Understanding Cirrus Cloud Behavior using A-Train and Geostationary Satellite and NCEP/NCAR Reanalysis Data Betsy Dupont and Jay Mace, University of Utah.

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Presentation transcript:

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: 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

Vertical Distribution of IWC Water Content (IWC) in Cirrus Clusters

Given the cloud distributions, what are the large-scale dynamics? Deep CirrusCirrus 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

Cluster 1 Cirrus Dissipating Event

Large-Scale Meteorology

Case study: a dissipating cirrus event

Cloud Level Dynamics NCEP/NCAR Reanalysis 18Z back in timeforward in time Evolution

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?