Angelica Castillo, Melanie Lorenz, Jannes Münchmeyer, Michaël Pons & Tobias Schnepper were awarded the EGU's Outstanding Student and Doctoral Presentation Prize (OSPP) 2022. This means that 5 out of 66 of these prizes went to GFZ researchers this year.

The EGU presents a number of special awards, including Outstanding Student and PhD candidate Presentation (OSPP) Awards, to further improve the overall quality of poster and PICO (Presenting Interactive COntent) presentations at the General Assemblies and, most importantly, to foster the excitement of early-career colleagues for presenting their work in these formats. The OSPP Awards are presented at the EGU Programme Group level.

For information on how to apply for an OSPP Award, please check our application and selection procedure guidelines for the OSPP contest.

The GFZ prize winners

Angelica M. Castillo is a Ph.D. candidate at the German Research Centre for Geosciences (GFZ) in Section 2.7 “Space Physics and Space Weather” and affiliated to the Physics department of the University Potsdam in Germany. The main focus of her research is the application and development of data assimilation tools for the field of Space Weather. Data assimilation techniques allow us to blend satellite observations and physics-based models in a statistically optimal manner. Thus, the optimal state of a dynamic system can be reconstructed, accurate forecasts can be estimated, and knowledge about missing processes in the physics-based model can be gained through comparison between the theoretical state estimate and the data assimilative state.

The presented work introduces the implementation of a disturbed Ensemble Kalman Filter (EnKF) for the reconstruction of the radiation belts electron population. The study assess the convergence of the EnKF solution to the standard Kalman filter (KF) state estimate by means of a synthetic experiment. Furthermore, two new 3D-EnKF approaches for electron phase space density are tested using real satellite observations and validated against a 3D split-operator KF. These efficient data assimilation tools deliver accurate approximations of the KF solution and are suitable for real-time forecasting.

Original presentation
Reconstructing the Dynamics of the Outer Electron Radiation Belt by Means of the Standard and Ensemble Kalman Filter With the VERB-3D Code (Castillo, A. M.; De Wiljes, J.; Shprits, Y. Y.; Aseev, N. A.)

Click here to download the poster/PICO file.

Melanie Lorenz is a PhD student at the University of Potsdam in Germany. Her doctoral research involves petrological, geochemical, and experimental studies of rare earth minerals from a REE prospect in Argentina. While investigating the miscibility gap between fluorapatites and fluorbritholites-(Ce), she increasingly noticed how difficult it can be to get access to well-described data sets and papers.

Since August 2021 Melanie has therefore been working for the Specialised Information Service for Geosciences (FID GEO) at the GFZ German Research Centre for Geosciences in Potsdam. Here, she supports geoscientists working in Germany on their way to make their research more visible and open. In her talk, “Promoting Open Science for Geosciences,” she explained her efforts at FID GEO and the importance of the information service for balanced collaboration between researchers, data repositories, and publishers towards open science for all.

Original presentation
FID GEO: Promoting Open Science for Geosciences (Lorenz, M.; Elger, K.; Achterberg, I.; Meistring, M.; Pfurr, N.; Semmler, M.)

Click here to download the poster/PICO file.

Jannes Münchmeyer is a PhD Student at GFZ Potsdam and the Humboldt University Berlin under the supervision of Prof. Frederik Tilmann and Prof. Ulf Leser. His research focuses on the detection and real-time assessment of earthquakes using machine learning methods. He developed deep learning methods for earthquake early warning and the real-time estimation of earthquake magnitude and location. Furthermore, he proposed a probabilistic framework for the study of earthquake rupture predictability and applied it to show that earthquake ruptures cannot be assessed precisely during their initial growth phase.

The research presented at EGU22 concerned a quantitative comparison of deep learning based seismic phase pickers. To conduct this study, Jannes and his collaborators built SeisBench: A framework for machine learning in seismology. In the study, he showed how previously published pickers perform when trained on diverse datasets and to which extent they are transferable across datasets. The study ends with specific advise on the optimal pickers for different application scenarios.

Original presentation
Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers (Münchmeyer, J.; Woollam, J.; Rietbrock, A.; Tilmann, F.; Lange, D.; Bornstein, T.; Diehl, T.; Giunchi, C.; Haslinger, F.; Jozinović, D.; Michelini, A.; Saul, J.; Soto, H.)

Click here to download the poster/PICO file.

Michaël Pons is a PhD student at the University of Potsdam and affiliated with the German Research Centre for Geosciences GFZ. He works with Prof. Stephan V. Sobolev in the Geodynamic Modelling Section 2.5 led by Dr. Sascha Brune. He is mainly interested in the surface expression resulting from subduction dynamics and overriding plate interaction using generic 2D models and highly resolved data-driven 3D geodynamic models, while incorporating realistic lateral mantle viscosity.

In the international graduate school StRATEGy (Surface Processes, Tectonics and Georesources: The Andean foreland basin of Argentina), he highlighted two new mechanisms associated with plate interaction at the convergent margin: (i) trench hindrance associated with slab steepening, which he presented at the EGU, and (2) crustal contraction and transpression of continental crust associated with the arrival of a flat slab (e.g. the Pampean and Laramide flat slab).

Original presentation
Variability of the shortening rate in Central Andes controlled by subduction dynamics and interaction between slab and overriding plate (Pons, M.; Sobolev, S.; Liu, S.; Neuharth, D.)

Click here to download the poster/PICO file.

Tobias Schnepper is a doctoral researcher at Section 3.4 “Fluid Systems Modelling”, at the GFZ German Research Centre for Geosciences. After completing his Master’s degree in “Geology” at the University of Bonn in cooperation with the Forschungszentrum Jülich, he started his research in Potsdam in August 2021. The focus of his work is on modelling hydrogeochemical processes in open-pit lignite mining lakes, associated waste rock piles and aquifers in connection with the realisation of hybrid pumped hydro power storages.

In his presentation, Tobias shared insights into the background, objectives and challenges of his ongoing research. In particular, the effects of dissolution and precipitation processes between minerals present and processed water on slope stability and water quality are of his interest. Initial simulations included both inverse models and non-dimensional reaction path models based on historical site data. These serve as a basis for more complex models, taking into account more recent chemical data.

Original presentation
Hydrogeochemical impact assessment of pumped hydro power storage in open-pit lignite mines (Schnepper, T.; Kühn, M.; Kempka, T.)

Click here to download the poster/PICO file.

(All texts are taken from the EGU Website.
Revised version (2022-12-08): Expansion to include four more prize winners.)