20 Oct 2021

20 Oct 2021

Review status: this preprint is currently under review for the journal AMT.

Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems

Simon Pfreundschuh1, Stuart Fox2, Patrick Eriksson1, David Duncan3, Stefan A. Buehler4, Manfred Brath4, Richard Cotton2, and Florian Ewald5 Simon Pfreundschuh et al.
  • 1Department of Space, Earth and Environment, Chalmers University of Technology, 41296 Gothenburg, Sweden
  • 2Met Office, FitzRoy Road, Exeter, EX1 3PB, United Kingdom
  • 3ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom
  • 4Meteorologisches Institut, Fachbereich Geowissenschaften, Centrum für Erdsystem und Nachhaltigkeitsforschung (CEN), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
  • 5Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Germany

Abstract. Accurate measurements of ice hydrometeors are required to improve the representation of clouds and precipitation in weather and climate models. In this study, a newly developed, synergistic retrieval algorithm that combines radar with passive millimeter and sub-millimeter observations is applied to observations of three frontally-generated, mid-latitude cloud systems in order to validate the retrieval and asses its capabilities to constrain the properties of ice hydrometeors. To account for uncertainty in the assumed shapes of ice particles, the retrieval is run multiple times while the assumed shape is varied. Good agreement with in situ measurements of ice water content and particle concentrations for particle maximum diameters larger than 200 μm is found for one of the flights for the Large Plate Aggregate and the 6-Bullet Rosette shapes. The variational retrieval fits the observations well although small systematic deviations are observed for some of the sub-millimeter pointing towards issues with the sensor calibration or the modeling of gas absorption. We find that the quality of the fit to the observations is independent of the assumed ice particle shape, indicating that the employed combination of observations is insufficient to constrain the shape of ice particles in the observed clouds. Compared to a radar-only retrieval, the results show an improved sensitivity of the synergistic retrieval to the microphysical properties of ice hydrometeors at the base of the cloud.

Our findings indicate that the synergy between active and passive microwave observations improve remote-sensing measurements of ice hydrometeors and may thus help to reduce uncertainties that affect currently available data products. Due to the increased sensitivity to their microphysical properties, the retrieval may also be a valuable tool to study ice hydrometeors in field campaigns. The good fits obtained to the observations increases confidence in the modeling of clouds in the Atmospheric Radiative Transfer Simulator and the corresponding single scattering database, which were used to implement the retrieval forward model. Our results demonstrate the suitability of these tools to produce realistic simulations for upcoming sub-millimeter sensors such as the Ice Cloud Image or the Arctic Weather Satellite.

Simon Pfreundschuh et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-306', Anonymous Referee #1, 13 Nov 2021
  • RC2: 'Comment on amt-2021-306', Anonymous Referee #2, 14 Nov 2021
  • RC3: 'Comment on amt-2021-306', Anonymous Referee #3, 15 Nov 2021

Simon Pfreundschuh et al.

Simon Pfreundschuh et al.


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Short summary
We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.