Analysis of 2D airglow imager data with respect to dynamics using machine learning

We demonstrate how machine learning can be easily applied to support the analysis of large quantities of excited hydroxyl (OH*) airglow imager data. We use a TCN (temporal convolutional network) classification algorithm to automatically pre-sort images into the three categories “dynamic” (images where small-scale motions like turbulence are likely to be found), “calm” (clear-sky images with weak airglow variations) and “cloudy” (cloudy images where no airglow analyses can be performed). The proposed approach is demonstrated using image data of FAIM 3 (Fast Airglow IMager), acquired at Oberpfaffenhofen, Germany, between 11 June 2019 and 25 February 2020, achieving a mean average precision of 0.82 in image classification. The attached video sequence demonstrates the classification abilities of the learned TCN. Within the dynamic category, we find a subset of 13 episodes of image series showing turbulence. As FAIM 3 exhibits a high spatial (23 m per pixel) and temporal (2.8 s per image) resolution, turbulence parameters can be derived to estimate the energy diffusion rate. Similarly to the results the authors found for another FAIM station (Sedlak et al., 2021), the values of the energy dissipation rate range from 0.03 to 3.18 W kg−1

Spuren der durch die Eruption des Hunga Tonga-Hunga Ha'apai ausgelösten Druckwelle auch in der Mittleren Atmosphäre über Europa

On January 15th 2022 the Hunga Tonga – Hunga Ha'apai volcano erupted and generated strong atmospheric pressure waves of which some propagated several times across the globe. At the Environmental Research Station “Schneefernerhaus” (UFS), as well as in whole Europe, signals could be detected even at MLT (Mesosphere-Lower-Thermosphere) heights (80-100 km) using the GRIPS (GRound-based Infrared P-branch Spectrometer) and the BAIER (Bavarian Airglow ImagER) instruments for the observation of the OH and the O2 airglow

Untersuchung von atmosphärischen Schwerewellen mit Kameradaten des OH-Nachtleuchtens

Atmosphärische Schwerewellen beeinflussen maßgeblich die Dynamik in der Atmosphäre. In der Mesopausenregion (etwa 80-90km Höhe) führen diese unter anderem zu einer Pol-zu-Pol-Zirkulation. Dies hat eine starke Abweichung vom Strahlungsgleichgewicht zur Folge und führt am Pol auf Höhe der Mesopause zu kalten Temperaturen im Sommer und warmen Temperaturen im Winter. Für die Charakterisierung der Schwerewellen in dieser Höhe kann das sogenannte OH-Nachtleuchten verwendet werden, eine chemilumineszente Emission, welche vor allem nachts mit speziellen bodengebundenen Kamerasystemen beobachtet werden kann. Schwerewellen modulieren die Intensität des OH-Nachtleuchtens, so dass durch dessen Beobachtung Rückschlüsse auf die Schwerewellen gezogen werden können. Im Rahmen dieser Arbeit wurden drei Kamerasysteme, sogenannte FAIM-Systeme (Fast Airglow IMager) aufgebaut und über fünf Jahre hinweg betrieben. Dies führt zu etwa 30 Millionen Aufnahmen des OH-Nachtleuchtens. Es wurde ein Verfahren entwickelt, um die Bilddaten auszuwerten und die Schwerewellenparameter aus den Bilddaten zu bestimmen. Die Schwerewellenparameter zeigen deutliche Muster sowohl auf saisonalen als auch tageszeitlichen Zeitskalen. Durch Kombination mit Winddaten können signifikante Einflüsse des Windes in unterschiedlichen Höhenschichten und unterschiedlichen Zeitskalen auf die Schwerewellenausbreitung festgestellt werden

High resolution observations of small scale gravity waves and turbulence features in the OH airglow layer

A new version of the Fast Airglow Imager (FAIM) for the detection of atmospheric waves in the OH airglow layer has been set up at the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR) in Oberpfaffenhofen (48.09° N, 11.28° E), Germany. The spatial resolution of the instrument is 16m in zenith direction with a field of view (FOV) of 11.1 km x 9.0 km at the OH layer height of ca. 87 km. Since November 2015, the system has been in operation in two different setups (zenith angles 46° and 0°) with a temporal resolution of 2.5 to 2.8 s. In a first case study we present observations of two small wave-like features that might be attributed to gravity wave instabilities. In order to spectrally analyse harmonic structures even on small spatial scales down to 550 m horizontal wavelength, we made use of the Maximum Entropy Method (MEM) since this method exhibits an excellent wavelength resolution. MEM further allows analysing relatively short data series, which considerably helps to reduce problems such as stationarity of the underlying data series from a statistical point of view. We present an observation of the subsequent decay of well-organized wave fronts into eddies, which we tentatively interpret in terms of an indication for the onset of turbulence. Another remarkable event which demonstrates the technical capabilities of the instrument was observed during the night of 4th to 5th April 2016. It reveals the disintegration of a rather homogenous brightness variation into several filaments moving in different directions and with different speeds. It resembles the formation of a vortex with a horizontal axis of rotation likely related to a vertical wind shear. This case shows a notable similarity to what is expected from theoretical modelling of Kelvin-Helmholtz instabilities (KHIs). The comparatively high spatial resolution of the presented new version of the FAIM airglow imager provides new insights into the structure of atmospheric wave instability and turbulent processes. Infrared imaging of wave dynamics on the sub-kilometre scale in the airglow layer supports the findings of theoretical simulations and modellings

Gravity wave instability structures and turbulence from more than 1.5 years of OH* airglow imager observations in Slovenia

We analyzed 286 nights of data from the OH* airglow imager FAIM 3 (Fast Airglow IMager) acquired at Otlica Observatory, Slovenia, between 26 October 2017 and 6 June 2019. Measurements were performed with a spatial resolution of 24 m per pixel and a temporal resolution of 2.8 s. Multiple turbulence episodes were observed and the energy dissipation rate in the upper mesosphere/lower thermosphere region was estimated from image sequences in 25 cases. Values range around 0.08 and 9.03 W/kg and would lead to an approximated localized maximum heating of 0.03–3.02 K per turbulence event