Development and Application of a Simplified Coplane Wind Retrieval Algorithm Using Dual-Beam Airborne Doppler Radar Observations for Tropical Cyclone Prediction

Christopher Melhauser Department of Meteorology, and Center for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania

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Fuqing Zhang Department of Meteorology, and Center for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania

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Abstract

Based on established coplane methodology, a simplified three-dimensional wind retrieval algorithm is proposed to derive two-dimensional wind vectors from radial velocity observations by the tail Doppler radars on board the NOAA P3 hurricane reconnaissance aircraft. Validated against independent in situ flight-level and dropsonde observations before and after genesis of Hurricane Karl (2010), each component of the retrieved wind vectors near the aircraft track has an average error of approximately 1.5 m s−1, which increases with the scanning angle and distance away from the aircraft track. Simulated radial velocities derived from a convection-permitting simulation of Karl are further used to systematically quantify errors of the simplified coplane algorithm. The accuracy of the algorithm is strongly dependent on the time between forward and backward radar scans and to a lesser extent, the zero vertical velocity assumption at large angles relative to a plane parallel with the aircraft wings. A proof-of-concept experiment assimilating the retrieved wind vectors with an ensemble Kalman filter shows improvements in track and intensity forecasts similar to assimilating radial velocity super observations or the horizontal wind vectors from the analysis retrievals provided by the Hurricane Research Division of NOAA. Future work is needed to systematically evaluate this simplified coplane algorithm with proper error characteristics for TC initialization and prediction through a large number of events to establish statistical significance.

Corresponding author address: Fuqing Zhang, Department of Meteorology, The Pennsylvania State University, University Park, PA 16802. E-mail: fzhang@psu.edu

Abstract

Based on established coplane methodology, a simplified three-dimensional wind retrieval algorithm is proposed to derive two-dimensional wind vectors from radial velocity observations by the tail Doppler radars on board the NOAA P3 hurricane reconnaissance aircraft. Validated against independent in situ flight-level and dropsonde observations before and after genesis of Hurricane Karl (2010), each component of the retrieved wind vectors near the aircraft track has an average error of approximately 1.5 m s−1, which increases with the scanning angle and distance away from the aircraft track. Simulated radial velocities derived from a convection-permitting simulation of Karl are further used to systematically quantify errors of the simplified coplane algorithm. The accuracy of the algorithm is strongly dependent on the time between forward and backward radar scans and to a lesser extent, the zero vertical velocity assumption at large angles relative to a plane parallel with the aircraft wings. A proof-of-concept experiment assimilating the retrieved wind vectors with an ensemble Kalman filter shows improvements in track and intensity forecasts similar to assimilating radial velocity super observations or the horizontal wind vectors from the analysis retrievals provided by the Hurricane Research Division of NOAA. Future work is needed to systematically evaluate this simplified coplane algorithm with proper error characteristics for TC initialization and prediction through a large number of events to establish statistical significance.

Corresponding author address: Fuqing Zhang, Department of Meteorology, The Pennsylvania State University, University Park, PA 16802. E-mail: fzhang@psu.edu
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