Nowcasting Convective Storm Initiation Using Satellite-Based Box-Averaged Cloud-Top Cooling and Cloud-Type Trends

• Published in: Journal of applied meteorology and climatology Vol. 50; no. 1; pp. 110 - 126
• Main Authors: Sieglaff, Justin M., Cronce, Lee M., Feltz, Wayne F., Bedka, Kristopher M., Pavolonis, Michael J., Heidinger, Andrew K.
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.01.2011
• Subjects: Aerospace industry; Algorithms; Anvil clouds; Atmospheric models; Aviation; Cirrus clouds; Cirrus shields; Cloud-to-ground lightning; Clouds; Convection clouds; Convective storms; Cooling; Cooling rate; Decision support systems; Earth, ocean, space; Exact sciences and technology; External geophysics; False alarms; GOES satellites; Infrared windows; Lightning; Meteorological observations; Meteorological satellites; Meteorology; Moisture content; Night; Nowcasting; Numerical prediction; Numerical weather forecasting; Pixels; Precipitation; Prediction models; Probability theory; Radar; Satellite imagery; Satellites; Standard deviation; Storm forecasting; Storms; Thunderstorms; Tornadoes; Trends; Validation studies; Weather; Weather forecasting; United States; Wisconsin; United States > US; USA, Wisconsin; Short term; algorithms; Weather forecast; trend-surface analysis; digital simulation; Forecast model; North America; Triggering; Meteorological radar; GOES satellites; Meteorological observation; Cooling rate; Space remote sensing; Satellite observation; Geostationary satellite; Ice cloud; decision support systems; Short range forecast; Radar observation; cooling; Numerical forecast; Nowcast; Cloud top; storms; Atmospheric electricity
• ISSN: 1558-8424; 1558-8432
• DOI: 10.1175/2010jamc2496.1

Short-term (0–1 h) convective storm nowcasting remains a problem for operational weather forecasting, and convective storms pose a significant monetary sink for the aviation industry. Numerical weather prediction models, traditional meteorological observations, and radar are all useful for short-term convective forecasting, but all have shortcomings. Geostationary imagers, while having their own shortcomings, are valuable assets for addressing the convective initiation nowcast problem. The University of Wisconsin Convective Initiation (UWCI) nowcasting algorithm is introduced for use as an objective, satellite-based decision support tool. The UWCI algorithm computes Geostationary Operational Environmental Satellite (GOES) Imager infrared window channel box-averaged cloud-top cooling rates and creates convective initiation nowcasts based on a combination of cloud-top cooling rates and satellite-derived cloud-top type–phase trends. The UWCI approach offers advantages over existing techniques, such as increased computational efficiency (decreased runtime) and day–night independence. A validation of the UWCI algorithm relative to cloud-to-ground lightning initiation events is also presented for 23 convective afternoons and 11 convective nights over the central United States during April–June and 1 night of July during 2008 and 2009. The mean probability of detection and false-alarm ratio are 56.3% (47.0%) and 25.5% (34.8%), respectively, for regions within a Storm Prediction Center severe storm risk area (entire validation domain). The UWCI algorithm is shown to perform 1) better in regimes with storms developing in previously clear to partly cloudy skies and along sharp boundaries and 2) poorer in other regimes such as scenes covered with cirrus shields, existing convective anvils, and fast cloud motion.