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Automated Detection of Polarimetric Tornadic Debris Signatures Using a Hydrometeor Classification Algorithm
被引:32
|作者:
Snyder, Jeffrey C.
Ryzhkov, Alexander V.
机构:
[1] Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, Norman, OK 73019 USA
[2] NOAA, OAR, Natl Severe Storms Lab, Norman, OK USA
关键词:
Severe storms;
Tornadoes;
Radars;
Radar observations;
Classification;
Nowcasting;
DOPPLER RADAR OBSERVATIONS;
X-BAND;
HIGH-RESOLUTION;
EL RENO;
MOBILE;
SUPERCELL;
OKLAHOMA;
THUNDERSTORMS;
OUTBREAK;
SPECTRA;
D O I:
10.1175/JAMC-D-15-0138.1
中图分类号:
P4 [大气科学(气象学)];
学科分类号:
0706 ;
070601 ;
摘要:
Although radial velocity data from Doppler radars can partially resolve some tornadoes, particularly large tornadoes near the radar, most tornadoes are not explicitly resolved by radar owing to inadequate spatiotemporal resolution. In addition, it can be difficult to determine which mesocyclones typically observed on radar are associated with tornadoes. Since debris lofted by tornadoes has scattering characteristics that are distinct from those of hydrometeors, the additional information provided by polarimetric weather radars can aid in identifying debris from tornadoes; the polarimetric tornadic debris signature (TDS) provides what is nearly ground truth that a tornado is ongoing (or has recently occurred). This paper outlines a modification to the hydrometeor classification algorithm used with the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) network in the United States to include a TDS category. Examples of automated TDS classification are provided for several recent cases that were observed in the United States.
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页码:1861 / 1870
页数:10
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