Validation of the Aeolus L2B Rayleigh winds and ECMWF short‐range forecasts in the upper troposphere and lower stratosphere using Loon super pressure balloon observations

Abstract

The novel Aeolus satellite, which carries the first Doppler wind lidar providing profiles of horizontal line‐of‐sight (HLOS) winds, addresses a significant gap in direct wind observations in the global observing system. The gap is particularly critical in the tropical upper troposphere and lower stratosphere (UTLS). This article validates the Aeolus Rayleigh–clear wind product and short‐range forecasts of the European Centre for Medium‐Range Weather Forecasts (ECMWF) with highly accurate winds from the Loon super pressure balloon network at altitudes between 16 and 20 km. Data from 229 individual balloon flights are analysed, applying a collocation criterion of 2 hr and 200 km. The comparison of Aeolus and Loon data shows systematic and random errors of prefix−$$ - $$0.31 and 6.37 m·$$ \cdotp $$sprefix−1$$ {}^{-1} $$, respectively, for the Aeolus Rayleigh–clear winds. The horizontal representativeness error of Aeolus HLOS winds (nearly the zonal wind component) in the UTLS ranges from 0.6–1.1 m·$$ \cdotp $$sprefix−1$$ {}^{-1} $$ depending on the altitude. The comparison of Aeolus and Loon datasets against ECMWF model forecasts suggests that the model systematically underestimates the HLOS winds in the tropical UTLS by about 1 m·$$ \cdotp $$sprefix−1$$ {}^{-1} $$. While Aeolus winds are currently considered as point winds by the ECMWF data assimilation system, the results of the present study demonstrate the need for a more realistic HLOS wind observation operator for assimilating Aeolus winds.

The QBO and global-scale tropical waves in Aeolus wind observations, radiosonde data, and reanalyses

“…Aeolus wind products are of high quality, as has been shown by several validations using airborne wind observations (e.g., Lux et al, 2020Lux et al, , 2022Witschas et al, 2022), super pressure balloons (e.g., Bley et al, 2022), ground based stations (e.g., Iwai et al, 2021;Baars et al, 2022;Ratynski et al, 2023), or radiosondes (e.g., Baars et al, 2020;Iwai et al, 2021;Ratynski et al, 2023). Consequently, numerical weather predictions benefit from the assimilation of Aeolus winds (e.g., Rennie et al, 2021Rennie et al, , 2022Zagar et al, 2021;Garrett et al, 2022;Martin et al, 2022;Pourret et al, 2022;Feng and Pu, 2023), and first scientific studies were carried out (e.g., Banyard et al, 2021;Wright et al, 2021) Due to the high inclination orbit of Aeolus, in the tropics the Aeolus horizontal line of sight (HLOS) deviates from the zonal direction by only about 10 • : the azimuth angle Φ of the HLOS (measured clockwise from due north) is about 260 • for ascending orbits, and about 100 • for descending orbits (assuming that the HLOS points towards the satellite). If (u, v, w) is the vector of atmospheric zonal, meridional, and vertical wind, and neglecting the vertical wind w, the HLOS wind observed by Aeolus is…”

Comparison of temperature and wind observations in the Tropics in a perfect‐model, global EnKF data assimilation system

“…The fact that Aeolus winds, in spite of their large random errors (in the Rayleigh channel), improve tropical analyses and forecasts in all operational NWP models is evidence of the limitations of mass‐field observations, as discussed in the Introduction within a simple $$$ f $$$‐plane shallow‐water framework. In fact, the Aeolus winds were also shown to correct systematic errors in the ECMWF model within the tropical tropopause layer (Rennie et al ., 2021; Bley et al ., 2022), improvements that may be crucial for the extratropical effects of better tropical analyses as argued by Gordon et al . (1972) half a century ago.…”

Aeolus Rayleigh‐channel winds in cloudy conditions

“…In fact, there were changes of the settings in 2019 in mid July, end of September, early October, mid October, and end of December and in 2020 at the end of March. These changes were motivated to improve Aeolus sampling of seasonal effects, such as the sampling of polar stratospheric clouds during the Antarctic winter period and dedicated campaigns as part of Aeolus calibration/validation (Cal/Val) activities; for example, the atmospheric motion vector (AMV) campaign (first half of October 2019) with very dense Mie sampling below 3 km for optimal collocation of Mie winds with AMV winds, Hoffman et al (2021) and the Strateole 3 campaign (end September 2019 and mid October 2019 until end of March 2020) for optimal collocation of Aeolus winds with superpressure balloons drifting around the globe in the stratosphere, Bley et al (2022). As a result, the sampling of atmospheric particulates is not constant over the full period, and sampling clouds at varying heights and at varying resolutions may at least partly explain the variations of the parameters in Figure 5.…”

“…(2021) and the Strateolecampaign (end September 2019 and mid October 2019 until end of March 2020) for optimal collocation of Aeolus winds with superpressure balloons drifting around the globe in the stratosphere, Bley et al . (2022). As a result, the sampling of atmospheric particulates is not constant over the full period, and sampling clouds at varying heights and at varying resolutions may at least partly explain the variations of the parameters in Figure 5.…”