A 20-Year, Hourly GOES Satellite Derived Deep Convective Cloud Climatology over the Western Hemisphere

Overshooting cloud tops (OTs) indicate the presence of a deep convective updraft with sufficient strength to penetrate through the local level of neutral buoyancy and into the lower stratosphere. OTs can transport tropospheric aerosols, chemical species, water vapor, and ice into the lower stratosphere, each of which have a significant impact on the Earth’s climate system. Thunderstorms with OTs also frequently produce hazardous weather such as heavy rainfall, lightning, aircraft turbulence and engine icing, damaging winds, large hail, and tornadoes. These hazards are typically concentrated near OT regions, so knowledge of where OTs are present is also very important to the weather forecasting community.

Automated OT detection methods have been developed in recent years at NASA Langley Research Center using support primarily from the NOAA GOES-R program. OTs appear anomalously cold in satellite infrared (IR) imagery and highly textured in visible imagery, signatures that can be reliably detected using pattern recognition methods. Imagery-based pattern recognition is combined with 1) NWP tropopause and equilibrium level analyses and 2) a large sample of both OT and non-OT anvil regions identified within 0.25 km MODIS imagery to develop a model to statistically differentiate between the two populations and arrive at an OT Probability product. Co-located high OT Probability values and visible texture detection are quite reliable indicators that an OT is truly present.

A combination of immediate access to an online GOES Imager data archive from the University of Wisconsin-Madison Space Science and Engineering Center via the McIDAS-X software and the extremely efficient LaRC OT detection processing framework has enabled development of a 20-year climatology of OT and deep convective anvil clouds over much of the Western Hemisphere (60° N-S, 30°-180° W). GOES imagery collected at 30-min intervals has been processed over this domain and compiled into hourly analyses, revealing the climatological behavior of deep convection throughout the diurnal cycle at high spatial resolution. This presentation will describe this unique and comprehensive dataset, highlighting daily, regional, and seasonal storm distributions and trends across the 20-year period.