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Science Lecture by Yunyan Zhang |
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Date: June 7, 2006
Time: 10:30am
Location: NIA, Rm 137
Additional Information: Presentation (.pdf)
Interpreting the Low Cloud Amount Climatology Using the Mixed-Layer Theory
Yunyan Zhang, UCLA
Stratocumulus is important for the global radiation budget. The
mixed-layer model (MLM), introduced by Lilly (1968), provides the
theoretical framework upon which most of our understanding of the
marine stratocumulus-topped boundary layer (STBL) is based. In this
study, the low cloud amount (LCA) is diagnosed based on the equilibrium
solutions of the mixed-layer model. This work aims to answer the
question: can the equilibrium solutions of the mixed-layer model well
represent the low cloud amount climatology? If yes, can the
equilibrium mixed layer framework contribute to the PBL parameterization in large-scale models? And what conditions most contribute to the climatology? If not, why does it fail?
ECMWF Reanalysis (ERA-40) data serve as large-scale boundary conditions
for the MLM calculations. Temporal and spatial distributions of the low
cloud amount are constructed at three different time scales: long term
monthly climatology (M-Climo), monthly (M-Monthly) and daily (M-Daily).
Results are compared to the International Satellite Cloud Climatology
Project (ISCCP) D2 data, especially in light of the relationship (e.g.,
Klein and Hartmann, 1993) between the low cloud amount and the lower
troposphere stability (LTS). We find that the seasonal variation in the
LTS is still the strongest signal dominant in LCA. Other seasonal
variations in the boundary conditions such as divergence and the
free-troposphere temperature contribute to LCA depending on their
correlation with the LTS and the strength of the LTS signal in
individual regions. The mixed layer model is more sensitive to
variations in mass fields, such as divergence, than in thermodynamics.
Synoptic variability improves the MLM LCA in most regions except
Namibia.
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