An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

More specifically, the algorithm consists of an in-cloud detection component and a boundary detection component. The in cloud detection component relies on the cloud-physics and weather-radar data to make a tentative determination of the in/out state. The boundary detection component examines the output of the in-cloud detection component and applies a hysteresis test, which helps prevent false boundary detections that would otherwise be triggered by momentary data fluctuations associated with isolated transient cloud puffs or data dropouts.

The algorithm was tested by applying it to a large set of data and comparing the results of the algorithm with results obtained through detailed manual examination of the data. The algorithm was found to be highly reliable and insensitive to transient instrumentation noise or data gaps, and it enabled full automation of detection of cloud edges.

This work was done by Jennifer G. Ward and Francis J. Merceret of Kennedy Space Center. For further information, access the Technical Support Package (TSP) free on-line at under the Information Sciences category. KSC-12574