Articles | Volume 15, issue 12
https://doi.org/10.5194/amt-15-3663-2022
© 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/amt-15-3663-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jun 2022
Research article |
| 20 Jun 2022
| 20 Jun 2022
Detection of supercooled liquid water containing clouds with ceilometers: development and evaluation of deterministic and data-driven retrievals
Australian Bureau of Meteorology, Melbourne, Victoria, Australia
Alain Protat
Australian Bureau of Meteorology, Melbourne, Victoria, Australia
Simon P. Alexander
Australian Antarctic Division, Kingston, Tasmania, Australia
Andrew R. Klekociuk
Australian Antarctic Division, Kingston, Tasmania, Australia
Peter Kuma
Department of Meteorology, Stockholm University, Stockholm, Sweden
Adrian McDonald
School of Physical and Chemical Sciences, University of Canterbury, Christchurch, Aotearoa/New Zealand
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Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
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MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
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
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
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William R. Hobbs, Andrew R. Klekociuk, and Yuhang Pan
Atmos. Chem. Phys., 20, 14757–14768, https://doi.org/10.5194/acp-20-14757-2020, https://doi.org/10.5194/acp-20-14757-2020, 2020
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W. John R. French, Andrew R. Klekociuk, and Frank J. Mulligan
Atmos. Chem. Phys., 20, 8691–8708, https://doi.org/10.5194/acp-20-8691-2020, https://doi.org/10.5194/acp-20-8691-2020, 2020
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We explore a quasi-quadrennial oscillation (QQO; 3–4 K amplitude, ~ 4-year period) in mesopause region temperatures observed in 24 years of hydroxyl airglow measurements over Davis, Antarctica (68° S, 78° E). Correlation and composite analysis using meteorological reanalysis and satellite data reveals complex patterns on the QQO timescale in both hemispheres. Modulation of the meridional circulation, linked to the propagation of gravity waves, plays a significant role in producing the QQO response.
Alain Protat and Ian McRobert
Atmos. Meas. Tech., 13, 3609–3620, https://doi.org/10.5194/amt-13-3609-2020, https://doi.org/10.5194/amt-13-3609-2020, 2020
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Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Simon P. Alexander, John J. Cassano, Sally Garrett, Jamie Halla, Sean Hartery, Mike J. Harvey, Simon Parsons, Graeme Plank, Vidya Varma, and Jonny Williams
Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, https://doi.org/10.5194/acp-20-6607-2020, 2020
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We evaluate clouds over the Southern Ocean in the climate model HadGEM3 and reanalysis MERRA-2 using ship-based ceilometer and radiosonde observations. We find the models underestimate cloud cover by 18–25 %, with clouds below 2 km dominant in reality but lacking in the models. We find a strong link between clouds, atmospheric stability and sea surface temperature in observations but not in the models, implying that sub-grid processes do not generate enough cloud in response to these conditions.
W. John R. French, Frank J. Mulligan, and Andrew R. Klekociuk
Atmos. Chem. Phys., 20, 6379–6394, https://doi.org/10.5194/acp-20-6379-2020, https://doi.org/10.5194/acp-20-6379-2020, 2020
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Julie M. Nicely, Bryan N. Duncan, Thomas F. Hanisco, Glenn M. Wolfe, Ross J. Salawitch, Makoto Deushi, Amund S. Haslerud, Patrick Jöckel, Béatrice Josse, Douglas E. Kinnison, Andrew Klekociuk, Michael E. Manyin, Virginie Marécal, Olaf Morgenstern, Lee T. Murray, Gunnar Myhre, Luke D. Oman, Giovanni Pitari, Andrea Pozzer, Ilaria Quaglia, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Kane Stone, Susan Strahan, Simone Tilmes, Holger Tost, Daniel M. Westervelt, and Guang Zeng
Atmos. Chem. Phys., 20, 1341–1361, https://doi.org/10.5194/acp-20-1341-2020, https://doi.org/10.5194/acp-20-1341-2020, 2020
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Differences in methane lifetime among global models are large and poorly understood. We use a neural network method and simulations from the Chemistry Climate Model Initiative to quantify the factors influencing methane lifetime spread among models and variations over time. UV photolysis, tropospheric ozone, and nitrogen oxides drive large model differences, while the same factors plus specific humidity contribute to a decreasing trend in methane lifetime between 1980 and 2015.
Laura E. Revell, Stefanie Kremser, Sean Hartery, Mike Harvey, Jane P. Mulcahy, Jonny Williams, Olaf Morgenstern, Adrian J. McDonald, Vidya Varma, Leroy Bird, and Alex Schuddeboom
Atmos. Chem. Phys., 19, 15447–15466, https://doi.org/10.5194/acp-19-15447-2019, https://doi.org/10.5194/acp-19-15447-2019, 2019
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Aerosols over the Southern Ocean consist primarily of sea salt and sulfate, yet are seasonally biased in our model. We test three sulfate chemistry schemes to investigate DMS oxidation, which forms sulfate aerosol. Simulated cloud droplet number concentrations improve using more complex sulfate chemistry. We also show that a new sea spray aerosol source function, developed from measurements made on a recent Southern Ocean research voyage, improves the model's simulation of aerosol optical depth.
Adrien Guyot, Jayaram Pudashine, Alain Protat, Remko Uijlenhoet, Valentijn R. N. Pauwels, Alan Seed, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 4737–4761, https://doi.org/10.5194/hess-23-4737-2019, https://doi.org/10.5194/hess-23-4737-2019, 2019
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We characterised for the first time the rainfall microphysics for Southern Hemisphere temperate latitudes. Co-located instruments were deployed to provide information on the sampling effect and spatio-temporal variabilities at micro scales. Substantial differences were found across the instruments, increasing with increasing values of the rain rate. Specific relations for reflectivity–rainfall are presented together with related uncertainties for drizzle and stratiform and convective rainfall.
Ingo Wohltmann, Ralph Lehmann, Georg A. Gottwald, Karsten Peters, Alain Protat, Valentin Louf, Christopher Williams, Wuhu Feng, and Markus Rex
Geosci. Model Dev., 12, 4387–4407, https://doi.org/10.5194/gmd-12-4387-2019, https://doi.org/10.5194/gmd-12-4387-2019, 2019
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We present a trajectory-based model for simulating the transport of air parcels by convection. Our model extends the approach of existing models by explicitly simulating vertical updraft velocities inside the clouds and the time that an air parcel spends inside the convective event.
Yuke Wang, Valerii Shulga, Gennadi Milinevsky, Aleksey Patoka, Oleksandr Evtushevsky, Andrew Klekociuk, Wei Han, Asen Grytsai, Dmitry Shulga, Valery Myshenko, and Oleksandr Antyufeyev
Atmos. Chem. Phys., 19, 10303–10317, https://doi.org/10.5194/acp-19-10303-2019, https://doi.org/10.5194/acp-19-10303-2019, 2019
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The major sudden stratospheric warming (SSW) dramatically changed atmospheric conditions. This event is accompanied by a sharp increase in the polar stratosphere temperature, zonal wind reverse, and strong changes in the polar mesosphere. These changes affect even the midlatitude mesosphere, which is not widely covered by observations. Our newly installed microwave radiometer allowed for studying mesospheric zonal wind and CO variations to understand the SSW 2018 effects at midlatitudes.
Robert C. Jackson, Scott M. Collis, Valentin Louf, Alain Protat, and Leon Majewski
Atmos. Chem. Phys., 18, 17687–17704, https://doi.org/10.5194/acp-18-17687-2018, https://doi.org/10.5194/acp-18-17687-2018, 2018
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This paper looks at a 17 year database of echo top heights of thunderstorms in Darwin retrieved by CPOL. We find that the echo top heights are generally bimodal, corresponding to cumulus congestus and deep convection, and show a greater bimodality during an inactive MJO. Furthermore, we find that convective cell areas are larger in break conditions compared to monsoon conditions, but only during MJO-inactive conditions.
Blanca Ayarzagüena, Lorenzo M. Polvani, Ulrike Langematz, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Dameris, Makoto Deushi, Steven C. Hardiman, Patrick Jöckel, Andrew Klekociuk, Marion Marchand, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke D. Oman, David A. Plummer, Laura Revell, Eugene Rozanov, David Saint-Martin, John Scinocca, Andrea Stenke, Kane Stone, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Atmos. Chem. Phys., 18, 11277–11287, https://doi.org/10.5194/acp-18-11277-2018, https://doi.org/10.5194/acp-18-11277-2018, 2018
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Stratospheric sudden warmings (SSWs) are natural major disruptions of the polar stratospheric circulation that also affect surface weather. In the literature there are conflicting claims as to whether SSWs will change in the future. The confusion comes from studies using different models and methods. Here we settle the question by analysing 12 models with a consistent methodology, to show that no robust changes in frequency and other features are expected over the 21st century.
Ben Jolly, Peter Kuma, Adrian McDonald, and Simon Parsons
Atmos. Chem. Phys., 18, 9723–9739, https://doi.org/10.5194/acp-18-9723-2018, https://doi.org/10.5194/acp-18-9723-2018, 2018
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Clouds in the Ross Sea and Ross Ice Shelf regions are examined using a combination of satellite observations from the CloudSat and CALIPSO satellite datasets. We show that previous studies may have included an artefact at high altitudes which under-estimated cloud occurrence. We also find that the meteorological regime is a stronger control of cloud occurrence, cloud type and cloud top than season over this region, though season is a strong control on the phase of cloud.
Christopher R. Yost, Kristopher M. Bedka, Patrick Minnis, Louis Nguyen, J. Walter Strapp, Rabindra Palikonda, Konstantin Khlopenkov, Douglas Spangenberg, William L. Smith Jr., Alain Protat, and Julien Delanoe
Atmos. Meas. Tech., 11, 1615–1637, https://doi.org/10.5194/amt-11-1615-2018, https://doi.org/10.5194/amt-11-1615-2018, 2018
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Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine malfunction or even power loss, and therefore it is important for aircraft to avoid flight through clouds that may have produced large quantities of ice particles. This study introduces a method by which potentially hazardous conditions can be detected using satellite imagery. It was found that potentially hazardous conditions were often located near or beneath very cold clouds and thunderstorm updrafts.
Fraser Dennison, Adrian McDonald, and Olaf Morgenstern
Atmos. Chem. Phys., 17, 14075–14084, https://doi.org/10.5194/acp-17-14075-2017, https://doi.org/10.5194/acp-17-14075-2017, 2017
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The Antarctic ozone is not centred directly over the pole. In this research we examine how the position and shape of the ozone hole changes using a chemistry–climate model. As ozone becomes increasingly depleted during the late 20th century the centre of the ozone hole moves toward the west and becomes more circular. As the ozone hole recovers over the course of the 21st century the ozone hole moves back towards the east.
Jesse W. Greenslade, Simon P. Alexander, Robyn Schofield, Jenny A. Fisher, and Andrew K. Klekociuk
Atmos. Chem. Phys., 17, 10269–10290, https://doi.org/10.5194/acp-17-10269-2017, https://doi.org/10.5194/acp-17-10269-2017, 2017
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An analysis of data from ozonesondes released at three southern oceanic sites shows the impact of stratospheric ozone in this region. Using a novel method of transport classification, this work estimates the seasonality and quantity of stratospherically sourced ozone. We find that ozone is transported most frequently in summer due to regional-scale low-pressure weather systems. We also estimate a stratospheric ozone source of 2.0–3.3 Tg/year over three Southern Ocean regions.
McKenna W. Stanford, Adam Varble, Ed Zipser, J. Walter Strapp, Delphine Leroy, Alfons Schwarzenboeck, Rodney Potts, and Alain Protat
Atmos. Chem. Phys., 17, 9599–9621, https://doi.org/10.5194/acp-17-9599-2017, https://doi.org/10.5194/acp-17-9599-2017, 2017
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Radar reflectivity is a valuable observational tool used to guide numerical weather model improvement. Biases in simulated reflectivity help identify potential errors in physical process and property representation in models. This study uniquely compares simulated and observed tropical convective systems to establish that a commonly documented high bias in radar reflectivity values at least partially results from the production of simulated ice particle sizes that are larger than observed.
Chris S.~M. Turney, Andrew Klekociuk, Christopher J. Fogwill, Violette Zunz, Hugues Goosse, Claire L. Parkinson, Gilbert Compo, Matthew Lazzara, Linda Keller, Rob Allan, Jonathan G. Palmer, Graeme Clark, and Ezequiel Marzinelli
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-51, https://doi.org/10.5194/tc-2017-51, 2017
Revised manuscript not accepted
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We demonstrate that a mid-twentieth century decrease in geopotential height in the southwest Pacific marks a Rossby wave response to equatorial Pacific warming, leading to enhanced easterly airflow off George V Land. Our results suggest that in contrast to ozone hole-driven changes in the Amundsen Sea, the 1979–2015 increase in sea ice extent off George V Land may be in response to reduced northward Ekman drift and enhanced (near-coast) production as a consequence of low latitude forcing.
Iain M. Reid, Andrew J. Spargo, Jonathan M. Woithe, Andrew R. Klekociuk, Joel P. Younger, and Gulamabas G. Sivjee
Ann. Geophys., 35, 567–582, https://doi.org/10.5194/angeo-35-567-2017, https://doi.org/10.5194/angeo-35-567-2017, 2017
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We measured temperatures in the atmosphere at heights near 90 km using nightglow emissions and compared them with satellite measurements and with measurements made with a meteor radar. We found good agreement between the techniques, which improved when we used the meteor radar and satellite data to measure densities at two heights separated by about 10 km to estimate the nightglow emission height.
Asen Grytsai, Andrew Klekociuk, Gennadi Milinevsky, Oleksandr Evtushevsky, and Kane Stone
Atmos. Chem. Phys., 17, 1741–1758, https://doi.org/10.5194/acp-17-1741-2017, https://doi.org/10.5194/acp-17-1741-2017, 2017
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Twenty years ago we discovered that the ozone hole shape is asymmetric. This asymmetry is minimum over the Weddell Sea region and maximum over the Ross Sea area. Later we detected that the position of the ozone minimum is shifting east. We have continued to follow this event, and a couple years ago we revealed that the shift is slowing down and starting to move back. We connect all this movement with ozone hole increase; since 2000 the ozone layer has been stabilizing and recently recovering.
Ethan R. Dale, Adrian J. McDonald, Jack H. J. Coggins, and Wolfgang Rack
The Cryosphere, 11, 267–280, https://doi.org/10.5194/tc-11-267-2017, https://doi.org/10.5194/tc-11-267-2017, 2017
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This work studies the affects of strong winds on sea ice within the Ross Sea polynya. We compare both automatic weather station (AWS) and reanalysis wind data with sea ice concentration (SIC) measurements based on satellite images. Due to its low resolution, the reanalysis data were unable to reproduce several relationships found between the AWS and SIC data. We find that the strongest third of wind speeds had the most significant affect on SIC and resulting sea ice production.
Leon S. Friedrich, Adrian J. McDonald, Gregory E. Bodeker, Kathy E. Cooper, Jared Lewis, and Alexander J. Paterson
Atmos. Chem. Phys., 17, 855–866, https://doi.org/10.5194/acp-17-855-2017, https://doi.org/10.5194/acp-17-855-2017, 2017
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Information from long-duration balloons flying in the Southern Hemisphere stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses. This work assesses the potential of the X Project Loon observations to validate outputs from the reanalysis models. In particular, we examined how the model winds compared with those derived from the balloon GPS information. We also examined simulated trajectories compared with the true trajectories.
Kane A. Stone, Olaf Morgenstern, David J. Karoly, Andrew R. Klekociuk, W. John French, N. Luke Abraham, and Robyn Schofield
Atmos. Chem. Phys., 16, 2401–2415, https://doi.org/10.5194/acp-16-2401-2016, https://doi.org/10.5194/acp-16-2401-2016, 2016
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This paper describes the set-up and evaluation of the Australian Community Climate and Earth System Simulator – chemistry-climate model.
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
R. S. Humphries, A. R. Klekociuk, R. Schofield, M. Keywood, J. Ward, and S. R. Wilson
Atmos. Chem. Phys., 16, 2185–2206, https://doi.org/10.5194/acp-16-2185-2016, https://doi.org/10.5194/acp-16-2185-2016, 2016
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This work represents the first observational study of atmospheric sub-micron aerosols in the East Antarctic pack ice region and found springtime aerosol concentrations were higher than any observed elsewhere in the Antarctic and Southern Ocean region. Further analysis suggested these aerosols formed in the Antarctic free troposphere. Their subsequent transport to the Southern Ocean, as suggest by trajectory analyses, could help to reduce the discrepancy in the radiative budget in the region.
C. S. M. Turney, C. J. Fogwill, A. R. Klekociuk, T. D. van Ommen, M. A. J. Curran, A. D. Moy, and J. G. Palmer
The Cryosphere, 9, 2405–2415, https://doi.org/10.5194/tc-9-2405-2015, https://doi.org/10.5194/tc-9-2405-2015, 2015
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Recent trends in ocean circulation, sea ice and climate over the Southern Ocean and Antarctica are highly complex. Here we report a new snow core from the South Pole alongside reanalysis of 20th century global atmospheric circulation. We demonstrate for the first time that atmospheric pressure anomalies in the mid-latitudes act as "gatekeepers" to meridional exchange over continental Antarctica, modulated by the tropical Pacific, with potentially significant impacts on surface mass balance.
R. S. Humphries, R. Schofield, M. D. Keywood, J. Ward, J. R. Pierce, C. M. Gionfriddo, M. T. Tate, D. P. Krabbenhoft, I. E. Galbally, S. B. Molloy, A. R. Klekociuk, P. V. Johnston, K. Kreher, A. J. Thomas, A. D. Robinson, N. R. P. Harris, R. Johnson, and S. R. Wilson
Atmos. Chem. Phys., 15, 13339–13364, https://doi.org/10.5194/acp-15-13339-2015, https://doi.org/10.5194/acp-15-13339-2015, 2015
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An atmospheric new particle formation event that was observed in the pristine East Antarctic pack ice during a springtime voyage in 2012 is characterised in terms of formation and growth rates. Known nucleation mechanisms (e.g. those involving sulfate, iodine and organics) were unable to explain observations; however, correlations with total gaseous mercury were found, leading to the suggestion of a possible mercury-driven nucleation mechanism not previously described.
J. M. Siddaway, S. V. Petelina, D. J. Karoly, A. R. Klekociuk, and R. J. Dargaville
Atmos. Chem. Phys., 13, 4413–4427, https://doi.org/10.5194/acp-13-4413-2013, https://doi.org/10.5194/acp-13-4413-2013, 2013
P. E. Huck, G. E. Bodeker, S. Kremser, A. J. McDonald, M. Rex, and H. Struthers
Atmos. Chem. Phys., 13, 3237–3243, https://doi.org/10.5194/acp-13-3237-2013, https://doi.org/10.5194/acp-13-3237-2013, 2013
S. P. Alexander, D. J. Murphy, and A. R. Klekociuk
Atmos. Chem. Phys., 13, 3121–3132, https://doi.org/10.5194/acp-13-3121-2013, https://doi.org/10.5194/acp-13-3121-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations
Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations
Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations
The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission
High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Improved spectral processing for a multi-mode pulse compression Ka–Ku-band cloud radar system
Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption
Ice water path retrievals from Meteosat-9 using quantile regression neural networks
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-109, https://doi.org/10.5194/amt-2023-109, 2023
Revised manuscript accepted for AMT
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals is always decreasing with the increasing distance from the cloud far edge. The decreasing is the direct consequence of the fact that the forward peak of particles phase functions is much larger than the receiver field of view.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
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The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
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This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
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.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
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We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
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Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
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The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
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Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
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We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
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Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
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SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
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Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
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Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
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With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
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Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
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This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
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A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Cited articles
Alexander, S. P. and Protat, A.: Cloud properties observed from the surface and by satellite at the northern edge of the Southern Ocean, J. Geophys. Res.-Atmos., 123, 443–456,
https://doi.org/10.1002/2017JD026552, 2018.
Alexander, S. P. and Protat, A.: Vertical profiling of aerosols with a
combined Raman-elastic backscatter lidar in the remote Southern Ocean marine
boundary layer (43–66∘ S, 132–150∘ E),
J. Geophys. Res.-Atmos., 124, 12107–12125, https://doi.org/10.1029/2019JD030628,
2019.
Alexander, S. P., McFarquhar, G. M., Marchand, R., Protat, A., Vignon,
É., Mace, G. G., and Klekociuk, A. R.: Mixed-phase clouds and
precipitation in Southern Ocean cyclones and cloud systems observed poleward
of 64∘ S by ship-based cloud radar and lidar, J. Geophys. Res.-Atmos., 126, e2020JD033626, https://doi.org/10.1029/2020JD033626, 2021.
Bennartz, R., Fell, F., Pettersen, C., Shupe, M. D., and Schuettemeyer, D.: Spatial and temporal variability of snowfall over Greenland from CloudSat observations, Atmos. Chem. Phys., 19, 8101–8121, https://doi.org/10.5194/acp-19-8101-2019, 2019.
Bjordal, J., Storelvmo, T., Alterskjær, K., and Carlsen, T.: Equilibrium
climate sensitivity above 5 ∘C plausible due to state-dependent
cloud feedback, Nat. Geosci., 13, 718–721, https://doi.org/10.1038/s41561-020-00649-1, 2020.
Bodas-Salcedo, A., Hill, P. G., Furtado, K., Williams, K. D., Field, P. R.,
Manners, J. C., Hyder, P., and Kato, S.: Large Contribution of Supercooled
Liquid Clouds to the Solar Radiation Budget of the Southern Ocean, J.
Climate, 29, 4213–4228, https://doi.org/10.1175/jcli-d-15-0564.1, 2016.
Bromwich, D. H., Werner, K., Casati, B., Powers, J. G., Gorodetskaya, I. V.,
Massonnet, F., Vitale, V., Heinrich, V. J., Liggett, D., Arndt, S., Barja,
B., Bazile, E., Carpentier, S., Carrasco, J. F., Choi, T., Choi, Y.,
Colwell, S. R., Cordero, R. R., Gervasi, M., Haiden, T., Hirasawa, N.,
Inoue, J., Jung, T., Kalesse, H., Kim, S., Lazzara, M. A., Manning, K. W.,
Norris, K., Park, S., Reid, P., Rigor, I., Rowe, P. M., Schmithüsen, H.,
Seifert, P., Sun, Q., Uttal, T., Zannoni, M., and Zou, X.: The Year of Polar
Prediction in the Southern Hemisphere (YOPP-SH), B. Am. Meteorol. Soc., 101, E1653–E1676, https://doi.org/10.1175/BAMS-D-19-0255.1, 2020.
Chen, T. and Guestrin, C.: Xgboost: A scalable tree boosting system, in: KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 13–17 August 2016, San Francisco, USA, 785–794 https://doi.org/10.1145/2939672.2939785, 2016.
Chen, T., He, T., Benesty, M., Khotilovich, V., Tang, Y., and Cho, H.:
Xgboost: extreme gradient boosting, manual, R package version 0.4-2, 1, 1–4, 2015.
Cossich, W., Maestri, T., Magurno, D., Martinazzo, M., Di Natale, G., Palchetti, L., Bianchini, G., and Del Guasta, M.: Ice and mixed-phase cloud statistics on the Antarctic Plateau, Atmos. Chem. Phys., 21, 13811–13833, https://doi.org/10.5194/acp-21-13811-2021, 2021.
Delanoë, J. and Hogan, R. J.: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds, J. Geophys. Res., 115, D00H29, https://doi.org/10.1029/2009JD012346, 2010.
Delanoë, J., Protat, A., Vinson, J.-P., Brett, W., Caudoux, C., Bertrand, F., Parent du Chatelet, J., Hallali, R., Barthes, L., Haeffelin, M., and Dupont, J.-C.: BASTA, a 95 GHz FMCW Doppler radar for cloud and fog studies, J. Atmos. Ocean. Tech., 33, 1023–1038, https://doi.org/10.1175/JTECH-D-15-0104.1, 2016.
Frey, W. R. and Kay, J. E.: The influence of extratropical cloud phase and
amount feedbacks on climate sensitivity, Clim. Dynam., 50, 3097–3116, https://doi.org/10.1007/s00382-017-3796-5, 2018.
Gehring, J., Vignon, E., Billault-Roux, A.-C., Ferrone, A., Protat, A.,
Alexander, S. P., and Berne: The influence of orographic gravity waves on
precipitation during an atmospheric river event at Davis, Antarctica, J. Geophys. Res.-Atmos., 127, e2021JD035210, https://doi.org/10.1029/2021JD035210, 2022.
Genthon, C., Berne, A., Grazioli, J., Durán Alarcón, C., Praz, C., and Boudevillain, B.: Precipitation at Dumont d'Urville, Adélie Land, East Antarctica: the APRES3 field campaigns dataset, Earth Syst. Sci. Data, 10, 1605–1612, https://doi.org/10.5194/essd-10-1605-2018, 2018
Gorodetskaya, I. V., Kneifel, S., Maahn, M., Van Tricht, K., Thiery, W., Schween, J. H., Mangold, A., Crewell, S., and Van Lipzig, N. P. M.: Cloud and precipitation properties from ground-based remote-sensing instruments in East Antarctica, The Cryosphere, 9, 285–304, https://doi.org/10.5194/tc-9-285-2015, 2015.
Grazioli, J., Genthon, C., Boudevillain, B., Duran-Alarcon, C., Del Guasta, M., Madeleine, J.-B., and Berne, A.: Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica, The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, 2017.
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.
Guyot, A., Alexander, S., Protat, A., Klekociuk, A., and McDonald, A.: PLATO Davis dataset (Austral Summer 2018-2019) (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.5832199, 2022.
Hämäläinen, K., Hirsikko, A., Leskinen, A., Komppula,
M., O'Connor, E. J., and Niemelä, S.: Evaluating atmospheric icing
forecasts with ground-based ceilometer profiles, Meteorol. Appl., 27, e1964, https://doi.org/10.1002/met.1964, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hogan, R. J. and Illingworth, A. J.: A climatology of supercooled layer
clouds from lidar ceilometer data, in: CLARE'98 Final workshop, 13–14 September 1999, 161–165, 1999.
Hogan, R. J. and Illingworth, A. J.: The effect of specular reflection on
spaceborne lidar measurements of ice clouds, Report of the ESA Retrieval
algorithm for EarthCARE project, 5 pp., 2003.
Hogan, R. J., Illingworth, A. J., O'connor, E. J., and Baptista, J. P.
V. P.: Characteristics of mixed-phase clouds. II: A climatology from
ground-based lidar, Q. J. Roy. Meteorol. Soc., 129, 2117–2134, https://doi.org/10.1256/qj.01.209, 2003.
Hogan, R. J., Behera, M. D., O'Connor, E. J., and Illingworth, A.
J.: Estimate of the global distribution of stratiform supercooled liquid
water clouds using the LITE lidar, Geophys. Res. Lett., 31, L05106, https://doi.org/10.1029/2003GL018977, 2004.
Hopkin, E., Illingworth, A. J., Charlton-Perez, C., Westbrook, C. D., and Ballard, S.: A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds, Atmos. Meas. Tech., 12, 4131–4147, https://doi.org/10.5194/amt-12-4131-2019, 2019.
Hu, Y., Winker, D., Vaughan, M., Lin, B., Omar, A., Trepte, C., Flittner, D., Yang, P., Nasiri, S. L., Baum, B., Holz, R., Sun, W., Liu, Z., Wang, Z., Young, S., Stamnes, K., Huang, J., and Kuehn, R.: CALIPSO/CALIOP cloud phase discrimination algorithm, J. Atmos. Ocean. Tech., 26, 2293–2309, https://doi.org/10.1175/2009JTECHA1280.1, 2009.
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9,
90–95, https://doi.org/10.1109/MCSE.2007.55, 2007.
Hyder, P., Edwards, J. M., Allan, R. P., Hewitt, H. T., Bracegirdle, T. J.,
Gregory, J. M., Wood, R. A., Meijers, A. J. S., Mulcahy, J., Field, P.,
Furtado, K., Bodas-Salcedo, A., Williams, K. D., Copsey, D., Josey, S. A.,
Liu, C., Roberts, C. D., Sanchez, C., Ridley, J., Thorpe, L., Hardiman,
S. C., Mayer, M., Berry, D. I., and Belcher, S. E.: Critical Southern Ocean
climate model biases traced to atmospheric model cloud errors, Nat. Commun.,
9, 3625, https://doi.org/10.1038/s41467-018-05634-2, 2018.
Illingworth, A. J., Hogan, R. J., O'Connor, E., Bouniol, D., Brooks, M. E.,
Delanoé, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J.
W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou,
J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van
Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and Wrench,
C. L.: Cloudnet, B. Am. Meteor. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007.
Jung, T., Gordon, N. D., Bauer, P., Bromwich, D. H., Chevallier, M., Day, J.
J., Dawson, J., Doblas-Reyes, F., Fairall, C., Goessling, H. F., Holland,
M., Inoue, J., Iversen, T., Klebe, S., Lemke, P., Losch, M., Makshtas, A.,
Mills, B., Nurmi, P., Perovich, D., Reid, P., Renfrew, I. A., Smith, G.,
Svensson, G., Tolstykh, M., and Yang, Q.: Advancing Polar Prediction
Capabilities on Daily to Seasonal Time Scales, B. Am. Meteorol. Soc., 97, 1631–1647, https://doi.org/10.1175/BAMS-D-14-00246.1, 2016.
Kay, J. E., Wall, C., Yettella, V., Medeiros, B., Hannay, C., Caldwell, P.,
and Bitz, C.: Global climate impacts of fixing the Southern Ocean shortwave
radiation bias in the Community Earth System Model (CESM), J. Climate, 29, 4617–4636, https://doi.org/10.1175/jcli-d-15-0358.1, 2016.
Kuma, P.: cl2nc (3.3.0), Zenodo [code], https://doi.org/10.5281/zenodo.4409716, 2020.
Kuma, P., McDonald, A. J., Morgenstern, O., Alexander, S. P., Cassano, J. J., Garrett, S., Halla, J., Hartery, S., Harvey, M. J., Parsons, S., Plank, G., Varma, V., and Williams, J.: Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations, Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, 2020.
Kuma, P., McDonald, A. J., Morgenstern, O., Querel, R., Silber, I., and Flynn, C. J.: Ground-based lidar processing and simulator framework for comparing models and observations (ALCF 1.0), Geosci. Model Dev., 14, 43–72, https://doi.org/10.5194/gmd-14-43-2021, 2021a.
Kuma, P., McDonald, A. J., Morgenstern, O., Querel, R., Silber, I., and Flynn, C. J.: Automatic Lidar and Ceilometer Framework (ALCF) (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.4411633, 2021b.
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.
Lawson, R. P. and Gettelman, A.: Impact of Antarctic clouds on climate,
P. Natl. Acad. Sci. USA, 111, 18156–18161, https://doi.org/10.1073/pnas.1418197111, 2014.
Lazzara, M. A.: A diagnostic study of Antarctic fog, PhD thesis, The University of Wisconsin, Madison, ISBN 9780549635857, 2008.
Listowski, C., Delanoë, J., Kirchgaessner, A., Lachlan-Cope, T., and King, J.: Antarctic clouds, supercooled liquid water and mixed phase, investigated with DARDAR: geographical and seasonal variations, Atmos. Chem. Phys., 19, 6771–6808, https://doi.org/10.5194/acp-19-6771-2019, 2019.
Listowski, C., Rojo, M., Claud, C., Delanoë, J., Rysman, J.-F.,
Cazenave, Q., and Noer, G.: New insights into the vertical structure of clouds in polar lows, using radar-lidar satellite observations, Geophys. Res. Lett., 47,
e2020GL088785, https://doi.org/10.1029/2020GL088785, 2020.
Lundberg, S. M. and Lee, S.-I.: A unified approach to interpreting model
predictions, Adv. Neural Inf. Process. Syst., 30, 4768–4777, 2017.
Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B.,
Katz, R., Himmelfarb, J., Bansal, N., and Lee, S.-I.: From local explanations
to global understanding with explainable AI for trees, Nature Machine Intelligence, 2, 56–67, https://doi.org/10.1038/s42256-019-0138-9, 2020 (code available at: https://github.com/slundberg/shap, last access: 10 December 2021).
Mace, G. G., Benson, S., and Hu, Y.: On the frequency of occurrence of the
ice phase in supercooled Southern Ocean low clouds derived from CALIPSO and
CloudSat, Geophys. Res. Lett., 47, e2020GL087554, https://doi.org/10.1029/2020GL087554, 2020.
Mace, G. G., Protat, A., and Benson, S.: Mixed-phase clouds over the Southern
Ocean as observed from satellite and surface based lidar and radar, J. Geophys. Res.-Atmos., 126, e2021JD034569, https://doi.org/10.1029/2021JD034569, 2021.
McErlich, C., McDonald, A., Schuddeboom, A., and Silber, I.: Comparing
satellite- and ground-based observations of cloud occurrence over high
southern latitude, J. Geophys. Res.-Atmos., 126, e2020JD033607, https://doi.org/10.1029/2020JD033607, 2021.
Mishchenko, M. I., Hovenier, J. W., and Travis, L. D. (Eds.): Light
Scattering by Nonspherical Particles: Theory, Measurements, and
Applications, Academic Press, Elsevier, chap. 14, 393–416, ISBN 9780080510200, 2000.
Morcrette, C., Brown, K., Bowyer, R., Gill, P., and Suri D.: Development and
Evaluation of In-Flight Icing Index Forecast for Aviation, Weather Forecast., 34, 731–750, https://doi.org/10.1175/WAF-D-18-0177.1, 2019.
Morille, Y., Haeffelin, M., Drobinski, P., and Pelon, J.: STRAT: An
automated algorithm to retrieve the vertical structure of the atmosphere
from single-channel lidar data, J. Atmos. Ocean. Tech., 24,
761–775, https://doi.org/10.1175/JTECH2008.1, 2007.
Münkel, C., Eresmaa, N., Räsänen, J., and Karppinen, A.:
Retrieval of mixing height and dust concentration with lidar ceilometer,
Bound.-Lay. Meteorol., 124, 117–128, https://doi.org/10.1007/s10546-006-9103-3, 2007.
Noh, Y.-J., Miller, S. D., Heidinger, A. K., Mace, G. G., Protat, A., and Alexander, S. P.: Satellite-based detection of daytime supercooled
liquid-topped mixed-phase clouds over the Southern Ocean using the Advanced
Himawari Imager, J. Geophys. Res.-Atmos., 124, 2677–2701, https://doi.org/10.1029/2018JD029524, 2019.
O'Connor, E. J., Illingworth, A. J., and Hogan, R. J.: A technique for
autocalibration of cloud lidar, J. Atmos. Ocean. Tech., 21, 777–786, 2004.
Ojala, M. and Garriga, G. C.: Permutation Tests for Studying Classifier
Performance, J. Mach. Learn. Res., 11, 1833–1863, 2010.
Pandas development team: Data structures for statistical computing in
python, McKinney, Proceedings of the 9th Python in Science Conference, 28 June–3 July 210, Austin, Texas, USA, vol. 445, 2010.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., and Vanderplas,
J.: Scikit-learn: Machine learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011.
Rew, R. and Davis, G.: NetCDF: an interface for scientific data access, IEEE
Comput. Graph. Appl., 10, 76–82, https://doi.org/10.1109/38.56302, 1990.
Ricaud, P., Del Guasta, M., Bazile, E., Azouz, N., Lupi, A., Durand, P., Attié, J.-L., Veron, D., Guidard, V., and Grigioni, P.: Supercooled liquid water cloud observed, analysed, and modelled at the top of the planetary boundary layer above Dome C, Antarctica, Atmos. Chem. Phys., 20, 4167–4191, https://doi.org/10.5194/acp-20-4167-2020, 2020.
Rossum, G.: Python reference manual, Centre for Mathematics and Computer
Science, Amsterdam, the Netherlands, 1995.
Royer, P., Bizard, A., Sauvage, L., and Thobois, L.: Validation protocol and
intercomparison campaigns with the R-MAN510 aerosol lidar, Proc. 17th Int.
Symp. for the Advancement of Boundary-Layer Remote Sensing, 28–31 January 2014, Auckland, New Zealand, 2014.
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/10.1002/2015GL067246, 2016.
Sotiropoulou, G., Vignon, É., Young, G., Morrison, H., O'Shea, S. J., Lachlan-Cope, T., Berne, A., and Nenes, A.: Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models, Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, 2021.
Tuononen, M., O'Connor, E. J., and Sinclair, V. A.: Evaluating solar radiation forecast uncertainty, Atmos. Chem. Phys., 19, 1985–2000, https://doi.org/10.5194/acp-19-1985-2019, 2019.
Van Der Walt, S., Colbert, S. C., and Varoquaux, G.: The NumPy array: a
structure for efficient numerical computation, Comput. Sci. Eng., 13,
22–30, https://doi.org/10.1109/MCSE.2011.37, 2011.
Van Tricht, K., Gorodetskaya, I. V., Lhermitte, S., Turner, D. D., Schween, J. H., and Van Lipzig, N. P. M.: An improved algorithm for polar cloud-base detection by ceilometer over the ice sheets, Atmos. Meas. Tech., 7, 1153–1167, https://doi.org/10.5194/amt-7-1153-2014, 2014.
Vignon, É., Alexander, S. P., DeMott, P. J., Sotiropoulou, G., Gerber,
F., Hill, T. C. J., Marchand, R., Nenes, A., and Berne, A.: Challenging and improving the simulation of
mid-level mixed-phase clouds over the high-latitude Southern Ocean, J. Geophys. Res.-Atmos., 126, e2020JD033490, https://doi.org/10.1029/2020JD033490, 2021.
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Jarrod Millman, K., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C., Polat, ̇I., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy 1.0 Contributors: SciPy
1.0 – Fundamental Algorithms for Scientific Computing in Python, arXiv [preprint], arXiv:1907.10121, 23 July 2019.
Zhang, D., Vogelmann, A., Kollias, P., Luke, E., Yang, F., Lubin, D., and Wang, Z.: Comparison of Antarctic and Arctic single-layer stratiform
mixed-phase cloud properties using ground-based remote sensing
measurements, J. Geophys. Res.-Atmos., 124, 10186–10204, https://doi.org/10.1029/2019JD030673, 2019.
Short summary
Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Ceilometers are instruments that are widely deployed as part of operational networks. They are...
