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Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product

  • Kamil Mroz
  • , Bernat Puidgomènech Treserras
  • , Alessandro Battaglia
  • , Pavlos Kollias
  • , Aleksandra Tatarevic
  • , Frederic Tridon
  • University of Leicester
  • McGill University
  • Polytechnic University of Turin

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

The Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission is a joint endeavour developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) and features a 94GHz Doppler Cloud Profiling Radar. This paper presents the theoretical basis of the cloud and precipitation microphysics (C-CLD) EarthCARE Level 2 (L2) algorithm. The C-CLD algorithm provides the best estimates of the vertical profiles of water mass content and hydrometeor characteristic size, obtained from radar reflectivity, path-integrated signal attenuation and hydrometeor sedimentation Doppler velocity estimates using optimal estimation (OE) theory. To obtain the forward model relations and the associated uncertainty, an ensemble-based method is used. This ensemble consists of a collection of in situ measured drop size distributions that cover natural microphysical variability. The ensemble mean and standard deviation represent the forward model relations and their microphysics-based uncertainty. The output variables are provided on the joint standard grid horizontal and EarthCARE Level 1b (L1b) vertical grid (1km along track and 100m vertically). The OE framework is not applied to liquid-only clouds in drizzle-free and lightly drizzling conditions, where a more statistical approach is preferred.

Original languageEnglish
Pages (from-to)2865-2888
Number of pages24
JournalAtmospheric Measurement Techniques
Volume16
Issue number11
DOIs
StatePublished - Jun 9 2023

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