Preprints
https://doi.org/10.5194/egusphere-2023-446
https://doi.org/10.5194/egusphere-2023-446
14 Mar 2023
 | 14 Mar 2023

Synergistic approach of hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework

Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié

Abstract. In cloudy situations, infrared and microwave observations are complementary, with infrared observations being sensitive to the small cloud droplets and ice particles and microwave observations sensitive to precipitation. This complementarity can lead to fruitful synergies in precipitation science (e.g. Kidd and Levizzani, 2022). However, several sources of errors do exist in the treatment of infrared and microwave data that could prevent such synergy. This paper studies several of these sources to estimate their impact on retrievals. To do so, simulations from the radiative transfer model RTTOV v13 are used to build simulated observations. Indeed, we make use of a fully simulated framework to explain the impacts of the identified errors. A combination of infrared and microwave frequencies is built within a Bayesian inversion framework. Synergy is studied using different experiments: (i) with several sources of errors eliminated; (ii) with only one source of errors considered at a time; (iii) with all sources of errors together. The derived retrievals of frozen hydrometeors for each experiment are examined in a statistical study of fifteen days in summer and fifteen days in winter over the Atlantic ocean. One of the main outcomes of the study is that the combination of infrared and microwave frequencies takes advantage of both spectral range strengths leading to accurate retrievals. Each source of error has more or less impact depending on the type of hydrometeor. Another outcome of the study is that even though the errors may decrease the magnitude of benefits generated by the combination of infrared and microwave frequencies, in all cases explored, their combination remains beneficial.

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Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-446', Anonymous Referee #1, 13 Apr 2023
    • AC1: 'Reply on RC1', Ethel Villeneuve, 14 Nov 2023
  • RC2: 'Comment on egusphere-2023-446', Anonymous Referee #2, 17 Oct 2023
    • AC2: 'Reply on RC2', Ethel Villeneuve, 14 Nov 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-446', Anonymous Referee #1, 13 Apr 2023
    • AC1: 'Reply on RC1', Ethel Villeneuve, 14 Nov 2023
  • RC2: 'Comment on egusphere-2023-446', Anonymous Referee #2, 17 Oct 2023
    • AC2: 'Reply on RC2', Ethel Villeneuve, 14 Nov 2023
Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié
Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié

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This is a very thorough quantification of uncertainties in hydrometeor retrieval from synergistic retrievals. This is rare (and difficult) both in that a thorough uncertainty analysis, and multi-sensor synergy retrievals, are both uncommon - let alone together. This analysis can be a pathfinder for this community and for others seeking to achieve similar goals. Uncertainty analyses are becoming increasingly important as sensors and retrievals improve, and as models are being more sophisticated about use of this information for assimilation or analysis.
Short summary
In cloudy situations, infrared and microwave observations are complementary, with infrared being sensitive to the top of clouds and microwave sensitive to precipitation. However, infrared satellite observations are underuse. This study aims to quantify if the inconsistencies in the modelling of clouds prevent the use of cloudy infrared observations in the process of weather forecast. It shows that the synergistic use of infrared and microwave observations is beneficial, depite inconsistencies.