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Topography-Dependent Motion Compensation: Application to UAVSAR Data

The UAVSAR L-band synthetic aperture radar system has been designed for repeat track interferometry in support of Earth science applications that require high-precision measurements of small surface deformations over timescales from hours to years. Conventional motion compensation algorithms, which are based upon assumptions of a narrow beam and flat terrain, yield unacceptably large errors in areas with even moderate topographic relief, i.e., in most areas of interest. This often limits the ability to achieve sub-centimeter surface change detection over significant portions of an acquired scene. To reduce this source of error in the interferometric phase, we have implemented an advanced motion compensation algorithm that corrects for the scene topography and radar beam width. Here we discuss the algorithm used, its implementation in the UAVSAR data processor, and the improvement in interferometric phase and correlation achieved in areas with significant topographic relief.

surface deformation↗

CSAPR2 cell-tracking data collected during TRACER

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells. While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.

54 ENVIRONMENTAL SCIENCES↗