Session 3.3 The Canadian CloudSat CALIPSO Validation Project: Evaluation of sensitivity and sub-pixel variability of CloudSat data products

Monday, 6 August 2007: 5:00 PM
Hall A (Cairns Convention Center)
David Hudak, EC, King City, ON, Canada; and H. W. Barker, K. B. Strawbridge, M. Wolde, A. Kankiewicz, and J. W. Strapp

Presentation PDF (1.2 MB)

Environment Canada is the lead agency in a comprehensive program to evaluate data products from CloudSat in cold season cloud systems. The project involves under flights of CloudSat by a Convair-580 research aircraft operated by the National Research Council of Canada. The instrumentation on the aircraft includes a full suite of in-situ cloud, precipitation and aerosol sensors. Also on the aircraft are a W-band radar and a dial-channel lidar similar to that are onboard the CloudSat and CALIPSO satellites.

The operational period consisted of flights during four two weeks periods between early November, 2006, and late February, 2007. The flight strategy entailed flights beneath the satellite during overpasses in south central Canada generally at or near cloud top, then vertical profiling of the cloud systems for an additional hour after the satellite underpasses.

To date, sixteen successful missions timed with the passage of CloudSat have been flown during the first three operational periods. The fourth period is scheduled for the last two weeks of February. The cases to date have included examples of precipitation from synoptic snow systems, lake-enhanced snow squalls and rain with a low bright band. Non-precipitation systems sampled include multi-layer clouds, mixed phase clouds, cirrus clouds, liquid stratocumulus clouds, and aerosols layers.

A comparison of the CloudSat radar data with the airborne radar and lidar data, with their higher sensitivity and spatial resolution, reveals noticeable shortcomings in cloud detection and in the identification of cloud features by CloudSat. The in-situ data collected by the aircraft provides additional quantitative details on cloud properties. This discrepancy in cloud features can lead to significant errors in satellite derived estimates of ice water content and liquid water content profiles in some circumstances. The critical assumptions in the algorithms are highlighted.

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