Rachael N. Cross, D. Bodine, R. Palmer, Casey B. Griffin, B. Cheong, S. Torres, C. Fulton, J. Lujan, T. Maruyama
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引用次数: 0
Abstract
When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters as it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics due to the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; Large-Eddy Simulations (LESs) of tornadoes; and a single-volume, T-matrix based emulator. Results show that increases (decreases) in horizontal and vertical wind speeds are related to decreases (increases) in correlation coefficient and increases (decreases) in TDS area and height for all simulated debris types. However, the range of correlation coefficient values varies with debris type, indicating that TDSs comprised of similar debris types can appear remarkably different on radar compared to a TDS with diverse scatterers. Such findings confirm past, observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data.
期刊介绍:
The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.