Articles | Volume 22, issue 11
https://doi.org/10.5194/acp-22-7593-2022
© 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-22-7593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jun 2022
Research article |
| 13 Jun 2022
| 13 Jun 2022
Evaluation of modelled summertime convective storms using polarimetric radar observations
Institute of Geosciences, Meteorology Department, Bonn University, Bonn, Germany
Silke Trömel
Institute of Geosciences, Meteorology Department, Bonn University, Bonn, Germany
Laboratory for Clouds and Precipitation Exploration, Geoverbund ABC/J, Bonn, Germany
Raquel Evaristo
Institute of Geosciences, Meteorology Department, Bonn University, Bonn, Germany
Clemens Simmer
Institute of Geosciences, Meteorology Department, Bonn University, Bonn, Germany
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Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
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The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
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
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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.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
P. Shrestha, M. Sulis, C. Simmer, and S. Kollet
Hydrol. Earth Syst. Sci., 19, 4317–4326, https://doi.org/10.5194/hess-19-4317-2015, https://doi.org/10.5194/hess-19-4317-2015, 2015
Short summary
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This study highlights the grid resolution dependence of energy and water balance of the 3-D physically based integrated surface-groundwater model. The non-local controls of soil moisture were found to be highly grid resolution dependent, but the local vegetation control strongly modulates the scaling behavior of surface energy fluxes. For coupled runs, variability in patterns of surface fluxes due to this scale dependence can affect the simulated atmospheric boundary layer and local circulation.
F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, and S. Kollet
Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, https://doi.org/10.5194/gmd-7-2531-2014, 2014
Velibor Pejcic, Kamil Mroz, Kai Mühlbauer, and Silke Trömel
EGUsphere, https://doi.org/10.5194/egusphere-2025-1414, https://doi.org/10.5194/egusphere-2025-1414, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Estimating the proportions of individual hydrometeor types (hydrometeor partitioning ratios, HPRs) in a mixture of a resolved radar volume and their evaluation is challenging. This study has three objectives, (1) to evaluate HPR retrievals, (2) to exploit the combination of dual-frequency (DF) space-borne radar (SR) and dual-polarisation (DP) ground-based radar (GR) observations for estimating HPRs based on SR DF observations and (3) to further improve HPR estimates based on DP GR observations.
Armin Blanke, Mathias Gergely, and Silke Trömel
Atmos. Chem. Phys., 25, 4167–4184, https://doi.org/10.5194/acp-25-4167-2025, https://doi.org/10.5194/acp-25-4167-2025, 2025
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The area-wide radar-based distinction between riming and aggregation is crucial for model microphysics and data assimilation. This study introduces a discrimination algorithm based on polarimetric radar networks only. Exploiting the unique opportunity to link fall velocities from Doppler spectra to polarimetric variables in an operational setting enables us to set up and evaluate a well-performing machine learning algorithm.
Lucas Reimann, Clemens Simmer, and Silke Trömel
Atmos. Chem. Phys., 23, 14219–14237, https://doi.org/10.5194/acp-23-14219-2023, https://doi.org/10.5194/acp-23-14219-2023, 2023
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Polarimetric radar observations were assimilated for the first time in a convective-scale numerical weather prediction system in Germany and their impact on short-term precipitation forecasts was evaluated. The assimilation was performed using microphysical retrievals of liquid and ice water content and yielded slightly improved deterministic 9 h precipitation forecasts for three intense summer precipitation cases with respect to the assimilation of radar reflectivity alone.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
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We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
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On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
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The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
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
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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.
Shaoning Lv, Clemens Simmer, Yijian Zeng, Jun Wen, Yuanyuan Guo, and Zhongbo Su
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-369, https://doi.org/10.5194/tc-2021-369, 2022
Preprint withdrawn
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The freeze-thaw of the ground is an interesting topic to climatology, hydrology, and other earth sciences. The global freeze-thaw distribution is available by passive microwave remote sensing technique. However, the remote sensing technique indirectly detects freeze-thaw states by measuring the brightness temperature difference between frozen and unfrozen soil. Thus, we present different interprets of the brightness signals to the FT-state by using its sub-daily character.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Shaoning Lv, Bernd Schalge, Pablo Saavedra Garfias, and Clemens Simmer
Hydrol. Earth Syst. Sci., 24, 1957–1973, https://doi.org/10.5194/hess-24-1957-2020, https://doi.org/10.5194/hess-24-1957-2020, 2020
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Passive remote sensing of soil moisture has good potential to improve weather forecasting via data assimilation in theory. We use the virtual reality data set (VR01) to infer the impact of sampling density on soil moisture ground cal/val activity. It shows how the sampling error is growing with an increasing sampling distance for a SMOS–SMAP scale footprint in about 40 km, 9 km, and 3 km. The conclusion will help in understanding the passive remote sensing soil moisture products.
José Dias Neto, Stefan Kneifel, Davide Ori, Silke Trömel, Jan Handwerker, Birger Bohn, Normen Hermes, Kai Mühlbauer, Martin Lenefer, and Clemens Simmer
Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, https://doi.org/10.5194/essd-11-845-2019, 2019
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This study describes a 2-month dataset of ground-based, vertically pointing triple-frequency cloud radar observations recorded during the winter season 2015/2016 in Jülich, Germany. Intensive quality control has been applied to the unique long-term dataset, which allows the multifrequency signatures of ice and snow particles to be statistically analyzed for the first time. The analysis includes, for example, aggregation and its dependence on cloud temperature, riming, and onset of melting.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
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This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
Christoph Beekmans, Johannes Schneider, Thomas Läbe, Martin Lennefer, Cyrill Stachniss, and Clemens Simmer
Atmos. Chem. Phys., 16, 14231–14248, https://doi.org/10.5194/acp-16-14231-2016, https://doi.org/10.5194/acp-16-14231-2016, 2016
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Sky imager cameras provide a full view of the sky with high spatial and temporal resolution and are used to derive cloud cover, cloud type or cloud-base height, if employed in a stereo configuration.
The application of a dense fisheye stereo method provides dense, consistent and quite complete 3-D cloud boundaries and can be fully automated. We present validation of our approach and cloud examples with high geometric complexity. Applications are radiative closure studies and cloud dynamics.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
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In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Xinxin Xie, Raquel Evaristo, Clemens Simmer, Jan Handwerker, and Silke Trömel
Atmos. Chem. Phys., 16, 7105–7116, https://doi.org/10.5194/acp-16-7105-2016, https://doi.org/10.5194/acp-16-7105-2016, 2016
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This study provides a first analysis of rainfall observations and related microphysical processes during the HOPE campaign, which will benefit future studies on the evaluation and improvement of climate models within the HD(CP)2 framework. The results conveyed in this study confirm that polarimetric radars have the capability to validate weather and climate models with respect to rainfall estimation and the ongoing microphysical processes.
P. Shrestha, M. Sulis, C. Simmer, and S. Kollet
Hydrol. Earth Syst. Sci., 19, 4317–4326, https://doi.org/10.5194/hess-19-4317-2015, https://doi.org/10.5194/hess-19-4317-2015, 2015
Short summary
Short summary
This study highlights the grid resolution dependence of energy and water balance of the 3-D physically based integrated surface-groundwater model. The non-local controls of soil moisture were found to be highly grid resolution dependent, but the local vegetation control strongly modulates the scaling behavior of surface energy fluxes. For coupled runs, variability in patterns of surface fluxes due to this scale dependence can affect the simulated atmospheric boundary layer and local circulation.
F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, and S. Kollet
Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, https://doi.org/10.5194/gmd-7-2531-2014, 2014
Related subject area
Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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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)
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On the Processes Determining the Slope of Cloud-Water Adjustments in Non-Precipitating Stratocumulus
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Cold pools mediate mesoscale adjustments of trade-cumulus fields to changes in cloud-droplet number concentration
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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
Building a comprehensive library of observed Lagrangian trajectories for testing modeled cloud evolution, aerosol-cloud interactions, and marine cloud brightening
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Effect of secondary ice production processes on the simulation of ice pellets using the Predicted Particle Properties microphysics scheme
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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.
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.
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.
Yao-Sheng Chen, Prasanth Prabhakaran, Fabian Hoffmann, Jan Kazil, Takanobu Yamaguchi, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-3891, https://doi.org/10.5194/egusphere-2024-3891, 2024
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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.
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.
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.
Konstantinos Kourtidis, Stavros Stathopoulos, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3314, https://doi.org/10.5194/egusphere-2024-3314, 2024
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The loud sound of thunder will induce mechanical effects on cloud droplets and ice particles, causing changes in their size distribution.
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.
Pouriya Alinaghi, Fredrik Jansson, Daniel A. Blázquez, and Franziska Glassmeier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3501, https://doi.org/10.5194/egusphere-2024-3501, 2024
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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.
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.
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.
Hsiang-He Lee, Xue Zheng, Shaoyue Qiu, and Yuan Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3199, https://doi.org/10.5194/egusphere-2024-3199, 2024
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The study investigates how aerosol-cloud interactions affect warm boundary layer stratiform clouds over the Eastern North Atlantic. High-resolution WRF-Chem simulations reveal that non-rain clouds at the edges of cloud systems are prone to evaporation, leading to an aerosol drying effect and a transition of aerosols back to accumulation mode for future activation. The study emphasizes that this dynamic behavior is often not adequately represented in most previous prescribed-aerosol simulations.
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.
Toshi Matsui, Daniel Hernandez-Deckers, Scott E. Giangrande, Thiago S. Biscaro, Ann Fridlind, and Scott Braun
Atmos. Chem. Phys., 24, 10793–10814, https://doi.org/10.5194/acp-24-10793-2024, https://doi.org/10.5194/acp-24-10793-2024, 2024
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Using computer simulations and real measurements, we discovered that storms over the Amazon were narrower but more intense during the dry periods, producing heavier rain and more ice particles in the clouds. Our research showed that cumulus bubbles played a key role in creating these intense storms. This study can improve the representation of the effect of continental and ocean environments on tropical regions' rainfall patterns in simulations.
Ravi Kumar Reddy Addula, Ingrid de Almeida Ribeiro, Valeria Molinero, and Baron Peters
Atmos. Chem. Phys., 24, 10833–10848, https://doi.org/10.5194/acp-24-10833-2024, https://doi.org/10.5194/acp-24-10833-2024, 2024
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Ice nucleation from supercooled droplets is important in many weather and climate modeling efforts. For experiments where droplets are steadily supercooled from the freezing point, our work combines nucleation theory and survival probability analysis to predict the nucleation spectrum, i.e., droplet freezing probabilities vs. temperature. We use the new framework to extract approximately consistent rate parameters from experiments with different cooling rates and droplet sizes.
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, https://doi.org/10.5194/acp-24-10425-2024, 2024
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Quantifying cloud response to aerosol perturbations presents a major challenge in understanding the human impact on climate. Using a large number of process-resolving simulations of marine stratocumulus, we show that solar heating drives a negative feedback mechanism that buffers the persistent negative trend in cloud water adjustment after sunrise. This finding has implications for the dependence of the cloud cooling effect on the timing of deliberate aerosol perturbations.
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024, https://doi.org/10.5194/acp-24-10245-2024, 2024
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We employ two methods to examine a laboratory experiment on clouds with both ice and liquid phases. The first assumes well-mixed properties; the second resolves the spatial distribution of turbulence and cloud particles. Results show that while the trends in mean properties generally align, when turbulence is resolved, liquid droplets are not fully depleted by ice due to incomplete mixing. This underscores the threshold of ice mass fraction in distinguishing mixed-phase clouds from ice clouds.
Patrick Peter, Sigrun Matthes, Christine Frömming, Patrick Jöckel, Luca Bugliaro, Andreas Giez, Martina Krämer, and Volker Grewe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2142, https://doi.org/10.5194/egusphere-2024-2142, 2024
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Our study examines how temperature and humidity representations influence contrail (-cirrus) formation criteria. Using various model setups, we identified biases that lead to overestimation of contrail formation areas. By comparing simulations with in-flight and satellite observations, we confirmed that humidity threshold choices greatly affect contrail predictions. These findings can help develop strategies for climate-optimized flight routes, potentially reducing aviation's climate effect.
Theresa Kiszler, Davide Ori, and Vera Schemann
Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024, https://doi.org/10.5194/acp-24-10039-2024, 2024
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Microphysical processes impact the phase-partitioning of clouds. In this study we evaluate these processes while focusing on low-level Arctic clouds. To achieve this we used an extensive simulation set in combination with a new diagnostic tool. This study presents our findings on the relevance of these processes and their behaviour under different thermodynamic regimes.
Shuaiqi Tang, Hailong Wang, Xiang-Yu Li, Jingyi Chen, Armin Sorooshian, Xubin Zeng, Ewan Crosbie, Kenneth L. Thornhill, Luke D. Ziemba, and Christiane Voigt
Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024, https://doi.org/10.5194/acp-24-10073-2024, 2024
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We examined marine boundary layer clouds and their interactions with aerosols in the E3SM single-column model (SCM) for a case study. The SCM shows good agreement when simulating the clouds with high-resolution models. It reproduces the relationship between cloud droplet and aerosol particle number concentrations as produced in global models. However, the relationship between cloud liquid water and droplet number concentration is different, warranting further investigation.
Cited articles
Allabakash, S., Lim, S., Chandrasekar, V., Min, K., Choi, J., and Jang, B.:
X-band dual-polarization radar observations of snow growth processes of a
severe winter storm: Case of 12 December 2013 in South Korea, J.
Atmos. Ocean. Tech., 36, 1217–1235, 2019. a
Ashby, S. F. and Falgout, R. D.: A parallel multigrid preconditioned conjugate
gradient algorithm for groundwater flow simulations, Nucl. Sci.
Eng., 124, 145–159, 1996. a
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical
weather prediction, Nature, 525, 47–55, 2015. a
Blahak, U.: Towards a better representation of high density ice particles in a
state-of-the-art two-moment bulk microphysical scheme, in: Proc. 15th Int.
Conf. Clouds and Precip., Cancun, Mexico, 20208, 2008. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and
aerosols, in: Climate change 2013: the physical science basis. Contribution
of Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, 571–657, Cambridge University Press, https://doi.org/10.1017/CBO9781107415324.016, 2013. a
Brandes, E. A., Zhang, G., and Vivekanandan, J.: Experiments in Rainfall
Estimation with a Polarimetric Radar in a Subtropical Environment, J.
Appl. Meteorol., 41, 674–685,
https://doi.org/10.1175/1520-0450(2002)041<0674:EIREWA>2.0.CO;2, 2002. a
Bringi, V., Kennedy, P., Huang, G.-J., Kleinkort, C., Thurai, M., and
Notaroš, B.: Dual-polarized radar and surface observations of a winter
graupel shower with negative Z dr column, J. Appl. Meteorol.
Clim., 56, 455–470, 2017. a
Brown, B. R., Bell, M. M., and Frambach, A. J.: Validation of simulated
hurricane drop size distributions using polarimetric radar, Geophys.
Res. Lett., 43, 910–917, 2016. a
Center, E. M.: The GFS atmospheric model, National Centers for Environmental
Prediction Office Note, 442, 14, 2003. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a
Crisologo, I., Warren, R. A., Mühlbauer, K., and Heistermann, M.: Enhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filter, Atmos. Meas. Tech., 11, 5223–5236, https://doi.org/10.5194/amt-11-5223-2018, 2018. a
Das, S. K., Hazra, A., Deshpande, S. M., Krishna, U. M., and Kolte, Y. K.:
Investigation of Cloud Microphysical Features During the Passage of a
Tropical Mesoscale Convective System: Numerical Simulations and X-Band Radar
Observations, Pure Appl. Geophys., 178, 185–204, 2021. a
Dawson, D. T., Mansell, E. R., Jung, Y., Wicker, L. J., Kumjian, M. R., and
Xue, M.: Low-level Z DR signatures in supercell forward flanks: The role of
size sorting and melting of hail, J. Atmos. Sci., 71,
276–299, 2014. a
Diederich, M., Ryzhkov, A., Simmer, C., Zhang, P., and Trömel, S.: Use of
specific attenuation for rainfall measurement at X-band radar wavelengths,
Part II: Rainfall estimates and comparison with rain gauges, J.
Hydrometeorol., 16, 503–516, 2015b. a
Doms, G. and Schättler, U.: A description of the nonhydrostatic regional
model LM, Part I: Dynamics and Numerics, Tech. rep., Deutscher Wetterdienst, Offenbach, 140 pp., 2002. a
DWD (Deutscher Wetterdienst): Pamore – Abruf archivierter Daten der Vorhersagemodelle [data set], https://www.dwd.de/DE/leistungen/pamore/pamore.html, last access: 25 May 2022. a
ECMWF: IFS Documentation CY25R1 – Part VII: ECMWF Wave Model, no. 7 in IFS
Documentation, ECMWF, operational implementation 9
April 2002, ECMWF, https://doi.org/10.21957/qkv9amafn, 2003. a
Figueras i Ventura, J., Honoré, F., and Tabary, P.: X-band polarimetric
weather radar observations of a hailstorm, J. Atmos. Ocean.
Technol., 30, 2143–2151, 2013. a
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm
refinements and characterization of new datasets, Remote Sens.
Environ., 114, 168–182, 2010. a
Gasper, F., Goergen, K., Shrestha, P., Sulis, M., Rihani, J., Geimer, M., and Kollet, S.: Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP v1.0) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q), Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, 2014 (data available at: https://www.terrsysmp.org/, last access: 25 May 2022). a, b, c
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourde-val, O., Trömel, S., Xie, X.,
Adamidis, P., Ament, F., Baars, H., Barthlott, C., Behrendt, A., Blahak, U., Bley, S., Brdar, S.,
Brueck, M., Crewell, S., Deneke, H., Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C.,
Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A., Hege, H.-C., Hoose,
C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S., Knippertz, P., Kuhn, A., van Laar, T., Macke,
A., Maurer, V., Mayer, B., Meyer, C. I., Muppa, S. K., Neggers, R. A. J., Orlandi, E., Pantillon,
F., Pospichal, B., Röber, N., Scheck, L., Seifert, A., Seifert, P., Senf, F., Siligam, P., Simmer, C.,
Steinke, S., Stevens, B., Wapler, K., Weniger, M., Wulfmeyer, V., Zängl, G., Zhang, D., and
Quaas, J.:
Large-eddy simulations over Germany using ICON: A comprehensive evaluation,
Q. J. Roy. Meteorol. Soc., 143, 69–100, 2017. a, b
Homeyer, C. R. and Kumjian, M. R.: Microphysical characteristics of
overshooting convection from polarimetric radar observations, J.
Atmos. Sci., 72, 870–891, 2015. a
Hubbert, J. C., Wilson, J. W., Weckwerth, T. M., Ellis, S. M., Dixon, M., and
Loew, E.: S-Pol’s polarimetric data reveal detailed storm features (and
insect behavior), Bull. Am. Meteorol. Soc., 99,
2045–2060, 2018. a
Igel, A. L., Igel, M. R., and van den Heever, S. C.: Make it a double? Sobering
results from simulations using single-moment microphysics schemes, J. Atmos. Sci., 72, 910–925, 2015. a
Ilotoviz, E., Khain, A., Ryzhkov, A. V., and Snyder, J. C.: Relationship
between aerosols, hail microphysics, and Z DR columns, J.
Atmos. Sci., 75, 1755–1781, 2018. a
Johnson, M., Jung, Y., Dawson, D. T., and Xue, M.: Comparison of simulated
polarimetric signatures in idealized supercell storms using two-moment bulk
microphysics schemes in WRF, Mon. Weather Rev., 144, 971–996, 2016. a
Jones, J. E. and Woodward, C. S.: Newton–Krylov-multigrid solvers for
large-scale, highly heterogeneous, variably saturated flow problems, Adv. Water Resour., 24, 763–774, 2001. a
Jung, Y., Xue, M., and Zhang, G.: Simulations of polarimetric radar signatures
of a supercell storm using a two-moment bulk microphysics scheme, J.
Appl. Meteorol. Clim., 49, 146–163, 2010. a
Jung, Y., Xue, M., and Tong, M.: Ensemble Kalman filter analyses of the 29–30
May 2004 Oklahoma tornadic thunderstorm using one-and two-moment bulk
microphysics schemes, with verification against polarimetric radar data,
Mon. Weather Rev., 140, 1457–1475, 2012. a
Kaltenboeck, R. and Ryzhkov, A.: Comparison of polarimetric signatures of hail
at S and C bands for different hail sizes, Atmos. Res., 123,
323–336, 2013. a
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud formation:
Homogeneous freezing of supercooled aerosols, J. Geophys.
Res.-Atmos., 107, D2, https://doi.org/10.1029/2001JD000470, 2002. a
Kärcher, B., Hendricks, J., and Lohmann, U.: Physically based parameterization
of cirrus cloud formation for use in global atmospheric models, J.
Geophys. Res.-Atmos., 111, D01205, https://doi.org/10.1029/2005JD006219, 2006. a
Khain, A., Ovtchinnikov, M., Pinsky, M., Pokrovsky, A., and Krugliak, H.: Notes
on the state-of-the-art numerical modeling of cloud microphysics, Atmos.
Res., 55, 159–224, 2000. a
Kim, D.-S., Maki, M., Shimizu, S., and Lee, D.-I.: X-band dual-polarization
radar observations of precipitation core development and structure in a
multi-cellular storm over Zoshigaya, Japan, 5 August 2008, J.
Meteorol. Soc. Jpn. Ser. II, 90, 701–719, 2012. a
Kollet, S. J. and Maxwell, R. M.: Integrated surface–groundwater flow
modeling: A free-surface overland flow boundary condition in a parallel
groundwater flow model, Adv. Water Resour., 29, 945–958, 2006. a
Kreklow, J., Tetzlaff, B., Burkhard, B., and Kuhnt, G.: Radar-Based
Precipitation Climatology in Germany—Developments, Uncertainties and
Potentials, Atmosphere, 11, 217, https://doi.org/10.3390/atmos11020217, 2020. a
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, 2014. a
Kulmala, M., Asmi, A., Lappalainen, H. K., Baltensperger, U., Brenguier, J.-L., Facchini, M. C., Hansson, H.-C., Hov, Ø., O'Dowd, C. D., Pöschl, U., Wiedensohler, A., Boers, R., Boucher, O., de Leeuw, G., Denier van der Gon, H. A. C., Feichter, J., Krejci, R., Laj, P., Lihavainen, H., Lohmann, U., McFiggans, G., Mentel, T., Pilinis, C., Riipinen, I., Schulz, M., Stohl, A., Swietlicki, E., Vignati, E., Alves, C., Amann, M., Ammann, M., Arabas, S., Artaxo, P., Baars, H., Beddows, D. C. S., Bergström, R., Beukes, J. P., Bilde, M., Burkhart, J. F., Canonaco, F., Clegg, S. L., Coe, H., Crumeyrolle, S., D'Anna, B., Decesari, S., Gilardoni, S., Fischer, M., Fjaeraa, A. M., Fountoukis, C., George, C., Gomes, L., Halloran, P., Hamburger, T., Harrison, R. M., Herrmann, H., Hoffmann, T., Hoose, C., Hu, M., Hyvärinen, A., Hõrrak, U., Iinuma, Y., Iversen, T., Josipovic, M., Kanakidou, M., Kiendler-Scharr, A., Kirkevåg, A., Kiss, G., Klimont, Z., Kolmonen, P., Komppula, M., Kristjánsson, J.-E., Laakso, L., Laaksonen, A., Labonnote, L., Lanz, V. A., Lehtinen, K. E. J., Rizzo, L. V., Makkonen, R., Manninen, H. E., McMeeking, G., Merikanto, J., Minikin, A., Mirme, S., Morgan, W. T., Nemitz, E., O'Donnell, D., Panwar, T. S., Pawlowska, H., Petzold, A., Pienaar, J. J., Pio, C., Plass-Duelmer, C., Prévôt, A. S. H., Pryor, S., Reddington, C. L., Roberts, G., Rosenfeld, D., Schwarz, J., Seland, Ø., Sellegri, K., Shen, X. J., Shiraiwa, M., Siebert, H., Sierau, B., Simpson, D., Sun, J. Y., Topping, D., Tunved, P., Vaattovaara, P., Vakkari, V., Veefkind, J. P., Visschedijk, A., Vuollekoski, H., Vuolo, R., Wehner, B., Wildt, J., Woodward, S., Worsnop, D. R., van Zadelhoff, G.-J., Zardini, A. A., Zhang, K., van Zyl, P. G., Kerminen, V.-M., S Carslaw, K., and Pandis, S. N.: General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) – integrating aerosol research from nano to global scales, Atmos. Chem. Phys., 11, 13061–13143, https://doi.org/10.5194/acp-11-13061-2011, 2011. a
Kumjian, M. R., Khain, A. P., Benmoshe, N., Ilotoviz, E., Ryzhkov, A. V., and
Phillips, V. T. J.: The Anatomy and Physics of ZDR Columns: Investigating a
Polarimetric Radar Signature with a Spectral Bin Microphysical Model, J. Appl. Meteorol. Clim., 53, 1820–1843,
https://doi.org/10.1175/JAMC-D-13-0354.1, 2014. a, b
Lang, S. E., Tao, W.-K., Zeng, X., and Li, Y.: Reducing the biases in simulated
radar reflectivities from a bulk microphysics scheme: Tropical convective
systems, J. Atmos. Sci., 68, 2306–2320, 2011. a
Louf, V., Protat, A., Warren, R. A., Collis, S. M., Wolff, D. B., Raunyiar, S.,
Jakob, C., and Petersen, W. A.: An integrated approach to weather radar
calibration and monitoring using ground clutter and satellite comparisons,
J. Atmos. Ocean. Technol., 36, 17–39, 2019. a
Maxwell, R. M.: A terrain-following grid transform and preconditioner for
parallel, large-scale, integrated hydrologic modeling, Adv. Water
Resour., 53, 109–117, 2013. a
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for
geophysical fluid problems, Rev. Geophys., 20, 851–875, 1982. a
Min, K.-H., Choo, S., Lee, D., and Lee, G.: Evaluation of WRF cloud
microphysics schemes using radar observations, Weather Forecast., 30,
1571–1589, 2015. a
Mishchenko, M. I., Hovenier, J. W., and Travis, L. D.: Light scattering by
nonspherical particles: theory, measurements, and applications, Tech. rep., Academic Press, San Diego, USA, ISBN: 9780124986602, 2000. a
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W., Harrington, J. Y.,
Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A., Pawlowska, H., Posselt, D. J., Prat, O.
P., Reimel, K. J., Shima, S.-I., van Diedenhoven, B., and Xue, L.: Confronting the challenge of modeling cloud and
precipitation microphysics, J. Adv. Model. Earth Syst.,
12, e2019MS001689, https://doi.org/10.1029/2019MS001689 2020. a
Mühlbauer, K., Shrestha, P., and Evaristo R.: Polarimetric radar observation processing tool, GitHub [code], https://github.com/meteo-ubonn/miubrt, last access: 25 May 2022. a
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A2H MODIS/Terra+Aqua Leaf Area
Index/FPAR 8-day L4 Global 500 m SIN Grid V006 [Data set], NASA EOSDIS Land
Processes DAAC, https://doi.org/10.5067/MODIS/MCD15A2H.006 (last access: 9 March 2019), 2015. a
Oleson, K. W., Niu, G. Y., Yang, Z. L., Lawrence, D. M., Thornton, P. E., Lawrence, P. J., Stöckli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., and Qian, T.: Improvements to
the Community Land Model and their impact on the hydrological cycle, J. Geophys. Res.-Biogeo., 113, G01021, https://doi.org/10.1029/2007JG000563, 2008. a
Oue, M., Tatarevic, A., Kollias, P., Wang, D., Yu, K., and Vogelmann, A. M.: The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory, Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, 2020. a
Peralta, C., Ben Bouallègue, Z., Theis, S., Gebhardt, C., and Buchhold, M.:
Accounting for initial condition uncertainties in COSMO-DE-EPS, J.
Geophys. Res.-Atmos., 117, D07108, https://doi.org/10.1029/2011JD016581, 2012. a
Protat, A., Bouniol, D., O'Connor, E. J., Baltink, H. K., Verlinde, J., and
Widener, K.: CloudSat as a Global Radar Calibrator, J. Atmos.
Ocean. Technol., 28, 445–452, https://doi.org/10.1175/2010JTECHA1443.1, 2011. a
Putnam, B. J., Xue, M., Jung, Y., Zhang, G., and Kong, F.: Simulation of
polarimetric radar variables from 2013 CAPS spring experiment storm-scale
ensemble forecasts and evaluation of microphysics schemes, Mon. Weather
Rev., 145, 49–73, 2017. a
Rahman, M., Sulis, M., and Kollet, S.: The subsurface–land surface–atmosphere
connection under convective conditions, Adv. Water Resour., 83,
240–249, 2015. a
Ramsauer, T., Weiß, T., and Marzahn, P.: Comparison of the GPM IMERG final
precipitation product to RADOLAN weather radar data over the topographically
and climatically diverse Germany, Remote Sens., 10, 2029, https://doi.org/10.3390/rs10122029, 2018. a
Raschendorfer, M.: The new turbulence parameterization of LM, COSMO Newsletter,
1, 89–97, 2001. a
Ritter, B. and Geleyn, J.-F.: A comprehensive radiation scheme for numerical
weather prediction models with potential applications in climate simulations,
Mon. Weather Rev,, 120, 303–325, 1992. a
Ryzhkov, A., Pinsky, M., Pokrovsky, A., and Khain, A.: Polarimetric Radar
Observation Operator for a Cloud Model with Spectral Microphysics, J. Appl. Meteorol. Clim., 50, 873–894,
https://doi.org/10.1175/2010JAMC2363.1, 2011. a, b
Ryzhkov, A. V., Snyder, J., Carlin, J. T., Khain, A., and Pinsky, M.: What
polarimetric weather radars offer to cloud modelers: forward radar operators
and microphysical/thermodynamic retrievals, Atmosphere, 11, 362, https://doi.org/10.3390/atmos11040362, 2020. a
Schuur, T., Ryzhkov, A., Heinselman, P., Zrnic, D., Burgess, D., and
Scharfenberg, K.: Observations and classification of echoes with the
polarimetric WSR-88D radar, Report of the National Severe Storms Laboratory,
Norman, OK, 46, 73069, 2003. a
Schwaller, M. R. and Morris, K. R.: A ground validation network for the Global
Precipitation Measurement mission, J. Atmos. Ocean.
Technol., 28, 301–319, 2011. a
Segal, Y. and Khain, A.: Dependence of droplet concentration on aerosol
conditions in different cloud types: Application to droplet concentration
parameterization of aerosol conditions, J. Geophys. Res.-Atmos., 111, D15204, https://doi.org/10.1029/2005JD006561, 2006. a, b
Seifert, A., Köhler, C., and Beheng, K. D.: Aerosol-cloud-precipitation effects over Germany as simulated by a convective-scale numerical weather prediction model, Atmos. Chem. Phys., 12, 709–725, https://doi.org/10.5194/acp-12-709-2012, 2012. a
Shrestha, P.: Characterization of Pre-Monsoon Aerosol and
Aerosol-Cloud-Rainfall Interactions in Central Nepal, Ph.D. thesis, Duke
University, https://hdl.handle.net/10161/3836 (last access: 1 June 2022), 2011. a
Shrestha, P.: Clouds and Vegetation Modulate Shallow Groundwater Table Depth,
J. Hydrometeorol., 22, 753–763, https://doi.org/10.1175/JHM-D-20-0171.1,
2021a. a, b
Shrestha, P.: High resolution hydrological simulations over Bonn Radar Domain, CRC/TR32 Database (TR32DB) [data set], https://doi.org/10.5880/TR32DB.40, 2021. a, b
Shrestha, P. and Simmer, C.: Modeled land atmosphere coupling response to soil
moisture changes with different generations of land surface models, Water,
12, 46, https://doi.org/10.3390/w12010046, 2020. a
Shrestha, P., Dimri, A. P., Schomburg, A., and Simmer, C.: Improved
understanding of an extreme rainfall event at the Himalayan foothills–a case
study using COSMO, Tellus A, 67,
26031, https://doi.org/10.3402/tellusa.v67.26031, 2015. a
Shrestha, P., Mendrok, J., Pejcic, V., Trömel, S., Blahak, U., and Carlin, J. T.: Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators, Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, 2022. a, b, c, d, e
Simmer, C., Thiele-Eich, I., Masbou, M., Amelung, W., Crewell, S., Diekkrueger, B.,
Ewert, F., Hendricks Franssen, H.-J., Huisman, A. J., Kemna, A., Klitzsch, S., Kollet, N.,
Langensiepen, M., Loehnert, U., Rahman, M., Rascher, U., Schneider, K., Schween, J., Shao, Y.,
Shrestha, P., Stiebler, M., Sulis, M., Vanderborght, J., Vereecken, H., van der Kruk, J., Zerenner,
T., and Waldhoff, G.: Monitoring and modeling the terrestrial system from pores to
catchments: the transregional collaborative research center on patterns in
the soil–vegetation–atmosphere system, Bull. Am.
Meteorol. Soc., 96, 1765–1787, 2015. a
Snyder, J. C., Bluestein, H. B., Venkatesh, V., and Frasier, S. J.:
Observations of polarimetric signatures in supercells by an X-band mobile
Doppler radar, Mon. Weather Rev., 141, 3–29, 2013. a
Snyder, J. C., Ryzhkov, A. V., Kumjian, M. R., Khain, A. P., and Picca, J.: A
ZDR Column Detection Algorithm to Examine Convective Storm Updrafts, Weather
Forecast., 30, 1819–1844, https://doi.org/10.1175/WAF-D-15-0068.1, 2015. a
Snyder, J. C., Bluestein, H. B., II, D. T. D., and Jung, Y.: Simulations of
Polarimetric, X-Band Radar Signatures in Supercells. Part II: ZDR Columns and
Rings and KDP Columns, J. Appl. Meteorol. Clim., 56,
2001 – 2026, https://doi.org/10.1175/JAMC-D-16-0139.1, 2017b. a
Staniforth, A., White, A., Wood, N., Thuburn, J., Zerroukat, M., Cordero, E.,
Davies, T., and Diamantakis, M.: Joy of UM 6.3 model formulation, Unified
Model Documentation Paper, 15, 2006. a
Steppeler, J., Doms, G., Schättler, U., Bitzer, H., Gassmann, A., Damrath,
U., and Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic
model LM, Meteorol. Atmos. Phys., 82, 75–96, 2003. a
Sulis, M., Langensiepen, M., Shrestha, P., Schickling, A., Simmer, C., and
Kollet, S. J.: Evaluating the influence of plant-specific physiological
parameterizations on the partitioning of land surface energy fluxes, J. Hydrometeorol., 16, 517–533, 2015. a
Suzuki, S.-I., Maesaka, T., Iwanami, K., Shimizu, S., and Kieda, K.: X-band
dual-polarization radar observations of the supercell storm that generated an
F3 tornado on 6 May 2012 in Ibaraki Prefecture, Japan, J.
Meteorol. Soc. Jpn. Ser. II, 96A, 25–33, https://doi.org/10.2151/jmsj.2017-019, 2018. a, b, c
Tao, W.-K., Shi, J. J., Chen, S. S., Lang, S., Lin, P.-L., Hong, S.-Y.,
Peters-Lidard, C., and Hou, A.: The impact of microphysical schemes on
hurricane intensity and track, Asia-Pa. J. Atmos. Sci.,
47, 1–16, 2011. a
Tao, W.-K., Wu, D., Lang, S., Chern, J.-D., Peters-Lidard, C., Fridlind, A.,
and Matsui, T.: High-resolution NU-WRF simulations of a deep
convective-precipitation system during MC3E: Further improvements and
comparisons between Goddard microphysics schemes and observations, J.
Geophys. Res.-Atmos., 121, 1278–1305, 2016. a
Testud, J., Le Bouar, E., Obligis, E., and Ali-Mehenni, M.: The rain profiling
algorithm applied to polarimetric weather radar, J. Atmos.
Ocean. Technol., 17, 332–356, 2000. a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in
large-scale models, Mon. Weather Rev., 117, 1779–1800, 1989. a
Trömel, S., Kumjian, M. R., Ryzhkov, A. V., Simmer, C., and Diederich, M.:
Backscatter differential phase – Estimation and variability, J.
Appl. Meteorol. Clim., 52, 2529–2548, 2013. a
Trömel, S., Ryzhkov, A. V., Hickman, B., Mühlbauer, K., and Simmer, C.:
Polarimetric Radar Variables in the Layers of Melting and Dendritic Growth at
X Band – Implications for a Nowcasting Strategy in Stratiform Rain, J. Appl. Meteorol. Clim., 58, 2497–2522, 2019. a
Trömel, S., Simmer, C., Blahak, U., Blanke, A., Doktorowski, S., Ewald, F., Frech, M., Gergely, M., Hagen, M., Janjic, T., Kalesse-Los, H., Kneifel, S., Knote, C., Mendrok, J., Moser, M., Köcher, G., Mühlbauer, K., Myagkov, A., Pejcic, V., Seifert, P., Shrestha, P., Teisseire, A., von Terzi, L., Tetoni, E., Vogl, T., Voigt, C., Zeng, Y., Zinner, T., and Quaas, J.: Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes, Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, 2021. a, b, c, d, e, f
Uebel, M., Herbst, M., and Bott, A.: Mesoscale simulations of atmospheric CO2
variations using a high-resolution model system with process-based CO2
fluxes, Q. J. Roy. Meteorol. Soc., 143,
1860–1876, 2017. a
van Lier-Walqui, M., Fridlind, A. M., Ackerman, A. S., Collis, S., Helmus, J.,
MacGorman, D. R., North, K., Kollias, P., and Posselt, D. J.: On polarimetric
radar signatures of deep convection for model evaluation: Columns of specific
differential phase observed during MC3E, Mon. Weather Rev., 144,
737–758, 2016. a
Warren, R. A., Protat, A., Siems, S. T., Ramsay, H. A., Louf, V., Manton,
M. J., and Kane, T. A.: Calibrating Ground-Based Radars against TRMM and GPM,
J. Atmos. Ocean. Technol., 35, 323–346,
https://doi.org/10.1175/JTECH-D-17-0128.1, 2018. a
Wicker, L. J. and Skamarock, W. C.: Time-splitting methods for elastic models
using forward time schemes, Mon. Weather Rev., 130, 2088–2097, 2002. a
Williams, E. R., Hood, K. T., Cho, J. Y. N., Smalley, D. J., Sandifer, J. B., Zrnic, D.,
Melnikov, V. M., Burgess, D. W., Forsyth, D., Webster, T. M., and Erickson, D.: End-to-end
calibration of NEXRAD differential reflectivity with metal spheres, in: Proc.
36th Conf. Radar Meteorol, Breckenridge, CO, 19 September 2013, Amer. Meteor. Soc., 15, 316, https://ams.confex.com/ams/36Radar/webprogram/Paper228796.html, (last access: 31 May 2022), 2013. a
Wolfensberger, D. and Berne, A.: From model to radar variables: a new forward
polarimetric radar operator for COSMO, Atmos. Meas. Tech.,
11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018, 2018. a
Xie, X., Evaristo, R., Troemel, S., Saavedra, P., Simmer, C., and Ryzhkov, A.:
Radar Observation of Evaporation and Implications for Quantitative
Precipitation and Cooling Rate Estimation, J. Atmos.
Ocean. Technol., 33, 1779–1792, https://doi.org/10.1175/JTECH-D-15-0244.1, 2016.
a, b
Xie, X., Shrestha, P., Mendrok, J., Carlin, J., Trömel, S., and Blahak, U.:
Bonn Polarimetric Radar forward Operator (B-PRO), CRC/TR32 Database (TR32DB) [code], https://doi.org/10.5880/TR32DB.41, 2021. a, b
Zeng, Y., Blahak, U., and Jerger, D.: An efficient modular volume-scanning
radar forward operator for NWP models: description and coupling to the COSMO
model, Q. J. Roy. Meteorol. Soc., 142,
3234–3256, 2016. a
Short summary
The study makes use of ensemble numerical simulations with forward operator to evaluate the simulated cloud and precipitation processes with radar observations. While comparing model data with radar has its own challenges due to errors in the forward operator and processed radar measurements, the model was generally found to underestimate the high reflectivity, width/magnitude (value) of ZDR columns and high precipitation.
The study makes use of ensemble numerical simulations with forward operator to evaluate the...
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