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This book is designed to represent subtropical marine
stratus and
stratocumulus (MSC) and surface winds in a simple but
physical
consistent way, which has applications in climate
modeling and
offshore wind energy development. A simple low cloud
cover
scheme is developed in Chapter 2, in which the
variation of MSC is
formulated by connecting low cloud amount with
lower tropospheric stability (LTS), large-scale
subsidence, and
dynamical transport of available dry inhibition
energy below trade
wind inversion. The new scheme produces realistic
seasonal and
inter-annual variations of MSC amounts and
systematically reduces
the NCAR CAM3.1 model biases as shown in Chapter 3.
The lower
troposphere available thermal inhibition energy is
also shown in
Chapter 4 to be a skillful predictor in diagnosing
MSC in monthly
and seasonal time-scales. The influence of MSC, ocean
SST, and
large-scale divergence on surface wind probability
distribution are
addressed in Chapter 5 using satellite observations
and a simple
stochastic model, which can successfully reproduce
the observed
mean, the standard deviation, and skewness of surface
wind speeds
in the southeast Pacific.
stratus and
stratocumulus (MSC) and surface winds in a simple but
physical
consistent way, which has applications in climate
modeling and
offshore wind energy development. A simple low cloud
cover
scheme is developed in Chapter 2, in which the
variation of MSC is
formulated by connecting low cloud amount with
lower tropospheric stability (LTS), large-scale
subsidence, and
dynamical transport of available dry inhibition
energy below trade
wind inversion. The new scheme produces realistic
seasonal and
inter-annual variations of MSC amounts and
systematically reduces
the NCAR CAM3.1 model biases as shown in Chapter 3.
The lower
troposphere available thermal inhibition energy is
also shown in
Chapter 4 to be a skillful predictor in diagnosing
MSC in monthly
and seasonal time-scales. The influence of MSC, ocean
SST, and
large-scale divergence on surface wind probability
distribution are
addressed in Chapter 5 using satellite observations
and a simple
stochastic model, which can successfully reproduce
the observed
mean, the standard deviation, and skewness of surface
wind speeds
in the southeast Pacific.