radar tracking
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2021 ◽  
Vol 14 (10) ◽  
pp. 6495-6514
Author(s):  
Timothy H. Raupach ◽  
Andrey Martynov ◽  
Luca Nisi ◽  
Alessandro Hering ◽  
Yannick Barton ◽  
...  

Abstract. We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain.


2021 ◽  
pp. 379-440
Author(s):  
Scott C. Winton
Keyword(s):  

Author(s):  
Nouredine Nour ◽  
Reda Belhaj-Soullami ◽  
Cedric L.R. Buron ◽  
Alain Peres ◽  
Frederic Barbaresco
Keyword(s):  

Author(s):  
E.N. Builov ◽  
◽  
S.A. Gorhkov ◽  
◽  
◽  
...  

A block diagram of the receiving part of a monopulse radar tracking by range and angular coordinates with a broadband sounding signal is presented. The features of correlation processing of a broadband linear-frequency-modulated signal with full frequency demodulation and algorithms for estimating coordinates are considered. A comparative analysis of the results of calculating errors in measuring the coordinates of air targets in short-range radars using narrow-band and broadband signals and different viewing angles is carried out.


2021 ◽  
Author(s):  
Timothy Hugh Raupach ◽  
Andrey Martynov ◽  
Luca Nisi ◽  
Alessandro Hering ◽  
Yannick Barton ◽  
...  

Abstract. We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain.


iScience ◽  
2021 ◽  
pp. 102499
Author(s):  
Joseph L. Woodgate ◽  
James C. Makinson ◽  
Natacha Rossi ◽  
Ka S. Lim ◽  
Andrew M. Reynolds ◽  
...  

Author(s):  
Yaowen Li ◽  
Gang Li ◽  
Yu Liu ◽  
Xiao-Ping Zhang ◽  
You He

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