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Understanding Cirrus Cloud Behavior using A-Train and Geostationary Satellite and NCEP/NCAR Reanalysis Data. Betsy Dupont and Jay Mace, University of Utah 13 th AMS Conference on Cloud Physics, Portland, OR, 2010 Approach:
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Understanding Cirrus Cloud Behavior using A-Train and Geostationary Satellite and NCEP/NCAR Reanalysis Data Betsy Dupont and Jay Mace, University of Utah 13th AMS Conference on Cloud Physics, Portland, OR, 2010 Approach: Consider the A-Train constellation as a single synergistic observational suite. Augment the instantaneous view of A-Train with the temporal view from geostationary.
Clustering of Cirrus Events • Cirrus defined using CloudSat/CALIPSO cloud mask and ECMWF temperature data • 100km cirrus events from the Atlantic Basin in 2007 • K-means cluster analysis based on P-dBZ patterns (Zhang et al., 2007)
Resulting Clusters 1 2 3 4 5 6
Vertical Distribution of IWC Water Content (IWC) in Cirrus Clusters
Given the cloud distributions, what are the large-scale dynamics? Deep Cirrus Cirrus with boundary layer cloud Associated with upper-level ridge Associated with surface warm front
Question: • What are the relationships between cirrus properties (and their temporal change) and the large-scale dynamics? • Next: • Track Cirrus in time following Soden (1998) approach • Case study of a dissipating cirrus event
Cloud Level Dynamics Evolution NCEP/NCAR Reanalysis 18Z back in time forward in time
Summary: Combining A-Train with Geostationary time series allows us to place events within a temporal context adding knowledge of changes in the cloud field. Compositing with large-scale reveals relationships between the cloud field and meteorology. Work in Progress: Do models simulate the relationship between large-scale dynamic and cirrus evolution? What are the microphysical processes that control the differences in growing and dissipating cases?