46 VAD and dual-Doppler Analysis of Wind Fields from Doppler Velocity Observed by HIWRAP

Tuesday, 1 April 2014
Golden Ballroom (Town and Country Resort )
Lin Tian, GESTAR/NASA Goddard Space Flight Center, Greenbelt, MD; and G. Heymsfield and S. Guimond

A new airborne dual-wavelength Doppler radar, High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), has been developed at NASA Goddard Space Flight Center. Unlike the ER-2 Doppler radar (EDOP), which has fixed antennas, HIWRAP scans downward conically with two different elevation angles. The conical scanning capability of HIWRAP greatly extends the capability of EDOP for estimating three-dimensional wind field inside the storm. HIWRAP flew for the first time during NASA GRIP field experiment.

In this paper, we have explored the feasibility of applying VAD and dual-Doppler analysis established for ground-based radar to downward scanning airborne Doppler radar. On a moving platform, a complete 360-degree scan is not a perfect circle, because the center of the scan moves with the aircraft. This introduces some errors if we apply the conventional VAD analysis directly. We found that such error is small in general. For typical values of HIWRAP scan rate and aircraft speed, the errors in horizontal wind speed is less than 5 m/s. However, errors in other VAD-derived parameters such as horizontal wind divergence could be as larger as the divergence itself depending on the situations. Based on these finding, we conclude that we can apply conventional VAD method directly to HIWRAP Doppler velocity data to derived horizontal wind fields.

For dual-Doppler analysis, we presented a method that is based the COPLAN method developed for ground-based radar. The main difference between the ground-based and the airborne case is the orientation of the so-called zero COPLAN. For ground-based radar, zero-coplan is the surface where the boundary condition can be specified easily. But for HIWRAP scanning geometry, the zero COPLAN is the vertical plane under the flight track where the boundary condition is unknown. A method to solve this problem, and to subsequently retrieve three-dimensional winds from HIWRAP observations will be presented in another paper. In this paper, we mainly focus on dual-Doppler analysis in the nadir plane under the flight track. For that plane, we found that errors in the horizontal wind speed along the flight track and vertical hydrometeor velocity are less than 2 m/s due to signal fluctuations.

We have applied VAD analysis to the first field data collected during NASA GRIP mission. Two cases are presented, the first is a stratiform case from Tropical storm Matthew and the second is from Hurricane Karl. For Matthew case, we first calculated the along track horizontal wind and sum of the vertical wind and hydrometeor fall speed using the dual-Doppler analysis. We then used the VAD method to derive the horizontal wind fields. The results show that the along track wind from VAD and dual-Doppler analysis in the nadir plan agrees in general. To calculate the divergence using VAD analysis, we have used vertical velocity derived from the Dual-Doppler synthesis. For Karl case, we retrieved horizontal winds from 15 hours of flight data collected by HIWRAP. The results capture the vortex structure of Karl, and provide valuable information for data assimilations. A comparison of the VAD-derived horizontal wind fields with that from a nearby dropsonde shows a good agreement except at altitudes above 6 km height where the data is noisy and contaminated by velocity folding.

VAD winds represent a mean over an area and smooth out many of the transient or local effects such as turbulent motions and small-scale terrain-induced features so that only the larger mesoscale and synoptic-scale feature of the winds remain. For convective storms and hurricanes, the wind fields are generally non-linear over the distances comparable to or greater than the diameter of the typical VAD circle for HIWRAP. In those situations VAD method may not be accurate but it still can capture large-scale features such as mean vortex structures. Such information has tremendous value for study of storm structure, for data assimilation, and for operational forecast of storm motion and location.

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