HRD-ESRL/PSD seminar – Dr. Evan Kalina – 13 August 2015

Dr. Kalina presented a seminar “Plowable hailstorms and hurricanes: Using novel observing platforms to improve forecasts of extreme weather events”


New observing technologies, including dual-polarization radars, total lightning networks, and unmanned aircraft systems, are greatly enhancing our ability to monitor and predict severe and hazardous weather events.

In part 1 of this talk, I will discuss how the recently upgraded Denver, CO Weather Service Radar-1988 Doppler (WSR-88D) can be used in conjunction with the Colorado Lightning Mapping Array (COLMA) to detect and forecast accumulating hailstorms in northeast Colorado. Previous such hailstorms have triggered motor vehicle accidents, road closures, airport delays, urban flooding, and water rescues in the Denver metropolitan area. Radar data from these events demonstrate that accumulating hailstorms result from slow storm motions (< 10 m s-1) that cause exceptionally long hailfall durations (9-28 min versus 1-7 min for more typical hailstorms) at the location(s) that experience accumulating hail. A new algorithm will be presented that uses the radar-estimated hailfall duration and the hail mass concentration to estimate the hail depth on the ground. I will also show that the radar data provide evidence of distinct peaks in storm intensity that occur shortly prior to accumulating hail. These markers of storm intensity include the presence of reflectivities greater than 70 dBZ, descending columns of differential reflectivity (ZDR) and correlation coefficient (ρHV) as small as -4 dB and 0.4, respectively, maxima in 50 dBZ echo top height of 11-15 km MSL, the development of bounded weak echo regions (BWERs), and enhanced graupel production. The increase in graupel particles results in a large supply of hailstone embryos and also enhances cloud electrification through the non-inductive charging mechanism. Therefore, lightning data from COLMA depict peaks in lightning flash rate that coincide with hail accumulation.

In part 2, I will show how the Coyote Unmanned Aircraft System (UAS) is being used to collect crucial meteorological data within the tropical cyclone boundary layer, a traditionally undersampled region of the hurricane. Two Coyote UAS flights in Major Hurricane Edouard (2014) collected pressure, temperature, moisture, and wind measurements in the eye, eyewall, and inflow layer, all within the lowest 1 km of the hurricane. Comparisons with dropsonde and airborne radar data demonstrate that the time-averaged Coyote data agree to within 1.4 m s-1 for winds, 0.4 °C for temperature, and 1.3 °C for dew point temperature. I will also present a preliminary comparison between the Coyote measurements and the boundary layer temperature and moisture fields used to initialize the Hurricane Weather Research and Forecasting (HWRF) Model for two of its Hurricane Edouard simulations.

The presentation is available on the anonymous ftp site:

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