Articles | Volume 8, issue 1
https://doi.org/10.5194/amt-8-237-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-237-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Jan 2015
Research article |
| 12 Jan 2015
A depolarisation lidar-based method for the determination of liquid-cloud microphysical properties
D. P. Donovan
CORRESPONDING AUTHOR
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE, De Bilt, the Netherlands
H. Klein Baltink
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE, De Bilt, the Netherlands
J. S. Henzing
Netherlands Organisation for Applied Scientific Research (TNO), Princetonlaan 6, Utrecht, the Netherlands
S. R. de Roode
Technical University of Delft (TUD), Delft, the Netherlands
A. P. Siebesma
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE, De Bilt, the Netherlands
Technical University of Delft (TUD), Delft, the Netherlands
Related authors
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-327, https://doi.org/10.5194/egusphere-2023-327, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
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 benefits of MSI in observing the complete scene besides the satellite track and to extend the lidar information to the swath. The algorithm is validated against simulated test scenes.
David Patrick Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-384, https://doi.org/10.5194/egusphere-2023-384, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The Earth Clouds and Radiation Explorer mission (EarthCARE) is an upcoming 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 was used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-145, https://doi.org/10.5194/egusphere-2023-145, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
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 L2 processing chain, in which the microphysical retrievals and target classification are performed.
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
EGUsphere, https://doi.org/10.5194/egusphere-2022-1241, https://doi.org/10.5194/egusphere-2022-1241, 2022
Short summary
Short summary
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.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-300, https://doi.org/10.5194/amt-2022-300, 2022
Preprint under review for AMT
Short summary
Short summary
The Level 2 algorithms development of EarthCARE satellite mission requires realistic three-dimensional cloud and aerosols scenes along the satellite orbits. One of the best way to produce these scenes is to use high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This manuscript describes the production and validation of three EarthCARE test scenes.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
EGUsphere, https://doi.org/10.5194/egusphere-2022-1217, https://doi.org/10.5194/egusphere-2022-1217, 2022
Short summary
Short summary
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 allowing a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Martin de Graaf, Karolina Sarna, Jessica Brown, Elma Tenner, Manon Schenkels, and Dave Donovan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-473, https://doi.org/10.5194/acp-2022-473, 2022
Revised manuscript under review for ACP
Short summary
Short summary
Simultaneous measurements were performed of cloud droplet sizes and smoke particles in and near clouds over the Ascension Island, a remote island in the Atlantic Ocean to test the hypothesis that more smoke particles will result in more but smaller cloud droplets. This was done during the dry season in Africa when vegetation fires produce smoke plumes drifting over the ocean, affecting the cloud droplet sizes over the ocean and the island.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Stephanie P. Rusli, David P. Donovan, and Herman W. J. Russchenberg
Atmos. Meas. Tech., 10, 4777–4803, https://doi.org/10.5194/amt-10-4777-2017, https://doi.org/10.5194/amt-10-4777-2017, 2017
Short summary
Short summary
A retrieval method exploiting a synergy of radar, lidar, and microwave radiometer measurements is developed to simultaneously derive microphysical properties of cloud and drizzle in a physically consistent way. After successful tests with simulated scenes, this technique is applied to data collected in Cabauw, the Netherlands. Evaluation of the results shows that the retrieved cloud and drizzle properties are consistent with what is derived from multiple independent retrieval methods.
Marco de Bruine, Arnoud Apituley, David Patrick Donovan, Hendrik Klein Baltink, and Marijn Jorrit de Haij
Atmos. Meas. Tech., 10, 1893–1909, https://doi.org/10.5194/amt-10-1893-2017, https://doi.org/10.5194/amt-10-1893-2017, 2017
Short summary
Short summary
To know how air pollution moves away from their sources, we need to know the height of the pollution. We use a laser instrument that detects particles of air pollution to precisely measure the height of the particles. Now we want to detect the layer where the pollution is. As the height of this layer changes with time it is difficult to automatically follow the correct layer. Pathfinder, which works like route planners that find the shortest way, improves this task.
X. J. Sun, R. W. Zhang, G. J. Marseille, A. Stoffelen, D. Donovan, L. Liu, and J. Zhao
Atmos. Meas. Tech., 7, 2695–2717, https://doi.org/10.5194/amt-7-2695-2014, https://doi.org/10.5194/amt-7-2695-2014, 2014
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-327, https://doi.org/10.5194/egusphere-2023-327, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
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 benefits of MSI in observing the complete scene besides the satellite track and to extend the lidar information to the swath. The algorithm is validated against simulated test scenes.
David Patrick Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-384, https://doi.org/10.5194/egusphere-2023-384, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The Earth Clouds and Radiation Explorer mission (EarthCARE) is an upcoming 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 was used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-145, https://doi.org/10.5194/egusphere-2023-145, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
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 L2 processing chain, in which the microphysical retrievals and target classification are performed.
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
EGUsphere, https://doi.org/10.5194/egusphere-2022-1241, https://doi.org/10.5194/egusphere-2022-1241, 2022
Short summary
Short summary
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.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-300, https://doi.org/10.5194/amt-2022-300, 2022
Preprint under review for AMT
Short summary
Short summary
The Level 2 algorithms development of EarthCARE satellite mission requires realistic three-dimensional cloud and aerosols scenes along the satellite orbits. One of the best way to produce these scenes is to use high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This manuscript describes the production and validation of three EarthCARE test scenes.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
EGUsphere, https://doi.org/10.5194/egusphere-2022-1217, https://doi.org/10.5194/egusphere-2022-1217, 2022
Short summary
Short summary
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 allowing a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Martin de Graaf, Karolina Sarna, Jessica Brown, Elma Tenner, Manon Schenkels, and Dave Donovan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-473, https://doi.org/10.5194/acp-2022-473, 2022
Revised manuscript under review for ACP
Short summary
Short summary
Simultaneous measurements were performed of cloud droplet sizes and smoke particles in and near clouds over the Ascension Island, a remote island in the Atlantic Ocean to test the hypothesis that more smoke particles will result in more but smaller cloud droplets. This was done during the dry season in Africa when vegetation fires produce smoke plumes drifting over the ocean, affecting the cloud droplet sizes over the ocean and the island.
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
Short summary
Short summary
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.
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
Short summary
Short summary
This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Xabier Pedruzo-Bagazgoitia, Stephan R. de Roode, Bianca Adler, Karmen Babić, Cheikh Dione, Norbert Kalthoff, Fabienne Lohou, Marie Lothon, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 20, 2735–2754, https://doi.org/10.5194/acp-20-2735-2020, https://doi.org/10.5194/acp-20-2735-2020, 2020
Short summary
Short summary
Using a high-resolution model we simulate the transition from night to day clouds on southern West Africa using observations from the DACCIWA project. We find that the radiative effects of clouds help mantain a thick cloud layer in the night, while the mixing of cloud air with air above during the day, aided by moisture and heat fluxes at the surface, thins this layer and promotes its transition to other clouds. The effect of changing wind with height accelerates the transition.
Stephanie P. Rusli, David P. Donovan, and Herman W. J. Russchenberg
Atmos. Meas. Tech., 10, 4777–4803, https://doi.org/10.5194/amt-10-4777-2017, https://doi.org/10.5194/amt-10-4777-2017, 2017
Short summary
Short summary
A retrieval method exploiting a synergy of radar, lidar, and microwave radiometer measurements is developed to simultaneously derive microphysical properties of cloud and drizzle in a physically consistent way. After successful tests with simulated scenes, this technique is applied to data collected in Cabauw, the Netherlands. Evaluation of the results shows that the retrieved cloud and drizzle properties are consistent with what is derived from multiple independent retrieval methods.
Marco de Bruine, Arnoud Apituley, David Patrick Donovan, Hendrik Klein Baltink, and Marijn Jorrit de Haij
Atmos. Meas. Tech., 10, 1893–1909, https://doi.org/10.5194/amt-10-1893-2017, https://doi.org/10.5194/amt-10-1893-2017, 2017
Short summary
Short summary
To know how air pollution moves away from their sources, we need to know the height of the pollution. We use a laser instrument that detects particles of air pollution to precisely measure the height of the particles. Now we want to detect the layer where the pollution is. As the height of this layer changes with time it is difficult to automatically follow the correct layer. Pathfinder, which works like route planners that find the shortest way, improves this task.
Mark J. Webb, Timothy Andrews, Alejandro Bodas-Salcedo, Sandrine Bony, Christopher S. Bretherton, Robin Chadwick, Hélène Chepfer, Hervé Douville, Peter Good, Jennifer E. Kay, Stephen A. Klein, Roger Marchand, Brian Medeiros, A. Pier Siebesma, Christopher B. Skinner, Bjorn Stevens, George Tselioudis, Yoko Tsushima, and Masahiro Watanabe
Geosci. Model Dev., 10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, https://doi.org/10.5194/gmd-10-359-2017, 2017
Short summary
Short summary
The Cloud Feedback Model Intercomparison Project (CFMIP) aims to improve understanding of cloud-climate feedback mechanisms and evaluation of cloud processes and cloud feedbacks in climate models. CFMIP also aims to improve understanding of circulation, regional-scale precipitation and non-linear changes. CFMIP is contributing to the 6th phase of the Coupled Model Intercomparison Project (CMIP6) by coordinating a hierarchy of targeted experiments with cloud-related model outputs.
J. J. van der Dussen, S. R. de Roode, and A. P. Siebesma
Atmos. Chem. Phys., 16, 691–701, https://doi.org/10.5194/acp-16-691-2016, https://doi.org/10.5194/acp-16-691-2016, 2016
Short summary
Short summary
A large-eddy simulation model is used to show that a weakening of the large-scale subsidence, which is associated with a future warmer climate, leads to a delay of the moment of break up of stratocumulus clouds during subtropical stratocumulus transitions. To understand what causes this delay, a novel analysis method is used to distil the contributions of individual physical processes to the evolution of the stratocumulus cloud thickness.
A. Di Noia, O. P. Hasekamp, G. van Harten, J. H. H. Rietjens, J. M. Smit, F. Snik, J. S. Henzing, J. de Boer, C. U. Keller, and H. Volten
Atmos. Meas. Tech., 8, 281–299, https://doi.org/10.5194/amt-8-281-2015, https://doi.org/10.5194/amt-8-281-2015, 2015
Short summary
Short summary
A neural network algorithm has been developed to retrieve aerosol microphysical parameters from ground-based measurements of skylight intensity and polarization. The neural network is capable of producing accurate estimates of aerosol optical thicknesses, effective radii and refractive index. In addition, it is shown that the use of the neural retrievals as initial guess for an iterative retrieval algorithm results in improved convergence and retrieval accuracy.
G. van Harten, J. de Boer, J. H. H. Rietjens, A. Di Noia, F. Snik, H. Volten, J. M. Smit, O. P. Hasekamp, J. S. Henzing, and C. U. Keller
Atmos. Meas. Tech., 7, 4341–4351, https://doi.org/10.5194/amt-7-4341-2014, https://doi.org/10.5194/amt-7-4341-2014, 2014
O. Geoffroy, A. P. Siebesma, and F. Burnet
Atmos. Chem. Phys., 14, 10897–10909, https://doi.org/10.5194/acp-14-10897-2014, https://doi.org/10.5194/acp-14-10897-2014, 2014
X. J. Sun, R. W. Zhang, G. J. Marseille, A. Stoffelen, D. Donovan, L. Liu, and J. Zhao
Atmos. Meas. Tech., 7, 2695–2717, https://doi.org/10.5194/amt-7-2695-2014, https://doi.org/10.5194/amt-7-2695-2014, 2014
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
D. C. S. Beddows, M. Dall'Osto, R. M. Harrison, M. Kulmala, A. Asmi, A. Wiedensohler, P. Laj, A.M. Fjaeraa, K. Sellegri, W. Birmili, N. Bukowiecki, E. Weingartner, U. Baltensperger, V. Zdimal, N. Zikova, J.-P. Putaud, A. Marinoni, P. Tunved, H.-C. Hansson, M. Fiebig, N. Kivekäs, E. Swietlicki, H. Lihavainen, E. Asmi, V. Ulevicius, P. P. Aalto, N. Mihalopoulos, N. Kalivitis, I. Kalapov, G. Kiss, G. de Leeuw, B. Henzing, C. O'Dowd, S. G. Jennings, H. Flentje, F. Meinhardt, L. Ries, H. A. C. Denier van der Gon, and A. J. H. Visschedijk
Atmos. Chem. Phys., 14, 4327–4348, https://doi.org/10.5194/acp-14-4327-2014, https://doi.org/10.5194/acp-14-4327-2014, 2014
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Instruments and Platforms
Processing reflectivity and Doppler velocity from EarthCARE’s cloud profiling radar: the C-FMR, C-CD and C-APC products
3D cloud envelope and cloud development velocity from simulated CLOUD (C3IEL) stereo images
Passive ground-based remote sensing of radiation fog
Locations for the best lidar view of mid-level and high clouds
VELOX – a new thermal infrared imager for airborne remote sensing of cloud and surface properties
Above-aircraft cirrus cloud and aerosol optical depth from hyperspectral irradiances measured by a total-diffuse radiometer
Impact of second-trip echoes for space-borne high-pulse-repetition-frequency nadir-looking W-band cloud radars
Spaceborne differential absorption radar water vapor retrieval capabilities in tropical and subtropical boundary layer cloud regimes
Multifrequency radar observations of clouds and precipitation including the G-band
Can machine learning correct microwave humidity radiances for the influence of clouds?
McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing
Cirrus cloud shape detection by tomographic extinction retrievals from infrared limb emission sounder measurements
Absolute calibration method for frequency-modulated continuous wave (FMCW) cloud radars based on corner reflectors
Evaluation of the reflectivity calibration of W-band radars based on observations in rain
A technical description of the Balloon Lidar Experiment (BOLIDE)
Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106
Mind the gap – Part 2: Improving quantitative estimates of cloud and rain water path in oceanic warm rain using spaceborne radars
Ice crystal characterization in cirrus clouds II: radiometric characterization of HaloCam for the quantitative analysis of halo displays
Mind the gap – Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars
Free-fall experiments of volcanic ash particles using a 2-D video disdrometer
Microwave Radar/radiometer for Arctic Clouds (MiRAC): first insights from the ACLOUD campaign
A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds
Evaluation of differential absorption radars in the 183 GHz band for profiling water vapour in ice clouds
Use of polarimetric radar measurements to constrain simulated convective cell evolution: a pilot study with Lagrangian tracking
Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach
Halo ratio from ground-based all-sky imaging
Aircraft-based stereographic reconstruction of 3-D cloud geometry
Polarization lidar: an extended three-signal calibration approach
The NCAS mobile dual-polarisation Doppler X-band weather radar (NXPol)
Initial report on polar mesospheric cloud observations by Himawari-8
Combining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds
A simple biota removal algorithm for 35 GHz cloud radar measurements
Improved cloud-phase determination of low-level liquid and mixed-phase clouds by enhanced polarimetric lidar
All-sky photogrammetry techniques to georeference a cloud field
Depolarization calibration and measurements using the CANDAC Rayleigh–Mie–Raman lidar at Eureka, Canada
Ice crystal characterization in cirrus clouds: a sun-tracking camera system and automated detection algorithm for halo displays
ISMAR: an airborne submillimetre radiometer
Sky camera geometric calibration using solar observations
Application of oxygen A-band equivalent width to disambiguate downwelling radiances for cloud optical depth measurement
Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals
How big is an OMI pixel?
Differential absorption radar techniques: water vapor retrievals
Design and characterization of specMACS, a multipurpose hyperspectral cloud and sky imager
A microbolometer-based far infrared radiometer to study thin ice clouds in the Arctic
Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)
Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields
Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals
Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler
Performance assessment of a triple-frequency spaceborne cloud–precipitation radar concept using a global cloud-resolving model
Development of a sky imaging system for short-term solar power forecasting
Pavlos Kollias, Bernat Puidgomènech Treserras, Alessandro Battaglia, Paloma Borque, and Aleksandra Tatarevic
EGUsphere, https://doi.org/10.5194/egusphere-2022-1284, https://doi.org/10.5194/egusphere-2022-1284, 2022
Short summary
Short summary
The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by European Space Agency (ESA) and the 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.
Paolo Dandini, Céline Cornet, Renaud Binet, Laetitia Fenouil, Vadim Holodovsky, Yoav Y. Schechner, Didier Ricard, and Daniel Rosenfeld
Atmos. Meas. Tech., 15, 6221–6242, https://doi.org/10.5194/amt-15-6221-2022, https://doi.org/10.5194/amt-15-6221-2022, 2022
Short summary
Short summary
3D cloud envelope and development velocity are retrieved from realistic simulations of multi-view
CLOUD (C3IEL) images. Cloud development velocity is derived by finding matching features
between acquisitions separated by 20 s. The tie points are then mapped from image to space via 3D
reconstruction of the cloud envelope obtained from 2 simultaneous images. The retrieved cloud
topography as well as the velocities are in good agreement with the estimates obtained from the
physical models.
Heather Guy, David D. Turner, Von P. Walden, Ian M. Brooks, and Ryan R. Neely
Atmos. Meas. Tech., 15, 5095–5115, https://doi.org/10.5194/amt-15-5095-2022, https://doi.org/10.5194/amt-15-5095-2022, 2022
Short summary
Short summary
Fog formation is highly sensitive to near-surface temperatures and humidity profiles. Passive remote sensing instruments can provide continuous measurements of the vertical temperature and humidity profiles and liquid water content, which can improve fog forecasts. Here we compare the performance of collocated infrared and microwave remote sensing instruments and demonstrate that the infrared instrument is especially sensitive to the onset of thin radiation fog.
Matthias Tesche and Vincent Noel
Atmos. Meas. Tech., 15, 4225–4240, https://doi.org/10.5194/amt-15-4225-2022, https://doi.org/10.5194/amt-15-4225-2022, 2022
Short summary
Short summary
Mid-level and high clouds can be considered natural laboratories for studying cloud glaciation in the atmosphere. While they can be conveniently observed from ground with lidar, such measurements require a clear line of sight between the instrument and the target cloud. Here, observations of clouds with two spaceborne lidars are used to assess where ground-based lidar measurements of mid- and upper-level clouds are least affected by the light-attenuating effect of low-level clouds.
Michael Schäfer, Kevin Wolf, André Ehrlich, Christoph Hallbauer, Evelyn Jäkel, Friedhelm Jansen, Anna Elizabeth Luebke, Joshua Müller, Jakob Thoböll, Timo Röschenthaler, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 15, 1491–1509, https://doi.org/10.5194/amt-15-1491-2022, https://doi.org/10.5194/amt-15-1491-2022, 2022
Short summary
Short summary
The new airborne thermal infrared imager VELOX is introduced. It measures two-dimensional fields of spectral thermal infrared radiance or brightness temperature within the large atmospheric window. The technical specifications as well as necessary calibration and correction procedures are presented. Example measurements from the first field deployment are analysed with respect to cloud coverage and cloud top altitude.
Matthew S. Norgren, John Wood, K. Sebastian Schmidt, Bastiaan van Diedenhoven, Snorre A. Stamnes, Luke D. Ziemba, Ewan C. Crosbie, Michael A. Shook, A. Scott Kittelman, Samuel E. LeBlanc, Stephen Broccardo, Steffen Freitag, and Jeffrey S. Reid
Atmos. Meas. Tech., 15, 1373–1394, https://doi.org/10.5194/amt-15-1373-2022, https://doi.org/10.5194/amt-15-1373-2022, 2022
Short summary
Short summary
A new spectral instrument (SPN-S), with the ability to partition solar radiation into direct and diffuse components, is used in airborne settings to study the optical properties of aerosols and cirrus. It is a low-cost and mechanically simple system but has higher measurement uncertainty than existing standards. This challenge is overcome by utilizing the unique measurement capabilities to develop new retrieval techniques. Validation is done with data from two NASA airborne research campaigns.
Alessandro Battaglia
Atmos. Meas. Tech., 14, 7809–7820, https://doi.org/10.5194/amt-14-7809-2021, https://doi.org/10.5194/amt-14-7809-2021, 2021
Short summary
Short summary
Space-borne radar returns can be contaminated by artefacts caused by radiation that undergoes multiple scattering events and appears to originate from ranges well below the surface range. While such artefacts have been rarely observed from the currently deployed systems, they may become a concern in future cloud radar systems, potentially enhancing cloud cover high up in the troposphere via ghost returns.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
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
Short summary
Short summary
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.
Inderpreet Kaur, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan
Atmos. Meas. Tech., 14, 2957–2979, https://doi.org/10.5194/amt-14-2957-2021, https://doi.org/10.5194/amt-14-2957-2021, 2021
Short summary
Short summary
Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.
Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, Valery Shcherbakov, Céline Cornet, Julien Delanoë, Yahya Gour, Olivier Jourdan, Sandra Banson, and Edouard Bray
Atmos. Meas. Tech., 14, 199–221, https://doi.org/10.5194/amt-14-199-2021, https://doi.org/10.5194/amt-14-199-2021, 2021
Short summary
Short summary
Spaceborne lidar and radar are suitable tools to investigate cloud vertical properties on a global scale. This paper presents the McRALI code that provides simulations of lidar and radar signals from the EarthCARE mission. Regarding radar signals, cloud heterogeneity induces a severe bias in velocity estimates. Regarding lidar signals, multiple scattering is not negligible. Our results also give some insight into the reliability of lidar signal modeling using independent column approximation.
Jörn Ungermann, Irene Bartolome, Sabine Griessbach, Reinhold Spang, Christian Rolf, Martina Krämer, Michael Höpfner, and Martin Riese
Atmos. Meas. Tech., 13, 7025–7045, https://doi.org/10.5194/amt-13-7025-2020, https://doi.org/10.5194/amt-13-7025-2020, 2020
Short summary
Short summary
This study examines the potential of new IR limb imager instruments and tomographic methods for cloud detection purposes. Simple color-ratio-based methods are examined and compared against more involved nonlinear convex optimization. In a second part, 3-D measurements of the airborne limb sounder GLORIA taken during the Wave-driven ISentropic Exchange campaign are used to exemplarily derive the location and extent of small-scale cirrus clouds with high spatial accuracy.
Felipe Toledo, Julien Delanoë, Martial Haeffelin, Jean-Charles Dupont, Susana Jorquera, and Christophe Le Gac
Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, https://doi.org/10.5194/amt-13-6853-2020, 2020
Short summary
Short summary
Cloud observations are essential to rainfall, fog and climate change forecasts. One key instrument for these observations is cloud radar. Yet, discrepancies are found when comparing radars from different ground stations or satellites. Our work presents a calibration methodology for cloud radars based on reference targets, including an analysis of the uncertainty sources. The method enables the calibration of reference instruments to improve the quality and value of the cloud radar network data.
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech., 13, 5799–5825, https://doi.org/10.5194/amt-13-5799-2020, https://doi.org/10.5194/amt-13-5799-2020, 2020
Short summary
Short summary
This study shows two methods for evaluating the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for operational monitoring of measurement quality.
Bernd Kaifler, Dimitry Rempel, Philipp Roßi, Christian Büdenbender, Natalie Kaifler, and Volodymyr Baturkin
Atmos. Meas. Tech., 13, 5681–5695, https://doi.org/10.5194/amt-13-5681-2020, https://doi.org/10.5194/amt-13-5681-2020, 2020
Short summary
Short summary
The Balloon Lidar Experiment was the first lidar dedicated to measurements in the mesosphere flown on a balloon. During a 6 d flight, it made high-resolution observations of polar mesospheric clouds which form at high latitudes during summer at ~ 83 km altitude and are the highest clouds in Earth's atmosphere. We describe the instrument and assess its performance. We could detect fainter clouds with higher resolution than what is possible with ground-based instruments.
Hannes J. Griesche, Patric Seifert, Albert Ansmann, Holger Baars, Carola Barrientos Velasco, Johannes Bühl, Ronny Engelmann, Martin Radenz, Yin Zhenping, and Andreas Macke
Atmos. Meas. Tech., 13, 5335–5358, https://doi.org/10.5194/amt-13-5335-2020, https://doi.org/10.5194/amt-13-5335-2020, 2020
Short summary
Short summary
In summer 2017, the research vessel Polarstern performed cruise PS106 to the Arctic north of Svalbard. In the frame of the cruise, remote-sensing observations of the atmosphere were performed on Polarstern to continuously monitor aerosol and clouds above the vessel. In our study, we present the deployed instrumentation and applied data analysis methods and provide case studies of the aerosol and cloud observations made during the cruise. Statistics of low-cloud occurrence are presented as well.
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
Short summary
Short summary
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.
Linda Forster, Meinhard Seefeldner, Andreas Baumgartner, Tobias Kölling, and Bernhard Mayer
Atmos. Meas. Tech., 13, 3977–3991, https://doi.org/10.5194/amt-13-3977-2020, https://doi.org/10.5194/amt-13-3977-2020, 2020
Short summary
Short summary
We present a procedure for both the geometric and absolute radiometric characterization of the weather-proof RGB camera HaloCamRAW, which is part of our automated halo observation system HaloCam, designed for the quantitative analysis of halo displays. By comparing the calibrated HaloCamRAW radiances of a 22° halo scene with radiative transfer simulations, we demonstrate the potential of developing a retrieval method for ice crystal properties, such as size, shape, and surface roughness.
Katia Lamer, Pavlos Kollias, Alessandro Battaglia, and Simon Preval
Atmos. Meas. Tech., 13, 2363–2379, https://doi.org/10.5194/amt-13-2363-2020, https://doi.org/10.5194/amt-13-2363-2020, 2020
Short summary
Short summary
According to ground-based radar observations, 50 % of liquid low-level clouds over the Atlantic extend below 1.2 km and are thinner than 400 m, thus limiting their detection from space. Using an emulator, we estimate that a 250 m resolution radar would capture cloud base better than the CloudSat radar which misses about 52 %. The more sensitive EarthCARE radar is expected to capture cloud cover but stretch cloud. This calls for the operation of interlaced pulse modes for future space missions.
Sung-Ho Suh, Masayuki Maki, Masato Iguchi, Dong-In Lee, Akihiko Yamaji, and Tatsuya Momotani
Atmos. Meas. Tech., 12, 5363–5379, https://doi.org/10.5194/amt-12-5363-2019, https://doi.org/10.5194/amt-12-5363-2019, 2019
Short summary
Short summary
This is a fundamental study on the features of aerodynamic parameters: terminal velocity, axis ratio, and canting angle. These are necessary for developing a quantitative ash fall estimation method based on weather radar. They were analyzed under controlled conditions from laboratory free-fall experiments, since the aerodynamic properties of the particles are highly dependent on external conditions. These results will help in the development of quantitative ash estimation.
Mario Mech, Leif-Leonard Kliesch, Andreas Anhäuser, Thomas Rose, Pavlos Kollias, and Susanne Crewell
Atmos. Meas. Tech., 12, 5019–5037, https://doi.org/10.5194/amt-12-5019-2019, https://doi.org/10.5194/amt-12-5019-2019, 2019
Short summary
Short summary
An improved understanding of Arctic mixed-phase clouds and their contribution to Arctic warming can be achieved by observations from airborne platforms with remote sensing instruments. Such an instrument is MiRAC combining active and passive techniques to gain information on the distribution of clouds, the occurrence of precipitation, and the amount of liquid and ice within the cloud. Operated during a campaign in Arctic summer, it could observe lower clouds often not seen by spaceborne radars.
Emma Hopkin, Anthony J. Illingworth, Cristina Charlton-Perez, Chris D. Westbrook, and Sue Ballard
Atmos. Meas. Tech., 12, 4131–4147, https://doi.org/10.5194/amt-12-4131-2019, https://doi.org/10.5194/amt-12-4131-2019, 2019
Short summary
Short summary
Ceilometers are laser cloud base recorders which retrieve information about atmospheric aerosol and differing cloud types. In order to ensure the information retrieved from the ceilometer is correct and comparable with other ceilometers in an observation network, a calibration is needed. Presented here is a novel automated calibration method, which includes a correction for the effects of water vapour in the atmosphere and shows its application on the UK Met Office's ceilometer network.
Alessandro Battaglia and Pavlos Kollias
Atmos. Meas. Tech., 12, 3335–3349, https://doi.org/10.5194/amt-12-3335-2019, https://doi.org/10.5194/amt-12-3335-2019, 2019
Short summary
Short summary
This work investigates the potential of an innovative differential absorption radar for retrieving relative humidity inside ice clouds. The radar exploits the strong spectral dependence of the water vapour absorption for frequencies close to the 183 GHz water vapour band.
Results show that observations from a system with 4–6 frequencies can provide
novel information for understanding the formation and growth of ice crystals.
Ann M. Fridlind, Marcus van Lier-Walqui, Scott Collis, Scott E. Giangrande, Robert C. Jackson, Xiaowen Li, Toshihisa Matsui, Richard Orville, Mark H. Picel, Daniel Rosenfeld, Alexander Ryzhkov, Richard Weitz, and Pengfei Zhang
Atmos. Meas. Tech., 12, 2979–3000, https://doi.org/10.5194/amt-12-2979-2019, https://doi.org/10.5194/amt-12-2979-2019, 2019
Short summary
Short summary
Weather radars are offering improved capabilities to investigate storm physics, which remain poorly understood. We investigate enhanced use of such data near Houston, Texas, where pollution sources often provide a convenient contrast between polluted and clean air. We conclude that Houston is a favorable location to conduct a future field campaign during June through September because isolated storms are common and tend to last an hour, allowing frequent observations of a full life cycle.
Kevin Wolf, André Ehrlich, Marek Jacob, Susanne Crewell, Martin Wirth, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1635–1658, https://doi.org/10.5194/amt-12-1635-2019, https://doi.org/10.5194/amt-12-1635-2019, 2019
Short summary
Short summary
Using passive spectral solar radiation and active lidar, radar, and microwave measurements with HALO during NARVAL-II, the cloud droplet number concentration of shallow trade wind cumulus is estimated. With stepwise inclusion of the different instruments into the retrieval, the benefits of the synergetic approach based on artificial measurements and two cloud cases are demonstrated. Significant improvement with the synergetic method compared to the solar-radiation-only method is reported.
Paolo Dandini, Zbigniew Ulanowski, David Campbell, and Richard Kaye
Atmos. Meas. Tech., 12, 1295–1309, https://doi.org/10.5194/amt-12-1295-2019, https://doi.org/10.5194/amt-12-1295-2019, 2019
Short summary
Short summary
The halo ratio indicates the strength of the 22° cirrus halo and gives valuable information on cloud properties. We obtain it from all-sky images by applying a range of transformations and corrections and averaging brightness azimuthally over sun-centred images. The ratio is then taken at two angles from the sun, 20° and 23°, in variance from previous suggestions. While we find ratios > 1 to be linked to halos, they can also occur under scattered cumuli as artefacts due to cloud edges.
Tobias Kölling, Tobias Zinner, and Bernhard Mayer
Atmos. Meas. Tech., 12, 1155–1166, https://doi.org/10.5194/amt-12-1155-2019, https://doi.org/10.5194/amt-12-1155-2019, 2019
Short summary
Short summary
Imaging technology allows us to quickly gather information on larger cloud fields. Unlike using lidar or radar, it is difficult to obtain accurate position information about the observed clouds. This work presents a method to retrieve the missing position information using RGB images from an airborne video camera. Using field campaign data, we observe and explain a median offset of 126 m compared to lidar data and show that systematic errors across the measurement swath are well below 50 m.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, Moritz Haarig, Jörg Schmidt, and Ulla Wandinger
Atmos. Meas. Tech., 12, 1077–1093, https://doi.org/10.5194/amt-12-1077-2019, https://doi.org/10.5194/amt-12-1077-2019, 2019
Short summary
Short summary
We propose an extended formalism for a full instrumental characterization of a three-channel lidar system, allowing the retrieval of highly accurate linear depolarization profiles. The results obtained at several depolarizing scenarios, the good agreement with the retrievals of a second collocated calibrated lidar system, and the long-term stability of the calibration parameters corroborate the potential and robustness of the new technique.
Ryan R. Neely III, Lindsay Bennett, Alan Blyth, Chris Collier, David Dufton, James Groves, Daniel Walker, Chris Walden, John Bradford, Barbara Brooks, Freya I. Addison, John Nicol, and Ben Pickering
Atmos. Meas. Tech., 11, 6481–6494, https://doi.org/10.5194/amt-11-6481-2018, https://doi.org/10.5194/amt-11-6481-2018, 2018
Short summary
Short summary
Mobile X-band radars are widely used by atmospheric scientists to observe clouds and make estimates of rainfall. Here we describe the National Centre for Atmospheric Science's mobile X-band dual-polarisation Doppler radar (NXPol). NXPol is the first radar of its kind in the UK. To demonstrate the radar’s capabilities, we present examples of its use in three field campaigns as well as an example from ongoing observations at the National Facility for Atmospheric and Radio Research.
Takuo T. Tsuda, Yuta Hozumi, Kento Kawaura, Keisuke Hosokawa, Hidehiko Suzuki, and Takuji Nakamura
Atmos. Meas. Tech., 11, 6163–6168, https://doi.org/10.5194/amt-11-6163-2018, https://doi.org/10.5194/amt-11-6163-2018, 2018
Short summary
Short summary
Polar mesospheric clouds (PMCs) or noctilucent clouds (NLCs) are the highest clouds in the Earth's atmosphere. In this paper, we introduce new PMC observations by the Japanese Geostationary Earth Orbit (GEO) meteorological satellite Himawari-8, which was launched in October 2014.
Martin Radenz, Johannes Bühl, Volker Lehmann, Ulrich Görsdorf, and Ronny Leinweber
Atmos. Meas. Tech., 11, 5925–5940, https://doi.org/10.5194/amt-11-5925-2018, https://doi.org/10.5194/amt-11-5925-2018, 2018
Short summary
Short summary
Ultra-high-frequency radar wind profilers are widely used for remote sensing of horizontal and vertical wind velocity. They emit electromagnetic radiation at a wavelength of 60 cm and receive signals from both falling particles and the air itself. In this paper, we describe a method to separate both signal components with the help of an additional cloud radar system in order to come up with undisturbed measurements of both vertical air velocity and the fall velocity of particles.
Madhu Chandra R. Kalapureddy, Patra Sukanya, Subrata K. Das, Sachin M. Deshpande, Govindan Pandithurai, Andrew L. Pazamany, Jha Ambuj K., Kaustav Chakravarty, Prasad Kalekar, Hari Krishna Devisetty, and Sreenivas Annam
Atmos. Meas. Tech., 11, 1417–1436, https://doi.org/10.5194/amt-11-1417-2018, https://doi.org/10.5194/amt-11-1417-2018, 2018
Short summary
Short summary
A new technique to separate cloud and non-hydrometeor returns from a cloud radar high-resolution reflectivity measurements is proposed. The TEST algorithm potentially identifies cloud height with the theoretical echo sensitivity curves and observed echo statistics for the cloud height tracing. TEST is more robust in identifying and filtering out the biota contributions by constraining further with spectral width and LDR measurements. This algorithm improves the monsoon cloud characterization.
Robert A. Stillwell, Ryan R. Neely III, Jeffrey P. Thayer, Matthew D. Shupe, and David D. Turner
Atmos. Meas. Tech., 11, 835–859, https://doi.org/10.5194/amt-11-835-2018, https://doi.org/10.5194/amt-11-835-2018, 2018
Short summary
Short summary
This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those measurements within the context of cloud radiative effects. It is found that effects related to lidar data recording systems can cause retrieval ambiguities that alter the interpretation of cloud phase in as much as 30 % of the available data. This misinterpretation of cloud-phase data can cause a misinterpretation of the effect of cloud phase on the surface radiation budget by as much as 10 to 30 %.
Pierre Crispel and Gregory Roberts
Atmos. Meas. Tech., 11, 593–609, https://doi.org/10.5194/amt-11-593-2018, https://doi.org/10.5194/amt-11-593-2018, 2018
Short summary
Short summary
In this study, we use an all-sky stereo camera network to perform geolocation of individual elements of a cloud field in order to track individual clouds and estimate some of their morphological characteristics and their evolution in time. Furthermore, this allows use of cloud geolocation for cloud airborne measurements. For example, in the case of instrumented UAVs, the GPS coordinates of the target cloud may be communicated in real time to the autopilot.
Emily M. McCullough, Robert J. Sica, James R. Drummond, Graeme Nott, Christopher Perro, Colin P. Thackray, Jason Hopper, Jonathan Doyle, Thomas J. Duck, and Kaley A. Walker
Atmos. Meas. Tech., 10, 4253–4277, https://doi.org/10.5194/amt-10-4253-2017, https://doi.org/10.5194/amt-10-4253-2017, 2017
Short summary
Short summary
CRL lidar in the Canadian High Arctic uses lasers and a telescope to study polar clouds, essential for understanding the changing global climate. Hardware added to CRL allows it to measure the polarization of returned laser light, indicating whether cloud particles are liquid or frozen. Calibrations show that traditional analysis methods work well, although CRL was not originally set up to make this type of measurement. CRL can now measure cloud particle phase every 5 min, every 37.5 m, 24h/day.
Linda Forster, Meinhard Seefeldner, Matthias Wiegner, and Bernhard Mayer
Atmos. Meas. Tech., 10, 2499–2516, https://doi.org/10.5194/amt-10-2499-2017, https://doi.org/10.5194/amt-10-2499-2017, 2017
Short summary
Short summary
Halo displays are produced by scattering of sunlight by smooth, hexagonal ice crystals. Consequently, the presence of a halo should contain information on particle shape. This study presents HaloCam, a novel sun-tracking camera system, and an automated detection algorithm to collect and evaluate long-term halo observations. Two-year HaloCam observations revealed that about 25 % of the detected cirrus clouds occurred together with a 22° halo indicating the presence of smooth, hexagonal crystals.
Stuart Fox, Clare Lee, Brian Moyna, Martin Philipp, Ian Rule, Stuart Rogers, Robert King, Matthew Oldfield, Simon Rea, Manju Henry, Hui Wang, and R. Chawn Harlow
Atmos. Meas. Tech., 10, 477–490, https://doi.org/10.5194/amt-10-477-2017, https://doi.org/10.5194/amt-10-477-2017, 2017
Short summary
Short summary
In this paper we present the ISMAR instrument, a new airborne submillimetre radiometer designed for cloud ice remote sensing. We discuss the instrument calibration and evaluate the main sources of bias and the radiometric sensitivity in different measurement scenarios. We also compare clear-sky zenith measurements from high altitude with radiative transfer simulations to demonstrate the performance of ISMAR in flight.
Bryan Urquhart, Ben Kurtz, and Jan Kleissl
Atmos. Meas. Tech., 9, 4279–4294, https://doi.org/10.5194/amt-9-4279-2016, https://doi.org/10.5194/amt-9-4279-2016, 2016
Short summary
Short summary
A model relating the position of objects in the 3-D world to their pixel coordinates has been developed for a fixed-focal length fisheye lens camera. An associated automated method to calibrate model parameters has been developed for a daytime skyward-pointing camera. The position of the sun throughout the day is used as input to the calibration algorithm. The accuracy of the calibration was found to be on the same order as the accuracy of sun position detection in an image.
Edward R. Niple, Herman E. Scott, John A. Conant, Stephen H. Jones, Frank J. Iannarilli, and Wellesley E. Pereira
Atmos. Meas. Tech., 9, 4167–4179, https://doi.org/10.5194/amt-9-4167-2016, https://doi.org/10.5194/amt-9-4167-2016, 2016
Penny M. Rowe, Christopher J. Cox, and Von P. Walden
Atmos. Meas. Tech., 9, 3641–3659, https://doi.org/10.5194/amt-9-3641-2016, https://doi.org/10.5194/amt-9-3641-2016, 2016
Short summary
Short summary
Clouds play an important role in the rapid climate change occurring in polar regions, yet cloud measurements are challenging in such harsh, remote environments. Here we explore how well a proposed low-power infrared spectrometer, which would be highly portable, could be used to determine cloud height. Using simulated data, we estimate retrieval accuracy, finding that such an instrument would be able to constrain cloud height, particular for low, thick clouds, which are common in polar region.
Martin de Graaf, Holger Sihler, Lieuwe G. Tilstra, and Piet Stammes
Atmos. Meas. Tech., 9, 3607–3618, https://doi.org/10.5194/amt-9-3607-2016, https://doi.org/10.5194/amt-9-3607-2016, 2016
Short summary
Short summary
The shapes and sizes of the FoV from the OMI satellite instrument were determined with extensive lab tests but never verified after launch. Here, collocated measurements from MODIS, flying in formation, were used to find the most optimal shape of the OMI FoV. This shape is not quadrangular, as suggested by the provided corner coordinates of a pixel, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels.
Luis Millán, Matthew Lebsock, Nathaniel Livesey, and Simone Tanelli
Atmos. Meas. Tech., 9, 2633–2646, https://doi.org/10.5194/amt-9-2633-2016, https://doi.org/10.5194/amt-9-2633-2016, 2016
Short summary
Short summary
We discuss the theoretical capabilities of a radar technique to measure profiles of water vapor in cloudy/precipitating areas. The method uses two radar pulses at different frequencies near the 183 GHz H2O absorption line to determine water vapor profiles by measuring the differential absorption on and off the line. Results of inverting synthetic data assuming a satellite radar are presented.
Florian Ewald, Tobias Kölling, Andreas Baumgartner, Tobias Zinner, and Bernhard Mayer
Atmos. Meas. Tech., 9, 2015–2042, https://doi.org/10.5194/amt-9-2015-2016, https://doi.org/10.5194/amt-9-2015-2016, 2016
Short summary
Short summary
The new spectrometer of the Munich Aerosol Cloud Scanner (specMACS) is a
multipurpose hyperspectral cloud and sky imager which is designated, but not limited, to investigations of cloud-aerosol interactions in Earth's atmosphere. This paper describes the specMACS instrument's hardware and software design and
characterizes the instrument performance. Initial measurements of cloud sides are presented which demonstrate the wide applicability of the instrument.
Quentin Libois, Christian Proulx, Liviu Ivanescu, Laurence Coursol, Ludovick S. Pelletier, Yacine Bouzid, Francesco Barbero, Éric Girard, and Jean-Pierre Blanchet
Atmos. Meas. Tech., 9, 1817–1832, https://doi.org/10.5194/amt-9-1817-2016, https://doi.org/10.5194/amt-9-1817-2016, 2016
Short summary
Short summary
Here we present a radiometer, FIRR, aimed at measuring atmospheric radiation in the far infrared, an underexplored region of the Earth spectrum. The FIRR is a prototype for the planned TICFIRE satellite mission dedicated to studying thin ice clouds in polar regions. Preliminary in situ measurements compare well with radiative transfer simulations. This highlights the high sensitivity of the FIRR to water vapor content and cloud physical properties, paving the way for new retrieval algorithms.
Kerry Meyer, Yuekui Yang, and Steven Platnick
Atmos. Meas. Tech., 9, 1785–1797, https://doi.org/10.5194/amt-9-1785-2016, https://doi.org/10.5194/amt-9-1785-2016, 2016
Short summary
Short summary
This paper presents the expected uncertainties of a single-channel cloud opacity retrieval technique and a temperature-based cloud phase approach in support of the Deep Space Climate Observatory (DSCOVR) mission; DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations. Results show that, for ice clouds, retrieval errors are minimal (< 2 %), while for liquid clouds the error is limited to within 10 %, although for thin clouds the error can be higher.
Bomidi Lakshmi Madhavan, John Kalisch, and Andreas Macke
Atmos. Meas. Tech., 9, 1153–1166, https://doi.org/10.5194/amt-9-1153-2016, https://doi.org/10.5194/amt-9-1153-2016, 2016
Short summary
Short summary
As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of pyranometer stations (99 nos.) was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. This paper provides the details of this unique setup of the network, data, quality control, uncertainty estimation and discussion of some case days.
A. Myagkov, P. Seifert, M. Bauer-Pfundstein, and U. Wandinger
Atmos. Meas. Tech., 9, 469–489, https://doi.org/10.5194/amt-9-469-2016, https://doi.org/10.5194/amt-9-469-2016, 2016
Short summary
Short summary
In this paper a newly developed scanning 35 GHz cloud radar MIRA-35 is described. The issues concerned with implementation, polarization calibration, and data processing are considered. Also, an algorithm for a characterization of shape and orientation distribution based on polarimetric observations from the cloud radar is presented. For demonstration, the developed retrieval technique is applied to a cloud system containing ice crystals with different habits.
J. Bühl, R. Leinweber, U. Görsdorf, M. Radenz, A. Ansmann, and V. Lehmann
Atmos. Meas. Tech., 8, 3527–3536, https://doi.org/10.5194/amt-8-3527-2015, https://doi.org/10.5194/amt-8-3527-2015, 2015
Short summary
Short summary
Case studies of combined vertical-velocity measurements of Doppler lidar, cloud radar and wind profiler are presented. The measurements were taken at the Meteorological Observatory, Lindenberg, Germany. Synergistic products are presented that are derived from the vertical-velocity measurements of the three instruments: a comprehensive classification mask of vertically moving atmospheric targets and the terminal fall velocity of water droplets and ice crystals corrected for vertical air motion.
J. Leinonen, M. D. Lebsock, S. Tanelli, K. Suzuki, H. Yashiro, and Y. Miyamoto
Atmos. Meas. Tech., 8, 3493–3517, https://doi.org/10.5194/amt-8-3493-2015, https://doi.org/10.5194/amt-8-3493-2015, 2015
Short summary
Short summary
Using multiple frequencies in cloud and precipitation radars enables them to be both sensitive enough to detect thin clouds and to penetrate heavy precipitation, profiling the entire vertical structure of the atmospheric component of the water cycle. Here, we evaluate the performance of a potential future three-frequency space-based radar system by simulating its observations using data from a high-resolution global atmospheric model.
B. Urquhart, B. Kurtz, E. Dahlin, M. Ghonima, J. E. Shields, and J. Kleissl
Atmos. Meas. Tech., 8, 875–890, https://doi.org/10.5194/amt-8-875-2015, https://doi.org/10.5194/amt-8-875-2015, 2015
Cited articles
Arabas, S., Pawlowska, H., and Grabowski, W. W.: Effective radius and droplet spectral width from in-situ aircraft observations in trade-wind cumuli during RICO, Geophys. Res. Letts., 36, L11803, https://doi.org/10.1029/2009gl038257, 2009.
Baedi, R., Dewit, J., Russchenberg, H., Erkelens, J., and Poiares-Baptista, J.: Estimating effective radius and liquid water content from radar and lidar based on the CLARE98 data-set, Phys. Chem. Earth, 25, 1057–1062, https://doi.org/10.1016/s1464-1909(00)00152-0, 2000.
Barker, H. W., Goldstein, R. K., and Stevens, D. E.: Monte Carlo Simulation of Solar Reflectances for Cloudy Atmospheres, J. Atmos. Sci., 60, 1881–1894, https://doi.org/10.1175/1520-0469(2003)060<1881:MCSOSR>2.0.CO;2, 2003.
Behrendt, A. and Nakamura, T.: Calculation of the calibration constant of polarization lidar and its dependency on atmospheric temperature, Opt. Express, 10, 805–817, 2002.
Bissonnette, L. R.: Lidar and multiple scattering, in: Lidar range-resolved optical remote sensing of the atmosphere, edited by: C. Weitkamp, Springer series in optical sciences, 102, ISBN 0387400753, 456 pp., 2005.
Bissonnette, L. R., Roy, G., and Roy, N.: Multiple-scattering-based lidar retrieval: method and results of cloud probings, Appl. Optics, 44, 5565–5581, 2005.
Buras, R. and Mayer, B.: Efficient unbiased variance reduction techniques for Monte Carlo simulations of radiative transfer in cloudy atmospheres: the solution, J. Quant. Spectrosc. Ra., 112, 434–447, https://doi.org/10.1016/j.jqsrt.2010.10.005, 2011.
Cao, X., Roy, G., Roy, N., and Bernier, R.: Comparison of the relationships between lidar integrated backscattered light and accumulated depolarization ratios for linear and circular polarization for water droplets, fog oil, and dust, Appl. Optics, 48, 4130–4141, 2009.
Chaikovskaya, L.: Remote sensing of clouds using linearly and circularly polarized laser beams: techniques to compute signal polarization, in: Light Scattering Reviews 3, edited by: Kokhanovsky, A. A., Springer Praxis Books, 191–228, Springer, Berlin Heidelberg, https://doi.org/10.1007/978-3-540-48546-9_6, 2008.
Chaikovskaya, L. I. and Zege, E. P.: Theory of polarized lidar sounding including multiple scattering, J. Quant. Spectrosc. Ra., 88, 21–35, https://doi.org/10.1016/j.jqsrt.2004.01.002, 2004.
Deirmendjian, D.: Electromagnetic scattering on spherical polydispersions, R (Rand Corporation), American Elsevier Pub. Co., 1969.
de Roode, S. R. and Los, A.: The effect of temperature and humidity fluctuations on the liquid water path of non-precipitating closed-cell stratocumulus clouds, Q. J. Roy. Meteor. Soc., 134, 403–416, https://doi.org/10.1002/qj.222, 2008.
Donovan, D., Voors, R., van Zadelhoff, G.-J., and Acarreta, J.-R.: ECSIM Model and Algorithms Document, KNMI Tech. Rep.: ECSIM-KNMI-TEC-MAD01-R, available at: http://www.knmi.nl/ zadelhof/file/ECSIM-KNMI-TEC-MAD01-122-R.pdf (last access: 23 September 2014), 2010.
Donovan, D. P. and Apituley, A.: Practical depolarization-ratio-based inversion procedure: lidar measurements of the Eyjafjallajküll ash cloud over the Netherlands, Appl. Optics, 52, 2394–2415, 2013{a}.
Donovan, D. P. and Apituley, A.: Practical depolarization-ratio-based inversion procedure: lidar measurements of the Eyjafjallajküll ash cloud over the Netherlands: erratum, Appl. Optics, 52, 4062–4062, 2013{b}.
Donovan, D. P. and van Lammeren, A. C. A. P.: Cloud effective particle size and water content profile retrievals using combined lidar and radar observations – 1. Theory and examples, J. Geophys. Res., 106, 27425–27448, 2001.
Dusek, U., Frank, G. P., Hildebrandt, L., Curtius, J., Schneider, J., Walter, S., Chand, D., Drewnick, F., Hings, S., Jung, D., Borrmann, S., and Andreae, M. O.: Size matters more than chemistry for cloud-nucleating ability of aerosol particles., Science, 312, 1375–1378, 2006
Eloranta, E. W.: Practical Model for the Calculation of Multiply Scattered Lidar Returns, Appl. Optics, 37, 2464–2472, 1998.
Fox, N. I. and Illingworth, A. J.: The potential of a spaceborne cloud radar for the detection of stratocumulus clouds, J. Appl. Meteorol., 36, 676–687, https://doi.org/10.1175/1520-0450-36.6.676, 1997{a}.
Fox, N. I. and Illingworth, A. J.: The retrieval of stratocumulus cloud properties by ground-based cloud radar, J. Appl. Meteorol., 36, 485–492, https://doi.org/10.1175/1520-0450(1997)036<0485:TROSCP>2.0.CO;2, 1997{b}.
Guerrero-Rascado, J. L., ao Costa, M. J., Bortoli, D., Silva, A. M., Lyamani, H., and Alados-Arboledas, L.: Infrared lidar overlap function: an experimental determination, Opt. Express, 18, 20350–20359, 2010.
Gultepe, I. and Isaac, G. A.: The relationship between cloud droplet and aerosol number concentrations for climate models, Int. J. Climatol., 16, 941–946, https://doi.org/10.1002/(SICI)1097-0088(199608)16:8<941::AID-JOC57>3.0.CO;2-O, 1996.
Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., Pier Siebesma, A., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A. F., Pino, D., de Roode, S. R., and Vilà-Guerau de Arellano, J.: Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, Geosci. Model Dev., 3, 415–444, https://doi.org/10.5194/gmd-3-415-2010, 2010.
Hogan, R. J.: Fast approximate calculation of multiply scattered lidar returns, Appl. Optics, 45, 5984–5992, 2006.
Hu, Y., Vaughan, M., Liu, Z., Lin, B., Yang, P., Flittner, D., Hunt, B., Kuehn, R., Huang, J., Wu, D., Rodier, S., Powell, K., Trepte, C., and Winker, D.: The depolarization – attenuated backscatter relation: CALIPSO lidar measurements vs. theory, Opt. Express, 15, 5327–5332, 2007.
Hu, Y.-X., Winker, D., Yang, P., Baum, B., Poole, L., and Vann, L.: Identification of cloud phase from PICASSO-CENA lidar depolarization: a multiple scattering sensitivity study, J. Quant. Spectrosc. Ra., 70, 569–579, https://doi.org/10.1016/S0022-4073(01)00030-9, 2001.
Jacobs, A., Barkmeijer, J., Siebesma, A., van der Plas, E., Wichers Schreur, B., Roozekrans, J., Holtslag, A., Steeneveld, G., Ronda, R., de Roode, S. R., Mendez Gomez, R., van den Brink, P., Haanstra, J., and Smit, L.: The Impact of Climate Change on the Critical Weather Conditions at Schiphol Airport (Impact), Dutch Knowledge for Climate Programme Office, ISBN 9789490070571, 76 pp., 2012.
Katsev, I. L., Zege, E. P., Prikhach, A. S., and Polonsky, I. N.: Efficient technique to determine backscattered light power for various atmospheric and oceanic sounding and imaging systems, J. Opt. Soc. Am. A, 14, 1338–1346, 1997.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128, 229–243, 2000.
Kim, D., Cheong, H., Kim, Y., Volkov, S., and Lee, J.: Optical depth and multiple scattering depolarization in liquid clouds, Opt. Rev., 17, 507–512, https://doi.org/10.1007/s10043-010-0091-7, 2010.
Kulmala, M., Asmi, A., Lappalainen, H. K., Baltensperger, U., Brenguier, J.-L., Facchini, M. C., Hansson, H.-C., Hov, Ø., O'Dowd, C. D., Pöschl, U., Wiedensohler, A., Boers, R., Boucher, O., de Leeuw, G., Denier van der Gon, H. A. C., Feichter, J., Krejci, R., Laj, P., Lihavainen, H., Lohmann, U., McFiggans, G., Mentel, T., Pilinis, C., Riipinen, I., Schulz, M., Stohl, A., Swietlicki, E., Vignati, E., Alves, C., Amann, M., Ammann, M., Arabas, S., Artaxo, P., Baars, H., Beddows, D. C. S., Bergström, R., Beukes, J. P., Bilde, M., Burkhart, J. F., Canonaco, F., Clegg, S. L., Coe, H., Crumeyrolle, S., D'Anna, B., Decesari, S., Gilardoni, S., Fischer, M., Fjaeraa, A. M., Fountoukis, C., George, C., Gomes, L., Halloran, P., Hamburger, T., Harrison, R. M., Herrmann, H., Hoffmann, T., Hoose, C., Hu, M., Hyvärinen, A., Hõrrak, U., Iinuma, Y., Iversen, T., Josipovic, M., Kanakidou, M., Kiendler-Scharr, A., Kirkevåg, A., Kiss, G., Klimont, Z., Kolmonen, P., Komppula, M., Kristjánsson, J.-E., Laakso, L., Laaksonen, A., Labonnote, L., Lanz, V. A., Lehtinen, K. E. J., Rizzo, L. V., Makkonen, R., Manninen, H. E., McMeeking, G., Merikanto, J., Minikin, A., Mirme, S., Morgan, W. T., Nemitz, E., O'Donnell, D., Panwar, T. S., Pawlowska, H., Petzold, A., Pienaar, J. J., Pio, C., Plass-Duelmer, C., Prévôt, A. S. H., Pryor, S., Reddington, C. L., Roberts, G., Rosenfeld, D., Schwarz, J., Seland, Ø., Sellegri, K., Shen, X. J., Shiraiwa, M., Siebert, H., Sierau, B., Simpson, D., Sun, J. Y., Topping, D., Tunved, P., Vaattovaara, P., Vakkari, V., Veefkind, J. P., Visschedijk, A., Vuollekoski, H., Vuolo, R., Wehner, B., Wildt, J., Woodward, S., Worsnop, D. R., van Zadelhoff, G.-J., Zardini, A. A., Zhang, K., van Zyl, P. G., Kerminen, V.-M., S Carslaw, K., and Pandis, S. N.: General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) – integrating aerosol research from nano to global scales, Atmos. Chem. Phys., 11, 13061–13143, https://doi.org/10.5194/acp-11-13061-2011, 2011.
Leaitch, W. R., Isaac, G. A., Strapp, J. W., Banic, C. M., and Wiebe, H. A.: The relationship between cloud droplet number concentrations and anthropogenic pollution: observations and climatic implications, J. Geophys. Res., 97, 2463–2474, https://doi.org/10.1029/91JD02739, 1992.
Leijnse, H., Uijlenhoet, R., van de Beek, C. Z., Overeem, A., Otto, T., Unal, C. M. H., Dufournet, Y., Russchenberg, H. W. J., Figueras i Ventura, J., Klein Baltink, H., and Holleman, I.: Precipitation measurement at CESAR, the Netherlands, J. Hydrometeorol., 11, 1322–1329, https://doi.org/10.1175/2010JHM1245.1, 2010.
Liou, K.: Preface, in: An Introduction to Atmospheric Radiation, edited by: Liou, K., vol. 84 of International Geophysics, xiii–xiv, Academic Press, https://doi.org/10.1016/S0074-6142(02)80015-8, 2002.
Liou, K.-N. and Schotland, R. M.: Multiple backscattering and depolarization from water clouds for a pulsed lidar system, J. Atmos. Sci., 28, 772–784, https://doi.org/10.1175/1520-0469(1971)028<0772:MBADFW>2.0.CO;2, 1971.
Liu, Y., Geerts, B., Miller, M., Daum, P., and McGraw, R.: Threshold radar reflectivity for drizzling clouds, Geophys. Res. Lett., 35, L03807, https://doi.org/10.1029/2007GL031201, 2008.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Lu, M.-L. and Seinfeld, J. H.: Effect of aerosol number concentration on cloud droplet dispersion: a large-eddy simulation study and implications for aerosol indirect forcing, J. Geophys. Res., 111, D02207, https://doi.org/10.1029/2005JD006419, 2006.
Malinka, A. V. and Zege, E. P.: Possibilities of warm cloud microstructure profiling with multiple-field-of-view Raman lidar, Appl. Optics, 46, 8419–8427, 2007.
Martin, G. M., Johnson, D. W., and Spice, A.: The measurement and parameterization of effective radius of droplets in warm stratocumulus clouds, J. Atmos. Sci., 51, 1823–1842, https://doi.org/10.1175/1520-0469(1994)051<1823:TMAPOE>2.0.CO;2, 1994.
McComiskey, A., Feingold, G., Shelby Frisch, A., Turner, D. D., Miller, M. A., Chiu, J. C., Min, Q., and Ogren, J. A.: An assessment of aerosol-cloud interactions in marine stratus clouds based on surface remote sensing, J. Geophys. Res., 114, D09203, https://doi.org/10.1029/2008JD011006, 2009.
Measures, R.: Laser Remote Sensing: Fundamentals and Applications, Krieger Publishing Company, ISBN 9780894646195, 510 pp., 1984.
Mensah, A. A., Holzinger, R., Otjes, R., Trimborn, A., Mentel, Th. F., ten Brink, H., Henzing, B., and Kiendler-Scharr, A.: Aerosol chemical composition at Cabauw, The Netherlands as observed in two intensive periods in May 2008 and March 2009, Atmos. Chem. Phys., 12, 4723–4742, https://doi.org/10.5194/acp-12-4723-2012, 2012.
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud droplet size distributions in low-level stratiform clouds, J. Atmos. Sci., 57, 295–311, https://doi.org/10.1175/1520-0469(2000)057<0295:CDSDIL>2.0.CO;2, 2000.
Pal, S. R. and Carswell, A. I.: Polarization Properties of Lidar Backscattering from Clouds, Appl. Optics, 12, 1530–1535, 1973.
Pawlowska, H., Grabowski, W. W., and Brenguier, J.-L.: Observations of the width of cloud droplet spectra in stratocumulus, Geophys. Res. Lett., 33, L19810, https://doi.org/10.1029/2006GL026841, 2006.
Petzold, A., Esselborn, M., Weinzierl, B., Ehret, G., Ansmann, A., Müller, D., Donovan, D., van Zadelhoff, G.-J., Berthier, S., Wiegner, M., Gasteiger, J., Buras, R., Mayer, B., Lajas, D., and Wehr, T.: ICAROHS – Inter-Comparison of Aerosol Retrievals and Observational Requirements for Multi-Wavelength HSRL Systems, Final Report, Tech. Rep. 22169/NL/CT–STSE-ICAROHS TN1, ESA, 2011.
Pinsky, M., Khain, A., Mazin, I., and Korolev, A.: Analytical estimation of droplet concentration at cloud base, J. Geophys. Res., 117, D18211, https://doi.org/10.1029/2012JD017753, 2012.
Platt, C. M. R.: Remote sounding of high clouds. III: Monte Carlo calculations of multiple-scattered lidar returns, J. Atmos. Sci., 38, 156–167, https://doi.org/10.1175/1520-0469(1981)038<0156:RSOHCI>2.0.CO;2, 1981.
Pounder, N. L., Hogan, R. J., Várnai, T., Battaglia, A., and Cahalan, R. F.: A variational method to retrieve the extinction profile in liquid clouds using multiple-field-of-view lidar, J. Appl. Meteorol. Clim., 51, 350–365, https://doi.org/10.1175/JAMC-D-10-05007.1, 2012.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.: Numerical Recipes 3rd Edition: The Art of Scientific Computing, Cambridge University Press, New York, NY, USA, 3rd Edn., 2007.
Pringle, K. J., Carslaw, K. S., Spracklen, D. V., Mann, G. M., and Chipperfield, M. P.: The relationship between aerosol and cloud drop number concentrations in a global aerosol microphysics model, Atmos. Chem. Phys., 9, 4131–4144, https://doi.org/10.5194/acp-9-4131-2009, 2009.
Rodgers, C.: Inverse Methods for Atmospheric Sounding: Theory and Practice, Series on Atmospheric Oceanic and Planetary Physics, Volume 2, World Scientific Publishing Company Inc., Incorporated, ISBN 9789810227401, 238 pp., 2000.
Roy, G. and Cao, X.: Inversion of water cloud lidar signals based on accumulated depolarization ratio, Appl. Optics, 49, 1630–1635, 2010.
Roy, G., Bissonnette, L., Bastille, C., and Vallée, G.: Retrieval of Droplet-Size Density Distribution from Multiple-Field-of-View Cross-Polarized Lidar Signals: Theory and Experimental Validation, Appl. Optics, 38, 5202–5211, 1999.
Sassen, K.: Polarization in lidar, in: Lidar, edited by: Weitkamp, C., vol. 102 of Springer Series in Optical Sciences, 19–42, Springer, New York, https://doi.org/10.1007/0-387-25101-4_2, 2005.
Sassen, K. and Petrilla, R. L.: Lidar depolarization from multiple scattering in marine stratus clouds, Appl. Optics, 25, 1450–1459, 1986.
Sassen, K. and Zhao, H.: Lidar multiple scattering in water droplet clouds: toward an improved treatment, Opt. Rev., 2, 394–400, https://doi.org/10.1007/s10043-995-0394-2, 1995.
Sauvageot, H. and Omar, J.: Radar reflectivity of cumulus clouds, J. Atmos. Ocean. Tech., 4, 264–272, https://doi.org/10.1175/1520-0426(1987)004<0264:RROCC>2.0.CO;2, 1987.
Schmidt, J., Wandinger, U., and Malinka, A.: Dual-field-of-view Raman lidar measurements for the retrieval of cloud microphysical properties, Appl. Optics, 52, 2235–2247, 2013.
Sun, Y.-Y. and Li, Z.-P.: Depolarization of polarized light caused by high altitude clouds. 2: Depolarization of lidar induced by water clouds, Appl. Optics, 28, 3633–3638, 1989.
Szczodrak, M., Austin, P. H., and Krummel, P. B.: Variability of optical depth and effective radius in marine stratocumulus clouds, J. Atmos. Sci., 58, 2912–2926, https://doi.org/10.1175/1520-0469(2001)058<2912:VOODAE>2.0.CO;2, 2001.
Tonttila, J., O'Connor, E. J., Niemelä, S., Räisänen, P., and Järvinen, H.: Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations, Atmos. Chem. Phys., 11, 9207–9218, https://doi.org/10.5194/acp-11-9207-2011, 2011.
Veselovskii, I., Korenskii, M., Griaznov, V., Whiteman, D. N., McGill, M., Roy, G., and Bissonnette, L.: Information content of data measured with a multiple-field-of-view lidar, Appl. Optics, 45, 6839–6848, 2006.
Voors, R., Donovan, D., Acarreta, J., Eisinger, M., Franco, R., Lajas, D., Moyano, R., Pirondini, F., Ramos, J., and Wehr, T.: ECSIM: the simulator framework for EarthCARE, Proc. SPIE, 6744, 67441Y–67441Y–11, https://doi.org/10.1117/12.737738, 2007.
Wang, J. and Geerts, B.: Identifying drizzle within marine stratus with W-band radar reflectivity, Atmos. Res., 69, 1–27, https://doi.org/10.1016/j.atmosres.2003.08.001, 2003.
Short summary
Stratocumulus clouds are important for weather and climate. They contain relatively little water but are optically thick enough to turn sunny days to grey and globally they have a strong impact on the Earth's energy budget. A new lidar (laser-radar) technique has been developed that is well suited for remotely measuring stratocumulus properties in the important cloud-based region. The technique can supply information that is difficult or impossible for other remote-sensing methods to provide.
Stratocumulus clouds are important for weather and climate. They contain relatively little water...
