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What Can We Learn from the CloudSat Radiometric Mode Observations of Snowfall over the Ice-Free Ocean?

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posted on 2020-12-16, 15:52 authored by Alessandro Battaglia, Giulia Panegrossi
The quantification of global snowfall by the current observing system remains challenging, with the CloudSat 94 GHz Cloud Profiling Radar (CPR) providing the current state-of-the-art snow climatology, especially at high latitudes. This work explores the potential of the novel Level-2 CloudSat 94 GHz Brightness Temperature Product (2B-TB94), developed in recent years by processing the noise floor data contained in the 1B-CPR product; the focus of the study is on the characterization of snow systems over the ice-free ocean, which has well constrained emissivity and backscattering properties. When used in combination with the path integrated attenuation (PIA), the radiometric mode can provide crucial information on the presence/amount of supercooled layers and on the contribution of the ice to the total attenuation. Radiative transfer simulations show that the location of the supercooled layers and the snow density are important factors affecting the warming caused by supercooled emission and the cooling induced by ice scattering. Over the ice-free ocean, the inclusion of the 2B-TB94 observations to the standard CPR observables (reflectivity profile and PIA) is recommended, should more sophisticated attenuation corrections be implemented in the snow CloudSat product to mitigate its well-known underestimation at large snowfall rates. Similar approaches will also be applicable to the upcoming EarthCARE mission. The findings of this paper are relevant for the design of future missions targeting precipitation in the polar regions.

History

Citation

Remote Sens. 2020, 12(20), 3285; Special Issue Radar Remote Sensing of Cloud and Precipitation https://doi.org/10.3390/rs12203285

Author affiliation

Department of Physics and Astronomy

Version

  • VoR (Version of Record)

Published in

Remote Sensing

Volume

12

Issue

20

Publisher

MDPI

eissn

2072-4292

Acceptance date

2020-10-06

Copyright date

2020

Available date

2020-10-10

Language

English

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