Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile and Leipzig, Germany
Abstract. Ground-based observations of horizontal winds have been performed in Leipzig (51.12 N, 12.43 E), Germany, and at Punta Arenas (53.35 S, 70.88 W), Chile, in the framework of the German initiative EVAA (Experimental Validation and Assimilation of Aeolus observations) with respect to the validation of the Mie and Rayleigh wind products of Aeolus (L2B data). In Leipzig, at the Leibniz Institute for Tropospheric Research (TROPOS), radiosondes have been launched on each Friday for the Aeolus overpasses (ascending orbit) since mid of May 2019. In Punta Arenas, scanning Doppler cloud radar observations have been performed in the frame of the DACAPO-PESO campaign (dacapo.tropos.de) for more than 3 years from end 2018 until end 2021. We present two case studies and long‐term statistics of the horizontal winds derived with the ground-based reference instruments compared to Aeolus Horizontal Line-of-Sight (HLOS) winds. It was found that the deviation of the Aeolus HLOS winds from the ground-reference is usually of Gaussian shape which allowed the use of the median bias and the scaled median absolute deviation (MAD) for the determination of the systematic and random error of Aeolus wind products, respectively. The case study from August 2020 with impressive atmospheric conditions in Punta Arenas shows that Aeolus is able to also capture strong wind speeds up to more than 100 m/s. The long-term validation has been performed for all product baselines since the change to the second laser (called FM-B) in June 2019 until summer 2022 and also partly for the era of the first laser (FM-A).
The long-term validation showed that the systematic error of the Aeolus wind products could be significantly lowered with the changes introduced into the processing chain (different baselines) during the mission lifetime. While in the early mission phase, systematic errors of more than 2 m/s (absolute values) were observed for both wind types (Mie cloudy and Rayleigh clear), these biases could be reduced with the algorithm improvements, such as the introduction of the correction for temperature fluctuations at the main telescope of Aeolus (M1 temperature correction) with Baseline 09. Hence, since Baseline 10, a significant improvement of the Aeolus data was found leading to a low bias (close to 0 m/s) and nearly similar values for the mid-latitudinal sites on both hemispheres. The random errors for the wind products were first decreasing with increasing baseline but later increasing again due to the performance losses of the Aeolus emitter. However, the systematic error is only slightly affected by this issue, so that one can conclude that the uncertainty introduced by the reduced atmospheric return signal received by Aeolus is mostly affecting the random error.
Even when considering these issues, we can confirm the general validity of Aeolus observations during its lifetime. This proves the general concept of this space explorer mission to perform active wind observations from space.
Holger Baars et al.
Status: final response (author comments only)
RC1: 'Comment on amt-2022-331', Anonymous Referee #1, 30 Jan 2023
- AC1: 'Reply on RC1', Holger Baars, 04 May 2023
RC2: 'Comment on amt-2022-331', Anonymous Referee #2, 02 Feb 2023
- AC2: 'Reply on RC2', Holger Baars, 04 May 2023
Holger Baars et al.
Holger Baars et al.
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The manuscript addresses the comparison activities between Aeolus wind products and analogous data at two distinct locations: Punta Arenas (Chile) and Leipzig (Germany). A scanning Doppler cloud radar was place in Punta Arenas, while radiosondes were systematically launched in Leipzig. Thus, Aeolus winds were compared to Leipzig radiosonde winds and to Punta Arenas Doppler cloud radar winds in different stages of the satellite mission. The dataset includes a significantly large period of time, providing consistency to the results. Furthermore, a significant effort was done in order to obtain a significantly large database of radiosonde measurements.
The comparison methodology applied is robust, and is analogous to the one applied in previous related studies. On the other hand, interesting case studies were presented and a relevant long-term study is performed. The results are correctly presented, and relevant conclusions are raised about Aeolus performance and the processing algorithms. However, the large number of plots makes the manuscript not easy to follow for the reader. Additionally, some figures should be reformatted in order to make them clearer to read and interpret.
The manuscript should be then accepted and susceptible of minor revisions.
The abstract is well written and structured. The concepts are well handled and a good overview of what has been done is provided. However, more precise information about the period used for each validation should be provided. Additionally, some concepts are not properly introduced (e.g., baselines, Mie cloudy, Rayleigh clear). On the other hand, some minor rephrasing could be performed to improve the understanding of the text.
The introduction section is equally well written. The manuscript is well referenced and this review is significantly valuable. However, again the period considered in the validation activities is not totally clear, as it is specified when they start but not when the end. Additionally, the satellite is introduced in this section, but no information is given about the scene classification, quality flags, Aeolus errors, for example. This information is partially lacking also later in the text. More information about the satellite should be included in the introduction or in Section 2, together with the detailed description of the locations and the instrumentation. On the other hand, this description is very well presented and detailed. In fact, Section 3.1 is overly detailed and it is not clear why this much details are needed for this specific study when so few details were given about Aeolus measuring technique and data processing.
The methodology used for the validation is robust and has been widely tested in previous studies. However, more information about the overpasses is lacking (e.g., mean distance, impact of the orbit shift), which can be easily introduced. The presented case studies help to clarify the procedure followed. Nevertheless, the editing of Section 4 should be improved.
Regarding Sections 5 and 6, mainly the editing of the figures should be improved. Some plots are hard to interpret, and the information is difficult to read, given the amount of tiny text included. All of the plots are interesting for the manuscript discussion. However, the authors should think of a better way of including that large number of plots. Additionally, given the number of plots, it is difficult to link the text with the figures while following the discussion.
On the other hand, there is not a clear criterion about when to use “Mie”, “Mie cloud”, “Rayleigh” or “Rayleigh clear”. For example, “Mie cloudy” is used in the figures, while “Rayleigh” (and not “Rayleigh clear”) is used, and while “Mie and Rayleigh winds” are used in the discussion. Some standardization should be performed or at least it should be made clear. Nevertheless, the discussion of Section 5 and 6 are valuable and interesting results were raised.