Abstract

Algorithms for the retrieval of atmospheric winds in precipitating systems from downward-pointing, conically scanning airborne Doppler radars are presented. The focus is on two radars: the Imaging Wind and Rain Airborne Profiler (IWRAP) and the High-Altitude IWRAP (HIWRAP). The IWRAP is a dual-frequency (C and Ku bands), multibeam (incidence angles of 30°–50°) system that flies on the NOAA WP-3D aircraft at altitudes of 2–4 km. The HIWRAP is a dual-frequency (Ku and Ka bands), dual-beam (incidence angles of 30° and 40°) system that flies on the NASA Global Hawk aircraft at altitudes of 18–20 km.

Retrievals of the three Cartesian wind components over the entire radar sampling volume are described, which can be determined using either a traditional least squares or variational solution procedure. The random errors in the retrievals due to the airborne radar geometry and noise in the Doppler velocities are evaluated using both an error propagation analysis with least squares theory and a numerical simulation of a hurricane. These analyses show that the vertical and along-track wind errors have strong across-track dependence with values ranging from 0.25 m s⁻¹ at nadir to 2.0 and 1.0 m s⁻¹ at the swath edges, respectively. The average across-track wind errors are ~2.5 m s⁻¹ or 7% of the hurricane wind speed. For typical rotated figure-four flight patterns through hurricanes, the zonal and meridional wind speed errors are ~1.5–2.0 m s⁻¹. Evaluations of both retrieval methods show that the variational procedure is generally preferable to the least squares procedure.

Examples of measured data retrievals from IWRAP during an eyewall replacement cycle in Hurricane Isabel (2003) and from HIWRAP during the development of Tropical Storm Matthew (2010) are shown. Comparisons of IWRAP-measured data retrievals at nadir to flight-level data show errors of ~2.0 m s⁻¹ for vertical winds and ~4.0 m s⁻¹ for horizontal wind speed (~7% of the hurricane wind speed). Additional sources of error, such as hydrometeor fall speed uncertainties and a small height offset in the comparisons, are likely responsible for the larger vertical wind errors when compared to the simulated error analyses.

Abstract

The present study describes methods to reduce the uncertainty of velocity–azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion. While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the second hurricane nature run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track and for the across-track wind is reduced from 0.36 to 0.08 m s⁻¹ and from 0.35 to 0.24 m s⁻¹, respectively. Although the study focuses on Doppler radars, the results are equally applicable to conically scanning Doppler lidars as well.