Preprints
https://doi.org/10.5194/egusphere-2024-829
https://doi.org/10.5194/egusphere-2024-829
10 Apr 2024
 | 10 Apr 2024
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

The Ice Cloud Imager: retrieval of frozen water column properties

Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson

Abstract. The Ice Cloud Imager (ICI) aboard the Second Generation of the EUMETSAT Polar System (EPS-SG) will provide novel measurements of ice hydrometeors. ICI is a passive conically scanning radiometer that will operate within a frequency range of 183 GHz to 664 GHz, helping to cover the present wavelength gap between microwave and infrared observations. Reliable global data will be produced on a daily basis. This paper presents the retrieval database to be used operationally and performs a final pre-launch assessment of ICI retrievals.

Simulations are performed within atmospheric states that are consistent with radar reflectivities and represent the three-dimensional variability of clouds. The radiative transfer calculations use empirically-based hydrometeor models. Azimuthal orientation of particles is mimicked, allowing for polarisation to be considered. The degrees of freedom of the ICI retrieval database are shown to vary according to cloud type. The simulations are considered to be the most detailed performed to this date. Simulated radiances are shown to be statistically consistent with real observations.

Machine learning is applied to perform inversions of the simulated ICI observations. The method used allows for the estimation of non-Gaussian uncertainties for each retrieved case. Retrievals of ice water path (IWP), mean mass height (Zm) and mean mass diameter (Dm) are presented. Distributions and zonal means of both database and retrieved IWP show agreement with DARDAR. Retrieval tests indicate that ICI will be sensitive to IWP between 10-2 and 101 kg m-2. Retrieval performance is shown to vary with climatic region and surface type, with the best performance achieved over tropical regions and over ocean. As a consequence of this study, retrievals on real observations will be possible from day one of the ICI operational phase.

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Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson

Status: open (until 22 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-829', Anonymous Referee #1, 01 May 2024 reply
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson

Model code and software

The Ice Cloud Imager: retrieval of frozen water column properties - Code Eleanor May https://doi.org/10.5281/zenodo.10839089

Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson

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Short summary
The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.