A Process Study on Thinning of Arctic Winter Cirrus Clouds With High‐Resolution ICON‐ART Simulations

In this study, cloud‐resolving simulations of a case study for a limited area of the hibernal Arctic were performed with the atmospheric modeling system ICON‐ART (ICOsahedral Nonhydrostatic‐Aerosol and Reactive Trace gases). A thorough comparison with data both from satellite as well as aircraft measurement is presented to validate the simulations. In addition, the model is applied to clarify the microphysical processes occurring when introducing artificial aerosol particles into the upper troposphere with the aim of modifying cirrus clouds in the framework of climate engineering. Former modeling studies investigating the climate effect of this method were performed with simplifying assumptions and much coarser resolution, reaching partly contradicting conclusions concerning the method's effectiveness. The primary effect of seeding is found to be a reduction of ice crystal number concentrations in cirrus clouds, leading to increased outgoing longwave radiative fluxes at the top of the atmosphere, thereby creating a cooling effect. Furthermore, a secondary effect is found, as ice crystals formed from the injected seeding aerosol particles lead to enhanced riming of cloud droplets within the planetary boundary layer. This effectively reduces the coverage of mixed‐phase clouds, thus generating additional cooling by increased upward longwave radiative fluxes at the surface. The efficacy of seeding cirrus clouds proves to be relatively independent from the atmospheric background conditions, scales with the number concentrations of seeding particles, and is highest for large aerosol particles.

[1]  J. Klett,et al.  Microphysics of Clouds and Precipitation , 1978, Nature.

[2]  J. Latham,et al.  Control of global warming? , 1990, Nature.

[3]  D. Hartmann,et al.  The Effect of Cloud Type on Earth's Energy Balance: Global Analysis , 1992 .

[4]  Yongxiang Hu,et al.  An Accurate Parameterization of the Radiative Properties of Water Clouds Suitable for Use in Climate Models , 1993 .

[5]  W. Cotton,et al.  Parameterization and Impact of Ice initiation Processes Relevant to Numerical Model Simulations of Cirrus Clouds. , 1994 .

[6]  Intercomparison of heating rates generated by global climate model longwave radiation codes , 1996 .

[7]  Q. Fu An Accurate Parameterization of the Infrared Radiative Properties of Cirrus Clouds for Climate Models , 1996 .

[8]  E. Mlawer,et al.  Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave , 1997 .

[9]  W. Rossow,et al.  Advances in understanding clouds from ISCCP , 1999 .

[10]  W. Cotton,et al.  Cloud resolving simulations of Arctic stratus: Part II: Transition-season clouds , 1999 .

[11]  U. Lohmann,et al.  Comparing Different Cloud Schemes of a Single Column Model by Using Mesoscale Forcing and Nudging Technique , 1999 .

[12]  William B. Rossow,et al.  Radiative Effects of Cloud-Type Variations , 2000 .

[13]  B. Luo,et al.  Water activity as the determinant for homogeneous ice nucleation in aqueous solutions , 2000, Nature.

[14]  E. O'connor,et al.  The CloudSat mission and the A-train: a new dimension of space-based observations of clouds and precipitation , 2002 .

[15]  U. Lohmann,et al.  A parameterization of cirrus cloud formation: Homogeneous freezing of supercooled aerosols , 2002 .

[16]  Ulrike Lohmann,et al.  A parameterization of cirrus cloud formation: Heterogeneous freezing , 2003 .

[17]  D. M. Murphy,et al.  Measurements of the concentration and composition of nuclei for cirrus formation , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[18]  M. Holland,et al.  Polar amplification of climate change in coupled models , 2003 .

[19]  B. Kärcher,et al.  The roles of dynamical variability and aerosols in cirrus cloud formation , 2003 .

[20]  Klaus Gierens,et al.  The global distribution of ice‐supersaturated regions as seen by the Microwave Limb Sounder , 2003 .

[21]  J. Gayet,et al.  On the distribution of relative humidity in cirrus clouds , 2004 .

[22]  J. Remedios,et al.  Colour indices for the detection and differentiation of cloud types in infra-red limb emission spectra , 2004 .

[23]  John E. Harries,et al.  Determining cloud forcing by cloud type from geostationary satellite data , 2005 .

[24]  Athanasios Nenes,et al.  Continued development of a cloud droplet formation parameterization for global climate models , 2005 .

[25]  Johannes Hendricks,et al.  Physically based parameterization of cirrus cloud formation for use in global atmospheric models , 2006 .

[26]  K. D. Beheng,et al.  A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description , 2006 .

[27]  P. Crutzen Albedo Enhancement by Stratospheric Sulfur Injections: A Contribution to Resolve a Policy Dilemma? , 2006 .

[28]  U. Lohmann,et al.  Impact of ice supersaturated regions and thin cirrus on radiation in the midlatitudes , 2007 .

[29]  D. Winker,et al.  Initial performance assessment of CALIOP , 2007 .

[30]  Qiang Fu,et al.  A New Parameterization of an Asymmetry Factor of Cirrus Clouds for Climate Models , 2007 .

[31]  S. McFarlane,et al.  Analysis of tropical radiative heating profiles: A comparison of models and observations , 2007 .

[32]  Paul J. DeMott,et al.  An Empirical Parameterization of Heterogeneous Ice Nucleation for Multiple Chemical Species of Aerosol , 2008 .

[33]  K. Sassen,et al.  Global distribution of cirrus clouds from CloudSat/Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements , 2008 .

[34]  A. Mangold,et al.  Ice supersaturations and cirrus cloud crystal numbers , 2008 .

[35]  A. Bertram,et al.  Ice nucleation on mineral dust particles: Onset conditions, nucleation rates and contact angles , 2008 .

[36]  U. Lohmann,et al.  Cirrus cloud formation and ice supersaturated regions in a global climate model , 2008 .

[37]  David M. Winker,et al.  CALIPSO Lidar Calibration Algorithms. Part I: Nighttime 532-nm Parallel Channel and 532-nm Perpendicular Channel , 2009 .

[38]  William Finnegan,et al.  Modification of cirrus clouds to reduce global warming , 2009 .

[39]  A. Nenes,et al.  Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei , 2009 .

[40]  A. Nenes,et al.  Parameterizing the competition between homogeneous and heterogeneous freezing in ice cloud formation – polydisperse ice nuclei , 2009 .

[41]  D. Winker,et al.  CALIPSO Lidar Description and Performance Assessment , 2009 .

[42]  Prashant Kumar,et al.  Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN , 2009 .

[43]  P. Stier,et al.  Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations , 2009 .

[44]  T. Peter,et al.  A simple model for cloud radiative forcing , 2009 .

[45]  D. Winker,et al.  Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms , 2009 .

[46]  S. Ghan,et al.  Representation of Arctic Mixed-Phase Clouds and the Wegener-Bergeron- Findeisen Process in Climate Models: Perspectives from a Cloud-Resolving Study , 2011 .

[47]  Elias G. Carayannis,et al.  Planet Earth 2011 - Global Warming Challenges and Opportunities for Policy and Practice , 2011 .

[48]  U. Blahak,et al.  Saharan Dust Event Impacts on Cloud Formation and Radiation over Western Europe , 2011 .

[50]  Paul J. DeMott,et al.  A Particle-Surface-Area-Based Parameterization of Immersion Freezing on Desert Dust Particles , 2012 .

[51]  M. Shupe,et al.  Resilience of persistent Arctic mixed-phase clouds , 2012 .

[52]  Corinna Hoose,et al.  Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments , 2012 .

[53]  C. Stubenrauch,et al.  A global climatology of upper-tropospheric ice supersaturation occurrence inferred from the Atmospheric Infrared Sounder calibrated by MOZAIC , 2012 .

[54]  Andrew Gettelman,et al.  Climate impacts of ice nucleation , 2012 .

[55]  H. Joos,et al.  Influence of heterog neous freezing n the microphysical and radiative properties of orographic cirrus clouds , 2013 .

[56]  E. Clothiaux,et al.  Arctic multilayered, mixed‐phase cloud processes revealed in millimeter‐wave cloud radar Doppler spectra , 2013 .

[57]  K. Caldeira,et al.  The Science of Geoengineering , 2013 .

[58]  K. Prather,et al.  Improvements to an Empirical Parameterization of Heterogeneous Ice Nucleation and Its Comparison with Observations , 2013 .

[59]  C. Kottmeier,et al.  Direct radiative effects of sea salt for the Mediterranean region under conditions of low to moderate wind speeds , 2013 .

[60]  G. Diskin,et al.  Ice nucleation and dehydration in the Tropical Tropopause Layer , 2013, Proceedings of the National Academy of Sciences.

[61]  Johannes Hendricks,et al.  Dust ice nuclei effects on cirrus clouds , 2013 .

[62]  C. Twohy,et al.  Clarifying the Dominant Sources and Mechanisms of Cirrus Cloud Formation , 2013, Science.

[63]  Steven Dobbie,et al.  The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds , 2013, Nature.

[64]  B. Stevens,et al.  Atmospheric component of the MPI‐M Earth System Model: ECHAM6 , 2013 .

[65]  T. J. Garrett,et al.  A simple framework for the dynamic response of cirrus clouds to local diabatic radiative heating , 2012, 1202.5050.

[66]  Johannes Orphal,et al.  Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) scientific objectives , 2014 .

[67]  S. Seneviratne,et al.  The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models , 2015, Climate Dynamics.

[68]  Johannes Orphal,et al.  Instrument concept of the imaging Fourier transform spectrometer GLORIA , 2014 .

[69]  Kerstin Stebel,et al.  Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations , 2014, Journal of geophysical research. Atmospheres : JGR.

[70]  T. Storelvmo,et al.  The climatic effects of modifying cirrus clouds in a climate engineering framework , 2014 .

[71]  T. Storelvmo,et al.  Cirrus cloud seeding: a climate engineering mechanism with reduced side effects? , 2014, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[72]  D. Shindell,et al.  Anthropogenic and Natural Radiative Forcing , 2014 .

[73]  T. Storelvmo,et al.  Cirrus cloud susceptibility to the injection of ice nuclei in the upper troposphere , 2014 .

[74]  G. Zängl,et al.  The ICON (ICOsahedral Non‐hydrostatic) modelling framework of DWD and MPI‐M: Description of the non‐hydrostatic dynamical core , 2015 .

[75]  P. Forster,et al.  A comparison of temperature and precipitation responses to different Earth radiation management geoengineering schemes , 2015 .

[76]  J. Penner,et al.  Can cirrus cloud seeding be used for geoengineering? , 2015 .

[77]  Jessica R. Meyer,et al.  A microphysics guide to cirrus clouds – Part 1: Cirrus types , 2015 .

[78]  B. Vogel,et al.  ICON-ART 1.0 - a new online-coupled model system from the global to regional scale , 2015 .

[79]  A. Seifert,et al.  Identifying sensitivities for cirrus modelling using a two-moment two-mode bulk microphysics scheme , 2015 .

[80]  U. Lohmann,et al.  Classical nucleation theory of homogeneous freezing of water: thermodynamic and kinetic parameters. , 2015, Physical chemistry chemical physics : PCCP.

[81]  Guosheng Liu,et al.  Assessing the Radiative Effects of Global Ice Clouds Based on CloudSat and CALIPSO Measurements , 2016 .

[82]  P. Seifert,et al.  Climatological and radiative properties of midlatitude cirrus clouds derived by automatic evaluation of lidar measurements , 2016 .

[83]  Erika Coppola,et al.  A multimodel intercomparison of resolution effects on precipitation: simulations and theory , 2016, Climate Dynamics.

[84]  P. Forster,et al.  An intensified hydrological cycle in the simulation of geoengineering by cirrus cloud thinning using ice crystal fall speed changes , 2016 .

[85]  U. Lohmann,et al.  Why cirrus cloud seeding cannot substantially cool the planet , 2016 .

[86]  Ulrike Lohmann,et al.  Is increasing ice crystal sedimentation velocity in geoengineering simulations a good proxy for cirrus cloud seeding , 2016 .

[87]  U. Lohmann,et al.  Heterogeneous ice nucleation on dust particles sourced from nine deserts worldwide – Part 1: Immersion freezing , 2016 .

[88]  S. Woods,et al.  High‐frequency gravity waves and homogeneous ice nucleation in tropical tropopause layer cirrus , 2016 .

[89]  H. Kalesse,et al.  Direct estimation of the global distribution of vertical velocity within cirrus clouds , 2017, Scientific Reports.

[90]  Alexei Kiselev,et al.  Active sites in heterogeneous ice nucleation—the example of K-rich feldspars , 2017, Science.

[91]  Tristan S. L'Ecuyer,et al.  The role of cloud phase in Earth's radiation budget , 2017 .

[92]  P. Braesicke,et al.  Denitrification, dehydration and ozone loss during the 2015/2016 Arctic winter , 2017 .

[93]  Hartwig Deneke,et al.  Large‐eddy simulations over Germany using ICON: a comprehensive evaluation , 2017 .

[94]  S. Gruber,et al.  Contrails and their impact on shortwave radiation and photovoltaic power production - a regional model study , 2017 .

[95]  B. Vogel,et al.  Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany , 2017 .

[96]  B. Vogel,et al.  Revealing the meteorological drivers of the September 2015 severe dust event in the Eastern Mediterranean , 2017 .

[97]  H. Wernli,et al.  Exceptional Air Mass Transport and Dynamical Drivers of an Extreme Wintertime Arctic Warm Event , 2017 .

[98]  A cirrus cloud climate dial? , 2017, Science.

[99]  P. Braesicke,et al.  Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016 , 2017 .

[100]  Zhengqiang Li,et al.  Aerosol optical, microphysical, chemical and radiative properties of high aerosol load cases over the Arctic based on AERONET measurements , 2018, Scientific Reports.

[101]  M. Santee,et al.  Airborne limb-imaging measurements of temperature, HNO3, O3, ClONO2, H2O and CFC-12 during the Arctic winter 2015/2016: characterization, in situ validation and comparison to Aura/MLS , 2018, Atmospheric Measurement Techniques.

[102]  An observational study of multiple cloud head structure in the FASTEX IOP 16 cyclone , .