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Abstract:
The trades and the inherent trade cumulus clouds cover large parts of the tropical
oceans. Trade cumulus clouds are ubiquitous but also very small in their horizontal
and vertical extent posing huge challenges on observing systems such as satellite
imagers. Climate models exhibit a significant spread in the response of trade
cumulus clouds to global warming motivating their intense study in recent years.
Within this thesis, I use high-resolution satellite images to gain new insights on
small and optically thin clouds in the trades.
The way trade wind clouds change with surface warming is decisive for their
feedback, which defines whether clouds further amplify or dampen the warming
of the climate system. Cloud feedback estimates can be investigated from so-called
cloud-controlling factors, their relation to cloud properties in the current climate
and their change with global warming. Results from my first study indicate a
wind-speed driven boundary layer in the trades. The surface trade winds show
the most powerful control on cloud properties such as cloud sizes, top heights or
cloud clustering. Furthermore, the Bowen ratio was firstly tested from observations
and emerges as a potential new control factor. Trade cumulus cloud properties also
show a susceptibility to the sea surface temperature and the stability of the lower
troposphere which are both projected to change in a warming climate and may
thus impact cloud feedbacks.
Investigating cloud-controlling factors is an ongoing task and seems to be within
reach from extensive measurements of the recent field campaign EUREC4A. First
analysis of cloud observations from multiple instruments indicate the frequent
occurrence of not only small, but also optically thin clouds. Due to their low
reflectance, such clouds are challenging to detect from passive imagers. High-
resolution imagers are able to detect small clouds, but, do conventional satellite
cloud products still miss optically thin clouds?
Within another study, I follow a new approach for defining the total cloud
cover consisting of clouds detected by conventional cloud masking schemes and
of undetected optically thin clouds. By simulating the well-understood clear-sky
signal I can extract clouds as a residual from the all-sky observation and circumvent
conventional but problematic thresholding tests in cloud masking schemes. From
evaluating a high-resolution satellite dataset collected during EUREC4A, I find
that optically thin clouds contribute 45 % to the total cloud cover and reduces
the average cloud reflectance by 29 %. Undetected optically thin clouds can have
major implications for estimates of the radiative effect of clouds and thus, cloud
feedbacks.
