Articles | Volume 10, issue 5
https://doi.org/10.5194/amt-10-1783-2017
© Author(s) 2017. 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-10-1783-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 May 2017
Research article |
| 12 May 2017
Optimizing observations of drizzle onset with millimeter-wavelength radars
Claudia Acquistapace
CORRESPONDING AUTHOR
Institute for Geophysics and Meteorology, University of Cologne, Pohligstr. 3, 50969 Cologne, Germany
Stefan Kneifel
Institute for Geophysics and Meteorology, University of Cologne, Pohligstr. 3, 50969 Cologne, Germany
Ulrich Löhnert
Institute for Geophysics and Meteorology, University of Cologne, Pohligstr. 3, 50969 Cologne, Germany
Pavlos Kollias
Stony Brook University, Stony Brook, NY 11794-5000, USA
Institute for Geophysics and Meteorology, University of Cologne, Pohligstr. 3, 50969 Cologne, Germany
Maximilian Maahn
Cooperative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA
Earth System Research Laboratory, National Oceanographic and Atmospheric Administration,
325 Broadway, Boulder, CO 80305, USA
Matthias Bauer-Pfundstein
METEK Meteorologische Messtechnik GmbH, Fritz-Straßmann-Straße 4, 25337 Elmshorn, Germany
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Cited
15 citations as recorded by crossref.
- Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities M. Cadeddu et al. 10.1109/TGRS.2017.2728699
- Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration? M. Maahn et al. 10.5194/amt-12-3151-2019
- Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model M. Costa-Surós et al. 10.5194/acp-20-5657-2020
- Detection of small drizzle droplets in a large cloud chamber using ultrahigh-resolution radar Z. Zhu et al. 10.5194/amt-17-1133-2024
- Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra C. Williams et al. 10.5194/amt-11-4963-2018
- Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach A. Billault-Roux et al. 10.5194/amt-16-911-2023
- A W-Band Radar–Radiometer System for Accurate and Continuous Monitoring of Clouds and Precipitation N. Küchler et al. 10.1175/JTECH-D-17-0019.1
- PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere M. Mech et al. 10.5194/gmd-13-4229-2020
- A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote Sensing C. Acquistapace et al. 10.1175/JTECH-D-18-0158.1
- Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars F. Ewald et al. 10.5194/amt-12-1815-2019
- Evaluation of the reflectivity calibration of W-band radars based on observations in rain A. Myagkov et al. 10.5194/amt-13-5799-2020
- New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra Z. Zhu et al. 10.5194/acp-22-7405-2022
- Remote Sensing of Sea Salt Aerosol below Trade Wind Clouds M. Klingebiel et al. 10.1175/JAS-D-18-0139.1
- Modeling the Microwave Emission of Snow on Arctic Sea Ice for Estimating the Uncertainty of Satellite Retrievals P. Rostosky et al. 10.1029/2019JC015465
- Classification of Hydrometeors During a Stratiform Precipitation Event in the Rainy Season of Liupanshan N. Feng et al. 10.3390/atmos16020132
15 citations as recorded by crossref.
- Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities M. Cadeddu et al. 10.1109/TGRS.2017.2728699
- Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration? M. Maahn et al. 10.5194/amt-12-3151-2019
- Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model M. Costa-Surós et al. 10.5194/acp-20-5657-2020
- Detection of small drizzle droplets in a large cloud chamber using ultrahigh-resolution radar Z. Zhu et al. 10.5194/amt-17-1133-2024
- Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra C. Williams et al. 10.5194/amt-11-4963-2018
- Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach A. Billault-Roux et al. 10.5194/amt-16-911-2023
- A W-Band Radar–Radiometer System for Accurate and Continuous Monitoring of Clouds and Precipitation N. Küchler et al. 10.1175/JTECH-D-17-0019.1
- PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere M. Mech et al. 10.5194/gmd-13-4229-2020
- A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote Sensing C. Acquistapace et al. 10.1175/JTECH-D-18-0158.1
- Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars F. Ewald et al. 10.5194/amt-12-1815-2019
- Evaluation of the reflectivity calibration of W-band radars based on observations in rain A. Myagkov et al. 10.5194/amt-13-5799-2020
- New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra Z. Zhu et al. 10.5194/acp-22-7405-2022
- Remote Sensing of Sea Salt Aerosol below Trade Wind Clouds M. Klingebiel et al. 10.1175/JAS-D-18-0139.1
- Modeling the Microwave Emission of Snow on Arctic Sea Ice for Estimating the Uncertainty of Satellite Retrievals P. Rostosky et al. 10.1029/2019JC015465
- Classification of Hydrometeors During a Stratiform Precipitation Event in the Rainy Season of Liupanshan N. Feng et al. 10.3390/atmos16020132
Discussed (final revised paper)
Latest update: 30 May 2025
Short summary
The goal of the paper is to understand what the optimal cloud radar settings for drizzle detection are. The number of cloud radars in the world has increased in the last 10 years and it is important to develop strategies to derive optimal settings which can be applied to all radar systems. The study is part of broader research focused on better understanding the microphysical process of drizzle growth using ground-based observations.
The goal of the paper is to understand what the optimal cloud radar settings for drizzle...
