Team: Dynamics
The work is primarily focused on the area of atmospheric eddy/wave dynamics (planetary waves, gravity waves, infrasound waves, turbulence). The focus is on the altitude range of the upper mesosphere and lower thermosphere (UMLT), i.e. the transition region to space. On the one hand, satellite-based measurements (e.g. TIMED-SABER), which are based on a cooperation with the NASA Langley Research Center and the Johns Hopkins University, form the data basis. On the other hand, for the IR remote sensing of this altitude range, our own passive ground-based and partly also airborne remote sensing sensors (14 IR spectrometers GRIPS, GRound-based Infrared P-branch Spectrometer; six IR cameras FAIM, Fast Airglow IMager) are used and further developed at various locations worldwide in order to be able to also record very small-scale structures in terms of space-time up to turbulence, which the satellite cannot observe. The natural phenomenon of atmospheric airglow is used here. These developments were rated as "excellent" in 2018 during the HGF review of the DLR space programme. The work is carried out in close cooperation with the University of Augsburg (DLR Collaborative Professorship Michael Bittner) and with the Bavarian Environmental Research Station Schneefernerhaus, UFS, on the Zugspitze; it is part of the international Network for the Detection of Mesospheric Change (NDMC), as well as the Virtual Alpine Observatory (VAO). Both programmes are coordinated by the department. For the altitude range of the strato- and troposphere, reanalysis-, satellite- and radiosonde-based data are used.
The methods used include mathematical approaches such as linear and non-linear statistical methods as well as complex spectral analysis for spatiotemporal data series (autoregressive and moving-average approaches such as the maximum entropy method, bi-spectral analysis, wavelets, harmonic analysis, empirical decomposition method, and increasingly also AI approaches) and numerical atmospheric models (wave propagation models HARPA and GROGRAT). The large amount of data makes it necessary to apply and adapt efficient algorithms in the field of pattern recognition and meanwhile also artificial intelligence methods (Sedlak et al., 2021; Wüst et al., 2017c). The use of quantum-accelerated machine learning is being prepared.
On the one hand, the applications lie in the improvement of climate models, in which waves are often only parameterized and thus the vortex-related redistribution of energy and momentum can only be roughly recorded. Based on the above-mentioned data basis, it has been possible to quantify the amount of transported energy of gravity waves, to draw conclusions about the horizontal direction of energy transport, to make the process of energy transfer in the UMLT quantitatively visible and to determine its seasonal variation depending on the observed period range (Hannawald, 2019; Sedlak et al., 2016, 2020; Wüst et al., 2016, 2017a, 2017b, 2020). Based on a tomographic approach, gravity waves can be retrieved in 3D. Other applications are indirectly and directly linked to weather patterns. Strong planetary waves in the stratosphere can determine the development of weather over several weeks ("stationary weather"), which is associated with extreme weather situations, such as the recent 2021 floods in central Europe. The analysis of these waves in the stratosphere has the potential to improve medium-term weather forecasts. On the other hand, low-pressure areas, as well as natural disasters such as tsunamis, volcanoes and earthquakes, generate infrasound in particular, which travels very quickly through the atmosphere (Kramer et al., 2015; Pilger et al., 2013; Bittner et al., 2010) and can be used for early warning by measuring infrasound above an epicentre over the sea using IR remote sensing. For this purpose, the team uses the HARPA/DLR propagation model (Pilger et al., 2013). The approach was proposed by us in 2010 (Bittner et al., 2010) and has since been confirmed by a US research group through extensive modelling (Inchin et al., 2020). In order to test the approach experimentally, a suitably equipped measurement container (including two FAIM cameras, a GRIPS spectrometer) will be set up at the European Southern Observatory (ESO) in Chile in the short term. A subduction zone runs off the coast of Chile and the probability of a tsunami occurring is comparatively high.