Articles | Volume 17, issue 24
https://doi.org/10.5194/amt-17-7169-2024
© Author(s) 2024. 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-17-7169-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Determination of low-level temperature profiles from microwave radiometer observations during rain
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
Moritz Lochmann
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
Pablo Saavedra Garfias
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
Heike Kalesse-Los
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
Related authors
Anna Trosits, Andreas Foth, Allison A. Wing, Johanna Roschke, Moritz Haarig, Anton Kötsche, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2026-4385, https://doi.org/10.5194/egusphere-2026-4385, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study shows the effect of air layers originating from the Saharan Desert on clouds over the tropical Atlantic observed during the ship-borne research campaign BOWTIE. These Saharan Air Layers (SAL) were analysed with data from several instruments providing atmospheric profiles and can be characterised by low moisture and dispersed mineral dust. The investigation suggests a suppression of vertical cloud development by the SAL, also affecting microphysical properties of the cloud.
Gianluca Di Natale, Helen Brindley, Laura Warwick, Sanjeevani Panditharatne, Ping Yang, Robert Oscar David, Tim Carlsen, Sorin Nicolae Vâjâiac, Alex Vlad, Sorin Ghemuleț, Richard Bantges, Andreas Foth, Martin Flügge, Reidar Lyngra, Hilke Oetjen, Dirk Schuettemeyer, Luca Palchetti, and Jonathan Murray
Atmos. Chem. Phys., 26, 1373–1394, https://doi.org/10.5194/acp-26-1373-2026, https://doi.org/10.5194/acp-26-1373-2026, 2026
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Cirrus clouds play a vital role in regulating Earth's energy balance. However, they remain incompletely understood, representing a major source of uncertainty in the predictive performance of climate models. We show that consistency between in situ measurements of cirrus cloud microphysics and ground-based remote sensing observations is achievable by simulating the emitted spectrum using current parameterizations of cirrus optical properties.
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
Atmos. Meas. Tech., 18, 487–508, https://doi.org/10.5194/amt-18-487-2025, https://doi.org/10.5194/amt-18-487-2025, 2025
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We present a technique to discriminate between the Cloudnet target classification of "drizzle or rain" and sea salt aerosols that is applicable to marine Cloudnet sites. The method is crucial for investigating the occurrence of precipitation and significantly improves the Cloudnet target classification scheme for measurements over the Barbados Cloud Observatory (BCO). A first-ever analysis of the Cloudnet product including the new "haze echo" target over 2 years at the BCO is presented.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
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.
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.
Anna Trosits, Andreas Foth, Allison A. Wing, Johanna Roschke, Moritz Haarig, Anton Kötsche, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2026-4385, https://doi.org/10.5194/egusphere-2026-4385, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study shows the effect of air layers originating from the Saharan Desert on clouds over the tropical Atlantic observed during the ship-borne research campaign BOWTIE. These Saharan Air Layers (SAL) were analysed with data from several instruments providing atmospheric profiles and can be characterised by low moisture and dispersed mineral dust. The investigation suggests a suppression of vertical cloud development by the SAL, also affecting microphysical properties of the cloud.
Hans Segura, Allison A. Wing, Heike Kalesse-Los, Ruben Carrasco, James H. Ruppert Jr., Anna Trosits, Louise Nuijens, Felix Ament, Daniel Blandfort, Michael M. Bell, Pierre Bosser, Delián Colón-Burgos, Geet George, Joelle Habib, Jochen Horstmann, Friedhelm Jansen, Lukas Kluft, Robert Kopte, Klas Ove Möller, Peristera Paschou, Hauke Schmidt, Michael Schlundt, Ilya Serikov, Martin Stelzner, Elizabeth J. Thompson, Werenfrid Wimmer, Marcus Dengler, and Daniel Klocke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-343, https://doi.org/10.5194/essd-2026-343, 2026
Preprint under review for ESSD
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BOWTIE (Beobachtung von Ozean und Wolken - Das Trans ITCZ Experiment) was an observational campaign occurring in summer 2024, which intensively took measurements from the upper ocean to the upper troposphere in the wettest region of the tropical Atlantic. Here, we provide an overview of the measurements and instrumentation, including remote sensing and conventional, which targeted small-scale processes under different weather regimes, from calm doldrums to gusty, precipitating events.
Jonas Witthuhn, Hartwig Deneke, Andreas Macke, Oscar Ritter, Jens Redemann, Connor J. Flynn, Abdulamid A. Fakoya, Bradley F. Lamkin, Emily D. Lenhardt, Logan T. Mitchell, Emily K. West, David M. Romps, Rusen Öktem, and Heike Kalesse-Los
Atmos. Chem. Phys., 26, 5727–5745, https://doi.org/10.5194/acp-26-5727-2026, https://doi.org/10.5194/acp-26-5727-2026, 2026
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This study examines how solar irradiance changes when sunlight passes from clear sky into cloud shadows, focusing on 3‑D radiative effects of shallow cumulus clouds. Using data from a dense pyranometer network and cloud masks from cameras we found that irradiance can rise up to 20 % above clear‑sky levels near cloud edges. Key drivers include sun‑cloud geometry and microphysical cloud properties. The results highlight the need to incorporate such 3‑D effects in atmospheric models.
Johanna Roschke, Benedikt Gast, Martin Radenz, Albert Ansmann, Patric Seifert, George McCosh, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2026-718, https://doi.org/10.5194/egusphere-2026-718, 2026
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This research introduces a new method that combines model simulations with satellite observations to attribute the influence of wildfire smoke on an airmass. By dynamically determining the height of smoke plumes, we overcome a key limitation of earlier fixed reception-height approaches. This advancement is crucial for improving our understanding of how wildfire emissions influence cloud formation and the broader Earth's climate system.
Anton Kötsche, Maximilian Maahn, Veronika Ettrichrätz, and Heike Kalesse-Los
Atmos. Chem. Phys., 26, 3277–3297, https://doi.org/10.5194/acp-26-3277-2026, https://doi.org/10.5194/acp-26-3277-2026, 2026
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We studied how turbulence affects snowfall in the Colorado Rockies, focusing on a turbulent layer behind Gothic Mountain. Using radar and surface observations, we found turbulence enhances snow growth by causing snowflakes to stick and form extra ice via collisions. Liquid water at cold temperatures further boosts snow formation. This work shows how turbulence shapes mountain snowfall and demonstrates radar-based methods to study precipitation processes.
Gianluca Di Natale, Helen Brindley, Laura Warwick, Sanjeevani Panditharatne, Ping Yang, Robert Oscar David, Tim Carlsen, Sorin Nicolae Vâjâiac, Alex Vlad, Sorin Ghemuleț, Richard Bantges, Andreas Foth, Martin Flügge, Reidar Lyngra, Hilke Oetjen, Dirk Schuettemeyer, Luca Palchetti, and Jonathan Murray
Atmos. Chem. Phys., 26, 1373–1394, https://doi.org/10.5194/acp-26-1373-2026, https://doi.org/10.5194/acp-26-1373-2026, 2026
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Cirrus clouds play a vital role in regulating Earth's energy balance. However, they remain incompletely understood, representing a major source of uncertainty in the predictive performance of climate models. We show that consistency between in situ measurements of cirrus cloud microphysics and ground-based remote sensing observations is achievable by simulating the emitted spectrum using current parameterizations of cirrus optical properties.
Kevin Ohneiser, Patric Seifert, Willi Schimmel, Fabian Senf, Tom Gaudek, Martin Radenz, Audrey Teisseire, Veronika Ettrichrätz, Teresa Vogl, Nina Maherndl, Nils Pfeifer, Jan Henneberger, Anna J. Miller, Nadja Omanovic, Christopher Fuchs, Huiying Zhang, Fabiola Ramelli, Robert Spirig, Anton Kötsche, Heike Kalesse-Los, Maximilian Maahn, Heather Corden, Alexis Berne, Majid Hajipour, Hannes Griesche, Julian Hofer, Ronny Engelmann, Annett Skupin, Albert Ansmann, and Holger Baars
Atmos. Chem. Phys., 25, 17363–17386, https://doi.org/10.5194/acp-25-17363-2025, https://doi.org/10.5194/acp-25-17363-2025, 2025
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This study focuses on a seeder-feeder cloud system on 8 Jan 2024 in Eriswil, Switzerland. It is shown how the interaction of these cloud systems changes the cloud microphysical properties and the precipitation patterns. A big set of advanced remote-sensing techniques and retrieval algorithms are applied, so that a detailed view on the seeder-feeder cloud system is available. The gained knowledge can be used to improve weather models and weather forecasts.
Anton Kötsche, Alexander Myagkov, Leonie von Terzi, Maximilian Maahn, Veronika Ettrichrätz, Teresa Vogl, Alexander Ryzhkov, Petar Bukovcic, Davide Ori, and Heike Kalesse-Los
Atmos. Chem. Phys., 25, 14045–14070, https://doi.org/10.5194/acp-25-14045-2025, https://doi.org/10.5194/acp-25-14045-2025, 2025
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Our study combines radar observations of snow with snowfall camera observations on the ground to enhance our understanding of radar variables and snowfall properties. We found that values of an important radar variable (KDP) can be related to many different snow particle properties and number concentrations. We were able to constrain which particle sizes contribute to KDP by using computer models of snowflakes and showed which microphysical processes during snow formation can influence KDP.
Pablo Saavedra Garfias and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2025-2327, https://doi.org/10.5194/egusphere-2025-2327, 2025
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Arctic low level mixed-phase clouds were analysed from 14 years of wintertime observations from the North Slope of Alaska. We found that Arctic cloud physical properties are in correlation with changes in upwind sea ice. The cloud liquid and ice water content increases as sea ice decreases, although not at the same magnitude. Moreover, we uncovered that cloud properties have oscillation properties along the years that resemble climate indicators like El Niño Southern Oscillation among others.
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
Atmos. Meas. Tech., 18, 487–508, https://doi.org/10.5194/amt-18-487-2025, https://doi.org/10.5194/amt-18-487-2025, 2025
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We present a technique to discriminate between the Cloudnet target classification of "drizzle or rain" and sea salt aerosols that is applicable to marine Cloudnet sites. The method is crucial for investigating the occurrence of precipitation and significantly improves the Cloudnet target classification scheme for measurements over the Barbados Cloud Observatory (BCO). A first-ever analysis of the Cloudnet product including the new "haze echo" target over 2 years at the BCO is presented.
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
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In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Pablo Saavedra Garfias, Heike Kalesse-Los, Luisa von Albedyll, Hannes Griesche, and Gunnar Spreen
Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, https://doi.org/10.5194/acp-23-14521-2023, 2023
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An important Arctic climate process is the release of heat fluxes from sea ice openings to the atmosphere that influence the clouds. The characterization of this process is the objective of this study. Using synergistic observations from the MOSAiC expedition, we found that single-layer cloud properties show significant differences when clouds are coupled or decoupled to the water vapour transport which is used as physical link between the upwind sea ice openings and the cloud under observation.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
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Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Samuel Kwakye, Heike Kalesse-Los, Maximilian Maahn, Patric Seifert, Roel van Klink, Christian Wirth, and Johannes Quaas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-69, https://doi.org/10.5194/amt-2023-69, 2023
Publication in AMT not foreseen
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Insect numbers in the atmosphere can be calculated using polarimetric weather radar but they have to be identified and separated from other echoes, especially weather phenomena. Here, the separation is demonstrated using three machine-learning algorithms and insect count data from suction traps and the nature of radar measurements of different radar echoes is revealed. Random forest is the best separating algorithm and insect echoes radar measurements are distinct.
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.
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.
Teresa Vogl, Maximilian Maahn, Stefan Kneifel, Willi Schimmel, Dmitri Moisseev, and Heike Kalesse-Los
Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, https://doi.org/10.5194/amt-15-365-2022, 2022
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We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.
Heike Kalesse-Los, Willi Schimmel, Edward Luke, and Patric Seifert
Atmos. Meas. Tech., 15, 279–295, https://doi.org/10.5194/amt-15-279-2022, https://doi.org/10.5194/amt-15-279-2022, 2022
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It is important to detect the vertical distribution of cloud droplets and ice in mixed-phase clouds. Here, an artificial neural network (ANN) previously developed for Arctic clouds is applied to a mid-latitudinal cloud radar data set. The performance of this technique is contrasted to the Cloudnet target classification. For thick/multi-layer clouds, the machine learning technique is better at detecting liquid than Cloudnet, but if lidar data are available Cloudnet is at least as good as the ANN.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Etienne Cheynet, Martin Flügge, Joachim Reuder, Jasna B. Jakobsen, Yngve Heggelund, Benny Svardal, Pablo Saavedra Garfias, Charlotte Obhrai, Nicolò Daniotti, Jarle Berge, Christiane Duscha, Norman Wildmann, Ingrid H. Onarheim, and Marte Godvik
Atmos. Meas. Tech., 14, 6137–6157, https://doi.org/10.5194/amt-14-6137-2021, https://doi.org/10.5194/amt-14-6137-2021, 2021
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The COTUR campaign explored the structure of wind turbulence above the ocean to improve the design of future multi-megawatt offshore wind turbines. Deploying scientific instruments offshore is both a financial and technological challenge. Therefore, lidar technology was used to remotely measure the wind above the ocean from instruments located on the seaside. The experimental setup is tailored to the study of the spatial correlation of wind gusts, which governs the wind loading on structures.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Cited articles
Araki, K., Murakami, M., Ishimoto, H., and Tajiri, T.: Ground-Based Microwave Radiometer Variational Analysis during No-Rain and Rain Conditions, Sola, 11, 108–112, https://doi.org/10.2151/sola.2015-026, 2015. a
Böck, T., Pospichal, B., and Löhnert, U.: Measurement uncertainties of scanning microwave radiometers and their influence on temperature profiling, Atmos. Meas. Tech., 17, 219–233, https://doi.org/10.5194/amt-17-219-2024, 2024. a
Cimini, D., Campos, E., Ware, R., Albers, S., Giuliani, G., Oreamuno, J., Joe, P., Koch, S. E., Cober, S., and Westwater, E.: Thermodynamic Atmospheric Profiling During the 2010 Winter Olympics Using Ground-Based Microwave Radiometry, IEEE T. Geosci. Remote, 49, 4959–4969, https://doi.org/10.1109/TGRS.2011.2154337, 2011. a, b, c
Cimini, D., Rosenkranz, P. W., Tretyakov, M. Y., Koshelev, M. A., and Romano, F.: Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals, Atmos. Chem. Phys., 18, 15231–15259, https://doi.org/10.5194/acp-18-15231-2018, 2018. a
Crewell, S. and Löhnert, U.: Accuracy of Boundary Layer Temperature Profiles Retrieved With Multifrequency Multiangle Microwave Radiometry, IEEE T. Geosci. Remote, 45, 2195–2201, https://doi.org/10.1109/TGRS.2006.888434, 2007. a, b, c, d
Decker, M. T., Westwater, E. R., and Guiraud, F. O.: Experimental Evaluation of Ground-Based Microwave Radiometric Sensing of Atmospheric Temperature and Water Vapor Profiles, J. Appl. Meteorol. Clim., 17, 1788–1795, https://doi.org/10.1175/1520-0450(1978)017<1788:EEOGBM>2.0.CO;2, 1978. a
Foth, A.: Brightness Temperature Data and Weather Station Data from General Scans of the Microwave Radiometer HATPRO, Zenodo [data set], https://doi.org/10.5281/zenodo.13692454, 2024a. a
Foth, A. and Pospichal, B.: Optimal estimation of water vapour profiles using a combination of Raman lidar and microwave radiometer, Atmos. Meas. Tech., 10, 3325–3344, https://doi.org/10.5194/amt-10-3325-2017, 2017. a
Güldner, J. and Spänkuch, D.: Results of Year-Round Remotely Sensed Integrated Water Vapor by Ground-Based Microwave Radiometry, J. Appl. Meteorol. Clim., 38, 981–988, https://doi.org/10.1175/1520-0450(1999)038<0981:ROYRRS>2.0.CO;2, 1999. a
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 Pressure Levels from 1940 to Present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.6860a573, 2019. a
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., 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., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 Global Reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
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: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations, B. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007. a
Jensen, M. P., Holdridge, D. J., Survo, P., Lehtinen, R., Baxter, S., Toto, T., and Johnson, K. L.: Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains site, Atmos. Meas. Tech., 9, 3115–3129, https://doi.org/10.5194/amt-9-3115-2016, 2016. a
Karstens, U., Simmer, C., and Ruprecht, E.: Remote Sensing of Cloud Liquid Water, Meteorol. Atmos. Phys., 54, 157–171, https://doi.org/10.1007/BF01030057, 1994. a
Kazama, S., Rose, T., Zimmermann, R., and Zimmermann, R.: A Precision Autocalibrating 7 Channel Radiometer for Environmental Research Applications, J. Remote Sens. Soc. Jpn., 19, 265–273, https://doi.org/10.11440/rssj1981.19.265, 1999. a
Küchler, N., Turner, D. D., Löhnert, U., and Crewell, S.: Calibrating Ground-based Microwave Radiometers: Uncertainty and Drifts, Radio Sci., 51, 311–327, https://doi.org/10.1002/2015RS005826, 2016. a
Larosa, S., Cimini, D., Gallucci, D., Nilo, S. T., and Romano, F.: PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations, Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, 2024. a
Lehmann, V.: Custom collection of Mwr Level 1c Data from Lindenberg between 16 Jul and 7 Sep 2020, ACTRIS Cloud remote sensing data centre unit (CLU) [data set], https://doi.org/10.60656/e938967bc0524dee, 2023. a
Liebe, H. J., Hufford, G. A., and Cotton, M. G.: Propagation Modeling of Moist Air and Suspended Water/Ice Particles at Frequencies below 1000 GHz, in: AGARD Conference Proceedings 542: Atmospheric Propagation Effects through Natural and Man-Made Obscurants for Visible to MM-Wave Radiation Electromagnetic Wave Propagation Panel Symposium, Palma de Mallorca, Spain, 17–20 May 1993, https://its.ntia.gov/publications/details.aspx?pub=2670 (last access: 9 December 2024), 1993. a
Löhnert, U. and Crewell, S.: Accuracy of Cloud Liquid Water Path from Ground-Based Microwave Radiometry 1. Dependency on Cloud Model Statistics, Radio Sci., 38, 8041, https://doi.org/10.1029/2002RS002654, 2003. a, b
Löhnert, U. and Maier, O.: Operational profiling of temperature using ground-based microwave radiometry at Payerne: prospects and challenges, Atmos. Meas. Tech., 5, 1121–1134, https://doi.org/10.5194/amt-5-1121-2012, 2012. a
Löhnert, U., van Meijgaard, E., Baltink, H. K., Groß, S., and Boers, R.: Accuracy Assessment of an Integrated Profiling Technique for Operationally Deriving Profiles of Temperature, Humidity, and Cloud Liquid Water, J. Geophys. Res., 112, D04205, https://doi.org/10.1029/2006JD007379, 2007. a
Maahn, M., Turner, D. D., Löhnert, U., Posselt, D. J., Ebell, K., Mace, G. G., and Comstock, J. M.: Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know, B. Am. Meteorol. Soc., 101, E1512–E1523, https://doi.org/10.1175/BAMS-D-19-0027.1, 2020. a, b
Marke, T., Löhnert, U., Tukiainen, S., Siipola, T., and Pospichal, B.: MWRpy: A Python Package for Processing Microwave Radiometer Data, Journal of Open Source Software., 9, 6733, https://doi.org/10.21105/joss.06733, 2024 (data available at: https://github.com/actris-cloudnet/mwrpy, last access: 9 December 2024). a, b
Maschwitz, G., Löhnert, U., Crewell, S., Rose, T., and Turner, D. D.: Investigation of ground-based microwave radiometer calibration techniques at 530 hPa, Atmos. Meas. Tech., 6, 2641–2658, https://doi.org/10.5194/amt-6-2641-2013, 2013. a
Mech, M., Maahn, M., Ori, D., and Orlandi, E.: PAMTRA: Passive and Active Microwave TRAnsfer Tool v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.3582992, 2019. a
Mech, M., Maahn, M., Kneifel, S., Ori, D., Orlandi, E., Kollias, P., Schemann, V., and Crewell, S.: PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, 2020. a, b
O'Connor, E.: Custom collection of model data from Lindenberg between 14 Jul and 20 Oct 2020, ACTRIS Cloud remote sensing data centre unit (CLU) [data set], https://doi.org/10.60656/ca8017ee6ef94027, 2023. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding - Theory and Practice, Vol. 2, World Scientific Publishing, https://doi.org/10.1142/3171, 2000. a
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A Network Suitable Microwave Radiometer for Operational Monitoring of the Cloudy Atmosphere, Atmos. Res., 75, 183–200, https://doi.org/10.1016/j.atmosres.2004.12.005, 2005. a, b
Schnitt, S., Foth, A., Kalesse-Los, H., Mech, M., Acquistapace, C., Jansen, F., Löhnert, U., Pospichal, B., Röttenbacher, J., Crewell, S., and Stevens, B.: Ground- and ship-based microwave radiometer measurements during EUREC4A, Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, 2024. a
Simmer, C.: Satellitenfernerkundung Hydrologischer Parameter Der Atmosphäre Mit Mikrowellen, Kovač, ISBN 3860641964, 1994. a
Solheim, F., Godwin, J. R., Westwater, E. R., Han, Y., Keihm, S. J., Marsh, K., and Ware, R.: Radiometric Profiling of Temperature, Water Vapor and Cloud Liquid Water Using Various Inversion Methods, Radio Sci., 33, 393–404, https://doi.org/10.1029/97RS03656, 1998. a
Sun, B., Reale, T., Schroeder, S., Pettey, M., and Smith, R.: On the Accuracy of Vaisala RS41 versus RS92 Upper-Air Temperature Observations, J. Atmos. Ocean. Tech., 36, 635–653, https://doi.org/10.1175/JTECH-D-18-0081.1, 2019. a
Turner, D., Cadeddu, M., Löhnert, U., Crewell, S., and Vogelmann, A.: Modifications to the Water Vapor Continuum in the Microwave Suggested by Ground-Based 150-GHz Observations, IEEE T. Geosci. Remote, 47, 3326–3337, https://doi.org/10.1109/TGRS.2009.2022262, 2009. a
Walbröl, A., Crewell, S., Engelmann, R., Orlandi, E., Griesche, H., Radenz, M., Hofer, J., Althausen, D., Maturilli, M., and Ebell, K.: Atmospheric Temperature, Water Vapour and Liquid Water Path from Two Microwave Radiometers during MOSAiC, Sci Data, 9, 534, https://doi.org/10.1038/s41597-022-01504-1, 2022. a
Wandinger, U.: Raman Lidar, in: Lidar – Range-Resolved Optical Remote Sensing of the Atmosphere, in: Springer Series in Optical Sciences, edited by: Weitkamp, C., Springer Berlin/Heidelberg, 102, 241–271, ISBN 0-387-40075-3, 2005. a
Ware, R., Cimini, D., Herzegh, P., Marzano, F., Vivekanandan, J., and Westwater, E.: Ground-Based Microwave Radiometer Measurements during Preicipitation, in: 8th Specialst Meeting on Microwave Radiometry, Rome, Italy, 24–27 February 2004, p. 3, 2004. a
Ware, R., Cimini, D., Campos, E., Giuliani, G., Albers, S., Nelson, M., Koch, S. E., Joe, P., and Cober, S.: Thermodynamic and Liquid Profiling during the 2010 Winter Olympics, Atmos. Res., 132–133, 278–290, https://doi.org/10.1016/j.atmosres.2013.05.019, 2013. a
Westwater, E. R., Crewell, S., Mätzler, C., and Cimini, D.: Principles of Surface-Based Microwave and Millimeter Wave Radiometric Remote Sensing of the Troposphere, Quad. Soc. Ital. Elettromagnetismo, 1, 50–90, 2005. a
Xu, G., Ware, R. S., Zhang, W., Feng, G., Liao, K., and Liu, Y.: Effect of Off-Zenith Observations on Reducing the Impact of Precipitation on Ground-Based Microwave Radiometer Measurement Accuracy, Atmos. Res., 140–141, 85–94, https://doi.org/10.1016/j.atmosres.2014.01.021, 2014. a, b
Short summary
Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Microwave radiometers are usually not able to provide atmospheric quantities such as temperature...