Articles | Volume 22, issue 18
https://doi.org/10.5194/acp-22-12055-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-12055-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Sep 2022
Research article |
| 16 Sep 2022
| 16 Sep 2022
The influence of multiple groups of biological ice nucleating particles on microphysical properties of mixed-phase clouds observed during MC3E
Sachin Patade
CORRESPONDING AUTHOR
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Deepak Waman
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Akash Deshmukh
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Ashok Kumar Gupta
Department of Earth and Environmental Sciences, Vanderbilt University, Nashville, Tennessee, USA
Arti Jadav
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Vaughan T. J. Phillips
Department of Physical Geography and Ecosystem Science, Lund
University, Lund, Sweden
Aaron Bansemer
Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Jacob Carlin
Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma and NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma, USA
Alexander Ryzhkov
Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma and NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma, USA
Related authors
Freddy P. Paul, Martanda Gautam, Deepak Waman, Sachin Patade, Ushnanshu Dutta, Christoffer Pichler, Marcin Jackowicz-Korczynski, and Vaughan Phillips
EGUsphere, https://doi.org/10.5194/egusphere-2024-3800, https://doi.org/10.5194/egusphere-2024-3800, 2025
Preprint archived
Short summary
Short summary
This study shows observations of a key mechanism for initiation of ice particles in clouds with a chamber deployed on the top of a mountain during snowfall in winter. The mechanism involves the fragmentation of snow particles in collisions with denser rimed ice precipitation, namely "graupel" or "hail". The study shows how the fragmentation can be represented in atmospheric models. An improved formulation of the mechanism is proposed in light of our observations with the chamber.
Xi Zhao, Xiaohong Liu, Vaughan T. J. Phillips, and Sachin Patade
Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, https://doi.org/10.5194/acp-21-5685-2021, 2021
Short summary
Short summary
Arctic mixed-phase clouds significantly influence the energy budget of the Arctic. We show that a climate model considering secondary ice production (SIP) can explain the observed cloud ice number concentrations, vertical distribution pattern, and probability density distribution of ice crystal number concentrations. The mixed-phase cloud occurrence and phase partitioning are also improved.
Jun-Ichi Yano, Vincent E. Larson, and Vaughan T. J. Phillips
Atmos. Chem. Phys., 25, 9357–9386, https://doi.org/10.5194/acp-25-9357-2025, https://doi.org/10.5194/acp-25-9357-2025, 2025
Short summary
Short summary
The distribution problems appear in atmospheric sciences at almost every corner when describing diverse processes. This paper presents a general formulation for addressing all these problems.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
Short summary
Short summary
Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Anton Kötsche, Alexander Myagkov, Leonie von Terzi, Maximilian Maahn, Veronika Ettrichrätz, Teresa Vogl, Alexander Ryzhkov, Petar Bukovcic, Davide Ori, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2025-734, https://doi.org/10.5194/egusphere-2025-734, 2025
Short summary
Short summary
Our study combines radar observations of snowf with snowfall camera observations on the ground to enhance our understanding of radar variables and snowfall properties. We found that values of an important radar variable (KDP) can be related to many different snow particle properties and number concentrations. We were able to constrain which particle sizes contribute to KDP by using computer models of snowflakes and showed which microphysical processes during snow formation can influence KDP.
Freddy P. Paul, Martanda Gautam, Deepak Waman, Sachin Patade, Ushnanshu Dutta, Christoffer Pichler, Marcin Jackowicz-Korczynski, and Vaughan Phillips
EGUsphere, https://doi.org/10.5194/egusphere-2024-3800, https://doi.org/10.5194/egusphere-2024-3800, 2025
Preprint archived
Short summary
Short summary
This study shows observations of a key mechanism for initiation of ice particles in clouds with a chamber deployed on the top of a mountain during snowfall in winter. The mechanism involves the fragmentation of snow particles in collisions with denser rimed ice precipitation, namely "graupel" or "hail". The study shows how the fragmentation can be represented in atmospheric models. An improved formulation of the mechanism is proposed in light of our observations with the chamber.
Nina Maherndl, Manuel Moser, Imke Schirmacher, Aaron Bansemer, Johannes Lucke, Christiane Voigt, and Maximilian Maahn
Atmos. Chem. Phys., 24, 13935–13960, https://doi.org/10.5194/acp-24-13935-2024, https://doi.org/10.5194/acp-24-13935-2024, 2024
Short summary
Short summary
It is not clear why ice crystals in clouds occur in clusters. Here, airborne measurements of clouds in mid-latitudes and high latitudes are used to study the spatial variability of ice. Further, we investigate the influence of riming, which occurs when liquid droplets freeze onto ice crystals. We find that riming enhances the occurrence of ice clusters. In the Arctic, riming leads to ice clustering at spatial scales of 3–5 km. This is due to updrafts and not higher amounts of liquid water.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
Short summary
Short summary
Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
John S. Schreck, Gabrielle Gantos, Matthew Hayman, Aaron Bansemer, and David John Gagne
Atmos. Meas. Tech., 15, 5793–5819, https://doi.org/10.5194/amt-15-5793-2022, https://doi.org/10.5194/amt-15-5793-2022, 2022
Short summary
Short summary
We show promising results for a new machine-learning based paradigm for processing field-acquired cloud droplet holograms. The approach is fast, scalable, and leverages GPUs and other heterogeneous computing platforms. It combines applications of transfer and active learning by using synthetic data for training and a small set of hand-labeled data for refinement and validation. Artificial noise applied during synthetic training enables optimized models for real-world situations.
Jonas K. F. Jakobsson, Deepak B. Waman, Vaughan T. J. Phillips, and Thomas Bjerring Kristensen
Atmos. Chem. Phys., 22, 6717–6748, https://doi.org/10.5194/acp-22-6717-2022, https://doi.org/10.5194/acp-22-6717-2022, 2022
Short summary
Short summary
Long-lived cold-layer clouds at subzero temperatures are observed to be remarkably persistent in their generation of ice particles and snow precipitation. There is uncertainty about why this is so. This motivates the present lab study to observe the long-term ice-nucleating ability of aerosol samples from the real troposphere. Time dependence of their ice nucleation is observed to be weak in lab experiments exposing the samples to isothermal conditions for up to about 10 h.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev., 15, 683–713, https://doi.org/10.5194/gmd-15-683-2022, https://doi.org/10.5194/gmd-15-683-2022, 2022
Short summary
Short summary
We describe in this paper the implementation of a process-based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.2. The performance of the model simulations for the year 2010 is evaluated against in situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved, although in some areas the model shows a decline in performance.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
Short summary
Short summary
The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
Rachel L. James, Vaughan T. J. Phillips, and Paul J. Connolly
Atmos. Chem. Phys., 21, 18519–18530, https://doi.org/10.5194/acp-21-18519-2021, https://doi.org/10.5194/acp-21-18519-2021, 2021
Short summary
Short summary
Secondary ice production (SIP) plays an important role in ice formation within mixed-phase clouds. We present a laboratory investigation of a potentially new SIP mechanism involving the collisions of supercooled water drops with ice particles. At impact, the supercooled water drop fragments form smaller secondary drops. Approximately 30 % of the secondary drops formed during the retraction phase of the supercooled water drop impact freeze over a temperature range of −4 °C to −12 °C.
Vaughan T. J. Phillips, Jun-Ichi Yano, Akash Deshmukh, and Deepak Waman
Atmos. Chem. Phys., 21, 11941–11953, https://doi.org/10.5194/acp-21-11941-2021, https://doi.org/10.5194/acp-21-11941-2021, 2021
Short summary
Short summary
For decades, high concentrations of ice observed in precipitating mixed-phase clouds have created an enigma. Such concentrations are higher than can be explained by the action of aerosols or by the spontaneous freezing of most cloud droplets. The controversy has partly persisted due to the lack of laboratory experimentation in ice microphysics, especially regarding fragmentation of ice, a topic reviewed by a recent paper. Our comment attempts to clarify some issues with regards to that review.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
Short summary
Short summary
Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
Short summary
Short summary
Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Xi Zhao, Xiaohong Liu, Vaughan T. J. Phillips, and Sachin Patade
Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, https://doi.org/10.5194/acp-21-5685-2021, 2021
Short summary
Short summary
Arctic mixed-phase clouds significantly influence the energy budget of the Arctic. We show that a climate model considering secondary ice production (SIP) can explain the observed cloud ice number concentrations, vertical distribution pattern, and probability density distribution of ice crystal number concentrations. The mixed-phase cloud occurrence and phase partitioning are also improved.
Cited articles
Bauer, H., Kasper-Giebl, A., Loflund, M., Giebl, H., Hitzenberger, R.,
Zibuschka, F., and Puxbaum, H.: The contribution of bacteria and fungal
spores to the organic carbon content of cloud water, precipitation and
aerosols, Atmos. Res., 64, 109–119, 2002.
Baumgardner, D., Abel, S. J., Axisa, D., Cotton, R., Crosier, J., Field, P.,
Gurganus, C., Heymsfield, A., Korolev, A., Krämer, M., Lawson, P.,
McFarquhar, G., Ulanowski, Z., and Um, J.: Cloud Ice Properties: In Situ
Measurement Challenges, Meteor. Mon., 58, 9.1–9.23, 2017.
Blyth, A. M. and Latham, J.: Development of ice and precipitation in New
Mexican summertime cumulus clouds, Q. J. R. Meteorol. Soc. 119, 91–120,
1993.
Bowers, R. M., Lauber, C. L., Wiedinmyer, C., Hamady, M., Hallar, A. G.,
Fall, R., Knight, R., and Fierer, N.: Characterization of airborne microbial
communities at a high-elevation site and their potential to act as
atmospheric ice nuclei, Appl. Environ. Microbiol., 75, 5121–30, https://doi.org/10.1128/AEM.00447-09, 2009.
Burrows, S. M., Elbert, W., Lawrence, M. G., and Pöschl, U.: Bacteria in the global atmosphere – Part 1: Review and synthesis of literature data for different ecosystems, Atmos. Chem. Phys., 9, 9263–9280, https://doi.org/10.5194/acp-9-9263-2009, 2009.
Carlin, J. T., Reeves, H. D., and Ryzhkov, A. V.: Polarimetric Observations
and Simulations of Sublimating Snow: Implications for Nowcasting, J.
Appl. Meteorol. Climatol., 60, 1035–1054, 2021.
Chen, Q., Yin, Y., Jiang, H., Chu, Z., Xue, L., Shi, R., Zhang, X., and Chen, J.: The roles of mineral dust as cloud condensation nuclei and icenuclei during the evolution of a hail storm, J. Geophys. Res.-Atmos., 124, 14262–14284, 2019.
Chin, M., Rood, R. B., Lin, S. J., Müller, J. F., and Thompson, A. M.:
Atmospheric sulfur cycle simulated in the global model GOCART: Model
description and global properties, J. Geophys. Res.-Atmos., 105, 24671–24687, https://doi.org/10.1029/2000JD900384, 2000.
Crawford, I., Bower, K. N., Choularton, T. W., Dearden, C., Crosier, J., Westbrook, C., Capes, G., Coe, H., Connolly, P. J., Dorsey, J. R., Gallagher, M. W., Williams, P., Trembath, J., Cui, Z., and Blyth, A.: Ice formation and development in aged, wintertime cumulus over the UK: observations and modelling, Atmos. Chem. Phys., 12, 4963–4985, https://doi.org/10.5194/acp-12-4963-2012, 2012.
Cui, Z. and Carslaw, K. S.: Enhanced vertical transport efficiency of
aerosol in convective clouds due to increases in tropospheric aerosol
abundance, J. Geophys. Res., 111, D15212, https://doi.org/10.1029/2005JD006781, 2006.
DeMott, P. J. and Prenni, A. J.: New Directions: Need for defining the
numbers and sources of biological aerosols acting as ice nuclei, Atmos.
Environ., 44, 1944–1945, 2010.
DeMott P. J., Prenni A. J., Liu, X., Kreidenweis, S. M., Petters, M. D.,
Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci. USA, 107, 11217–11222, 2010.
Deshmukh, A., Phillips, V. J. T. P., Bansemer A., Patade, S., and Waman, D.:
New Empirical Formulation for the Sublimational Breakup of Graupel and
Dendritic Snow, J. Atmos. Sci., 79, 317–336, https://doi.org/10.1175/JAS-D-20-0275.1,
2021.
Després, V. R., Huffman, J. A., Burrows, S. M., Hoose, C., Safatov, A. S., Buryak, G., Fröhlich-Nowoisky, J., Elbert, W., Andreae, M. O., and Pöschl, U.: Primary biological aerosol particles in the atmosphere: a review, Tellus B, 64, 15598, https://doi.org/10.3402/tellusb.v64i0.15598, 2012.
Dong, X. and Mace, G. G.: Arctic stratus cloud properties and radiative
forcing derived from ground-based data collected at Barrow, Alaska, J. Climate, 16, 445–461, https://doi.org/10.1175/1520-0442(2003)016<0445:ASCPAR>2.0.CO;2, 2003.
Fan, J., Comstock, J. M., and Ovchinnikov, M.: The cloud condensation nuclei and ice
nuclei effects on tropical anvil characteristics and water vapor of the
tropical tropopause layer, Environ. Res. Lett., 5, 044005,
https://doi.org/10.1088/1748-9326/5/4/044005, 2010.
Fan, J., Liu, Y-C, Xu, K. M., North, K., Collis, S., Dong, X., Zhang, G. J.,
Chen, Q., Kollias, P., and Ghan, S. J.: Improving representation of
convective transport for scale-aware parameterization: 1. Convection and
cloud properties simulated with spectral bin and bulk microphysics, J.
Geophys. Res. Atmos., 120, 3485–3509. https://doi.org/10.1002/2014JD022142, 2015.
Fan, J., Han, B., Varble, A., Morrison, H., North, K., Kollias, P., Chen,
B., Dong, X., Giangrande, S., Khain, A., Lin, Y., Mansell, E., Milbrandt, J.
A., Stenz, R., Thompson, G., and Wang, Y: Cloud-resolving model intercomparison
of an MC3E squall line case: Part I – Convective updrafts, J. Geophys. Res. Atmos., 122, 9351–9378, 2017.
Field, P. R. and Heymsfeld, A. J: Importance of snow to global
precipitation, Geophys. Res. Lett., 42, 9512–9520, https://doi.org/10.1002/2015GL065497, 2015.
Field, P. R., Heymsfield, A. J., and Bansemer, A.: Shattering and Particle
Interarrival Times Measured by Optical Array Probes in Ice Clouds, J. Atmos. Ocean. Technol., 23, 1357–1371, 2006.
Fridlind, A. M., Li, X., Wu, D., van Lier-Walqui, M., Ackerman, A. S., Tao, W.-K., McFarquhar, G. M., Wu, W., Dong, X., Wang, J., Ryzhkov, A., Zhang, P., Poellot, M. R., Neumann, A., and Tomlinson, J. M.: 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, https://doi.org/10.5194/acp-17-5947-2017, 2017.
Fröhlich-Nowoisky, J., Kampf, C. J., Weber, B., Huffman,
J. A., Pöhlker, C., Andreae, M. O., Lang-Yona, N., Burrows, S. M., Gunthe, S. S., Elbert, W., Su, H., Hoor,
P., Thines, E., Hoffmann, T., Desprìes, V. R., and Pöoschl, U.: Bioaerosols in the Earth system: climate, health, and ecosystem interactions, Atmos. Res. 182, 346–376, 2016.
Garcia, E., Hill, T. C. J., Prenni, A. J., DeMott, P. J., Franc, G. D., and
Kreidenweis, S. M.: Biogenic ice nuclei in boundary layer air over two US
high plains agricultural regions, J. Geophys. Res.-Atmos., 117, 1–12, https://doi.org/10.1029/2012JD018343, 2012.
Giangrande, S. E., Collis, S., Theisen, A. K., and Tokay, A.: Precipitation
estimation from the ARM distributed radar network during the MC3E campaign,
J. Appl. Meteorol. Climatol., 53, 2130–2147, https://doi.org/10.1175/JAMC-D-13-0321.1, 2014.
Grützun, V., Knoth, O., and Simmel, M.: Simulation of the influence of
aerosol particle characteristics on clouds and precipitation with LM-SPECS:
Model description and first results, Atmos. Res., 90, 233–242,
https://doi.org/10.1016/j.atmosres.2008.03.002, 2008.
Hallett, J., and Mossop S. C.: Production of secondary ice particles during
the riming process, Nature, 249, 26–28,
https://doi.org/10.1038/249026a0, 1974.
Han, B., Fan, J., Varble, A., Morrison, H., Williams, C. R., Chen, B., Dong, X., Giangrande, S. E., Khain, A., Mansell, E., Milbrandt, J. A., Shpund, J., and Thompson, G.: Cloud-resolving model intercomparison of an MC3E squall line case: Part II. Stratiform precipitation properties, J. Geophys. Res.-Atmos., 124, 1090–1117, 2019.
Heymsfield, A. J., Schmitt, C., Chen, C., Bansemer, A., Gettelman, A.,
Field, P. R., and Liu, C.: Contributions of the Liquid and Ice Phases to
Global Surface Precipitation: Observations and Global Climate Modeling,
J. Atmos. Sci., 77, 2629–2648, 2020.
Hoose, C. and Möhler, O.: Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments, Atmos. Chem. Phys., 12, 9817–9854, https://doi.org/10.5194/acp-12-9817-2012, 2012.
Hoose, C., Kristjánsson, J. E., and Burrows, S. M.: How important is
biological ice nucleation in clouds on a global scale?, Environ. Res. Lett., 5, 024009, https://doi.org/10.1088/1748-9326/5/2/024009, 2010a.
Hoose, C., Kristjánsson, J. E., Chen, J. P., and Hazra, A.: A
Classical-Theory-Based Parameterization of Heterogeneous Ice Nucleation by
Mineral Dust, Soot, and Biological Particles in a Global Climate Model, J.
Atmos. Sci., 67, 2483–2503, https://doi.org/10.1175/2010jas3425.1, 2010b.
Huang, S., Wei, H., Chen, J., Wu, Z., Zhang, D., and Fu, P.: Overview of
biological ice nucleating particles in the atmosphere, Environ.
Internat., 146, 106197, https://doi.org/10.1016/j.envint.2020.106197, 2021.
Huffman, J. A., Prenni, A. J., DeMott, P. J., Pöhlker, C., Mason, R. H., Robinson, N. H., Fröhlich-Nowoisky, J., Tobo, Y., Després, V. R., Garcia, E., Gochis, D. J., Harris, E., Müller-Germann, I., Ruzene, C., Schmer, B., Sinha, B., Day, D. A., Andreae, M. O., Jimenez, J. L., Gallagher, M., Kreidenweis, S. M., Bertram, A. K., and Pöschl, U.: High concentrations of biological aerosol particles and ice nuclei during and after rain, Atmos. Chem. Phys., 13, 6151–6164, https://doi.org/10.5194/acp-13-6151-2013, 2013.
Hummel, M., Hoose, C., Pummer, B., Schaupp, C., Fröhlich-Nowoisky, J., and Möhler, O.: Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation, Atmos. Chem. Phys., 18, 15437–15450, https://doi.org/10.5194/acp-18-15437-2018, 2018.
Jaenicke, R.: Abundance of cellular material and proteins in the
atmospheric, Science, 308, p. 73, https://doi.org/10.1126/science.1106335, 2005.
Jensen, M. P., Petersen, W. A., Bansemer, A., Bharadwaj, N., Carey, L. D., Cecil, D. J., Collis, S. M., Del Genio, A. D., Dolan, B., Gerlach, J., Giangrande, S. E., Heymsfield, A., Heymsfield, G., Kollias, P., Lang, T. J., Nesbitt, S. W., Neumann, A., Poellot, M., Rutledge, S. A., Schwaller, M., Tokay, A., Williams, C. R., Wolff, D. B., Xie, S., and Zipser, E. J.: The midlatitude continental convective clouds experiment (MC3E), B. Am. Meteorol. Soc., 97, 1667–1686, https://doi.org/10.1175/BAMS-D-14-00228.1, 2016.
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo,
D. J., and Krämer, M.: Overview of Ice Nucleating Particles,
Meteor. Mon., 58, 1.1–1.33, 2017.
Knopf, D. A., Alpert, P. A., Wang, B., and Aller, J. Y.: Stimulation of ice
nucleation by
marine diatoms, Nat. Geosci. 4, 88–90, https://doi.org/10.1038/ngeo1037, 2011.
Korolev, A. and Leisner, T.: Review of experimental studies of secondary ice production, Atmos. Chem. Phys., 20, 11767–11797, https://doi.org/10.5194/acp-20-11767-2020, 2020.
Korolev, A. V., Kuznetsov, S. V., Makarov, Y. E., and Novikov, V. S:
Evaluation of Measurements of Particle Size and Sample Area from Optical
Array Probes, J. Atmos. Ocean. Technol., 8, 514–522, 1991.
Korolev, A., McFarquhar, G., Field, P. R., Franklin, C., Lawson, P., Wang,
Z., Williams, E., Abel, S. J., Axisa, D., Borrmann, S., Crosier, J., Fugal,
J., Krämer, M., Lohmann, U., Schlenczek, O., Schnaiter, M., and
Wendisch, M.: Mixed-Phase Clouds: Progress and Challenges, Meteor. Mon., 58, 5.1–5.50, 2017.
Korolev, A., Heckman, I., Wolde, M., Ackerman, A. S., Fridlind, A. M., Ladino, L. A., Lawson, R. P., Milbrandt, J., and Williams, E.: A new look at the environmental conditions favorable to secondary ice production, Atmos. Chem. Phys., 20, 1391–1429, https://doi.org/10.5194/acp-20-1391-2020, 2020.
Kumjian, M. R. and Lombardo, K. A.: Insights into the evolving microphysical
and kinematic structure of northeastern U.S. winter storms from
dual-polarization Doppler radar, Mon. Wea. Rev., 145, 1033–1061,
https://doi.org/10.1175/MWR-D-15-0451.1, 2017.
Lawson, R. P., Woods, S., and Morrison, H.: The microphysics of ice and
precipitation 1195 development in tropical cumulus clouds, J. Atmos. Sci.,
72, 2429–2445, https://doi.org/10.1175/JAS-D-14-0274.1, 2015.
Levin, Z., Yankofsky, S., Pardes, D., and Magal, N.: J. Clim. Appl. Meteorol., 26, 1188–97, 1987.
Malm, W. C., Sisler, J. F., Huffman, D., Eldred, R. A., and Cahill, T. A.:
Spatial and seasonal trends in particle concentration and optical extinction
in the United States, J. Geophys. Res., 99, 1347–1370, 1994.
Mattias-Maser, S. and Jaenicke, R.: The size distribution of primary biological aerosol particles with radii >0.2 mm in an urban/rural
influenced region, Atmos. Res. 39, 279–286, 1995.
Mattias-Maser, S., Brinkmann, J., and Schneider, W.: The size distribution of
marine atmospheric aerosol with regard to primary biological aerosol
particles over the South Atlantic Ocean, Atmos. Environ., 33, 3569–3575, 1999.
Matthias-Maser, S., Bogs, B., and Jaenicke, R.: The size distribution of primary
biological aerosol particles in cloud water on the mountain Kleiner
Feldberg/Taunus (FRG), Atmos. Res., 54, 1–13, 2000.
Matus, A. V. and L'Ecuyer, T. S.: The role of cloud phase in Earth's
radiation budget, J. Geophys. Res.-Atmos., 122, 2559–2578,
https://doi.org/10.1002/2016JD025951, 2017.
Möhler, O., Georgakopoulos, D. G., Morris, C. E., Benz, S., Ebert, V., Hunsmann, S., Saathoff, H., Schnaiter, M., and Wagner, R.: Heterogeneous ice nucleation activity of bacteria: new laboratory experiments at simulated cloud conditions, Biogeosciences, 5, 1425–1435, https://doi.org/10.5194/bg-5-1425-2008, 2008.
Moisseev, D. N., Lautaportti, S., Tyynela, J., and Lim,
S.: Dual-polarization radar signatures in snowstorms: Role of
snowflake aggregation, J. Geophys. Res.-Atmos., 120, 12644–12655, https://doi.org/10.1002/2015JD023884.
Morris, C. E., Conen F., Huffman, A. J., Phillips, V. J. T. P., Pöschl,
U., and Sands, D. C.: Bioprecipitation: A feedback cycle linking Earth
history, ecosystem dynamics and land use through biological ice nucleators
in the atmosphere, Global Change Biology, 20, 341–351,
https://doi.org/10.1111/gcb.12447, 2014,
Mülmenstädt, J., Sourdeval, O., Delanoë, J., and Quaas, J.:
Frequency of occurrence of rain from liquid-, mixed-, and ice-phase clouds
derived from A-Train satellite retrievals, Geophys. Res. Lett., 42, 6502–6509, 2015.
Murray, B. J., O'Sullivan, D., Atkinson, J. D., and Webb, M. E.: Ice
nucleation by particles immersed in supercooled cloud droplets, Chem. Soc.
Rev., 41, 6519–6554, https://doi.org/10.1039/c2cs35200a, 2012.
Patade, S., Phillips, V. T. J., Amato, P., Bingemer, H. G., Burrows, S. M.,
DeMott, P. J., Goncalves, F. L. T., Knopf, D. A., Morris, C. E., Alwmark,
C., Artaxo, P., Pöhlker, C., Schrod, J., and Weber, B.: Empirical
Formulation for Multiple Groups of Primary Biological Ice Nucleating
Particles from Field Observations over Amazonia, J. Atmos. Sci., 78, 2195–2220, 2021.
Phillips, V. T. J. and Patade, S.: Multiple Environmental Influences on the
Lightning of Cold-based Continental Convection. Part II: Sensitivity Tests
for its Charge Structure and Land-Ocean Contrast, J. Atmos. Sci., 79, 263–300, https://doi.org/10.1175/JAS-D-20-0234.1, 2021.
Phillips, V. T. J., Donner, L. J., and Garner, S.: Nucleation processes in
deep convection simulated by a cloud-system resolving model with
double-moment bulk microphysics, J. Atmos. Sci., 64, 738–761, 2007.
Phillips, V. T. J., DeMott, P. J., and Andronache, C.: An Empirical
Parameterization of Heterogeneous Ice Nucleation for Multiple Chemical
Species of Aerosol, J. Atmos. Sci., 65, 2757–2783, 2008.
Phillips, V. T. J., Andronache, C., Christner, B., Morris, C. E., Sands, D. C., Bansemer, A., Lauer, A., McNaughton, C., and Seman, C.: Potential impacts from biological aerosols on ensembles of continental clouds simulated numerically, Biogeosciences, 6, 987–1014, https://doi.org/10.5194/bg-6-987-2009, 2009.
Phillips, V. T. J., Demott, P. J., Andronache, C., Pratt, K. A., Prather, K.
A., Subramanian, R., and Twohy, C.: Improvements to an empirical
parameterization of heterogeneous ice nucleation and its comparison with
observations, J. Atmos. Sci., 70, 378–409, https://doi.org/10.1175/JAS-D-12-080.1, 2013.
Phillips, V. T. J., Yano, J. I., and Khain, A.: Ice multiplication by
breakup in ice-ice collisions. Part I: Theoretical formulation, J. Atmos. Sci., 74, 1705–1719, https://doi.org/10.1175/JAS-D-16-0224.1, 2017a.
Phillips, V. T. J., Yano, J., Formenton, M., Ilotoviz, E., Kanawade, V.,
Kudzotsa, I., Sun, J., Bansemer, A., Detwiler, A. G., Khain, A., and
Tessendorf, S. A.: Ice Multiplication by Breakup in Ice–Ice Collisions,
Part II: Numerical Simulations, J. Atmos. Sci., 74, 2789–2811, 2017b.
Phillips, V. T. J., Patade, S., Gutierrez, J., and Bansemer, A.: Secondary
ice production by fragmentation of freezing drops: Formulation and theory,
J. Atmos. Sci., 75, 3031–3070, https://doi.org/10.1175/JAS-D-17-0190.1, 2018.
Phillips, V. T. J., Formenton, M., Kanawade, V. P., Karlsson, L. R., Patade,
S., Sun, J., Barthe, C., Pinty, J., Detwiler, A. G., Lyu, W., and
Tessendorf, S. A.: Multiple Environmental Influences on the Lightning of
Cold-Based Continental Cumulonimbus Clouds, Part I: Description and
Validation of Model, J. Atmos. Sci., 77, 3999–4024, 2020.
Pörtner, H.-O., Roberts, D. C., Poloczanska, E. S., Mintenbeck, K., Tignor, M., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., and Okem, A.: Summary for policymakers, in: Climate change 2022: Impact, adaptation, and vulnerability: Summary for policy makers: Working group II Contribution to the sixth assessment report of the Intergovernmental Panel on Climate Change, Cambridge University Press, in press, 2022.
Prenni, A. J., Tobo, Y., Garcia, E., DeMott, P. J., Huffman, J. A., McCluskey, C. S., Kreidenweis, S. M., Prenni, J. E., Pöhlker, C., and Pöschl, U.: The impact of rain on ice nuclei populations at a forested site in Colorado, Geophys. Res. Lett., 40, 227–231, https://doi.org/10.1029/2012GL053953, 2012.
Ryzhkov, A., Pinsky, M., Pokrovsky, A., and Khain, A.: Polarimetric Radar
Observation Operator for a Cloud Model with Spectral Microphysics, J. Appl. Meteorol. Climatol., 50, 873–894, 2011.
Sahyoun, M., Wex, H., Gosewinkel, U., Šantl-Temkiv, T., Nielsen, N. W.,
Finster, K., Sørensen, J. H., Stratmann, F., and Korsholm, U. S.: On the
usage of classical nucleation theory in quantification of the impact of
bacterial INP on weather and climate, Atmos. Environ., 139, 230–240,
https://doi.org/10.1016/j.atmosenv.2016.05.034, 2016.
Sesartic, A., Lohmann, U., and Storelvmo, T.: Bacteria in the ECHAM5-HAM global climate model, Atmos. Chem. Phys., 12, 8645–8661, https://doi.org/10.5194/acp-12-8645-2012, 2012.
Sesartic, A., Lohmann, U., and Storelvmo, T.: Modelling the impact of fungal
spore ice nuclei on clouds and precipitation, Environ. Res. Lett., 8, 014029, https://doi.org/10.1088/1748-9326/8/1/014029, 2013.
Sinclair, V. A., Moisseev, D., and von Lerber, A.: How
dual-polarization radar observations can be used to verify model
representation of secondary ice, J. Geophys. Res.-Atmos., 121, 10954–10970, https://doi.org/10.1002/2016JD025381, 2016.
Sotiropoulou, G., Vignon, É., Young, G., Morrison, H., O'Shea, S. J., Lachlan-Cope, T., Berne, A., and Nenes, A.: Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models, Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, 2021a.
Sotiropoulou, G., Ickes, L., Nenes, A., and Ekman, A. M. L.: Ice multiplication from ice–ice collisions in the high Arctic: sensitivity to ice habit, rimed fraction, ice type and uncertainties in the numerical description of the process, Atmos. Chem. Phys., 21, 9741–9760, https://doi.org/10.5194/acp-21-9741-2021, 2021b.
Spracklen, D. V. and Heald, C. L.: The contribution of fungal spores and bacteria to regional and global aerosol number and ice nucleation immersion freezing rates, Atmos. Chem. Phys., 14, 9051–9059, https://doi.org/10.5194/acp-14-9051-2014, 2014.
Szyrmer, W. and Zawadzki, I.: Biogenic and anthropogenic sources of ice-forming
nuclei: A review, B. Am. Meteorol. Soc., 78, 209–228, 1997.
Tsushima, Y., Emori S., Ogura T., Kimoto, M., Webb, M. J., Williams, K. D.,
Ringer, M. A., Soden, B. J., Li, B., and Andronova, N.: Importance of the mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study, Clim. Dynam., 27, 113–126, 2006.
Xie, S., Zhang, Y., Giangrande, S. E., Jensen, M. P., McCoy, R., and Zhang, M.:
Interactions between cumulus convection and its environment as revealed by
the MC3E sounding array, J. Geophys. Res., 119, 11784–11808, https://doi.org/10.1002/2014JD022011, 2014.
Zhao, X. and Liu, X.: Global importance of secondary ice
production, Geophys. Res. Lett., 48, e2021GL092581,
https://doi.org/10.1029/2021GL092581, 2021.
Zuidema, P., Westwater, E. R., Fairall, C., and Hazen, D.: Ship-based liquid
water path estimates in marine stratocumulus, J. Geophys. Res., 110, D20206, https://doi.org/10.1029/2005JD005833, 2005.
Short summary
This modeling study focuses on the role of multiple groups of primary biological aerosol particles as ice nuclei on cloud properties and precipitation. This was done by implementing a more realistic scheme for biological ice nucleating particles in the aerosol–cloud model. Results show that biological ice nucleating particles have a limited role in altering the ice phase and precipitation in deep convective clouds.
This modeling study focuses on the role of multiple groups of primary biological aerosol...
Altmetrics
Final-revised paper
Preprint