Assessments of Doppler Velocity Errors of EarthCARE Cloud Profiling Radar Using Global Cloud System Resolving Simulations: Effects of Doppler Broadening and Folding

• Published in: IEEE transactions on geoscience and remote sensing Vol. 60; pp. 1 - 9
• Main Authors: Hagihara, Yuichiro, Ohno, Yuichi, Horie, Hiroaki, Roh, Woosub, Satoh, Masaki, Kubota, Takuji, Oki, Riko
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cirrus clouds; Clouds; Data analysis; Data processing; Doppler effect; Doppler measurement accuracy; Doppler radar; Doppler sonar; Earth Clouds Aerosol and Radiation Explorer (EarthCARE); Errors; Folding; Global Cloud System Resolving Models (GCSRMs); Horizontal integration; Integration; Japanese space program; Precipitation; Profiling; Pulse repetition frequency; Radar; Random errors; Reflectance; Satellites; Simulation; Simulators; Space missions; spaceborne Doppler radar; Spaceborne radar; Standard deviation; unfolding method; Velocity; Velocity distribution; Velocity errors
• ISSN: 0196-2892; 1558-0644; 1558-0644
• DOI: 10.1109/TGRS.2021.3060828

The Earth Clouds, Aerosol, and Radiation Explorer (EarthCARE) is a satellite mission jointly developed by the Japan Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA). One challenging feature of this mission is the observation of Doppler velocity by the Cloud Profiling Radar (EC-CPR). The Doppler measurement accuracy is affected by random errors induced by Doppler broadening due to the finite beamwidth and Doppler folding caused by the finite pulse repetition frequency. We investigated the impact of horizontal (along-track) integration and unfolding methods on the reduction of Doppler errors, in order to improve Doppler data processing in the JAXA standard algorithm. We simulated EC-CPR-observed Doppler velocities from pulse-pair covariances with the latest EC-CPR specifications using the radar reflectivity factor and Doppler velocity fields simulated by a satellite data simulator and a global cloud system resolving simulation. Two representative cases of a cirrus cloud and precipitation were examined. In the cirrus cloud case, the standard deviation of random error was decreased to 0.5 m/s for −10 dB <inline-formula> <tex-math notation="LaTeX">{Z} _{\mathbf {e}} </tex-math></inline-formula> after 10-km horizontal integration. In the precipitation case, large falling speeds of precipitation caused Doppler folding errors due to larger Doppler velocities than that in the cirrus cloud case. When <inline-formula> <tex-math notation="LaTeX">{Z} _{\mathbf {e}} </tex-math></inline-formula> is larger than −15 dB <inline-formula> <tex-math notation="LaTeX">{Z} _{\mathbf {e}} </tex-math></inline-formula>, the standard deviations of random error were less than 1.0 m/s after 10-km horizontal integration and unfolding.