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

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 x2212;10 dB 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 is larger than x2212;15 dB the standard deviations of random error were less than 1.0 m/s after 10-km horizontal integration and unfolding.

Automated summary

This study investigated the impact of horizontal integration and unfolding methods on reducing Doppler measurement errors and simulated Doppler velocities in cirrus cloud and precipitation cases. The results showed that Doppler errors can be significantly reduced by applying appropriate horizontal integration and unfolding methods.