Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-875-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-17-875-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Feb 2024
Research article |
| 01 Feb 2024
| 01 Feb 2024
An intercomparison of EarthCARE cloud, aerosol, and precipitation retrieval products
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
National Centre for Earth Observation, University of Reading, Reading, UK
Howard W. Barker
Environment and Climate Change Canada, Victoria, BC, Canada
Jason N. S. Cole
Environment and Climate Change Canada, Toronto, ON, Canada
Nicole Docter
Institute of Meteorology, Free University of Berlin, Berlin, Germany
David P. Donovan
R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), de Bilt, the Netherlands
Robin J. Hogan
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Department of Meteorology, University of Reading, Reading, UK
Anja Hünerbein
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Pavlos Kollias
School of Marine and Atmospheric Sciences, Stonybrook University, Stonybrook, NY, USA
Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, QC, Canada
Bernat Puigdomènech Treserras
Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, QC, Canada
Zhipeng Qu
Environment and Climate Change Canada, Toronto, ON, Canada
Ulla Wandinger
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Gerd-Jan van Zadelhoff
R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), de Bilt, the Netherlands
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Cristofer Jimenez, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Daniel Alexander Knopf, Sandro Dahlke, Johannes Bühl, Holger Baars, Patric Seifert, and Ulla Wandinger
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Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Mélissa Cholette, Cuong Nguyen, and Mengistu Wolde
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Nitika Yadlapalli Yurk, Matthew Lebsock, Juan Socuellamos, Raquel Rodriguez Monje, Ken Cooper, and Pavlos Kollias
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Marco Coppola, Alessandro Battaglia, Frederic Tridon, and Pavlos Kollias
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Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
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Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3051, https://doi.org/10.5194/egusphere-2024-3051, 2024
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We investigated how the uncertainty in representing water vapour continuum absorption in the shortwave affects clear-sky shortwave radiative feedback. For current surface temperature, the impact is modest (<2 %). In a warmer world, continuum induced error in estimated shortwave feedback is up to ~5 %. Using the MT_CKD model in radiative transfer calculations may lead to an underestimation of the shortwave feedback. Constraining shortwave continuum will contribute to reducing these discrepancies.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Julian Hofer, Moritz Haarig, Ulla Wandinger, Bernd Heinold, Ina Tegen, Matthias Faust, Holger Baars, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
EGUsphere, https://doi.org/10.5194/egusphere-2024-3159, https://doi.org/10.5194/egusphere-2024-3159, 2024
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This study investigates how hematite (an iron oxide mineral) in the Saharan Desert dust affects how dust particles interact with radiation. Using lidar data from Cabo Verde (2021–2022) and hematite content from atmospheric model simulations, the results show that higher hematite fraction leads to stronger particle backscattering at specific wavelengths. These findings can improve the representaiton of mineral dust in climate models, particularly regarding their radiative effect.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
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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Ping Wang, David Patrick Donovan, Gerd-Jan van Zadelhoff, Jos de Kloe, Dorit Huber, and Katja Reissig
Atmos. Meas. Tech., 17, 5935–5955, https://doi.org/10.5194/amt-17-5935-2024, https://doi.org/10.5194/amt-17-5935-2024, 2024
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We describe the new feature mask (AEL-FM) and aerosol profile retrieval (AEL-PRO) algorithms developed for Aeolus lidar and present the evaluation of the Aeolus products using CALIPSO data for dust aerosols over Africa. We have found that Aeolus and CALIPSO show similar aerosol patterns in the collocated orbits and have good agreement for the extinction coefficients for the dust aerosols, especially for the cloud-free scenes. The finding is applicable to Aeolus L2A product Baseline 17.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
David Patrick Donovan, Gerd-Jan van Zadelhoff, and Ping Wang
Atmos. Meas. Tech., 17, 5301–5340, https://doi.org/10.5194/amt-17-5301-2024, https://doi.org/10.5194/amt-17-5301-2024, 2024
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ATLID (atmospheric lidar) is the lidar to be flown on the Earth Clouds and Radiation Explorer satellite (EarthCARE). EarthCARE is a joint European–Japanese satellite mission that was launched in May 2024. ATLID is an advanced lidar optimized for cloud and aerosol property profile measurements. This paper describes some of the key novel algorithms being applied to this lidar to retrieve cloud and aerosol properties. Example results based on simulated data are presented and discussed.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
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Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
Atmos. Chem. Phys., 24, 5637–5657, https://doi.org/10.5194/acp-24-5637-2024, https://doi.org/10.5194/acp-24-5637-2024, 2024
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This study analyzed coastal convective cells from June through September 2018–2021. The cells were classified and their lifecycles were analyzed to better understand their characteristics. Features such as convective-core growth, for example, are shown. The study found differences in the initiation location of shallow convection and in the aerosol loading in deep convective environments. This work provides a foundation for future analyses of convection or other tracked events elsewhere.
Nicole Docter, Anja Hünerbein, David P. Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
Atmos. Meas. Tech., 17, 2507–2519, https://doi.org/10.5194/amt-17-2507-2024, https://doi.org/10.5194/amt-17-2507-2024, 2024
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MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
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A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond A. Shaw, Alex B. Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech., 17, 1133–1143, https://doi.org/10.5194/amt-17-1133-2024, https://doi.org/10.5194/amt-17-1133-2024, 2024
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In this article, we demonstrate the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with centimeter-scale resolution, single drizzle drops with a diameter larger than 40 µm can be detected. This study demonstrates the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultrahigh-resolution radar for atmospheric sensing.
Athena Augusta Floutsi, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, https://doi.org/10.5194/amt-17-693-2024, 2024
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We introduce an aerosol-typing scheme (HETEAC-Flex) based on lidar-derived intensive optical properties and applicable to ground-based and spaceborne lidars. HETEAC-Flex utilizes the optimal estimation method and enables the identification of up to four different aerosol components, as well as the determination of their contribution to the aerosol mixture in terms of relative volume. The aerosol components represent common aerosol types such as dust, sea salt, smoke and pollution.
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.
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 24, 597–612, https://doi.org/10.5194/acp-24-597-2024, https://doi.org/10.5194/acp-24-597-2024, 2024
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The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 54 Wm-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and gives suggestions for improvements.
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.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
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We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Rodanthi-Elisavet Mamouri, Albert Ansmann, Kevin Ohneiser, Daniel A. Knopf, Argyro Nisantzi, Johannes Bühl, Ronny Engelmann, Annett Skupin, Patric Seifert, Holger Baars, Dragos Ene, Ulla Wandinger, and Diofantos Hadjimitsis
Atmos. Chem. Phys., 23, 14097–14114, https://doi.org/10.5194/acp-23-14097-2023, https://doi.org/10.5194/acp-23-14097-2023, 2023
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For the first time, rather clear evidence is found that wildfire smoke particles can trigger strong cirrus formation. This finding is of importance because intensive and large wildfires may occur increasingly often in the future as climate change proceeds. Based on lidar observations in Cyprus in autumn 2020, we provide detailed insight into the cirrus formation at the tropopause in the presence of aged wildfire smoke (here, 8–9 day old Californian wildfire smoke).
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
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.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
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Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Albert Ansmann, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Jessie M. Creamean, Matthew C. Boyer, Daniel A. Knopf, Sandro Dahlke, Marion Maturilli, Henriette Gebauer, Johannes Bühl, Cristofer Jimenez, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 23, 12821–12849, https://doi.org/10.5194/acp-23-12821-2023, https://doi.org/10.5194/acp-23-12821-2023, 2023
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The 1-year MOSAiC (2019–2020) expedition with the German ice breaker Polarstern was the largest polar field campaign ever conducted. The Polarstern, with our lidar aboard, drifted with the pack ice north of 85° N for more than 7 months (October 2019 to mid-May 2020). We measured the full annual cycle of aerosol conditions in terms of aerosol optical and cloud-process-relevant properties. We observed a strong contrast between polluted winter and clean summer aerosol conditions.
Jason N. S. Cole, Howard W. Barker, Zhipeng Qu, Najda Villefranque, and Mark W. Shephard
Atmos. Meas. Tech., 16, 4271–4288, https://doi.org/10.5194/amt-16-4271-2023, https://doi.org/10.5194/amt-16-4271-2023, 2023
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Measurements from the EarthCARE satellite mission will be used to retrieve profiles of cloud and aerosol properties. These retrievals are combined with auxiliary information about surface properties and atmospheric state, e.g., temperature and water vapor. This information allows computation of 1D and 3D solar and thermal radiative transfer for small domains, which are compared with coincident radiometer observations to continually assess EarthCARE retrievals.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
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We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
Holger Baars, Joshua Walchester, Elizaveta Basharova, Henriette Gebauer, Martin Radenz, Johannes Bühl, Boris Barja, Ulla Wandinger, and Patric Seifert
Atmos. Meas. Tech., 16, 3809–3834, https://doi.org/10.5194/amt-16-3809-2023, https://doi.org/10.5194/amt-16-3809-2023, 2023
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In 2018, the Aeolus satellite of the European Space Agency (ESA) was launched to improve weather forecasts through global measurements of wind profiles. Given the novel lidar technique onboard, extensive validation efforts have been needed to verify the observations. For this reason, we performed long-term validation measurements in Germany and Chile. We found significant improvement in the data products due to a new algorithm version and can confirm the general validity of Aeolus observations.
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.
Nicole Docter, Rene Preusker, Florian Filipitsch, Lena Kritten, Franziska Schmidt, and Jürgen Fischer
Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, https://doi.org/10.5194/amt-16-3437-2023, 2023
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We describe the stand-alone retrieval algorithm used to derive aerosol properties relying on measurements of the Multi-Spectral Imager (MSI) aboard the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. This aerosol data product will be available as M-AOT after the launch of EarthCARE. Additionally, we applied the algorithm to simulated EarthCARE MSI and Moderate Resolution Imaging Spectroradiometer (MODIS) data for prelaunch algorithm verification.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
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Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
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.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
Atmos. Meas. Tech., 16, 2485–2510, https://doi.org/10.5194/amt-16-2485-2023, https://doi.org/10.5194/amt-16-2485-2023, 2023
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We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
Martin de Graaf, Karolina Sarna, Jessica Brown, Elma V. Tenner, Manon Schenkels, and David P. Donovan
Atmos. Chem. Phys., 23, 5373–5391, https://doi.org/10.5194/acp-23-5373-2023, https://doi.org/10.5194/acp-23-5373-2023, 2023
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Clouds over the oceans reflect sunlight and cool the earth. Simultaneous measurements were performed of cloud droplet sizes and smoke particles in and near the cloud base over Ascension Island, a remote island in the Atlantic Ocean, to determine the sensitivity of cloud droplets to smoke from the African continent. The smoke was found to reduce cloud droplet sizes, which makes the cloud droplets more susceptible to evaporation, reducing cloud lifetime.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
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DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
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.
Pavlos Kollias, Bernat Puidgomènech Treserras, Alessandro Battaglia, Paloma C. Borque, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 1901–1914, https://doi.org/10.5194/amt-16-1901-2023, https://doi.org/10.5194/amt-16-1901-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by the European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) features the first spaceborne 94 GHz Doppler cloud-profiling radar (CPR) with Doppler capability. Here, we describe the post-processing algorithms that apply quality control and corrections to CPR measurements and derive key geophysical variables such as hydrometeor locations and best estimates of particle sedimentation fall velocities.
Zackary Mages, Pavlos Kollias, Zeen Zhu, and Edward P. Luke
Atmos. Chem. Phys., 23, 3561–3574, https://doi.org/10.5194/acp-23-3561-2023, https://doi.org/10.5194/acp-23-3561-2023, 2023
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Cold-air outbreaks (when cold air is advected over warm water and creates low-level convection) are a dominant cloud regime in the Arctic, and we capitalized on ground-based observations, which did not previously exist, from the COMBLE field campaign to study them. We characterized the extent and strength of the convection and turbulence and found evidence of secondary ice production. This information is useful for model intercomparison studies that will represent cold-air outbreak processes.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310, https://doi.org/10.5194/acp-22-12287-2022, https://doi.org/10.5194/acp-22-12287-2022, 2022
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Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Albert Ansmann, Kevin Ohneiser, Alexandra Chudnovsky, Daniel A. Knopf, Edwin W. Eloranta, Diego Villanueva, Patric Seifert, Martin Radenz, Boris Barja, Félix Zamorano, Cristofer Jimenez, Ronny Engelmann, Holger Baars, Hannes Griesche, Julian Hofer, Dietrich Althausen, and Ulla Wandinger
Atmos. Chem. Phys., 22, 11701–11726, https://doi.org/10.5194/acp-22-11701-2022, https://doi.org/10.5194/acp-22-11701-2022, 2022
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For the first time we present a systematic study on the impact of wildfire smoke on ozone depletion in the Arctic (2020) and Antarctic stratosphere (2020, 2021). Two major fire events in Siberia and Australia were responsible for the observed record-breaking stratospheric smoke pollution. Our analyses were based on lidar observations of smoke parameters (Polarstern, Punta Arenas) and NDACC Arctic and Antarctic ozone profiles as well as on Antarctic OMI satellite observations of column ozone.
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Hannes J. Griesche, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 22, 9313–9348, https://doi.org/10.5194/acp-22-9313-2022, https://doi.org/10.5194/acp-22-9313-2022, 2022
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This article describes an intercomparison of radiative fluxes and cloud properties from satellite, shipborne observations, and 1D radiative transfer simulations. The analysis focuses on research for PS106 expedition aboard the German research vessel, Polarstern. The results are presented in detailed case studies, time series for the PS106 cruise and extended to the central Arctic region. The findings illustrate the main periods of agreement and discrepancies of both points of view.
Zeen Zhu, Pavlos Kollias, Edward Luke, and Fan Yang
Atmos. Chem. Phys., 22, 7405–7416, https://doi.org/10.5194/acp-22-7405-2022, https://doi.org/10.5194/acp-22-7405-2022, 2022
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Drizzle (small rain droplets) is an important component of warm clouds; however, its existence is poorly understood. In this study, we capitalized on a machine-learning algorithm to develop a drizzle detection method. We applied this algorithm to investigate drizzle occurrence and found out that drizzle is far more ubiquitous than previously thought. This study demonstrates the ubiquitous nature of drizzle in clouds and will improve understanding of the associated microphysical process.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 15, 3121–3140, https://doi.org/10.5194/amt-15-3121-2022, https://doi.org/10.5194/amt-15-3121-2022, 2022
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Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a satellite spectrometer.
Alessandro Battaglia, Paolo Martire, Eric Caubet, Laurent Phalippou, Fabrizio Stesina, Pavlos Kollias, and Anthony Illingworth
Atmos. Meas. Tech., 15, 3011–3030, https://doi.org/10.5194/amt-15-3011-2022, https://doi.org/10.5194/amt-15-3011-2022, 2022
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We present an instrument simulator for a new sensor, WIVERN (WInd VElocity Radar Nephoscope), a conically scanning radar payload with Doppler capabilities, recently down-selected as one of the four candidates for the European Space Agency Earth Explorer 11 program. The mission aims at measuring horizontal winds in cloudy areas. The simulator is instrumental in the definition and consolidation of the mission requirements and the evaluation of mission performances.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384, https://doi.org/10.5194/acp-22-2365-2022, https://doi.org/10.5194/acp-22-2365-2022, 2022
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Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
Moritz Haarig, Albert Ansmann, Ronny Engelmann, Holger Baars, Carlos Toledano, Benjamin Torres, Dietrich Althausen, Martin Radenz, and Ulla Wandinger
Atmos. Chem. Phys., 22, 355–369, https://doi.org/10.5194/acp-22-355-2022, https://doi.org/10.5194/acp-22-355-2022, 2022
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The irregular shape of dust particles makes it difficult to treat them correctly in optical models. Atmospheric measurements of dust optical properties are therefore of great importance. The present study increases the space of observed parameters from 355 and 532 nm towards 1064 nm, which is of special importance for large dust particles. The lidar ratio influenced by mineralogy and the depolarization ratio influenced by shape are measured for the first time at all three wavelengths.
Jonas Witthuhn, Anja Hünerbein, Florian Filipitsch, Stefan Wacker, Stefanie Meilinger, and Hartwig Deneke
Atmos. Chem. Phys., 21, 14591–14630, https://doi.org/10.5194/acp-21-14591-2021, https://doi.org/10.5194/acp-21-14591-2021, 2021
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Knowledge of aerosol–radiation interactions is important for understanding the climate system and for the renewable energy sector. Here, two complementary approaches are used to assess the consistency of the underlying aerosol properties and the resulting radiative effect in clear-sky conditions over Germany in 2015. An approach based on clear-sky models and broadband irradiance observations is contrasted to the use of explicit radiative transfer simulations using CAMS reanalysis data.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 21, 14039–14058, https://doi.org/10.5194/acp-21-14039-2021, https://doi.org/10.5194/acp-21-14039-2021, 2021
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This numerical study provides insights into the sensitivity of shallow-cumulus dilution to geostrophic vertical wind profile. The cumulus dilution is strongly sensitive to vertical wind shear in the cloud layer, with shallow cumuli being more diluted in sheared environments. On the other hand, wind shear in the subcloud layer leads to less diluted cumuli. The sensitivities are explained by jointly considering the impacts of vertical velocity and the properties of the entrained air.
Ronny Engelmann, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Martin Radenz, Julian Hofer, Dietrich Althausen, Sandro Dahlke, Marion Maturilli, Igor Veselovskii, Cristofer Jimenez, Robert Wiesen, Holger Baars, Johannes Bühl, Henriette Gebauer, Moritz Haarig, Patric Seifert, Ulla Wandinger, and Andreas Macke
Atmos. Chem. Phys., 21, 13397–13423, https://doi.org/10.5194/acp-21-13397-2021, https://doi.org/10.5194/acp-21-13397-2021, 2021
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A Raman lidar was operated aboard the icebreaker Polarstern during MOSAiC and monitored aerosol and cloud layers in the central Arctic up to 30 km height. The article provides an overview of the spectrum of aerosol profiling observations and shows aerosol–cloud interaction studies for liquid-water and ice clouds. A highlight was the detection of a 10 km deep wildfire smoke layer over the North Pole up to 17 km height from the fire season of 2019, which persisted over the whole winter period.
Jing Feng, Yi Huang, and Zhipeng Qu
Atmos. Meas. Tech., 14, 5717–5734, https://doi.org/10.5194/amt-14-5717-2021, https://doi.org/10.5194/amt-14-5717-2021, 2021
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It is challenging to measure the atmospheric conditions above convective storms. In this study, a method of retrieving thermodynamic variables above convective storms using a combination of satellite-based observations from a hyperspectral infrared sounder and active sensors is developed. We find that this method captures the spatial distributions of thermodynamic anomalies above convective clouds well. This method is potentially applicable to observations from current and future satellites.
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215, https://doi.org/10.5194/gmd-14-5205-2021, https://doi.org/10.5194/gmd-14-5205-2021, 2021
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A major limitation in training machine-learning emulators is often caused by the lack of data. This paper presents a cheap way to increase the size of training datasets using statistical techniques and thereby improve the performance of machine-learning emulators.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
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The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Karolina Sarna, David P. Donovan, and Herman W. J. Russchenberg
Atmos. Meas. Tech., 14, 4959–4970, https://doi.org/10.5194/amt-14-4959-2021, https://doi.org/10.5194/amt-14-4959-2021, 2021
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We show a method for obtaining cloud optical extinction with a lidar system. We use a scheme in which a lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique, we show that it is possible to obtain the cloud optical extinction with an error better than 5 % up to 90 m within the cloud.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Katia Lamer, Mariko Oue, Alessandro Battaglia, Richard J. Roy, Ken B. Cooper, Ranvir Dhillon, and Pavlos Kollias
Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, https://doi.org/10.5194/amt-14-3615-2021, 2021
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Observations collected during the 25 February 2020 deployment of the VIPR at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the differential reflectivity from Ka–G band pair provides larger signals than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes.
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
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A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Jörg Schmidt, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15247–15263, https://doi.org/10.5194/acp-20-15247-2020, https://doi.org/10.5194/acp-20-15247-2020, 2020
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A novel lidar method to study cloud microphysical properties (of liquid water clouds) and to study aerosol–cloud interaction (ACI) is developed and presented in this paper. In Part 1, the theoretical framework including an error analysis is given together with an overview of the aerosol information that the same lidar system can obtain. The ACI concept based on aerosol and cloud information is also explained. Applications of the proposed approach to lidar measurements are presented in Part 2.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Patric Seifert, Robert Wiesen, Martin Radenz, Zhenping Yin, Johannes Bühl, Jörg Schmidt, Boris Barja, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15265–15284, https://doi.org/10.5194/acp-20-15265-2020, https://doi.org/10.5194/acp-20-15265-2020, 2020
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Part 2 presents the application of the dual-FOV polarization lidar technique introduced in Part 1. A lidar system was upgraded with a second polarization telescope, and it was deployed at the southernmost tip of South America. A comparison with alternative remote sensing techniques and the evaluation of the aerosol–cloud–wind relation in a convective boundary layer in pristine marine conditions are presented in two case studies, demonstrating the potential of the approach for ACI studies.
Marek Jacob, Pavlos Kollias, Felix Ament, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 5757–5777, https://doi.org/10.5194/gmd-13-5757-2020, https://doi.org/10.5194/gmd-13-5757-2020, 2020
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We compare clouds in different cloud-resolving atmosphere simulations with airborne remote sensing observations. The focus is on warm shallow clouds in the Atlantic trade wind region. Those clouds are climatologically important but challenging for climate models. We use forward operators to apply instrument-specific thresholds for cloud detection to model outputs. In this comparison, the higher-resolution model better reproduces the layered cloud structure.
Holger Baars, Alina Herzog, Birgit Heese, Kevin Ohneiser, Karsten Hanbuch, Julian Hofer, Zhenping Yin, Ronny Engelmann, and Ulla Wandinger
Atmos. Meas. Tech., 13, 6007–6024, https://doi.org/10.5194/amt-13-6007-2020, https://doi.org/10.5194/amt-13-6007-2020, 2020
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A first validation for the European satellite Aeolus is presented. Aeolus is the first satellite that can actively measure horizontal wind profiles from space.
Radiosonde launches on board the German research vessel Polarstern have been utilized to validate Aeolus observations over the Atlantic Ocean, a region where almost no other reference measurements are available. It is shown that Aeolus is able to measure accurately atmospheric winds and thus may significantly improve weather forecasts.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 20, 13217–13239, https://doi.org/10.5194/acp-20-13217-2020, https://doi.org/10.5194/acp-20-13217-2020, 2020
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This numerical study provides insights into selected environmental sensitivities of shallow-cumulus dilution. Among the parameters under consideration, the dilution of the cloud cores is strongly sensitive to continentality and cloud-layer relative humidity and weakly sensitive to subcloud- and cloud-layer depths. The impacts of all four parameters are interpreted using a similarity theory of shallow cumulus and buoyancy-sorting arguments.
Alessandro Battaglia, Pavlos Kollias, Ranvir Dhillon, Katia Lamer, Marat Khairoutdinov, and Daniel Watters
Atmos. Meas. Tech., 13, 4865–4883, https://doi.org/10.5194/amt-13-4865-2020, https://doi.org/10.5194/amt-13-4865-2020, 2020
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Warm rain accounts for slightly more than 30 % of the total rain amount and 70 % of the total rain area in the tropical belt and usually appears in kilometer-size cells. Spaceborne radars adopting millimeter wavelengths are excellent tools for detecting such precipitation types and for separating between the cloud and rain components. Our work highlights the benefits of operating multifrequency radars and discusses the impact of antenna footprints in quantitative estimates of liquid water paths.
Mario Mech, Maximilian Maahn, Stefan Kneifel, Davide Ori, Emiliano Orlandi, Pavlos Kollias, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, https://doi.org/10.5194/gmd-13-4229-2020, 2020
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The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package written in Python and Fortran for the simulation of microwave remote sensing observations. PAMTRA models the interaction of radiation with gases, clouds, precipitation, and the surface using either in situ observations or model output as input parameters. The wide range of applications is demonstrated for passive (radiometer) and active (radar) instruments on ground, airborne, and satellite platforms.
Cited articles
Cole, J. N. S., Barker, H. W., Qu, Z., Villefranque, N., and Shephard, M. W.: Broadband radiative quantities for the EarthCARE mission: the ACM-COM and ACM-RT products, Atmos. Meas. Tech., 16, 4271–4288, https://doi.org/10.5194/amt-16-4271-2023, 2023. a, b, c, d
Delanoë, J. M. E. and Hogan, R. J.: A variational scheme for retrieving ice cloud properties from combined radar, lidar, and infrared radiometer, J. Geophys. Res., 113, D07204, https://doi.org/10.1029/2007JD009000, 2008. a, b
Docter, N., Preusker, R., Filipitsch, F., Kritten, L., Schmidt, F., and Fischer, J.: Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product, Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, 2023. a, b, c
Donovan, D. P., Kollias, P., Velázquez Blázquez, A., and van Zadelhoff, G.-J.: The Generation of EarthCARE L1 Test Data sets Using Atmospheric Model Data Sets, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-384, 2023a. a, b, c
Eisinger, M., Marnas, F., Wallace, K., Kubota, T., Tomiyama, N., Ohno, Y., Tanaka, T., Tomita, E., Wehr, T., and Bernaerts, D.: The EarthCARE Mission: Science Data Processing Chain Overview, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1998, 2023. a, b, c, d
Haarig, M., Hünerbein, A., Wandinger, U., Docter, N., Bley, S., Donovan, D., and van Zadelhoff, G.-J.: Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-327, 2023. a, b, c
Hogan, R. J., Brooks, M. E., Illingworth, A. J., Donovan, D. P., Tinel, C., Bouniol, D., and Baptista, J. P. V. P.: Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds, J. Atmos. Ocean. Tech., 23, 211–227, https://doi.org/10.1175/JTECH1837.1, 2006a. a
Hogan, R. J., Mittermaier, M. P., and Illingworth, A. J.: The retrieval of ice water content from radar reflectivity factor and temperature and its use in evaluating a mesoscale model, J. Appl. Meteorol. Clim., 45, 301–317, https://doi.org/10.1175/JAM2340.1, 2006b. a
Hünerbein, A., Bley, S., Deneke, H., Meirink, J. F., van Zadelhoff, G.-J., and Walther, A.: Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-305, 2023a. a, b, c, d
Hünerbein, A., Bley, S., Horn, S., Deneke, H., and Walther, A.: Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products, Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, 2023b. a, b, c
Irbah, A., Delanoë, J., van Zadelhoff, G.-J., Donovan, D. P., Kollias, P., Puigdomènech Treserras, B., Mason, S., Hogan, R. J., and Tatarevic, A.: The classification of atmospheric hydrometeors and aerosols from the EarthCARE radar and lidar: the A-TC, C-TC and AC-TC products, Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, 2023. a, b, c, d, e, f, g, h, i, j
Kollias, P., Puidgomènech Treserras, B., Battaglia, A., Borque, P. C., and Tatarevic, A.: Processing reflectivity and Doppler velocity from EarthCARE's cloud-profiling radar: the C-FMR, C-CD and C-APC products, Atmos. Meas. Tech., 16, 1901–1914, https://doi.org/10.5194/amt-16-1901-2023, 2023. a, b, c, d, e
Mroz, K., Treserras, B. P., Battaglia, A., Kollias, P., Tatarevic, A., and Tridon, F.: Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product, Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, 2023. a, b, c, d, e, f, g, h, i
Qu, Z., Barker, H. W., Cole, J. N. S., and Shephard, M. W.: Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product, Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, 2023a. a, b
Qu, Z., Donovan, D. P., Barker, H. W., Cole, J. N. S., Shephard, M. W., and Huijnen, V.: Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system, Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, 2023b. a, b
van Zadelhoff, G.-J., Barker, H. W., Baudrez, E., Bley, S., Clerbaux, N., Cole, J. N. S., de Kloe, J., Docter, N., Domenech, C., Donovan, D. P., Dufresne, J.-L., Eisinger, M., Fischer, J., García-Marañón, R., Haarig, M., Hogan, R. J., Hünerbein, A., Kollias, P., Koopman, R., Madenach, N., Mason, S. L., Preusker, R., Puigdomènech Treserras, B., Qu, Z., Ruiz-Saldaña, M., Shephard, M., Velázquez-Blazquez, A., Villefranque, N., Wandinger, U., Wang, P., and Wehr, T.: EarthCARE level-2 demonstration products from simulated scenes, Version 10.10, Zenodo [data set], https://doi.org/10.5281/zenodo.7728948, 2023a. a
van Zadelhoff, G.-J., Donovan, D. P., and Wang, P.: Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product, Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, 2023b. a, b
Wandinger, U., Haarig, M., Baars, H., Donovan, D., and van Zadelhoff, G.-J.: Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products, Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, 2023. a, b, c, d
Wehr, T., Kubota, T., Tzeremes, G., Wallace, K., Nakatsuka, H., Ohno, Y., Koopman, R., Rusli, S., Kikuchi, M., Eisinger, M., Tanaka, T., Taga, M., Deghaye, P., Tomita, E., and Bernaerts, D.: The EarthCARE mission – science and system overview, Atmos. Meas. Tech., 16, 3581–3608, https://doi.org/10.5194/amt-16-3581-2023, 2023. a, b, c, d
Short summary
When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
When the EarthCARE mission enters its operational phase, many retrieval data products will be...
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