Abstract

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 xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <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 xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Z} _{\mathbf {e}}$ </tex-math></inline-formula> is larger than −15 dB <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <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.

Highlights

  • T HE Earth Clouds, Aerosol, and Radiation Explorer (EarthCARE; hereafter EC) is a satellite missionManuscript received May 26, 2020; revised October 26, 2020 and February 10, 2021; accepted February 16, 2021

  • Two active and two passive sensors will be installed on the EC satellite: Cloud Profiling Radar (CPR), ATmospheric LIDar (ATLID), Multi Spectral Imager (MSI), and Broadband Radiometer (BBR) [1]

  • The EarthCARE CPR (EC-CPR)-observed Doppler velocities are calculated from pulse-pair covariances, which were simulated in this study using globally simulated EC-CPR data

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Summary

INTRODUCTION

T HE Earth Clouds, Aerosol, and Radiation Explorer (EarthCARE; hereafter EC) is a satellite mission. The EC-CPR is expected to detect thinner cirrus clouds and small water clouds in the lower atmosphere more frequently (e.g., [5]) It can measure the vertical motion of clouds and precipitation globally. We obtained simulated EC-CPR observation data with the same horizontal and vertical resolution as the EC-CPR using GCSRM output and a satellite data simulator. The EC-CPR-observed Doppler velocities are calculated from pulse-pair covariances, which were simulated in this study using globally simulated EC-CPR data (i.e., radar reflectivity factor and Doppler velocity) Using those covariances, we investigate the effectiveness of horizontal (along-track) integration and the unfolding method, in order to evaluate and improve Doppler data processing in the JAXA standard algorithm.

DATA AND METHOD
RESULTS
Cirrus Cloud Case
Precipitation Case
CONCLUSION
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