Ann M. Fridlind

Organization

NASA Goddard Institute for Space Studies

Contact person by email

Business Phone

Work

(212) 678-5674

Business Address

2880 Broadway
New York, NY 10025
United States

First Author Publications

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.
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.
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.
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.
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.
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.
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.
Fridlind, A.M., et al. (2004), Evidence for the Predominance of Mid-Tropospheric Aerosols as Subtropical Anvil Cloud Nuclei, Science, 304, 718.
Fridlind, A.M., and M.Z. Jacobson (2003), Point and column aerosol radiative closure during ACE 1: Effects of particle shape and size, J. Geophys. Res., 108, doi:10.1029/2001JD001553.

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

Co-Authored Publications

Diamond, M.S., 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.
Diamond, M.S., 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.
Tornow, F., et al. (2023), On the Impact of a Dry Intrusion Driving Cloud-Regime Transitions in a Midlatitude Cold-Air Outbreak, J. Atmos. Sci., 80, 2881-2896, doi:10.1175/JAS-D-23-0040.1.
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.
Lee, H., et al. (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.
Marinescu, P.J., et al. (2021), Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment, J. Atmos. Sci., 78, 1147-1172, doi:10.1175/JAS-D-20-0200.1.
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.
Tornow, F., et al. (2021), Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks, Atmos. Chem. Phys., 21, 12049-12067, doi:10.5194/acp-21-12049-2021.
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.
Redemann, J., et al. (2020), 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. Discuss., doi:10.5194/acp-2020-449.
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.
Lee, H., et al. (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.
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.
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.
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.
Tao, W., et al. (2016), High-resolution NU-WRF simulations of a deep convective-precipitation system during MC3E: Part I: Comparisons between Goddard microphysics schemes and observations, J. Geophys. Res., 121, 1278-1305, doi:10.1002/2015JD023986.
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.
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.
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.
Jackson, R.C., et al. (2015), The dependence of cirrus gamma size distributions expressed as volumes in N0-λ-μ phase space and bulk cloud properties on environmental conditions: Results from the Small Ice Particles in Cirrus Experiment (SPARTICUS), J. Geophys. Res., 120, doi:10.1002/2015JD023492.
Lin, W., et al. (2015), RACORO continental boundary layer cloud investigations: 3. Separation of parameterization biases single-column model CAM5 simulations of shallow cumulus, J. Geophys. Res., 120, 6015-6033, doi:10.1002/2014JD022524.
Mrowiec, 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.
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.
Wang, S., et al. (2015), Simulations of cloud-radiation interaction using large-scale forcing derived from the CINDY/DYNAMO northern sounding array, J. Adv. Modeling Earth Syst., 7, 1472-1498, doi:10.1002/2015MS000461.
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.
Petch, J., et al. (2014), Evaluation of intercomparisons of four different types of model simulating TWP-ICE, Q. J. R. Meteorol. Soc., 140, 826-837, doi:10.1002/qj.2192.
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: 1. Deep convective updraft properties, J. Geophys. Res., 119, 13,891-13,918, doi:10.1002/2013JD021371.
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.
Rio, C., et al. (2013), Control of deep convection by sub-cloud lifting processes: the ALP closure in the LMDZ5B general circulation model, Clim. Dyn., 40, 2271-2292, doi:10.1007/s00382-012-1506-x.
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.
Mrowiec, 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.
Zhu, P., et al. (2012), A limited area model (LAM) intercomparison study of a TWP-ICE active monsoon mesoscale convective event, J. Geophys. Res., 117, D11208, doi:10.1029/2011JD016447.
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.
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., et al. (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.
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.
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.
Quinn, P., et al. (2008), Short-lived pollutants in the Arctic: their climate impact and possible mitigation strategies, Atmos. Chem. Phys., 8, 1723-1735, doi:10.5194/acp-8-1723-2008.
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.
McFarquhar, G.M., et al. (2007), Ice properties of single-layer stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 1. Observations, J. Geophys. Res., 112, D24201, doi:10.1029/2007JD008633.
Lopez, J., 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.
HEYMSFIELD, A.J., et al. (2005), Homogeneous Ice Nucleation in Subtropical and Tropical Convection and Its Influence on Cirrus Anvil Microphysics, J. Atmos. Sci., 62, 41-64.
Jensen, E.J., et al. (2005), Ice supersaturations exceeding 100% at the cold tropical tropopause: implications for cirrus formation and dehydration, Atmos. Chem. Phys., 5, 851-862, doi:10.5194/acp-5-851-2005.
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.

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

National Aeronautics and Space Administration

National Aeronautics and
Space Administration