Publications in Peer Reviewed Journals

  • Graf, M., Chwala, C., Polz, J., and Kunstmann, H.: Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data, Hydrol. Earth Syst. Sci., 24, 2931–2950, https://doi.org/10.5194/hess-24-2931-2020, 2020.

  • Sieck, K., Nam, C., Bouwer, L.M., Rechid, D., and Jacob, D. (2020): Weather extremes over Europe under 1.5°C and 2.0°C global warming from HAPPI regional climate regional climate ensemble simulations. Earth System Dynamics Discussions.
    https://doi.org/10.5194/esd-2020-4 (in review)

  • Tarasova, L., Basso, S., Wendi, D., Viglione, A., Kumar, R., and Merz, R. (2020): A process‐based framework to characterize and classify runoff events: The event typology of Germany. Water Resources Research, 56, e2019WR026951.
    https://doi.org/10.1029/2019WR026951

  • Graf, M., Chwala, C., Polz, J., and Kunstmann, H. (2020): Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data. Hydrology and Earth System Sciences, 24, 2931–2950.
    https://doi.org/10.5194/hess-24-2931-2020

  • Polz, J., Chwala, C., Graf, M., & Kunstmann, H. (2020): Rain event detection in commercial microwave link attenuation data using convolutional neural networks. Atmospheric Measurement Techniques, 13, 3835–3853.
    https://doi.org/10.5194/amt-13-3835-2020

  • Haroon, A, Swidinsky, A., Hölz, S., Jegen, M. and Tezkan, B. (2020): Step-on versus step-off signals in time-domain controlled source electromagnetic methods using a grounded electric dipole. Geophysical Prospecting, 0016-8025.
    https://doi.org/10.1111/1365-2478.13016

  • Micallef, A., Person, M., Berndt, C., Bertoni, C., Cohen, D., Dugan, B., Evans, R., Haroon, A., Hensen, C., Jegen, M., Key, K., Kooi, H., Liebetrau, V., Lofi, J., Mailloux, B.J., Martin‐Nagle, R., Michael, H.A., Mueller, T., Schmidt, M., Schwalenberg, K., Trembath‐Reichert, E., Weymer, B., Zhang, Y., Thomas, A.T. (2020): Offshore freshened groundwater in continental margins, Reviews of Geophysics. doi.org/10.1029/2020RG000706

  • Vlasenko, A., Matthias, V. and Callies U. (2021): Simulation of Chemical Transport Model Estimates by means of Neural Network using Meteorological Data. Atmospheric Environment, 118236. ISSN 1352-2310. https://doi.org/10.1016/j.atmosenv.2021.118236

  • González E., Purkiani k., Buck, F. Stäbler F. and Greinert J. (2021): Spatiotemporal visualisation of a deep sea sediment plume dispersion experiment. Workshop on Visualisation in Environmental Sciences (EnvirVis) (2021) S. Dutta and K. Feige and K. Rink and D. Zeckzer (Editors). https://doi.org/10.2312/envirvis.20211082

  • Buck V., Stäbler F., González E.  and Greinert J. (2021): Digital Earth Viewer: a 4D visualisation platform for geoscience datasets. Workshop on Visualisation in Environmental Sciences (EnvirVis) (2021) S. Dutta and K. Feige and K. Rink and D. Zeckzer (Editors). https://doi.org/10.2312/envirvis.20211081

  • Haroon, A., Micallef, A., Jegen, M., Schwalenberg, K., Karstens, J., Berndt, C., et al. (2021). Electrical resistivity anomalies offshore a carbonate coastline: Evidence for freshened groundwater? Geophysical Research Letters, 48, e2020GL091909. https://doi.org/10.1029/2020GL091909

  • Graf, M., Hachem, A. E., Eisele, M., Seidel, J., Chwala, C., Kunstmann, H., Bárdossy, A. (2021). Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales. Journal of Hydrology: Regional Studies, Volume 37, 100883, ISSN 2214-5818. https://doi.org/10.1016/j.ejrh.2021.100883.