Abstract

Abstract. The first space-based Doppler wind lidar (DWL) on board the Aeolus satellite was launched by the European Space Agency (ESA) on 22 August 2018 to obtain global profiles of horizontal line-of-sight (HLOS) wind speed. In this study, the Raleigh-clear and Mie-cloudy winds for periods of baseline 2B02 (from 1 October to 18 December 2018) and 2B10 (from 28 June to 31 December 2019 and from 20 April to 8 October 2020) were validated using 33 wind profilers (WPRs) installed all over Japan, two ground-based coherent Doppler wind lidars (CDWLs), and 18 GPS radiosondes (GPS-RSs). In particular, vertical and seasonal analyses were performed and discussed using WPR data. During the baseline 2B02 period, a positive bias was found to be in the ranges of 0.5 to 1.7 m s−1 for Rayleigh-clear winds and 1.6 to 2.4 m s−1 for Mie-cloudy winds using the three independent reference instruments. The statistical comparisons for the baseline 2B10 period showed smaller biases, −0.8 to 0.5 m s−1 for the Rayleigh-clear and −0.7 to 0.2 m s−1 for the Mie-cloudy winds. The vertical analysis using WPR data showed that the systematic error was slightly positive in all altitude ranges up to 11 km during the baseline 2B02 period. During the baseline 2B10 period, the systematic errors of Rayleigh-clear and Mie-cloudy winds were improved in all altitude ranges up to 11 km as compared with the baseline 2B02. Immediately after the launch of Aeolus, both Rayleigh-clear and Mie-cloudy biases were small. Within the baseline 2B02, the Rayleigh-clear and Mie-cloudy biases showed a positive trend. For the baseline 2B10, the Rayleigh-clear wind bias was generally negative for all months except August 2020, and Mie-cloudy wind bias gradually fluctuated. Both Rayleigh-clear and Mie-cloudy biases did not show a marked seasonal trend and approached zero towards September 2020. The dependence of the Rayleigh-clear wind bias on the scattering ratio was investigated, showing that there was no significant bias dependence on the scattering ratio during the baseline 2B02 and 2B10 periods. Without the estimated representativeness error associated with the comparisons using WPR observations, the Aeolus random error was determined to be 6.7 (5.1) and 6.4 (4.8) m s−1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively. The main reason for the large Aeolus random errors is the lower laser energy compared to the anticipated 80 mJ. Additionally, the large representativeness error of the WPRs is probably related to the larger Aeolus random error. Using the CDWLs, the Aeolus random error estimates were in the range of 4.5 to 5.3 (2.9 to 3.2) and 4.8 to 5.2 (3.3 to 3.4) m s−1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively. By taking the GPS-RS representativeness error into account, the Aeolus random error was determined to be 4.0 (3.2) and 3.0 (2.9) m s−1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively.

Highlights

  • Accurate numerical weather prediction (NWP) is useful for commercial activities, such as agriculture, fisheries, construction, transportation, and energy development, and for daily life

  • We evaluated the bias and random error for wind measurements of the coherent Doppler wind lidars (CDWLs) using the methods described by Iwai et al (2013)

  • Scatter plots of Aeolus horizontal line-of-sight (HLOS) wind speed against wind profilers (WPRs) HLOS wind speed for Rayleigh-clear winds and Mie-cloudy winds during the baseline 2B02 and 2B10 periods are presented in Figs. 4 and 5, respectively

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Summary

Introduction

Accurate numerical weather prediction (NWP) is useful for commercial activities, such as agriculture, fisheries, construction, transportation, and energy development, and for daily life. Measurement of the three-dimensional global wind field is crucial for NWP and for air quality monitoring and forecasting, climate studies, and various meteorological studies. The wind observations obtained by the global meteorological observing system, which contains radiosondes, wind profilers (WPRs), and aircraft, are routinely assimilated in NWP models. The radiosondes, WPRs, and aircraft during takeoff and landing provide accurate and precise vertical wind profiles. Satellite-borne microwave scatterometers and radiometers can estimate ocean surface vector winds using microwave return from the ocean roughness. These instruments capture mesoscale wind field at the ocean surface well, they do not provide any profiling information. AMVs have a large coverage area and high temporal and horizontal resolutions, but the limited accuracy of AMV winds is mainly caused by significant systematic and correlated errors due to uncertainties of their height assignment (e.g. Folger and Weissmann, 2014)

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