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

Zuo, Haichen; Hasager, Charlotte Bay; Karagali, Ioanna; Stoffelen, Ad; Marseille, Gert‐Jan; Kloe, Jos de

doi:10.5194/amt-15-4107-2022

Cited by 17 publications

(15 citation statements)

References 29 publications

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“…The ceiling of Aeolus vertical bins can be adjusted and was increased to 30 km in the area of the HTHH plume (30 • S-0 • ) a few days after the eruption. We use the Mie product which is of better quality than the Rayleigh product inside the plume (Zuo et al, 2022).…”

Section: A15 Aladinmentioning

confidence: 99%

The evolution and dynamics of the Hunga Tonga–Hunga Ha'apai sulfate aerosol plume in the stratosphere

et al. 2022

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Abstract. We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24–26 km over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35∘ S and 20∘ N until June due to the zonal symmetry of the summer stratospheric circulation at 22–26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume.

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Section: A15 Aladinmentioning

confidence: 99%

The evolution and dynamics of the Hunga Tonga–Hunga Ha'apai sulfate aerosol plume in the stratosphere

et al. 2022

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“…The accuracy and precision of the Aeolus wind data, which is included in the Level-2B (L2B) product, has been evaluated in the context of numerous calibration and validation (Cal/Val) activities. These studies include model comparisons (Martin et al, 2021;Chen et al, 2021) and the validation of the Aeolus wind product against ground-based and airborne instruments (Zuo et al, 2022;Wu et al, 2022;Liu et al, 2022;Bedka et al, 2021;Iwai et al, 2021;Fehr et al, 2020Fehr et al, , 2021Baars et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign

Lux

Witschas

Geiß

et al. 2022

Preprint

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Abstract. Since the start of the European Space Agency’s Aeolus mission in 2018, various studies were dedicated to the evaluation of its wind data quality, and particularly to the determination of the systematic and random errors of the Rayleigh-clear and Mie-cloudy wind results provided in the Aeolus Level-2B (L2B) product. The quality control (QC) schemes applied in the analyses mostly rely on the estimated error (EE), reported in the L2B data, using different and often subjectively chosen thresholds for rejecting data outliers. This work gives insight into the calculation of the EE for the two receiver channels and reveals its limitations as a measure of the actual wind error. The spatial and temporal variability of the Rayleigh and Mie EE values, together with the inconsistency in the QC approaches, hampers the comparability of the results across different validation studies. It is demonstrated that a precise error assessment of the Aeolus winds necessitates a careful statistical analysis, including a rigorous screening for gross errors to be compliant with the error definitions formulated in the Aeolus mission requirements. To this end, the modified Z-score and normal quantile plots are shown to be useful statistical tools for effectively eliminating gross errors and for evaluating the normality of the wind error distribution in dependence on the applied QC scheme, respectively. The influence of different QC approaches and thresholds on key statistical parameters is discussed in the context of the Joint Aeolus Tropical Atlantic Campaign (JATAC), which was conducted in Cabo Verde in September 2021. Aeolus winds are compared against model background data from the European Centre for Medium-range Weather Forecasts (ECMWF) before assimilation of Aeolus winds and against wind data measured with the 2-µm heterodyne-detection Doppler wind lidar (DWL) onboard the Falcon aircraft. The two studies make evident that the error distribution of the Mie-cloudy winds is strongly skewed with a preponderance of positively biased gross errors distorting the statistics if not filtered out properly. Effective outlier removal is accomplished by applying a two-step QC based on the EE and the modified Z-score, thereby ensuring an error distribution with a high degree of normality while retaining a large portion of wind results from the original dataset. The same is true for the Rayleigh-clear winds, although the errors are more homogeneously distributed. After utilization of the described QC approach, the systematic errors of the L2B Rayleigh-clear and Mie-cloudy winds are determined to be below 0.3 m s-1 with respect to both the ECMWF model background and the 2-µm DWL. Differences in the random errors relative to the two reference datasets (Mie vs. model: 5.3 m s-1, Mie vs. DWL: 4.1 m s-1; Rayleigh vs. model: 7.8 m s-1; Rayleigh vs. DWL: 8.2 m s-1) are elaborated in the text.

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“…After the successful launch, calibration and validation works have been widely carried out worldwide. Owing to the continually improved data processing chain, from Baseline 10 with M1-temperature-based bias correction and daily updates of global offset bias removal (Data Innovation and Science Cluster, 2020), the systematic errors of both Rayleigh-clear winds and Mie-cloudy winds are almost within 0.5 m s -1 despite some cases in the polar regions, and the random errors mainly vary between 4 m s -1 and 8 m s -1 for Rayleigh-clear winds and between 2.0 m s -1 and 5 m s -1 for Mie-cloudy winds (Belova et al, 2021;Iwai et al, 2021;Witschas et al, 2022;Zuo et al, 2022). However, what should be noted is that Aeolus has been suffering unexpected signal loss since the launch, probably due to the decreasing emitted laser energy for the FM-A period (August 2018 -June 2019) and/or laser-induced contamination for the FM-B period (July 2019 -September 2022) (Straume-Lindner et al, 2021).…”

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confidence: 99%

The impact of Aeolus winds on surface wind forecast over tropical ocean and high latitude regions

Zuo

Hasager

2022

Preprint

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Abstract. To detect global wind profiles and improve numerical weather prediction (NWP), the European Space Agency (ESA) launched the Aeolus satellite carrying a space-borne Doppler Wind Lidar in 2018. After the successful launch, the European Centre for Medium-Range Weather Forecasts (ECMWF) performed the observing system experiments (OSEs) to evaluate the contribution of Aeolus data to NWP. This study aims to assess the impact of Aeolus wind assimilation in the ECMWF model on surface wind forecast over tropical ocean regions by taking buoy measurements for reference and over high latitude regions by taking weather station data for reference for the year 2020. The assessments were conducted through inter-comparison analysis and triple collocation analysis. The results show that with Aeolus data assimilation, the tropical sea surface wind forecast could be slightly improved at some forecast time steps. The random errors of u (zonal) and v (meridional) wind components from OSEs are within 1 m s-1 with respect to the model resolution. For the high latitude regions, Aeolus can reduce the wind forecast errors in the Northern Hemisphere with forecast extending, particularly during the first half-year of 2020 and during the winter months. For the Southern Hemisphere, the positive impact is mainly found for the u component at most forecast steps during June, July and August. Moreover, compared with the tropical ocean regions and the region > 60° N, the random error of OSEs for the region > 60° S increases significantly to 3 m s-1 with forecast extending. Overall, this study demonstrates the ability of Aeolus winds to improve surface wind forecast over tropical oceans and high latitude regions, which provides valuable information for practical applications with Aeolus data in the future.

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

Cited by 17 publications

References 29 publications

The evolution and dynamics of the Hunga Tonga–Hunga Ha'apai sulfate aerosol plume in the stratosphere

The evolution and dynamics of the Hunga Tonga–Hunga Ha'apai sulfate aerosol plume in the stratosphere

Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign

The impact of Aeolus winds on surface wind forecast over tropical ocean and high latitude regions

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