Impact of ice cloud heterogeneity on retrievals using passive satellite sensors

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Dr. Chenxi Wang

NASA Goddard Space Flight Center/ESSIC

Monday November 19, 2018, 12:00-1:00 PM

ESSIC Conference Room 4102, 5825 University Research Ct, College Park, MD 20740

Abstract:

Spaceborne passive instruments are widely used to infer long term ice cloud properties due to their large temporal and spatial coverage. However, retrievals from passive sensor can be significantly different due to different sensitivities at individual channels, over-simplified forward models, cloud sub-pixel and vertical heterogeneity effects.

In the first part of this presentation, with an established ice cloud profile database inferred from one-year CALIPSO/CloudSat observations, we will quantitatively estimate the impacts from ice cloud vertical heterogeneity on pixel-level retrievals and level-3 cloud records from passive sensors. In the second part, we will show a practical method that utilizes joint thermal infrared and microwave observations in ice cloud retrievals. This new method is designed to reduce large uncertainties from individual instruments and mitigate cloud sub-pixel heterogeneity effect at coarse spatial resolutions of passive microwave sensors.

Bio-sketch:

Dr. Chenxi Wang is an Assistant Research Scientist working at ESSIC/UMD and NASA GSFC Climate and Radiation Laboratory (613.0). His current research interests include atmospheric radiative transfer modeling and remote sensing of ice and liquid water clouds. He joined ESSIC/GSFC as a Postdoctoral Research Associate after earning his PhD in Atmospheric Sciences from the Texas A&M University in 2013.

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