Processing of TerraSAR-X/TanDEM-X High Resolution Radar Data using Persistent Scatterers Method

Abstract Microwave links can be used for the estimation of path-averaged rainfall by using either the path-integrated attenuation or the difference in attenuation of two signals with different frequencies and/or polarizations. Link signals have been simulated using measured time series of raindrop size distributions (DSDs) over a period of nearly 2 yr, in combination with wind velocity data and Taylor’s hypothesis. For this purpose, Taylor’s hypothesis has been tested using more than 1.5 yr of high-resolution radar data. In terms of correlation between spatial and temporal profiles of rainfall intensities, the validity of Taylor’s hypothesis quickly decreases with distance. However, in terms of error statistics, the hypothesis is seen to hold up to distances of at least 10 km. Errors and uncertainties (mean bias error and root-mean-square error, respectively) in microwave link rainfall estimates due to spatial DSD variation are at a minimum at frequencies (and frequency combinations) where the power-law relation for the conversion to rainfall intensity is close to linear. Errors generally increase with link length, whereas uncertainties decrease because of the decrease of scatter about the retrieval relations because of averaging of spatially variable DSDs for longer links. The exponent of power-law rainfall retrieval relations can explain a large part of the variation in both bias and uncertainty, which means that the order of magnitude of these error statistics can be predicted from the value of this exponent, regardless of the link length.

Download Full-text

Precipitation and Fatal Motor Vehicle Crashes: Continental Analysis with High-Resolution Radar Data

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-18-0001.1 ◽

2019 ◽

Vol 100 (8) ◽

pp. 1453-1461 ◽

Cited By ~ 3

Author(s):

Scott E. Stevens ◽

Carl J. Schreck ◽

Shubhayu Saha ◽

Jesse E. Bell ◽

Kenneth E. Kunkel

Keyword(s):

United States ◽

High Resolution ◽

Motor Vehicle ◽

Radar Data ◽

The United States ◽

Motor Vehicle Crashes ◽

Vehicle Crashes ◽

Fatal Crash ◽

Fatal Crashes ◽

High Resolution Radar

AbstractMotor vehicle crashes remain a leading cause of accidental death in the United States, and weather is frequently cited as a contributing factor in fatal crashes. Previous studies have investigated the link between these crashes and precipitation typically using station-based observations that, while providing a good estimate of the prevailing conditions on a given day or hour, often fail to capture the conditions present at the actual time and location of a crash. Using a multiyear, high-resolution radar reanalysis and information on 125,012 fatal crashes spanning the entire continental United States over a 6-yr period, we find that the overall risk of a fatal crash increases by approximately 34% during active precipitation. The risk is significant in all regions of the continental United States, and it is highest during the morning rush hour and during the winter months.

Download Full-text

SAR image formation and exploitation using high resolution radar data

2018 5th International Conference on Electrical and Electronic Engineering (ICEEE) ◽

10.1109/iceee2.2018.8391387 ◽

2018 ◽

Author(s):

Bouaraba Azzedine ◽

Rekioua Badreddine

Keyword(s):

High Resolution ◽

Image Formation ◽

Radar Data ◽

Sar Image ◽

High Resolution Radar

Download Full-text

Some Considerations for the Use of High-Resolution Mobile Radar Data in Tornado Intensity Determination

Weather and Forecasting ◽

10.1175/waf-d-14-00026.1 ◽

2014 ◽

Vol 29 (4) ◽

pp. 799-827 ◽

Cited By ~ 50

Author(s):

Jeffrey C. Snyder ◽

Howard B. Bluestein

Keyword(s):

High Resolution ◽

Rural Areas ◽

Radar Data ◽

Radial Velocities ◽

Wind Speeds ◽

Rapid Scan ◽

X Band ◽

Central United States ◽

High Resolution Radar ◽

Single Polarization

Abstract The increasing number of mobile Doppler radars used in field campaigns across the central United States has led to an increasing number of high-resolution radar datasets of strong tornadoes. There are more than a few instances in which the radar-measured radial velocities substantially exceed the estimated wind speeds associated with the enhanced Fujita (EF) scale rating assigned to a particular tornado. It is imperative, however, to understand what the radar data represent if one wants to compare radar observations to damage-based EF-scale estimates. A violent tornado observed by the rapid-scan, X-band, polarimetric mobile radar (RaXPol) on 31 May 2013 contained radar-relative radial velocities exceeding 135 m s−1 in rural areas essentially devoid of structures from which damage ratings can be made. This case, along with others, serves as an excellent example of some of the complications that arise when comparing radar-estimated velocities with the criteria established in the EF scale. In addition, it is shown that data from polarimetric radars should reduce the variance of radar-relative radial velocity estimates within the debris field compared to data from single-polarization radars. Polarimetric radars can also be used to retrieve differential velocity, large magnitudes of which are spatially associated with large spectrum widths inside the polarimetric tornado debris signature in several datasets of intense tornadoes sampled by RaXPol.

Download Full-text