Articles | Volume 19, issue 19
https://doi.org/10.5194/acp-19-12431-2019
© Author(s) 2019. 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-19-12431-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Microphysics of summer clouds in central West Antarctica simulated by the Polar Weather Research and Forecasting Model (WRF) and the Antarctic Mesoscale Prediction System (AMPS)
Keith M. Hines
CORRESPONDING AUTHOR
Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH 43210, USA
David H. Bromwich
Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH 43210, USA
Atmospheric Sciences Program, Department of Geography, The Ohio State University, Columbus, OH 43210, USA
Sheng-Hung Wang
Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH 43210, USA
Israel Silber
Department of Meteorology and Atmospheric Sciences, The Pennsylvania State University, University Park, PA 16802, USA
Johannes Verlinde
Department of Meteorology and Atmospheric Sciences, The Pennsylvania State University, University Park, PA 16802, USA
Dan Lubin
Scripps Institution of Oceanography, University of California, San
Diego, La Jolla, CA 96802, USA
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David Bromwich, Sheng-Hung Wang, Xun Zou, and Alexandra Ensign
Earth Syst. Sci. Data, 17, 2953–2962, https://doi.org/10.5194/essd-17-2953-2025, https://doi.org/10.5194/essd-17-2953-2025, 2025
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Antarctica is a major player in Earth’s climate, with the most direct influence arising from its potential to raise the global sea level by 1 m or more in the coming decades. Near-surface air temperature is the primary variable used to monitor the climate of this remote but important region. Continent-wide direct but sparse measurements that started around 1958 are used to construct a monthly air temperature dataset for all of Antarctica, spanning the period from 1958 to 2022.
Fan Mei, Qi Zhang, Damao Zhang, Jerome D. Fast, Gourihar Kulkarni, Mikhail S. Pekour, Christopher R. Niedek, Susanne Glienke, Israel Silber, Beat Schmid, Jason M. Tomlinson, Hardeep S. Mehta, Xena Mansoura, Zezhen Cheng, Gregory W. Vandergrift, Nurun Nahar Lata, Swarup China, and Zihua Zhu
Atmos. Chem. Phys., 25, 3425–3444, https://doi.org/10.5194/acp-25-3425-2025, https://doi.org/10.5194/acp-25-3425-2025, 2025
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This study highlights the unique capability of the ArcticShark, an uncrewed aerial system, in measuring vertically resolved atmospheric properties. Data from 32 research flights in 2023 reveal seasonal patterns and correlations with conventional measurements. The consistency and complementarity of in situ and remote sensing methods are highlighted. The study demonstrates the ArcticShark’s versatility in bridging data gaps and improving the understanding of vertical atmospheric structures.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data, 17, 29–42, https://doi.org/10.5194/essd-17-29-2025, https://doi.org/10.5194/essd-17-29-2025, 2025
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We present ARMTRAJ, a set of multipurpose trajectory datasets, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for air mass coordinates and state variables. ARMTRAJ will soon become a near real-time product that will accompany past, ongoing, and future ARM deployments.
Zhenhai Zhang, F. Martin Ralph, Xun Zou, Brian Kawzenuk, Minghua Zheng, Irina V. Gorodetskaya, Penny M. Rowe, and David H. Bromwich
The Cryosphere, 18, 5239–5258, https://doi.org/10.5194/tc-18-5239-2024, https://doi.org/10.5194/tc-18-5239-2024, 2024
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Atmospheric rivers (ARs) are long, narrow corridors of strong water vapor transport in the atmosphere. ARs play an important role in extreme weather in polar regions, including heavy rain and/or snow, heat waves, and surface melt. The standard AR scale is developed based on the midlatitude climate and is insufficient for polar regions. This paper introduces an extended version of the AR scale tuned to polar regions, aiming to quantify polar ARs objectively based on their strength and impact.
Abigail S. Williams, Jeramy L. Dedrick, Lynn M. Russell, Florian Tornow, Israel Silber, Ann M. Fridlind, Benjamin Swanson, Paul J. DeMott, Paul Zieger, and Radovan Krejci
Atmos. Chem. Phys., 24, 11791–11805, https://doi.org/10.5194/acp-24-11791-2024, https://doi.org/10.5194/acp-24-11791-2024, 2024
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The measured aerosol size distribution modes reveal distinct properties characteristic of cold-air outbreaks in the Norwegian Arctic. We find higher sea spray number concentrations, smaller Hoppel minima, lower effective supersaturations, and accumulation-mode particle scavenging during cold-air outbreaks. These results advance our understanding of cold-air outbreak aerosol–cloud interactions in order to improve their accurate representation in models.
Grégory V. Cesana, Olivia Pierpaoli, Matteo Ottaviani, Linh Vu, Zhonghai Jin, and Israel Silber
Atmos. Chem. Phys., 24, 7899–7909, https://doi.org/10.5194/acp-24-7899-2024, https://doi.org/10.5194/acp-24-7899-2024, 2024
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Better characterizing the relationship between sea ice and clouds is key to understanding Arctic climate because clouds and sea ice affect surface radiation and modulate Arctic surface warming. Our results indicate that Arctic liquid clouds robustly increase in response to sea ice decrease. This increase has a cooling effect on the surface because more solar radiation is reflected back to space, and it should contribute to dampening future Arctic surface warming.
Kristopher Scarci, Ryan C. Scott, Madison L. Ghiz, Andrew M. Vogelmann, and Dan Lubin
Atmos. Chem. Phys., 24, 6681–6697, https://doi.org/10.5194/acp-24-6681-2024, https://doi.org/10.5194/acp-24-6681-2024, 2024
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We demonstrate what can be learned about an Antarctic region's climate from basic atmospheric irradiance measurements made by broadband and filter radiometers, instruments suitable for deployment at very remote sites, assisted by meteorological reanalysis and satellite remote sensing. Analysis of shortwave and longwave irradiance reveals subtle contrasts between meteorological regimes favoring cloud ice versus liquid water, relevant to onset versus inhibition of surface melt over ice shelves.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
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Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
Frederic Tridon, Israel Silber, Alessandro Battaglia, Stefan Kneifel, Ann Fridlind, Petros Kalogeras, and Ranvir Dhillon
Atmos. Chem. Phys., 22, 12467–12491, https://doi.org/10.5194/acp-22-12467-2022, https://doi.org/10.5194/acp-22-12467-2022, 2022
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The role of ice precipitation in the Earth water budget is not well known because ice particles are complex, and their formation involves intricate processes. Riming of ice crystals by supercooled water droplets is an efficient process, but little is known about its importance at high latitudes. In this work, by exploiting the deployment of an unprecedented number of remote sensing systems in Antarctica, we find that riming occurs at much lower temperatures compared with the mid-latitudes.
Jeramy L. Dedrick, Georges Saliba, Abigail S. Williams, Lynn M. Russell, and Dan Lubin
Atmos. Meas. Tech., 15, 4171–4194, https://doi.org/10.5194/amt-15-4171-2022, https://doi.org/10.5194/amt-15-4171-2022, 2022
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A new method is presented to retrieve the sea spray aerosol size distribution by combining submicron size and nephelometer scattering based on Mie theory. Using available sea spray tracers, we find that this approach serves as a comparable substitute to supermicron size distribution measurements, which are limited in availability at marine sites. Application of this technique can expand sea spray observations and improve the characterization of marine aerosol impacts on clouds and climate.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
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The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Madison L. Ghiz, Ryan C. Scott, Andrew M. Vogelmann, Jan T. M. Lenaerts, Matthew Lazzara, and Dan Lubin
The Cryosphere, 15, 3459–3494, https://doi.org/10.5194/tc-15-3459-2021, https://doi.org/10.5194/tc-15-3459-2021, 2021
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We investigate how melt occurs over the vulnerable ice shelves of West Antarctica and determine that the three primary mechanisms can be evaluated using archived numerical weather prediction model data and satellite imagery. We find examples of each mechanism: thermal blanketing by a warm atmosphere, radiative heating by thin clouds, and downslope winds. Our results signify the potential to make a multi-decadal assessment of atmospheric stress on West Antarctic ice shelves in a warming climate.
Stefanie Kremser, Mike Harvey, Peter Kuma, Sean Hartery, Alexia Saint-Macary, John McGregor, Alex Schuddeboom, Marc von Hobe, Sinikka T. Lennartz, Alex Geddes, Richard Querel, Adrian McDonald, Maija Peltola, Karine Sellegri, Israel Silber, Cliff S. Law, Connor J. Flynn, Andrew Marriner, Thomas C. J. Hill, Paul J. DeMott, Carson C. Hume, Graeme Plank, Geoffrey Graham, and Simon Parsons
Earth Syst. Sci. Data, 13, 3115–3153, https://doi.org/10.5194/essd-13-3115-2021, https://doi.org/10.5194/essd-13-3115-2021, 2021
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Aerosol–cloud interactions over the Southern Ocean are poorly understood and remain a major source of uncertainty in climate models. This study presents ship-borne measurements, collected during a 6-week voyage into the Southern Ocean in 2018, that are an important supplement to satellite-based measurements. For example, these measurements include data on low-level clouds and aerosol composition in the marine boundary layer, which can be used in climate model evaluation efforts.
Israel Silber, Ann M. Fridlind, Johannes Verlinde, Andrew S. Ackerman, Grégory V. Cesana, and Daniel A. Knopf
Atmos. Chem. Phys., 21, 3949–3971, https://doi.org/10.5194/acp-21-3949-2021, https://doi.org/10.5194/acp-21-3949-2021, 2021
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Long-term ground-based radar and sounding measurements over Alaska (Antarctica) indicate that more than 85 % (75 %) of supercooled clouds are precipitating at cloud base and that 75 % (50 %) are precipitating to the surface. Such high prevalence is reconciled with lesser spaceborne estimates by considering radar sensitivity. Results provide a strong observational constraint for polar cloud processes in large-scale models.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Richard Querel, Israel Silber, and Connor J. Flynn
Geosci. Model Dev., 14, 43–72, https://doi.org/10.5194/gmd-14-43-2021, https://doi.org/10.5194/gmd-14-43-2021, 2021
Jun Liu, Jeramy Dedrick, Lynn M. Russell, Gunnar I. Senum, Janek Uin, Chongai Kuang, Stephen R. Springston, W. Richard Leaitch, Allison C. Aiken, and Dan Lubin
Atmos. Chem. Phys., 18, 8571–8587, https://doi.org/10.5194/acp-18-8571-2018, https://doi.org/10.5194/acp-18-8571-2018, 2018
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Observations of the organic components of the natural aerosol are scarce in Antarctica, which limits our understanding of natural aerosols and their connection to cloud albedo. We took yearlong measurements of organic aerosols at McMurdo Station. The natural organic aerosol was 150 times higher in summer than in winter. We showed the natural sources of OM were characterized by amide, which may be from seabird populations. Acid was high in summer and likely formed by secondary reactions.
Flavio Justino, Douglas Lindemann, Fred Kucharski, Aaron Wilson, David Bromwich, and Frode Stordal
Clim. Past, 13, 1081–1095, https://doi.org/10.5194/cp-13-1081-2017, https://doi.org/10.5194/cp-13-1081-2017, 2017
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These modeling results have enormous implications for paleoreconstructions of the MIS31 climate that assume overall ice-free conditions in the vicinity of the Antarctic continent. Since these reconstructions may depict dominant signals in a particular time interval and locale, they cannot be assumed to geographically represent large-scale domains, and their ability to reproduce long-term environmental conditions should be considered with care.
Yinghui Lu, Zhiyuan Jiang, Kultegin Aydin, Johannes Verlinde, Eugene E. Clothiaux, and Giovanni Botta
Atmos. Meas. Tech., 9, 5119–5134, https://doi.org/10.5194/amt-9-5119-2016, https://doi.org/10.5194/amt-9-5119-2016, 2016
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The database contains the complete (polarimetric) scattering information for different types of ice particles at different incident and scattered radiation directions at four microwave wavelengths. These results are useful for understanding the dependence of ice-particle scattering properties on ice-particle orientation with respect to the incident and scattered radiation. It is also useful in ice-property retrievals, radar forward simulation.
Israel Silber, Colin Price, and Craig J. Rodger
Atmos. Chem. Phys., 16, 3279–3288, https://doi.org/10.5194/acp-16-3279-2016, https://doi.org/10.5194/acp-16-3279-2016, 2016
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We report for the first time that the semi-annual oscillation (SAO) is one of the dominant oscillations in the nighttime lower ionosphere, using ground-based measurements of VLF signals reflected off the lower part of the ionosphere. We conclude that the origins of this oscillation are oscillatory changes of the D region's electrical characteristics, driven by NOx transport from the lower thermosphere. This oscillation should be considered in lower ionospheric and VLF wave propagation models.
C. Wesslén, M. Tjernström, D. H. Bromwich, G. de Boer, A. M. L. Ekman, L.-S. Bai, and S.-H. Wang
Atmos. Chem. Phys., 14, 2605–2624, https://doi.org/10.5194/acp-14-2605-2014, https://doi.org/10.5194/acp-14-2605-2014, 2014
B. H. Kahn, F. W. Irion, V. T. Dang, E. M. Manning, S. L. Nasiri, C. M. Naud, J. M. Blaisdell, M. M. Schreier, Q. Yue, K. W. Bowman, E. J. Fetzer, G. C. Hulley, K. N. Liou, D. Lubin, S. C. Ou, J. Susskind, Y. Takano, B. Tian, and J. R. Worden
Atmos. Chem. Phys., 14, 399–426, https://doi.org/10.5194/acp-14-399-2014, https://doi.org/10.5194/acp-14-399-2014, 2014
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Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Magnitude and timescale of liquid water path adjustments to cloud droplet number concentration perturbations for nocturnal non-precipitating marine stratocumulus
Cold pools mediate mesoscale adjustments of trade-cumulus fields to changes in cloud droplet number concentration
Numerical case study of the aerosol–cloud interactions in warm boundary layer clouds over the eastern North Atlantic with an interactive chemistry module
Influence of temperature and humidity on contrail formation regions in the general circulation model EMAC: a spring case study
On the impact of thunder on cloud ice crystals and droplets
Counteracting influences of gravitational settling modulate aerosol impacts on cloud-base-lowering fog characteristics
The critical number and size of precipitation embryos to accelerate warm rain initiation
Impact on the stratocumulus-to-cumulus transition of the interaction of cloud microphysics and macrophysics with large-scale circulation
Technical note: Phase space depiction of cloud condensation nuclei activation and cloud droplet diffusional growth
Impact of wildfire smoke on Arctic cirrus formation – Part 2: Simulation of MOSAiC 2019–2020 cases
Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble
Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme
Assessing glaciogenic seeding impacts in Australia’s Snowy Mountains: an ensemble modeling approach
Exploiting airborne far-infrared measurements to optimise an ice cloud retrieval
Microphysics regimes due to haze–cloud interactions: cloud oscillation and cloud collapse
Influence of Secondary Ice Production on cloud and rain properties: Analysis of the HYMEX IOP7a Heavy Precipitation Event
The influence of Amazonian anthropogenic emissions on new particle formation, aerosol, cloud and surface rain
Impact of secondary ice production on thunderstorm electrification under different aerosol conditions
Accelerated impact of airborne glaciogenic seeding of stratiform clouds by turbulence
Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path
Evaluation of biases in mid-to-high-latitude surface snowfall and cloud phase in ERA5 and CMIP6 using satellite observations
Failed cyclogenesis of a mesoscale convective system near Cape Verde: The role of the Saharan trade wind layer among other inhibiting factors observed during the CADDIWA field campaign
Dynamical imprints on precipitation cluster statistics across a hierarchy of high-resolution simulations
Ice formation processes key in determining WCB outflow cirrus properties
Role of a key microphysical factor in mixed-phase stratocumulus clouds and their interactions with aerosols
High-resolution modelling of early contrail evolution from hydrogen-powered aircraft
Investigating the impact of subgrid-scale aerosol-cloud interaction on mesoscale meteorology prediction
Correction of ERA5 temperature and relative humidity biases by bivariate quantile mapping for contrail formation analysis
Can pollen affect precipitation?
Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response
The impact of the mesh size and microphysics scheme on the representation of mid-level clouds in the ICON model in hilly and complex terrain
The role of ascent timescales for warm conveyor belt (WCB) moisture transport into the upper troposphere and lower stratosphere (UTLS)
On the Processes Determining the Slope of Cloud-Water Adjustments in Non-Precipitating Stratocumulus
High sensitivity of simulated fog properties to parameterized aerosol activation in case studies from ParisFog
Adiabatic and radiative cooling are both important causes of aerosol activation in simulated fog events in Europe
Estimating the concentration of silver iodide needed to detect unambiguous signatures of glaciogenic cloud seeding
Ice-nucleating particle concentration impacts cloud properties over Dronning Maud Land, East Antarctica, in COSMO-CLM2
Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China
The impact of aerosol on cloud water: a heuristic perspective
The presence of clouds lowers climate sensitivity in the MPI-ESM1.2 climate model
Diurnal variation in an amplified canopy urban heat island during heat wave periods in the megacity of Beijing: roles of mountain–valley breeze and urban morphology
Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble
Ambient and Intrinsic Dependencies of Evolving Ice-Phase Particles within a Decaying Winter Storm During IMPACTS
Adjustments to an abrupt solar forcing in the CMIP6 abrupt-solm4p experiment
Building a comprehensive library of observed Lagrangian trajectories for testing modeled cloud evolution, aerosol-cloud interactions, and marine cloud brightening
High ice water content in tropical mesoscale convective systems (a conceptual model)
Evolution of cloud droplet temperature and lifetime in spatiotemporally varying subsaturated environments with implications for ice nucleation at cloud edges
Effect of secondary ice production processes on the simulation of ice pellets using the Predicted Particle Properties microphysics scheme
Simulated particle evolution within a winter storm: contributions of riming to radar moments and precipitation fallout
Arctic Multilayer Clouds Require Accurate Thermodynamic Profiles and Efficient Primary and Secondary Ice Processes for a Realistic Structure and Composition
Yao-Sheng Chen, Prasanth Prabhakaran, Fabian Hoffmann, Jan Kazil, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 25, 6141–6159, https://doi.org/10.5194/acp-25-6141-2025, https://doi.org/10.5194/acp-25-6141-2025, 2025
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Injecting sea salt aerosols into marine stratiform clouds can distribute the cloud water over more droplets in smaller sizes. This process is expected to make the clouds brighter, allowing them to reflect more sunlight back to space. However, it may also cause the clouds to lose water over time, reducing their ability to reflect sunlight. We use a computer model to show that the loss of cloud water occurs relatively quickly and does not completely offset the initial brightening.
Pouriya Alinaghi, Fredrik Jansson, Daniel A. Blázquez, and Franziska Glassmeier
Atmos. Chem. Phys., 25, 6121–6139, https://doi.org/10.5194/acp-25-6121-2025, https://doi.org/10.5194/acp-25-6121-2025, 2025
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Shallow clouds in the trades are a major source of uncertainty in climate projections. These clouds organize into striking mesoscale patterns that are exactly what climate models lack. This study explores the origin of such patterns and investigates how variations in microscale properties control them. The importance of microscale effects is compared to that of large-scale forcing on the mesoscale organization of trade-cumulus fields.
Hsiang-He Lee, Xue Zheng, Shaoyue Qiu, and Yuan Wang
Atmos. Chem. Phys., 25, 6069–6091, https://doi.org/10.5194/acp-25-6069-2025, https://doi.org/10.5194/acp-25-6069-2025, 2025
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The study investigates how aerosol–cloud interactions affect warm boundary layer stratiform clouds over the eastern North Atlantic. High-resolution weather model simulations reveal that non-rain clouds at the edge of cloud systems are prone to evaporation, leading to an aerosol drying effect and a transition of aerosols back to the accumulation mode for future activation. The study shows that this dynamic behavior is often not adequately represented in most previous prescribed-aerosol simulations.
Patrick Peter, Sigrun Matthes, Christine Frömming, Patrick Jöckel, Luca Bugliaro, Andreas Giez, Martina Krämer, and Volker Grewe
Atmos. Chem. Phys., 25, 5911–5934, https://doi.org/10.5194/acp-25-5911-2025, https://doi.org/10.5194/acp-25-5911-2025, 2025
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Our study examines how well the global climate model EMAC (ECHAM/MESSy Atmospheric Chemistry) predicts contrail formation by analysing temperature and humidity – two key factors for contrail development and persistence. The model underestimates temperature, leading to an overprediction of contrail formation and larger ice-supersaturated regions. Adjusting the model improves temperature accuracy but adds uncertainties. Better predictions of contrail formation areas can help optimise flight tracks to reduce aviation's climate effect.
Konstantinos Kourtidis, Stavros Stathopoulos, and Vassilis Amiridis
Atmos. Chem. Phys., 25, 5935–5946, https://doi.org/10.5194/acp-25-5935-2025, https://doi.org/10.5194/acp-25-5935-2025, 2025
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The sound of thunder induces mechanical effects on cloud droplets and ice particles, causing changes in their size distribution. A shock wave near the lightning channel causes extensive shattering of cloud particles. At a distance, the audio wave will cause agglomeration of particles. So, thunder may influence the rain generation process and the radiative properties of clouds. As global warming may influence the occurrence rate of lightning, a climate feedback may be induced by these mechanisms.
Nathan H. Pope and Adele L. Igel
Atmos. Chem. Phys., 25, 5433–5444, https://doi.org/10.5194/acp-25-5433-2025, https://doi.org/10.5194/acp-25-5433-2025, 2025
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We used an atmospheric model that simulates a single column to study the sensitivity of marine fog formed through the lowering of the base of a stratus cloud to meteorology and aerosols. We found that higher aerosol concentration reduces the likelihood and duration of fog but leads to denser fog. This overall trend was caused by multiple physical mechanisms depending on conditions.
Jung-Sub Lim, Yign Noh, Hyunho Lee, and Fabian Hoffmann
Atmos. Chem. Phys., 25, 5313–5329, https://doi.org/10.5194/acp-25-5313-2025, https://doi.org/10.5194/acp-25-5313-2025, 2025
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Rain formation in warm clouds begins when small droplets collide, but this process can be slow without larger droplets. We used simulations to explore the role of bigger droplets, known as precipitation embryos, in triggering rain. We found that they speed up rain only when their size and number exceed a critical threshold. This threshold becomes larger when collisions are naturally efficient, such as in clouds with broad droplet size distributions or strong turbulence.
Je-Yun Chun, Robert Wood, Peter N. Blossey, and Sarah J. Doherty
Atmos. Chem. Phys., 25, 5251–5271, https://doi.org/10.5194/acp-25-5251-2025, https://doi.org/10.5194/acp-25-5251-2025, 2025
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This study explores how aerosols affect clouds transitioning from stratocumulus to cumulus along trade winds under varying atmospheric conditions. We found that aerosols typically reduce precipitation and raise cloud height, but their impact changes when subsidence changes by aerosol enhancement are considered. Our findings indicate that the cooling effect of aerosols might be overestimated if these atmospheric changes are not accounted for.
Wojciech W. Grabowski and Hanna Pawlowska
Atmos. Chem. Phys., 25, 5273–5285, https://doi.org/10.5194/acp-25-5273-2025, https://doi.org/10.5194/acp-25-5273-2025, 2025
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A simple diagram to depict cloud droplets' formation via the activation of cloud condensation nuclei (CCN) as well as their subsequent growth and evaporation is presented.
Albert Ansmann, Cristofer Jimenez, Daniel A. Knopf, Johanna Roschke, Johannes Bühl, Kevin Ohneiser, and Ronny Engelmann
Atmos. Chem. Phys., 25, 4867–4884, https://doi.org/10.5194/acp-25-4867-2025, https://doi.org/10.5194/acp-25-4867-2025, 2025
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In this study, we focus on the potential impact of wildfire smoke on cirrus formation. Aerosol and cirrus observations with lidar and radar during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, presented in the companion paper (Ansmann et al., 2025), are closely linked to comprehensive modeling of ice nucleation in cirrus evolution processes, presented in this article. A clear impact of wildfire smoke on cirrus formation was found.
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
Atmos. Chem. Phys., 25, 4547–4570, https://doi.org/10.5194/acp-25-4547-2025, https://doi.org/10.5194/acp-25-4547-2025, 2025
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Whether increased aerosol increases or decreases liquid cloud mass has been a longstanding question. Observed correlations suggest that aerosols thin liquid cloud, but we are able to show that observations were consistent with an increase in liquid cloud in response to aerosols by leveraging a model where causality could be traced.
Tim Lüttmer, Peter Spichtinger, and Axel Seifert
Atmos. Chem. Phys., 25, 4505–4529, https://doi.org/10.5194/acp-25-4505-2025, https://doi.org/10.5194/acp-25-4505-2025, 2025
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We investigate ice formation pathways in idealized convective clouds using a novel microphysics scheme that distinguishes between five ice classes each with their own unique formation mechanism. Ice crystals from rime splintering form the lowermost layer of ice crystals around the updraft core. The majority of ice crystals in the anvil of the convective cloud stems from frozen droplets. Ice stemming from homogeneous and deposition nucleation was only relevant in the overshoot.
Sisi Chen, Lulin Xue, Sarah A. Tessendorf, Thomas Chubb, Andrew Peace, Suzanne Kenyon, Johanna Speirs, Jamie Wolff, and Bill Petzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-1434, https://doi.org/10.5194/egusphere-2025-1434, 2025
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This study aims to investigate how cloud seeding affects snowfall in Australia's Snowy Mountains. By running simulations with different setups, we found that seeding impact varies greatly with weather conditions. Seeding increased snow in stable weather but sometimes reduced it in stormy weather. This helps us better understand when seeding works best to boost water supplies.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Rui Song, Richard Siddans, Richard Bantges, Jonathan Murray, Stuart Fox, and Cathryn Fox
EGUsphere, https://doi.org/10.5194/egusphere-2025-647, https://doi.org/10.5194/egusphere-2025-647, 2025
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Upwelling radiation with wavelengths between 15 and 100 microns is theorised to be highly sensitive to the properties of ice clouds, particularly the shape of the ice crystals. We exploit this sensitivity and perform the first retrieval of ice cloud properties using these wavelengths from an observation taken on an aircraft and evaluate it against measurements of the cloud’s properties.
Fan Yang, Hamed Fahandezh Sadi, Raymond A. Shaw, Fabian Hoffmann, Pei Hou, Aaron Wang, and Mikhail Ovchinnikov
Atmos. Chem. Phys., 25, 3785–3806, https://doi.org/10.5194/acp-25-3785-2025, https://doi.org/10.5194/acp-25-3785-2025, 2025
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Large-eddy simulations of a convection cloud chamber show two new microphysics regimes, cloud oscillation and cloud collapse, due to haze–cloud interactions. Our results suggest that haze particles and their interactions with cloud droplets should be considered especially in polluted conditions. To properly simulate haze–cloud interactions, we need to resolve droplet activation and deactivation processes, instead of using Twomey-type activation parameterization.
Pierre Grzegorczyk, Wolfram Wobrock, Aymeric Dziduch, and Céline Planche
EGUsphere, https://doi.org/10.5194/egusphere-2025-819, https://doi.org/10.5194/egusphere-2025-819, 2025
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The impact of secondary ice production (SIP) on a HYMEX intense precipitation event is investigated using 3D bin microphysics. Including SIP improves agreement with in situ aircraft observations (ice crystal number concentration and supercooled drop number fraction), generates small ice crystals and redistributes condensed water mass toward smaller particle sizes. As these crystals melt, the liquid precipitation flux decreases, reducing total precipitation by 8 % and heavy rainfall by 20 %.
Xuemei Wang, Kenneth S. Carslaw, Daniel P. Grosvenor, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2025-132, https://doi.org/10.5194/egusphere-2025-132, 2025
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Anthropogenic emissions can influence aerosol particle number concentrations via new particle formation. Our model simulations predict around 10 % increase of the particle and cloud droplet number concentrations when doubling the emissions in the Manaus region in the Amazonian wet season. However, the corresponding changes in cloud water and rain mass are around 4 %. Such weak response implied that this convective environment is not sensitive to the localised anthropogenic emission changes here.
Shiye Huang, Jing Yang, Jiaojiao Li, Qian Chen, Qilin Zhang, and Fengxia Guo
Atmos. Chem. Phys., 25, 1831–1850, https://doi.org/10.5194/acp-25-1831-2025, https://doi.org/10.5194/acp-25-1831-2025, 2025
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Aerosol and secondary ice production are both vital to charge separation in thunderstorms, but the relative importance of different SIP processes to cloud electrification under different aerosol conditions is not well understood. In this study, we show in a clean environment, the shattering of freezing drops has the greatest effect on the charging rate, while in a polluted environment, both rime splintering and the shattering of freezing drops have a significant effect on cloud electrification.
Meilian Chen, Xiaoqin Jing, Jiaojiao Li, Jing Yang, Xiaobo Dong, Bart Geerts, Yan Yin, Baojun Chen, Lulin Xue, Mengyu Huang, Ping Tian, and Shaofeng Hua
EGUsphere, https://doi.org/10.5194/egusphere-2025-47, https://doi.org/10.5194/egusphere-2025-47, 2025
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Several recent studies have reported complete cloud glaciation induced by airborne-based glaciogenic cloud seeding over plains. Since turbulence is an important factor to maintain clouds in mixed-phase, it is hypothesized that turbulence may have an impact on the seeding effect. This hypothesis is evident in the present study, which shows turbulence can accelerate the impact of airborne glaciogenic seeding of stratiform clouds.
Harri Kokkola, Juha Tonttila, Silvia M. Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo Henrik Virtanen, Pekka Kolmonen, and Antti Arola
Atmos. Chem. Phys., 25, 1533–1543, https://doi.org/10.5194/acp-25-1533-2025, https://doi.org/10.5194/acp-25-1533-2025, 2025
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Understanding how atmospheric aerosols affect clouds is a scientific challenge. One question is how aerosols affects the amount of cloud water. We used a cloud-scale model to study these effects on marine clouds. The study showed that variations in cloud properties and instrument noise can cause bias in satellite-derived cloud water content. However, our results suggest that for similar weather conditions with well-defined aerosol concentrations, satellite data can reliably track these effects.
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, Haochi Che, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1353–1383, https://doi.org/10.5194/acp-25-1353-2025, https://doi.org/10.5194/acp-25-1353-2025, 2025
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This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their link to surface snowfall in CloudSat–CALIPSO, ERA5, and the CMIP6 models. Significant discrepancies were found, with ERA5 and CMIP6 consistently overestimating sLCC and snowfall frequency. This bias is likely due to cloud microphysics parameterization. This conclusion has implications for accurately representing cloud phase and snowfall in future climate projections.
Guillaume Feger, Jean-Pierre Chaboureau, Thibaut Dauhut, Julien Delanoë, and Pierre Coutris
EGUsphere, https://doi.org/10.5194/egusphere-2025-105, https://doi.org/10.5194/egusphere-2025-105, 2025
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The Saharan air at trade wind layer, cold pools, and upper tropospheric dry air are identified as the three main factors inhibiting the cyclogenesis of the Pierre Henri mesoscale convective system. The findings were obtained trough observations made during two flights of the CADDIWA campaign and a convection-permitting simulation run with the Meso-NH model. They provide new insights into the complex dynamics of cyclogenesis in the Cape Verde region and challenge the existing model of the SAL.
Claudia Christine Stephan and Bjorn Stevens
Atmos. Chem. Phys., 25, 1209–1226, https://doi.org/10.5194/acp-25-1209-2025, https://doi.org/10.5194/acp-25-1209-2025, 2025
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Tropical precipitation cluster area and intensity distributions follow power laws, but the physical processes responsible for this behavior remain unknown. We analyze global simulations that realistically represent precipitation processes. We consider Earth-like planets as well as virtual planets to realize different types of large-scale dynamics. Our finding is that power laws in Earth’s precipitation cluster statistics stem from the robust power laws in Earth’s atmospheric wind field.
Tim Lüttmer, Annette Miltenberger, and Peter Spichtinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-185, https://doi.org/10.5194/egusphere-2025-185, 2025
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We investigate ice formation pathways in a warm conveyor belt case study. We employ a multi-phase microphysics scheme that distinguishes between ice from different nucleation processes. Ice crystals in the cirrus outflow mostly stem from in-situ formation. Hence they were formed directly from the vapor phase. Sedimentational redistribution modulates cirrus properties and leads to a disagreement between cirrus origin classifications based on thermodynamic history and nucleation processes.
Seoung Soo Lee, Chang Hoon Jung, Jinho Choi, Young Jun Yoon, Junshik Um, Youtong Zheng, Jianping Guo, Manguttathil G. Manoj, Sang-Keun Song, and Kyung-Ja Ha
Atmos. Chem. Phys., 25, 705–726, https://doi.org/10.5194/acp-25-705-2025, https://doi.org/10.5194/acp-25-705-2025, 2025
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This study attempts to test a general factor that explains differences in the properties of different mixed-phase clouds using a modeling tool. Although this attempt is not to identify a factor that can perfectly explain and represent the properties of different mixed-phase clouds, we believe that this attempt acts as a valuable stepping stone towards a more complete, general way of using climate models to better predict climate change.
Annemarie Lottermoser and Simon Unterstraßer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3859, https://doi.org/10.5194/egusphere-2024-3859, 2025
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Contrail-cirrus significantly contributes to aviation's overall climate impact. As hydrogen combustion and fuel cell use are emerging technologies for aircraft propulsion, we simulated individual contrails from hydrogen propulsion during the first six minutes after exhaust emission, termed the vortex phase. The ice crystal loss during that stage is crucial as the number of ice crystals has a large impact on the further evolution of contrails into contrail-cirrus and their radiative forcing.
Wenjie Zhang, Hong Wang, Xiaoye Zhang, Yue Peng, Zhaodong Liu, Deying Wang, Da Zhang, Chen Han, Yang Zhao, Junting Zhong, Wenxing Jia, Huiqiong Ning, and Huizheng Che
EGUsphere, https://doi.org/10.5194/egusphere-2024-3677, https://doi.org/10.5194/egusphere-2024-3677, 2025
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We implement a real-time subgrid-scale aerosol-cloud interaction (ACI) mechanism in a mesoscale atmospheric chemistry system and find that subgrid-scale ACI can improve meteorological factors predictions. This study demonstrates the importance of real-time subgrid-scale ACI to weather forecast and the necessity of multiscale ACI studies.
Kevin Wolf, Nicolas Bellouin, Olivier Boucher, Susanne Rohs, and Yun Li
Atmos. Chem. Phys., 25, 157–181, https://doi.org/10.5194/acp-25-157-2025, https://doi.org/10.5194/acp-25-157-2025, 2025
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ERA5 atmospheric reanalysis and airborne in situ observations from IAGOS are compared in terms of the representation of the contrail formation potential and the presence of supersaturation. Differences are traced back to biases in ERA5 relative humidity fields. Those biases are addressed by applying a quantile mapping technique that significantly improved contrail estimation based on post-processed ERA5 data.
Marje Prank, Juha Tonttila, Xiaoxia Shang, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 25, 183–197, https://doi.org/10.5194/acp-25-183-2025, https://doi.org/10.5194/acp-25-183-2025, 2025
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Large primary bioparticles such as pollen can be abundant in the atmosphere. In humid conditions pollen can rupture and release a large number of fine sub-pollen particles (SPPs). The paper investigates what kind of birch pollen concentrations are needed for the pollen and SPPs to start playing a noticeable role in cloud processes and alter precipitation formation. In the studied cases only the largest observed pollen concentrations were able to noticeably alter the precipitation formation.
Luís Filipe Escusa dos Santos, Hannah C. Frostenberg, Alejandro Baró Pérez, Annica M. L. Ekman, Luisa Ickes, and Erik S. Thomson
Atmos. Chem. Phys., 25, 119–142, https://doi.org/10.5194/acp-25-119-2025, https://doi.org/10.5194/acp-25-119-2025, 2025
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The Arctic is experiencing enhanced surface warming. The observed decline in Arctic sea-ice extent is projected to lead to an increase in Arctic shipping activity, which may lead to further climatic feedbacks. Using an atmospheric model and results from marine engine experiments that focused on fuel sulfur content reduction and exhaust wet scrubbing, we investigate how ship exhaust particles influence the properties of Arctic clouds. Implications for radiative surface processes are discussed.
Nadja Omanovic, Brigitta Goger, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 14145–14175, https://doi.org/10.5194/acp-24-14145-2024, https://doi.org/10.5194/acp-24-14145-2024, 2024
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We evaluated the numerical weather model ICON in two horizontal resolutions with two bulk microphysics schemes over hilly and complex terrain in Switzerland and Austria, respectively. We focused on the model's ability to simulate mid-level clouds in summer and winter. By combining observational data from two different field campaigns, we show that an increase in the horizontal resolution and a more advanced cloud microphysics scheme is strongly beneficial for cloud representation.
Cornelis Schwenk and Annette Miltenberger
Atmos. Chem. Phys., 24, 14073–14099, https://doi.org/10.5194/acp-24-14073-2024, https://doi.org/10.5194/acp-24-14073-2024, 2024
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Warm conveyor belts (WCBs) transport moisture into the upper atmosphere, where it acts as a greenhouse gas. This transport is not well understood, and the role of rapidly rising air is unclear. We simulate a WCB and look at fast- and slow-rising air to see how moisture is (differently) transported. We find that for fast-ascending air more ice particles reach higher into the atmosphere and that frozen cloud particles are removed differently than during slow ascent, which has more water vapour.
Fabian Hoffmann, Yao-Sheng Chen, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-3893, https://doi.org/10.5194/egusphere-2024-3893, 2024
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Clouds reflect a substantial portion of the incoming solar radiation back into space. This capacity is determined by the number of cloud droplets, which in turn is influenced by the number of aerosol particles, forming the basis for aerosol-cloud-climate interactions. In this study, we use a simple mixed-layer approach to understand the effect of aerosol on cloud water in non-precipitating stratocumulus.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Anthony Jones, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, Noah Asch, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3376, https://doi.org/10.5194/egusphere-2024-3376, 2024
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We study aerosol-fog interactions near Paris using a weather and climate model with high spatial resolution. We show that our model can simulate fog lifecycle effectively. We find that the fog droplet number concentrations, the amount of liquid water in the fog, and the vertical structure of the fog are highly sensitive to the parameterization that simulates droplet formation and growth. The changes we propose could improve fog forecasts significantly without increasing computational costs.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3397, https://doi.org/10.5194/egusphere-2024-3397, 2024
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We study the lifecycle of fog events in Europe using a weather and climate model. By incorporating droplet formation and growth driven by radiative cooling, our model better simulates the total liquid water in foggy atmospheric columns. We show that both adiabatic and radiative cooling play significant, often equally important roles in driving droplet formation and growth. We discuss strategies to address droplet number overpredictions, by improving model physics and addressing model artifacts.
Jing Yang, Jiaojiao Li, Meilian Chen, Xiaoqin Jing, Yan Yin, Bart Geerts, Zhien Wang, Yubao Liu, Baojun Chen, Shaofeng Hua, Hao Hu, Xiaobo Dong, Ping Tian, Qian Chen, and Yang Gao
Atmos. Chem. Phys., 24, 13833–13848, https://doi.org/10.5194/acp-24-13833-2024, https://doi.org/10.5194/acp-24-13833-2024, 2024
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Detecting unambiguous signatures is vital for examining cloud-seeding impacts, but often, seeding signatures are immersed in natural variability. In this study, reflectivity changes induced by glaciogenic seeding using different AgI concentrations are investigated under various conditions, and a method is developed to estimate the AgI concentration needed to detect unambiguous seeding signatures. The results aid in operational seeding-based decision-making regarding the amount of AgI dispersed.
Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig
Atmos. Chem. Phys., 24, 13751–13768, https://doi.org/10.5194/acp-24-13751-2024, https://doi.org/10.5194/acp-24-13751-2024, 2024
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We use a regional climate model, COSMO-CLM², enhanced with a module resolving aerosol processes, to study Antarctic clouds. We prescribe different concentrations of ice-nucleating particles to our model to assess how these clouds respond to concentration changes, validating results with cloud and aerosol observations from the Princess Elisabeth Antarctica station. Our results show that aerosol–cloud interactions vary with temperature, providing valuable insights into Antarctic cloud dynamics.
Yi Li, Xiaoli Liu, and Hengjia Cai
Atmos. Chem. Phys., 24, 13525–13540, https://doi.org/10.5194/acp-24-13525-2024, https://doi.org/10.5194/acp-24-13525-2024, 2024
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The influence of different aerosol modes on cloud processes remains controversial. We modified the aerosol spectra and concentrations to simulate a warm stratiform cloud process in Jiangxi, China, using the WRF-SBM scheme. Research shows that different aerosol spectra have diverse effects on cloud droplet spectra, cloud development, and the correlation between dispersion (ε) and cloud physics quantities. Compared to cloud droplet concentration, ε is more sensitive to the volume radius.
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024, https://doi.org/10.5194/acp-24-13403-2024, 2024
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Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying the foundation for so-called aerosol–cloud–climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024, https://doi.org/10.5194/acp-24-12793-2024, 2024
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Clouds play a crucial role in the Earth's energy balance, as they can either warm up or cool down the area they cover depending on their height and depth. They are expected to alter their behaviour under climate change, affecting the warming generated by greenhouse gases. This paper proposes a new method to estimate their overall effect on this warming by simulating a climate where clouds are transparent. Results show that with the model used, clouds have a stabilising effect on climate.
Tao Shi, Yuanjian Yang, Ping Qi, and Simone Lolli
Atmos. Chem. Phys., 24, 12807–12822, https://doi.org/10.5194/acp-24-12807-2024, https://doi.org/10.5194/acp-24-12807-2024, 2024
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This paper explored the formation mechanisms of the amplified canopy urban heat island intensity (ΔCUHII) during heat wave (HW) periods in the megacity of Beijing from the perspectives of mountain–valley breeze and urban morphology. During the mountain breeze phase, high-rise buildings with lower sky view factors (SVFs) had a pronounced effect on the ΔCUHII. During the valley breeze phase, high-rise buildings exerted a dual influence on the ΔCUHII.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
Atmos. Chem. Phys., 24, 12661–12685, https://doi.org/10.5194/acp-24-12661-2024, https://doi.org/10.5194/acp-24-12661-2024, 2024
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Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's surface. It plays an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3423, https://doi.org/10.5194/egusphere-2024-3423, 2024
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Numerical modeling simulations are used to investigate ice crystal growth and decay processes within a banded region of enhanced precipitation rates during a prominent winter storm. We identify robust primary ice growth in the upper portion of the cloud but decay exceeding 70 % during fallout through a subsaturated layer. The ice fall characteristics and decay rate are sensitive to the ambient cloud properties which has implications for radar-based measurements and precipitation accumulations.
Charlotte Lange and Johannes Quaas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3229, https://doi.org/10.5194/egusphere-2024-3229, 2024
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We studied how the Earth’s climate system adjusts to sudden changes in the energy budget, by analyzing data of four climate models, which simulated a 4 % reduction of incoming solar energy. We found rapid cooling of the atmosphere and shifts in cloud cover and atmospheric circulation patterns like land-sea-circulation. Our research helps to better understand cloud adjustments, which are a main source of uncertainty in climate models. This can improve future climate predictions.
Ehsan Erfani, Robert Wood, Peter Blossey, Sarah J. Doherty, and Ryan Eastman
EGUsphere, https://doi.org/10.5194/egusphere-2024-3232, https://doi.org/10.5194/egusphere-2024-3232, 2024
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In this study, we explore how marine clouds interact with aerosols. We introduce a novel approach to identify a reduced number of representative cases from a wide array of observed environmental conditions prevalent in the Northeast Pacific. We created over 2200 trajectories from observations and used cloud-resolving simulations to investigate how marine low clouds evolve in two different cases. It is shown that aerosols can delay cloud breakup, but their impact depends on precipitation.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
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The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Puja Roy, Robert M. Rauber, and Larry Di Girolamo
Atmos. Chem. Phys., 24, 11653–11678, https://doi.org/10.5194/acp-24-11653-2024, https://doi.org/10.5194/acp-24-11653-2024, 2024
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Cloud droplet temperature and lifetime impact cloud microphysical processes such as the activation of ice-nucleating particles. We investigate the thermal and radial evolution of supercooled cloud droplets and their surrounding environments with an aim to better understand observed enhanced ice formation at supercooled cloud edges. This analysis shows that the magnitude of droplet cooling during evaporation is greater than estimated from past studies, especially for drier environments.
Mathieu Lachapelle, Mélissa Cholette, and Julie M. Thériault
Atmos. Chem. Phys., 24, 11285–11304, https://doi.org/10.5194/acp-24-11285-2024, https://doi.org/10.5194/acp-24-11285-2024, 2024
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Hazardous precipitation types such as ice pellets and freezing rain are difficult to predict because they are associated with complex microphysical processes. Using Predicted Particle Properties (P3), this work shows that secondary ice production processes increase the amount of ice pellets simulated while decreasing the amount of freezing rain. Moreover, the properties of the simulated precipitation compare well with those that were measured.
Andrew DeLaFrance, Lynn A. McMurdie, Angela K. Rowe, and Andrew J. Heymsfield
Atmos. Chem. Phys., 24, 11191–11206, https://doi.org/10.5194/acp-24-11191-2024, https://doi.org/10.5194/acp-24-11191-2024, 2024
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Using a numerical model, the process whereby falling ice crystals accumulate supercooled liquid water droplets is investigated to elucidate its effects on radar-based measurements and surface precipitation. We demonstrate that this process accounted for 55% of the precipitation during a wintertime storm and is uniquely discernable from other ice crystal growth processes in Doppler velocity measurements. These results have implications for measurements from airborne and spaceborne platforms.
Gabriella Wallentin, Annika Oertel, Luisa Ickes, Peggy Achtert, Matthias Tesche, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2024-2988, https://doi.org/10.5194/egusphere-2024-2988, 2024
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Multilayer clouds are common in the Arctic but remain understudied. We use an atmospheric model to simulate multilayer cloud cases from the Arctic expedition MOSAiC 2019/2020. We find that it is complex to accurately model these cloud layers due to the lack of correct temperature and humidity profiles. The model also struggles to capture the observed cloud phase, the relative concentration of cloud droplets and cloud ice. We constrain our model to measured aerosols to mitigate this issue.
Cited articles
Andreas, E. L, Horst, T. W., Grachev, A. A., Persson, P. O. G., Fairall, C. W., Guest, P. S., and Jordan, R. E.: Parametrizing turbulent exchange over summer sea ice and the marginal ice zone, Q. J. Roy. Meteor. Soc., 136, 927–943, https://doi.org/10.1002/qj.618, 2010.
Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A. J., and Xiao, Q.-N.: A
three-dimensional (3DVAR) data assimilation system for use with MM5:
Implementation and initial results, Mon. Weather Rev., 132, 897–914,
https://doi.org/10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2, 2004.
Barlage, M., Chen, F., Tewari, M., Ikeda, K., Gochis, D., Dudhia, J.,
Rasmussen, R., Livneh, B., Ek, M., and Mitchell, K.: Noah land model
modifications to improve snowpack prediction in the Colorado Rocky
Mountains, J. Geophys. Res., 115, D22101, https://doi.org/10.1029/2009JD013470, 2010.
Bracegirdle, T. J. and Marshal, G. J.: The reliability of Antarctic tropospheric pressure and temperature in the latest global reanalyses, J. Climate, 25, 7138–7146, https://doi.org/10.1175/JCLI-D-11-00685.1, 2012.
Bromwich, D. H., Hines, K. M., and Bai, L. S.: Development and testing of Polar WRF: 2. Arctic Ocean, J. Geophys. Res., 114, D08122,
https://doi.org/10.1029/2008JD010300, 2009.
Bromwich, D. H., Nicolas, J. P., Hines, K. M., Kay, J. E., Key, E., Lazzara,
M. A., Lubin, D., McFarquhar, G. M., Gorodetskaya, I., Grosvenor, D. P.,
Lachlan-Cope, T. A., and van Lipzig, N.: Tropospheric clouds in Antarctica, Rev. Geophys., 50, RG1004, https://doi.org/10.1029/2011RG000363, 2012.
Bromwich, D. H., Nicolas, J. P., Monaghan, A. J., Lazzara, M. A., Keller, L. M., Weidner, G. A., and Wilson, A. B.: Central West Antarctica among the most
rapidly warming regions on Earth, Nat. Geosci., 6, 139–145,
https://doi.org/10.1038/ngeo1671, 2013a.
Bromwich, D. H., Otieno, F. O., Hines, K., Manning, K., and Shilo, E.: Comprehensive evaluation of polar weather research and forecasting
performance in the Antarctic, J. Geophys. Res., 118, 274–292,
https://doi.org/10.1029/2012JD018139, 2013b.
Bromwich, D. H., Nicolas, J. P., Monaghan, A. J., Lazzara, M. A., Keller, L. M., Weidner, G. A., and Wilson, A. B.: Corrigendum: Central West Antarctica among the most rapidly warming regions on Earth, Nat. Geosci., 7, 76,
https://doi.org/10.1038/ngeo2016, 2014.
Cadeddu, M.: G-Band Vapor Radiometer Profiler (GVRP) Handbook,
Office of Science, DOE Office of Biological and
Environmental Research, USA, DOE/SC-ARM/TR-091, https://doi.org/10.2172/982364, 2010.
Cadeddu, M. P., Turner, D. D., and Liljegren, J. C.: A Neural Network for Real-Time Retrievals of PWV and LWP From Arctic Millimeter-Wave Ground-Based
Observations, IEEE T. Geosci. Remote, 47,
1887–1900, https://doi.org/10.1109/TGRS.2009.2013205, 2009.
Cassano, J. J., DuViviera, A., Roberts, A., Hughes, M., Seefeldt, M., Brunke,
M., Craig, A., Fisel, B., Gutowski, W., Hamman, J., Higgins, M., Maslowski,
W., Nijssen, B., Osinski, R., and Zeng, X.: Development of the Regional Arctic System Model (RASM): Near surface atmospheric climate sensitivity, J.
Climate, 30, 5729–5753, https://doi.org/10.1175/JCLI-D-15-0775.1, 2017.
Chou, M. D., Suarez, M. J., Liang, X. Z., and Yan, M. M. H.: A thermal infrared radiation parameterization for atmospheric studies, NASA/TM-2001-104606, 19, 56 pp., 2001.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: A summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005.
Cook, D.: ARM: Surface Energy Balance System (SEBS) Handbook, Atmospheric
Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory, Argonne,
IL, 2018.
Cooper, W. A.: Ice initiation in natural clouds, Precipitation
Enhancement – A Scientific Challenge, Meteorol. Mon., 29–32, 1986.
Deb, P., Orr, A., Hosking, J. S., Phillips, T., Turner, J., Bannister, D.,
Pope, J. O., and Colwell, S.: An assessment of the Polar Weather Research and
Forecasting (WRF) model representation of near-surface meteorological
variables over West Antarctica, J. Geophys. Res., 121, 1532–1548,
https://doi.org/10.1002/2015jd024037, 2016.
DeConto, R.M., Pollard, D.: Contributions of Antarctica to past and future
sea level rise, Nature, 531, 591–597, https://doi.org/10.1038/nature17145, 2016.
Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach,
H., Holm, E.V., Isaksen, L.,i Kalberg, P., Kohler, M., Matricardi, M.,
McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-J., Park, B.-K., Peubey, C.,
de Rosnay, P., Tavolato, C., Thepaut, J.-N., Vitart, F.: The ERA-Interim
reanalysis: Configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Dooraghi, M., Reda, I., Xie, Y., Morris, V., Andreas, A., Kutchenreiter, M.,
Habte, A., and Sengupta, M.: ARM: Sky Radiation Sensor: 60-Second Downwelling
Irradiances (Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), https://doi.org/10.5439/1025281, 1996.
Flynn, C. J., Mendoza, A., Zheng, Y., and Mathurb, S.: Novel
polarization-sensitive micropulse lidar measurement technique, Opt. Express, 15, 2785–2790, https://doi.org/10.1364/OE.15.002785, 2007.
Fogt, R. L. and Bromwich, D. H.: Atmospheric moisture and cloud cover
characteristics forecast by AMPS, Weather Forecast., 23, 914–930,
https://doi.org/10.1175/2008/WAF2006100.1, 2008.
Grosvenor, D. P., Choularton, T. W., Lachlan-Cope, T., Gallagher, M. W., Crosier, J., Bower, K. N., Ladkin, R. S., and Dorsey, J. R.: In-situ aircraft observations of ice concentrations within clouds over the Antarctic Peninsula and Larsen Ice Shelf, Atmos. Chem. Phys., 12, 11275–11294, https://doi.org/10.5194/acp-12-11275-2012, 2012.
Hines, K. M. and Bromwich, D. H.: Development and testing of Polar Weather Research and Forecasting (WRF) model. Part I: Greenland Ice Sheet meteorology, Mon. Weather Rev., 136, 1971–1989, https://doi.org/10.1175/2007MWR2112.1,
2008.
Hines, K. M. and Bromwich, D. H.: Simulation of late summer Arctic clouds during ASCOS with Polar WRF, Mon. Weather Rev., 145, 521–541, https://doi.org/10.1175/MWR-D-16-0079.1, 2017.
Hines, K. M., Bromwich, D. H., Bai, L.-S., Barlage, M., and Slater, A. S.: Development and testing of polar Weather Research and Forecasting Model: Part III. Arctic land, J. Climate, 24, 26–48, https://doi.org/10.1175/2010JCLI3460.1, 2011.
Hines, K. M., Bromwich, D. H., Bai, L., Bitz, C. M., Powers, J. G., and Manning,
K. W.: Sea ice enhancements to Polar WRF, Mon. Weather Rev., 143, 2363–2385, https://doi.org/10.1175/MWR-D-14-00344.1, 2015.
Hogan, A. W.: Aerosol exchange in the remote troposphere, Tellus, 38, 197–213, 1986.
Holdridge, D. and Kyrouac, J.: ARM: ARM-Standard Meteorological Instrumentation at Surface (Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), https://doi.org/10.5439/1025220, 1993.
Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A revised approach to ice
microphysical processes for the bulk parameterization of clouds and
precipitation, Mon. Weather Rev., 132, 103–120,
https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2,
2004.
Janjć, Z. I.: The step-mountain Eta coordinate model: Further
developments of the convection, viscous sublayer, and turbulence closure
schemes, Mon. Weather Rev., 122, 927–945,
https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2,
1994.
Kain, J. S.: The Kain–Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170–181,
https://doi.org/10.1175/1520-0450(2004)04360;0170:tkcpau62;2.0.co;2, 2004.
Kato, S., Rose F. G., Sun-Mack S., Miller W. F., Chen Y., Rutan D. A., Stephens G. L., Loeb N. G., Minnis P., Wielicki B. A., Winker D. M., Charlock T. P., Stackhouse P. W., Xu K.-M., and Collins W.: Computation of top-of-atmosphere and
surface irradiances with CALIPSO, CloudSat, and MODIS-derived cloud and aerosol properties. J. Geophys. Res., 116, D19209. https://doi.org/10.1029/2011JD016050, 2011.
King J. C., Gadian, A., Kirchgaessner, A., Kuipers, Munneke, P.,
Lachlan-Cope, T. A., Orr, A., Reijmer, C., van den Broeke, M. R., van Wessem, J. M., and Weeks, M.: Validation of the summertime surface energy budget of Larsen C Ice Shelf (Antarctica) as represented in three high-resolution atmospheric models, J. Geophys. Res., 120, 1335–1347,
https://doi.org/10.1002/2014JD022604, 2015.
Klein, S. A., McCoy, R. B., Morrison, H., Ackerman, A. S., Avramov, A., de
Boer, G. Chen, M., Cole, J. N. S., Del Genio, A., Falk, M., Foster, M. J.,
Fridlind, A. M., Golaz, J.-C., Hashino, T., Harrington, J. Y., Hoose, C.,
Khairoutdinov, M., Larson, V. E., Liu, X., Luo, Y., McFarquhar, G., Menon,
S., Neggers, R. A. J., Park, S., Poellot, M., Schmidt, J. M., Sednev, I.,
Shipway, B. J., Shupe, M. D., Spangenberg, D., Sud, Y. C., Turner, D. D., Veron, D. E., von Salzen, K., Walker, G., Wang, Z., Wolf, A.B., Xie, S., Xu, K., Yang, F., and Zhang G.: Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single-layer cloud, Q. J. Roy. Meteor. Soc., 135, 979–1002, https://doi.org/10.1002/qj.416, 2009.
Lachlan-Cope, T., Listowski, C., and O'Shea, S.: The microphysics of clouds over the Antarctic Peninsula – Part 1: Observations, Atmos. Chem. Phys., 16, 15605–15617, https://doi.org/10.5194/acp-16-15605-2016, 2016.
Lazzara, M. A., Weidner, G. A., Keller, L. M., Thom, J. E., and Cassano, J. J.: Antarctic Automatic Weather Station Program: 30 years of polar observations, B. Am. Meteorol. Soc., 93, 1519–1537, https://doi.org/10.1175/BAMS-D-11-00015.1, 2012.
Listowski, C. and Lachlan-Cope, T.: The microphysics of clouds over the Antarctic Peninsula – Part 2: modelling aspects within Polar WRF, Atmos. Chem. Phys., 17, 10195–10221, https://doi.org/10.5194/acp-17-10195-2017, 2017.
Lubin, D., Chen, B., Bromwich, D. H., Somerville, R. C. J., Lee, W.-H., and Hines, K. M.: The impact of Antarctic cloud radiative properties on a GCM climate simulation, J. Climate, 11, 447–462, https://doi.org/10.1175/1520-0442(1998)0112.0, 1998.
Mather, J. H. and Voyles, J. W.: The ARM climate research facility: A review of structure and capabilities, B. Am. Meteorol. Soc., 94, 377–392,
https://doi.org/10.1175/BAMS-D-11-00218.1, 2013.
McCoy, D. T., Hartmann, D. L., Zelinka, M. D., Ceppi, P., and Grosvenor, D. P.: Mixed-phase cloud physics and Southern Ocean cloud feedback in climate
models, J. Geophys. Res., 120, 9539–9554, https://doi.org/10.1002/2015JD023603, 2015.
Milbrandt, J. A. and Morrison, H.: Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part III: Introduction of multiple free categories, J. Atmos. Sci., 73, 975–995,
https://doi.org/10.1175/JAS-D-15-0204.1, 2016.
Milbrandt, J. A. and Yau, M. K.: A multimoment bulk microphysics
parameterization. Part II: A proposed three-moment closure and scheme
description, J. Atmos. Sci., 62, 3065–3081, https://doi.org/10.1175/JAS3535.1, 2005.
Morris, V. R.: Microwave radiometer (MWR) handbook, ARM-TR-016, DOE Office of Science, Office of Biological and Environmental Research, 20 pp.,
https://doi.org/10.2172/1020715, 2006.
Morrison, H. and Milbrandt, J. A.: Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: Scheme
description and idealized tests, J. Atmos. Sci., 72, 287–311,
https://doi.org/10.1175/JAS-D-14-0065.1, 2015.
Morrison, H. and Pinto, J. O.: Intercomparison of bulk cloud microphysics
schemes in mesoscale simulations of springtime Arctic mixed-phase stratiform
clouds, Mon. Weather Rev., 134, 1880–1990, 2006.
Morrison, H., Curry, J. A., and Khvorostyanov, V. I.: A new double-moment
microphysics scheme for application in cloud and climate models. Part I:
Description, J. Atmos. Sci., 62, 1665–1677, https://doi.org/10.1175/JAS3446.1, 2005.
Morrison, H., Pinto, J. O., Curry, J. A., and McFarquhar, G. M.: Sensitivity of modeled Arctic mixed-phase stratocumulus to cloud condensation and ice
nuclei over regionally varying surface conditions, J. Geophys. Res., 113,
D05203, https://doi.org/10.1029/2007JD008729, 2008.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall
line: Comparison of one- and two-moment schemes, Mon. Weather Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
Nakanishi, M. and Niino, H.: An improved Mellor-Yamada level-3 model: Its
numerical stability and application to a regional prediction of advection
fog, Bound.-Lay. Meteorol., 119, 397–407, https://doi.org/10.1007/s10546-005-9030-8,
2006.
NCAR Mesoscale and Microscale Meteorology: The Weather Research and Forecasting model, available at: https://www.mmm.ucar.edu/weather-research-and-forecasting-model, last accessed 7 August 2019.
Nicolas, J. P. and Bromwich, D. H.: Climate of West Antarctica and influence of marine air intrusions, J. Climate, 24, 49–67, https://doi.org/10.1175/2010JCLI3322.1, 2011.
Nicolas, J. P. and Bromwich, D. H.: New reconstruction of Antarctic near-surface temperatures: Multidecadal trends and reliability of global reanalyses, J. Climate, 27, 8070–8093, https://doi.org/10.1175/JCLI-D-13-00733.1, 2014.
Nicolas, J. P, Scott, R. C., Cadeddu, M. P., Bromwich, D. H., Verlinde, J.,
Lubin, D., Russell, L. M., Jenkinson, C., Powers, H. H., Ryczek, M., Stone,
G., and Wille, J.: January 2016 extensive summer melt in West Antarctica
favoured by strong El Nino, Nat. Commun., 8, 15799, https://doi.org/10.1038/ncomms15799, 2017.
NOAA Environmental Modeling Center: The GFS Atmospheric Model, NCEP Office
Note 442, 14 pp., available at: https://www.emc.ncep.noaa.gov/officenotes/newernotes/on442.pdf (last access: 27 September 2019), 2003.
O'Shea, S. J., Choularton, T. W., Flynn, M., Bower, K. N., Gallagher, M., Crosier, J., Williams, P., Crawford, I., Fleming, Z. L., Listowski, C., Kirchgaessner, A., Ladkin, R. S., and Lachlan-Cope, T.: In situ measurements of cloud microphysics and aerosol over coastal Antarctica during the MAC campaign, Atmos. Chem. Phys., 17, 13049–13070, https://doi.org/10.5194/acp-17-13049-2017, 2017.
Pavolonis, M. and Key, J.: Antarctic cloud radiative forcing at the surface
estimated from the AVHRR Polar Pathfinder and ISCCP D1 datasets, 1985–93, J.
Appl. Meteorol., 42, 827–840, https://doi.org/10.1175/1520-0450(2003)042<0827:ACRFAT>2.0.CO;2, 2003.
Polar Meteorology Group: AMPS database, available at: http://polarmet.osu.edu/AMPS/, last access: 29 September 2017.
Polar Meteorology Group: The Polar WRF model, available at: http://polarmet.osu.edu/PWRF/registration.php, last access: 7 August 2019.
Pon, K.: The representation of low cloud in the Antarctic Mesoscale
Prediction System, MS thesis, Atmospheric Sciences Program, Dept. of
Geography, The Ohio State University, 80 pp., 2015.
Powers, J. G., Manning, K. W., Bromwich, D. H., Cassano, J. J., and Cayette, A. M.: A decade of Antarctic science support through AMPS, B. Am. Meteorol. Soc., 93, 1699–1712, https://doi.org/10.1175/BAMS-D-11-00186.1, 2012.
Rignot, E.: Changes in West Antarctic ice stream dynamics observed with ALOS
PALSAR data, Geophys. Res. Lett., 35, L12505, https://doi.org/10.1029/2008GL033365,
2008.
Schmeisser, L., Backman, J., Ogren, J. A., Andrews, E., Asmi, E., Starkweather, S., Uttal, T., Fiebig, M., Sharma, S., Eleftheriadis, K., Vratolis, S., Bergin, M., Tunved, P., and Jefferson, A.: Seasonality of aerosol optical properties in the Arctic, Atmos. Chem. Phys., 18, 11599–11622, https://doi.org/10.5194/acp-18-11599-2018, 2018.
Scott, R. C. and Lubin, D.: Unique manifestations of mixed-phase cloud
microphysics over Ross Island and the Ross Ice Shelf, Antarctica, Geophys.
Res. Lett., 43, 2936–2945, https://doi.org/10.1002/2013JD021132, 2016.
Scott, R. C., Lubin, D., Vogelmann, A. M., and Kato, S.: West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites, J. Climate, 30, 6151–6170, https://doi.org/10.1175/JCLI-D-16-0644.1, 2017.
Shupe, M. and Intrieri, J.: Cloud radiative forcing of the Arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle, J.
Climate, 17, 616–628, https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2, 2004.
Shupe, M. D.: Clouds at Arctic atmospheric observatories. Part II:
Thermodynamic phase characteristics, J. Appl. Meteorol. Clim., 50, 645–661,
https://doi.org/10.1175/2010JAMC2468.1, 2011.
Silber, I., Verlinde, J., Eloranta, E. W., and Cadeddu, M.: Antarctic cloud
macrophysical, thermodynamic phase, and atmospheric inversion coupling
properties at McMurdo Station: I. Principal data processing and climatology,
J. Geophys. Res., 123, 6099–6121, https://doi.org/10.1029/2018JD028279, 2018a.
Silber, I., Verlinde, J., Eloranta, E. W., Flynn, C. J., and Flynn, D. M.:
Reprocessed MPL data sets, https://doi.org/10.5439/1468777, 2018b.
Silber, I., Verlinde, J., Eloranta, E. W., Flynn, C. J., and Flynn, D. M.: Polar liquid cloud base detection algorithms for high spectral resolution or
micropulse lidar data, J. Geophys. Res.-Atmos., 123, 4310–4322, https://doi.org/10.1029/2017JD027840, 2018c.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X.-Y., Wang, W., and Powers, J. G: A description of the Advanced Research WRF Version 3, NCAR Tech, Note NCAR/TN-475+STR, 125 pp., 2008.
Slingo, J. M.: The development and verification of a cloud prediction scheme
for the ECMWF model, Q. J. Roy. Meteor. Soc., 113, 899–927,
https://doi.org/10.1002/qj.49711347710, 1987.
Solomon, A., Shupe, M. D., Persson, P. O. G., and Morrison, H.: Moisture and dynamical interactions maintaining decoupled Arctic mixed-phase stratocumulus in the presence of a humidity inversion, Atmos. Chem. Phys., 11, 10127–10148, https://doi.org/10.5194/acp-11-10127-2011, 2011.
Solomon, A., Shupe, M. D., Persson, O., Morrison, H., Yamaguchi, T.,
Caldwell, P. M., and de Boer, G.: The sensitivity of springtime Arctic
mixed-phase stratocumulus clouds to surface-layer and cloud-top
inversion-layer moisture sources, J. Atmos. Sci., 71, 574–595,
https://doi.org/10.1175/JAS-D-13-0179, 2014.
Solomon, A., Feingold, G., and Shupe, M. D.: The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus, Atmos. Chem. Phys., 15, 10631–10643, https://doi.org/10.5194/acp-15-10631-2015, 2015.
Steig, E. J. Schneider, D. P., Rutherford, S. D., Mann, M. E., Comiso, J. C., and Shindell, D. T.: Warming of the Antarctic ice-sheet surface since the 1957 International Geophysical Year, Nature, 457, 459–462,
https://doi.org/10.1038/nature07669, 2009.
Thompson, G., and Eidhammer, T.: A study of aerosol impacts on clouds and
precipitation development in a large winter cyclone, J. Atmos. Sci., 71,
3636–3658, https://doi.org/10.1175/JAS-D-13-0305.1, 2014.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization, Mon. Weather Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1, 2008.
Tjernström, M., Leck, C., Birch, C. E., Bottenheim, J. W., Brooks, B. J., Brooks, I. M., Bäcklin, L., Chang, R. Y.-W., de Leeuw, G., Di Liberto, L., de la Rosa, S., Granath, E., Graus, M., Hansel, A., Heintzenberg, J., Held, A., Hind, A., Johnston, P., Knulst, J., Martin, M., Matrai, P. A., Mauritsen, T., Müller, M., Norris, S. J., Orellana, M. V., Orsini, D. A., Paatero, J., Persson, P. O. G., Gao, Q., Rauschenberg, C., Ristovski, Z., Sedlar, J., Shupe, M. D., Sierau, B., Sirevaag, A., Sjogren, S., Stetzer, O., Swietlicki, E., Szczodrak, M., Vaattovaara, P., Wahlberg, N., Westberg, M., and Wheeler, C. R.: The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design, Atmos. Chem. Phys., 14, 2823–2869, https://doi.org/10.5194/acp-14-2823-2014, 2014.
Turner, J., Lachlan-Cope, T. A., Colwell, S., Marshall, G. J., and Connolley,
W. M.: Significant warming of the Antarctic winter troposphere, Science,
311, 1914–1917, https://doi.org/10.1126/science.1121652, 2006.
van Tricht K., Lhermitte, S., Lenaerts, J. T. M., Gorodetskaya, I. V.,
L'Ecuyer, T. S., Noah, B., van den Broeke, R., Turner D. D., and van Lipzig,
N. P. M.: Clouds enhance Greenland ice sheet meltwater runoff, Nat. Commun.,
7, 10266, https://doi.org/10.1038/ncomms10266, 2016.
Wagenbach, D., Gorlach, U., Moser, K., and Munnich, K. O.: Coastal Antarctic
aerosol: the seasonal pattern of its chemical composition and radionuclide
content, Tellus B, 40, 426–436, 1988.
Wille, J. D., Bromwich, D. H., Cassano, J. J., Nigro, M. A., Mateling, M. E., and Lazzara, M. A.: Evaluation of the AMPS boundary layer simulations on the Ross Ice Shelf, Antarctica, with unmanned aircraft observations, J. Appl.
Meteorol. Clim., 56, 2239–2258, https://doi.org/10.1175/JAMC-D-16-0339.1, 2017.
Wilson, A. B., Bromwich, D. H., and Hines, K. M.: Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis, J. Geophys. Res., 116, D11112, https://doi.org/10.1029/2010JD015013, 2011.
Wilson, A. B., Bromwich, D. H., and Hines, K. M.: Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain. Part II. Atmospheric hydrologic cycle, J. Geophys. Res., 117, D04107, https://doi.org/10.1029/2011JD016765, 2012.
Witze, A.: Antarctic clouds studied for first time in five decades, Nature,
529, 12–12, https://doi.org/10.1038/529012a, 2016.
Short summary
We explore how well clouds are represented in numerical weather prediction over Antarctica, a very difficult environment for field programs where few studies have been conducted. Fortunately, a 2015–2017 field program for West Antarctica supplied observations. We achieve promising results with newer, more advanced cloud schemes. We need to understand the role of clouds and precipitation in the maintenance of the Antarctic ice mass to understand and predict sea level change over the 21st century.
We explore how well clouds are represented in numerical weather prediction over Antarctica, a...
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