92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Thursday, 26 January 2012: 11:00 AM
Development and Application of a Satellite-Based Cloud Object-Tracking Methodology
Room 245 (New Orleans Convention Center )
Daniel C. Hartung, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Seiglaff, L. M. Cronce, and W. F. Feltz

An automated satellite object-based methodology has been recently developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin-Madison to validate the University of Wisconsin Convective Initiation / Cloud Top Cooling (UWCI/CTC) algorithm (Sieglaff et al., 2011). This validation concept uses the satellite-derived quantity, 11-micron top of troposphere cloud emissivity (Pavolonis, 2010) as input into the Warning Decision Support System Integrated Information (WDSS-II) object-tracking framework developed at the University of Oklahoma (Lakshmanan et al., 2007). The WDSS-II software is configured to create cloud objects based upon the 11-micron top of troposphere cloud emissivity field. Within WDSS-II the cloud objects are assigned object IDs, which are tracked with time to minimize broken tracks and allow individual cloud clusters to maintain the same unique object ID for as long as they are present in the corresponding satellite data. Finally, a unique post-processing step preserves the oldest object IDs for those clusters that overlap between consecutive satellite scans; this allows for the WDSS-II cloud clusters to maintain the same unique object ID from infancy (very small object) to convective storm maturity (large object).

This validation approach combines satellite observations, satellite derived-algorithm outputs, and ground-based observations (radar and lightning detection observations) to validate the algorithm and explore relationships between various observations vital to understanding the behavior and development of convection from a satellite perspective. The methodology is being primarily used to validate and determine relationships between the UWCI/CTC algorithm output (Sieglaff et al., 2011) and various NEXRAD fields including composite reflectivity, vertically integrated liquid (VIL), echo tops, Probability of Severe Hail (POSH), etc. that directly influence the nearcasting of severe thunderstorms and aviation hazards such as convectively-induced turbulence.

This work showcases an overview of the validation approach, demonstrates an application of the validation procedure relating UWCI/CTC algorithm output and NEXRAD observations, and highlights the predictive lead-time capabilities of various thresholds of cloud top cooling rates ahead of ground-based radar signatures and NLDN lightning.

Supplementary URL: