Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4219-2020
© Author(s) 2020. 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-13-4219-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Aug 2020
Research article |
| 12 Aug 2020
| 12 Aug 2020
Synergistic radar and radiometer retrievals of ice hydrometeors
Simon Pfreundschuh
CORRESPONDING AUTHOR
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
Patrick Eriksson
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
Stefan A. Buehler
Meteorologisches Institut, Fachbereich Geowissenschaften, Centrum für Erdsystem und Nachhaltigkeitsforschung (CEN), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Manfred Brath
Meteorologisches Institut, Fachbereich Geowissenschaften, Centrum für Erdsystem und Nachhaltigkeitsforschung (CEN), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
David Duncan
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
now at: European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, UK
Richard Larsson
Max Planck Institute for Solar System Research, Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany
Robin Ekelund
Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
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Cited
12 citations as recorded by crossref.
- Bulk hydrometeor optical properties for microwave and sub-millimetre radiative transfer in RTTOV-SCATT v13.0 A. Geer et al. 10.5194/gmd-14-7497-2021
- Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms Y. Liu & G. Mace 10.5194/amt-15-927-2022
- Assessing Synergistic Radar and Radiometer Retrievals of Ice Cloud Microphysics for the Atmosphere Observing System (AOS) Architecture Y. Liu et al. 10.1109/TGRS.2022.3165578
- A New Deep-Learning-Based Framework for Ice Water Path Retrieval From Microwave Humidity Sounder-II Aboard FengYun-3D Satellite W. Wang et al. 10.1109/TGRS.2024.3352654
- Relation Models of Surface Parameters and Backscattering (or Radiation) Fields as a Tool for Solving Remote Sensing Problems K. Nezhalska et al. 10.3390/computation12050104
- A Novel Ice Cloud Retrieval Algorithm for Submillimeter Wave Radiometers: Simulations and Application to an Airborne Experiment P. Dong et al. 10.1109/TGRS.2023.3274633
- Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems S. Pfreundschuh et al. 10.5194/amt-15-677-2022
- Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework E. Villeneuve et al. 10.5194/amt-17-3567-2024
- Ice water path retrievals from Meteosat-9 using quantile regression neural networks A. Amell et al. 10.5194/amt-15-5701-2022
- Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network W. Wang et al. 10.5194/amt-15-6489-2022
- Using passive and active observations at microwave and sub-millimetre wavelengths to constrain ice particle models R. Ekelund et al. 10.5194/amt-13-501-2020
- Towards an operational Ice Cloud Imager (ICI) retrieval product P. Eriksson et al. 10.5194/amt-13-53-2020
10 citations as recorded by crossref.
- Bulk hydrometeor optical properties for microwave and sub-millimetre radiative transfer in RTTOV-SCATT v13.0 A. Geer et al. 10.5194/gmd-14-7497-2021
- Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms Y. Liu & G. Mace 10.5194/amt-15-927-2022
- Assessing Synergistic Radar and Radiometer Retrievals of Ice Cloud Microphysics for the Atmosphere Observing System (AOS) Architecture Y. Liu et al. 10.1109/TGRS.2022.3165578
- A New Deep-Learning-Based Framework for Ice Water Path Retrieval From Microwave Humidity Sounder-II Aboard FengYun-3D Satellite W. Wang et al. 10.1109/TGRS.2024.3352654
- Relation Models of Surface Parameters and Backscattering (or Radiation) Fields as a Tool for Solving Remote Sensing Problems K. Nezhalska et al. 10.3390/computation12050104
- A Novel Ice Cloud Retrieval Algorithm for Submillimeter Wave Radiometers: Simulations and Application to an Airborne Experiment P. Dong et al. 10.1109/TGRS.2023.3274633
- Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems S. Pfreundschuh et al. 10.5194/amt-15-677-2022
- Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework E. Villeneuve et al. 10.5194/amt-17-3567-2024
- Ice water path retrievals from Meteosat-9 using quantile regression neural networks A. Amell et al. 10.5194/amt-15-5701-2022
- Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network W. Wang et al. 10.5194/amt-15-6489-2022
Latest update: 17 Jul 2024
Short summary
The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
The next generation of European operational weather satellites will carry a novel microwave...
