The role of mesoscale cloud morphology in the shortwave cloud feedback
A supervised neural network algorithm is used to categorize near-global satellite retrievals into three mesoscale cellular convective (MCC) cloud morphology patterns. At constant cloud amount, morphology patterns differ in brightness associated with the amount of optically thin cloud features. Environmentally driven transitions from closed MCC to other morphology patterns, typically accompanied by more optically thin cloud features, are used as a framework to quantify the morphology contribution to the optical depth component of the shortwave cloud feedback. A marine heat wave is used as an out-of-sample test of closed MCC occurrence predictions. Morphology shifts in optical depth between 65 degrees S and 65 degrees N under projected environmental changes (i.e., from an abrupt quadrupling of CO2) assuming constant cloud cover contributes between 0.04 and 0.07 W m(-2) K-1 (aggregate of 0.06) to the global mean cloud feedback.
document
http://n2t.net/ark:/85065/d7n01bfc
eng
geoscientificInformation
Text
publication
2016-01-01T00:00:00Z
publication
2023-01-01T00:00:00Z
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
None
OpenSky Support
UCAR/NCAR - Library
PO Box 3000
Boulder
80307-3000
name: homepage
pointOfContact
OpenSky Support
UCAR/NCAR - Library
PO Box 3000
Boulder
80307-3000
name: homepage
pointOfContact
2023-08-18T18:19:48.173639