Validation of Aeolus winds using ground-based radars in Antarctica and in northern Sweden

Abstract

Abstract. Winds measured by lidar from the Aeolus satellite are compared with winds measured by two ground-based radars – MARA in Antarctica (70.77∘ S, 11.73∘ E) and ESRAD (67.88∘ N, 21.10∘ E) in Arctic Sweden – for the period 1 July–31 December 2019. Aeolus is a demonstrator mission to test whether winds measured by Doppler lidar from space can have sufficient accuracy to contribute to improved weather forecasting. A comprehensive programme of calibration and validation has been undertaken following the satellite launch in 2018, but, so far, direct comparison with independent measurements from the Arctic or Antarctic regions have not been made. The comparison covers heights from the low troposphere to just above the tropopause. Results for each radar site are presented separately for Rayleigh (clear) winds, Mie (cloudy) winds, sunlit (“summer”) and non-sunlit (“winter”) seasons, and ascending and descending satellite tracks. Horizontally projected line-of-sight (HLOS) winds from Aeolus, reprocessed using baseline 2B10, for passes within 100 km of the radar sites, are compared with HLOS winds calculated from 1 h averaged radar horizontal wind components. The agreement in most data subsets is very good, with no evidence of significant biases (<1 m s−1). Possible biases are identified for two subsets (about −2 m s−1 for the Rayleigh winds for the descending passes at MARA and about 2 m s−1 for the Mie winds for the ascending passes at ESRAD, both in winter), but these are only marginally significant. A robust significant bias of about 7 m s−1 is found for the Mie winds for the ascending tracks at MARA in summer. There is also some evidence for increased random error (by about 1 m s−1) for the Aeolus Mie winds at MARA in summer compared to winter. This might be related to the presence of sunlight scatter over the whole of Antarctica as Aeolus transits across it during summer.

Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at La Réunion Island and the Observatoire de Haute Provence

“…Therefore, the statistical parameters include the correlation coefficient, SD, MAD, bias, slope, and intercept. We can compare our results to other instruments that weren't mentioned during previous sections, such as ALADIN Airborne Demonstrators (A2D) (Witschas et al, 2020;Lux et al, 2020a;, airborne Doppler Wind Lidars (DWL) (Witschas et al, 2020;Witschas et al, 2022) and Radar Wind Profilers (WPR) (Zuo et al, 2022;Guo et al, 2021;Belova et al, 2021;Iwai et al, 2021). Close to Wu's (2021) observations, we observe the same consistency and similarities with the more recent studies.…”

Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia

“…Later, Guo et al (2021) compared the Aeolus winds with radar wind profiler (RWP) measurements over China, showing that the mean differences are −0.64 and −0.28 m s −1 with the standard deviations of 6.82 and 4.2 m s −1 for Rayleigh-clear and Mie-cloudy winds, respectively. Validation was also conducted over the polar regions, and a good agreement with ground-based RWP measurements was obtained in most cases (Belova et al, 2021). More recently, Iwai et al (2021) validated Aeolus 2B02 and 2B10 wind products by comparing with wind profilers, ground-based coherent Doppler wind lidars, and GPS radiosondes over Japan, with the inter-comparison results for wind profilers and radiosondes showing improved quality of Aeolus 2B10 winds as both biases and random errors were smaller compared to those for the 2B02 product.…”

Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics

“…For the use of Aeolus observations in NWP models, a detailed characterization of the data quality as well as the minimization of systematic errors is crucial. Thus, several scientific and technical studies have been performed and published in the meanwhile, addressing the performance of ALADIN (Atmospheric LAser Doppler INstrument) on-board Aeolus and the quality of the wind data products (e.g., Bedka et al, 2021;Martin et al, 2021;Baars et al, 2020;Guo et al, 2021;Zuo et al, 2022;Wu et al, 2022;Chou et al, 2021;Belova et al, 2021).…”