A. M., et al. (2016), Derivation of physical and optical properties of mid-latitude cirrus ice crystals for a size-resolved cloud microphysics model, Atmos. Chem. Phys., 16, 7251-7283, doi:10.5194/acp-16-7251-2016.
Miller, D., et al. (2016), The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds, J. Geophys. Res., 121, 4122-4141, doi:10.1002/2015JD024322.
Pithan, F., et al. (2016), Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison, J. Adv. Modeling Earth Syst., 8, 1345-1357, doi:10.1002/2016MS000630.
van Diedenhoven, B., et al. (2016), On Averaging Aspect Ratios and Distortion Parameters over Ice Crystal Population Ensembles for Estimating Effective Scattering Asymmetry Parameters, J. Atmos. Sci., 73, 775-787, doi:10.1175/JAS-D-15-0150.1.
van Diedenhoven, B., et al. (2016), Vertical variation of ice particle size in convective cloud tops, Geophys. Res. Lett., 43, doi:10.1002/2016GL068548.
Van Lier-Walqui, M., et al. (2016), On Polarimetric Radar Signatures of Deep Convection for Model Evaluation: Columns of Specific Differential Phase Observed during MC3E*, Mon. Wea. Rev., 144, 737-758, doi:10.1175/MWR-D-15-0100.1.
Zhang, Z., et al. (2016), A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method, J. Geophys. Res., 121, 7007-7025, doi:10.1002/2016JD024837.
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.
Cho, H., et al. (2015), Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans, J. Geophys. Res., 120, doi:10.1002/2015JD023161.
Endo, S., et al. (2015), RACORO continental boundary layer cloud investigations: 2. Large-eddy simulations of cumulus clouds and evaluation with in situ and ground-based observations, J. Geophys. Res., 120, 5993-6014, doi:10.1002/2014JD022525.
Fridlind, A. M., et al. (2015), High ice water content at low radar reflectivity near deep convection – Part 1: Consistency of in situ and remote-sensing observations with stratiform rain column simulations, Atmos. Chem. Phys., 15, 11713-11728, doi:10.5194/acp-15-11713-2015.
Mrowiec, A. A., et al. (2015), Properties of a Mesoscale Convective System in the Context of an Isentropic Analysis, J. Atmos. Sci., 72, 1945-1962, doi:10.1175/JAS-D-14-0139.1.
Pincus, R., et al. (2015), Radiative flux and forcing parameterization error in aerosol-free clear skies, Geophys. Res. Lett., 42, 5485-5492, doi:10.1002/2015GL064291.
Vogelmann, A. M., et al. (2015), RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large-scale forcings, J. Geophys. Res., 120, 5962-5992, doi:10.1002/2014JD022713.
Ovchinnikov, M., et al. (2014), Intercomparison of large-eddy simulations of Arctic mixed-phase clouds: Importance of ice size distribution assumptions, J. Adv. Modeling Earth Syst., 6, 223-248, doi:10.1002/2013MS000282.
van Diedenhoven, B., et al. (2014), A Flexible Parameterization for Shortwave Optical Properties of Ice Crystals*, J. Atmos. Sci., 71, 1763-1782, doi:10.1175/JAS-D-13-0205.1.
van Diedenhoven, B., et al. (2014), Variation of ice crystal size, shape, and asymmetry parameter in tops of tropical deep convective clouds, J. Geophys. Res., 119, 11,809-11,825, doi:10.1002/2014JD022385.
Varble, A., et al. (2014), Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 2. Precipitation microphysics, J. Geophys. Res., 119, 13,919-13,945, doi:10.1002/2013JD021372.
Varble, A., et al. (2014), Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 1. Deep convective updraft properties, J. Geophys. Res., 119, 13,891-13,918, doi:10.1002/2013JD021371.
van Diedenhoven, B., et al. (2013), Remote sensing of ice crystal asymmetry parameter using multi-directional polarization measurements – Part 2: Application to the Research Scanning Polarimeter, Atmos. Chem. Phys., 13, 3185-3203, doi:10.5194/acp-13-3185-2013.
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.
Fridlind, A. M., et al. (2012), A comparison of TWP-ICE observational data with cloud-resolving model results, J. Geophys. Res., 117, D05204, doi:10.1029/2011JD016595.
Fridlind, A. M., et al. (2012), A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes, J. Atmos. Sci., 69, 365-389, doi:10.1175/JAS-D-11-052.1.
Mrowiec, A. A., et al. (2012), Analysis of cloud-resolving simulations of a tropical mesoscale convective system observed during TWP-ICE: Vertical fluxes and draft properties in convective and stratiform regions, J. Geophys. Res., 117, D19201, doi:10.1029/2012JD017759.
van Diedenhoven, B., et al. (2012), Remote sensing of ice crystal asymmetry parameter using multi-directional polarization measurements – Part 1: Methodology and evaluation with simulated measurements, Atmos. Meas. Tech., 5, 2361-2374, doi:10.5194/amt-5-2361-2012.
van Diedenhoven, B., et al. (2012), Evaluation of Hydrometeor Phase and Ice Properties in Cloud-Resolving Model Simulations of Tropical Deep Convection Using Radiance and Polarization Measurements, J. Atmos. Sci., 69, 3290-3314, doi:10.1175/JAS-D-11-0314.1.
Zhang, Z., et al. (2012), Effects of cloud horizontal inhomogeneity and drizzle on remote sensing of cloud droplet effective radius: Case studies based on large-eddy simulations, J. Geophys. Res., 117, D19208, doi:10.1029/2012JD017655.
Avramov, A., et al. (2011), Toward ice formation closure in Arctic mixed‐phase boundary layer clouds during ISDAC, J. Geophys. Res., 116, D00T08, doi:10.1029/2011JD015910.
Botta, G., et al. (2011), Millimeter wave scattering from ice crystals and their aggregates: Comparing cloud model simulations with X‐ and Ka‐band radar measurements, J. Geophys. Res., 116, D00T04, doi:10.1029/2011JD015909.
Fridlind, A. M., and A. S. Ackerman (2011), Estimating the Sensitivity of Radiative Impacts of Shallow, Broken Marine Clouds to Boundary Layer Aerosol Size Distribution Parameter Uncertainties for Evaluation of Satellite Retrieval Requirements, J. Atmos. Oceanic Technol., 28, 530-538, doi:10.1175/2010JTECHA1520.1.
Morrison, H., et al. (2011), Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA/FIRE-ACE, J. Adv. Model. Earth Syst., 3, M06003, doi:10.1029/2011MS000066.
van Diedenhoven, B., A. M. Fridlind, and A. S. Ackerman (2011), Influence of Humidified Aerosol on Lidar Depolarization Measurements below Ice-Precipitating Arctic Stratus, J. Appl. Meteor. Climat., 50, 2184-2192, doi:10.1175/JAMC-D-11-037.1.
vanZanten, M. C., et al. (2011), Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO, J. Adv. Model. Earth Syst., 3, doi:10.1029/2011MS000056.
Varble, A., et al. (2011), Evaluation of cloud‐resolving model intercomparison simulations using TWP‐ICE observations: Precipitation and cloud structure, J. Geophys. Res., 116, D12206, doi:10.1029/2010JD015180.
Alexandrov, M. D., A. Marshak, and A. S. Ackerman (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., A. S. Ackerman, and A. Marshak (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.
Klein, S. A., et al. (2009), Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single-layer cloud, Q. J. R. Meteorol. Soc., 135, 979-1002, doi:10.1002/qj.416.
van Diedenhoven, B., et al. (2009), An evaluation of ice formation in large-eddy simulations of supercooled Arctic stratocumulus using ground-based lidar and cloud radar, J. Geophys. Res., 114, D10203, doi:10.1029/2008JD011198.
Sayres, D., et al. (2008), Validation and determination of ice water contentradar reflectivity relationships during CRYSTALFACE: Flight requirements for future comparisons, J. Geophys. Res., 113, D05208, doi:10.1029/2007JD008847.
Charlson, R. J., et al. (2007), On the climate forcing consequences of the albedo continuum between cloudy and clear air, Tellus, 59, 715-727, doi:10.1111/j.1600-0889.2007.00297.x.
Fridlind, A. M., et al. (2007), Ice properties of single-layer stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 2. Model results, J. Geophys. Res., 112, D24202, doi:10.1029/2007JD008646.
Jensen, E., A. S. Ackerman, and J. A. Smith (2007), Can overshooting convection dehydrate the tropical tropopause layer?, J. Geophys. Res., 112, D11209, doi:10.1029/2006JD007943.
Senocak, I., et al. (2007), Study of near-surface models for large-eddy simulations of a neutrally stratified atmospheric boundary layer, Bound.-Lay. Meteorology, 124, 405-424, doi:10.1007/s10546-007-9181-x.
Wyant, M. C., et al. (2007), A single-column model intercomparison of a heavily drizzling stratocumulus-topped boundary layer, J. Geophys. Res., 112, D24204, doi:10.1029/2007JD008536.
Jensen, E., and A. S. Ackerman (2006), Homogeneous aerosol freezing in the tops of high-altitude tropical cumulonimbus clouds, Geophys. Res. Lett., 33, L08802, doi:10.1029/2005GL024928.
Kirkpatrick, M. P., et al. (2006), On the Application of the Dynamic Smagorinsky Model to Large-Eddy Simulations of the Cloud-Topped Atmospheric Boundary Layer, J. Atmos. Sci., 63, 526-546.
Lopez, J. P., et al. (2006), CO signatures in subtropical convective clouds and anvils during CRYSTAL-FACE: An analysis of convective transport and entrainment using observations and a cloud-resolving model, J. Geophys. Res., 111, D09305, doi:10.1029/2005JD006104.
Smith, J. A., et al. (2006), Role of deep convection in establishing the isotopic composition of water vapor in the tropical transition layer, Geophys. Res. Lett., 33, L06812, doi:10.1029/2005GL024078.
Stevens, B., et al. (2005), Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus, Mon. Wea. Rev., 133, 1443-1462, doi:10.1175/MWR2930.1.
Fridlind, A. M., et al. (2004), Evidence for the Predominance of Mid-Tropospheric Aerosols as Subtropical Anvil Cloud Nuclei, Science, 304, 718.
Xueref, I., et al. (2004), Combining a receptor-oriented framework for tracer distributions with a cloud-resolving model to study transport in deep convective clouds: Application to the NASA CRYSTAL-FACE campaign, Geophys. Res. Lett., 31, L14106, doi:10.1029/2004GL019811.
Gelino, C. R., et al. (2002), L—dwarf variability, I-Band Observations. Astrophysical Journal, 577, 433-446.
Marley, M. S., et al. (2002), Clouds and chemistry: Brown dwarf atmospheric properties from optical and infrared colors, Astrophysical Journal, 568, 335-342.
McFarlane, S. A., K. F. Evans, and A. S. Ackerman (2002), A Bayesian algorithm for the retrieval of liquid water cloud properties from microwave radiometer and millimeter radar data, J. Geophys. Res., 107, 4317, doi:10.1029/2001JD001011.
Stevens, D. E., A. S. Ackerman, and C. S. Bretherton (2002), Effects of domain size and numerical resolution on the simulation of shallow cumulus convection, J. Atmos. Sci., 59, 3285-3301.
Jensen, E., et al. (2001), A conceptual model of the dehydration of air due to freeze-drying by optically thin, laminar cirrus rising slowly across the tropical tropopause, J. Geophys. Res., 106, 17237-17252, doi:10.1029/2000JD900649.
Stevens, B., et al. (2001), Trade-wind cumuli under a strong inversion, J. Atmos. Sci., 58, 1870-1891.
Stevens, B., et al. (2001), Simulations of trade wind cumuli under a strong inversion, J. Atmos. Sci., 58, 1870-1891, doi:10.1175/1520-0469(2001)058<1870:SOTWCU>2.0.CO;2.
Taylor, J. P., and A. S. Ackerman (1999), A case study of pronounced perturbations to cloud properties and boundary layer dynamics due to aerosol emissions, Q. J. R. Meteorol. Soc., 125, 2643-2661.

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