A Self-Consistent Hierarchy of Cirrus Cloud Property Retrieval Algorithms
Mace, G.G. and Zhang, Y., University of Utah
Fourteenth Atmospheric Radiation Measurement (ARM) Science Team Meeting
The problem of deriving cloud properties from remotely sensed data remains fundamentally important to many problems relevant to ARM. We have been working to derive a suite of cloud property retrieval algorithms that increase logically in complexity. Using an extensive set of aircraft data to constrain the physical relationships between various empirically derived parameters, we describe a suite of algorithms that increase in complexity from simple 2-parameter schemes that return a simple estimate of the cirrus cloud particle size distribution to multi parameter algorithms that can be used to derive bimodal size spectra. The importance of accurate and extensive aircraft in situ measurements will be shown to be a critical aspect of this undertaking.
Note: This is the poster abstract presented at the meeting; an extended version was not provided by the author(s).
