Title :

Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors

Author(s) :

Bruno, Olimpia [Auteur]
Karlsruhe Institute of Technology = Karlsruher Institut für Technologie [KIT]
Hoose, Corinna [Auteur]
Karlsruhe Institute of Technology = Karlsruher Institut für Technologie [KIT]
Storelvmo, Trude [Auteur]
Department of Geosciences [Oslo]
Coopman, Quentin [Auteur]
Karlsruhe Institute of Technology [KIT]
Stengel, Martin [Auteur]
Deutscher Wetterdienst [Offenbach] [DWD]

Journal title :

Geophysical Research Letters

Abbreviated title :

Geophysical Research Letters

Volume number :

48

Publisher :

American Geophysical Union (AGU)

Publication date :

2021-01-28

HAL domain(s) :

Planète et Univers [physics]/Océan, Atmosphère

English abstract : [en]

One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed‐phase clouds. With the aim of understanding how the supercooled liquid fraction (SLF) in clouds with ...
Show more >One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed‐phase clouds. With the aim of understanding how the supercooled liquid fraction (SLF) in clouds with temperature from −40°C to 0°C is related to temperature, geographical location, and cloud type, our analysis contains a comparison of four satellite‐based datasets (one derived from active and three from passive satellite sensors), and focuses on SLF distribution near‐globally, but also stratified by latitude and continental/maritime regions. Despite the warm bias in cloud top temperature of the passive sensor compared to the active sensor and the phase mismatch in collocated data, all datasets indicate, at the same height‐level, an increase of SLF with cloud optical thickness, and generally larger SLF in the Southern Hemisphere than in the Northern Hemisphere (up to about 20% difference), with the exception of continental low‐level clouds, for which the opposite is true.Show less >

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

Université de Lille
CNRS

Collections :

• Autres travaux scientifiques

Research team(s) :

Interactions Rayonnement Nuages (IRN)

Submission date :

2024-01-09T17:34:23Z
2024-01-09T17:55:42Z
2024-01-09T18:06:42Z
2024-08-29T08:48:36Z