Investigating Terrain Effects on Nearshore Cloud Evolution in Deepwave through Time-Lapse Photogrammetry

Abstract:

Stereo images of cloud patterns and nearshore waves upstream of the Southern Alps during the DEEPWAVE field campaign are presented through photogrammetric analysis. The photos highlighted in this case were taken in the afternoon of Friday, 13 June 2014. These photos were chosen because they may allow for focused analysis of terrain effects on cloud evolution. Stratocumulus and other cumuliform, as well as cirrus clouds were captured as the sun set over the Tasman Sea, one of the South Pacific Ocean’s marginal seas. Breaks in the thin band of stratocumulus along the shoreline, as well as the total time for cloud layer dissipation are also of interest. A possible barrier jet causing the southward motion of the stratocumulus layer is also investigated. Views look northwest from Serpentine Road in Kumara Junction, South Island, New Zealand.

An Integrated Sounding System (ISS) located at the Hokitika Airport was the primary source of vertical profiles. The upper air sounding closest to the shoot time and location, plotted from Hokitika’s 11:05 UTC upsonde data, shows 10 mph NE winds near the surface. Images were taken on days with research flights over New Zealand from 2 June to 23 June 2014 to match DEEPWAVE objectives. On the night of 13 June 2014, NSF/NCAR’s HIAPER GV research aircraft completed a flight from Christchurch over the South Island. This flight became known as Intensive Observing Period 3 (IOP 3) Sensitivity Flight.

Methods applied in the Terrain-Induced Rotor Experiment (T-REX) by Grubišić and Grubišić (2007) were closely followed while capturing stereo photographic images. Two identical cameras were positioned with a separation baseline near 270 meters. Each camera was tilted upward approximately seven degrees and carefully positioned to capture parallel fields of view of the site. Developing clouds were captured using synchronized camera timers on a five second interval. Ultimately, cloud locations and measurements can be determined using the recorded GPS locations of the cameras. The Camera Calibration Toolbox available for MATLAB was used in order to perform these elaborate triangulation calculations.