Near-global three-dimensional hail signals detected by using gpm-dpr observations

5Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.

Abstract

This study proposes a method of detecting three-dimensional hail distribution by using the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) products in combination with the atmospheric temperature from a reanalysis product. In this study, the hail class contains hailstones, high-density graupel, and small frozen droplets. The radar reflectivity at the Ku-band (ZKu) and dual-frequency ratio (DFR) values are examined for hydrometeor classification at the five atmospheric temperature ranges in comparison to the ground radar product in a test hailstorm case. A simple model assuming binary collision for the riming process, which represents a significant reduction in the number concentration with the conservation of the mass concentration, explains well the hail signals on the scatterplot of ZKu and the DFR. This study determines the thresholds of the ZKu and DFR values at each temperature range based on the simple model. Furthermore, this study evaluates the thresholds in 74 hailstorm cases and proposes two filters to remove melting snow and rain contamination below the freezing level. The 5-year dataset of the GPM-DPR observations shows that hail is widely distributed over oceanic convergence zones as well as over continental convective regions. Most oceanic hail layers are found to be thin (i.e., less than 1500 m) and confined near the freezing level. Therefore, such hail signals have been potentially missed by ground observations. An additional filter removes such thin hail layers and effectively works to detect only deep hailstorms, specifically over continental regions.

Cite

CITATION STYLE

APA

Seiki, T. (2021). Near-global three-dimensional hail signals detected by using gpm-dpr observations. Journal of the Meteorological Society of Japan, 99(2), 379–402. https://doi.org/10.2151/jmsj.2021-018

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free