ORCID • E-Mail • ResearchGate
2022
Vogl, T., M. Maahn, S. Kneifel, W. Schimmel, D. Moisseev, and H. Kalesse, 2022: Using artificial neural networks to predict riming from Doppler cloud radar observations. Atmos. Meas. Tech., 15, 365–381 https://doi.org/10.5194/amt-2021-137
2021
Vogl, T., Hrdina, A., and Thomas, C. K., 2021: Choosing an optimal β factor for relaxed eddy accumulation applications across vegetated and non-vegetated surfaces. Biogeosciences, 18, 5097–5115, https://doi.org/10.5194/bg-18-5097-2021
Trömel, S., Simmer, C., Blahak, U., Blanke, A., Doktorowski, S., Ewald, F., Frech, M., Gergely, M., Hagen, M., Janjic, T., Kalesse-Los, H. and Kneifel, S. and Knote, C. and Mendrok, J. and Moser, M. and Köcher, G. and Mühlbauer, K. and Myagkov, A. and Pejcic, V. and Seifert, P. and Shrestha, P. and Teisseire, A. and von Terzi, L. and Tetoni, E. and Vogl, T. and Voigt, C. and Zeng, Y. and Zinner, T. and Quaas, J.: Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes, Atmos. Chem. Phys., https://doi.org/10.5194/acp-21-17291-2021, 2021.
Hartmann, M., Gong, X., Kecorius, S., van Pinxteren, M., Vogl, T., Welti, A., Wex, H., Zeppenfeld, S., Herrmann, H., Wiedensohler, A., and Stratmann, F.: Terrestrial or marine – indications towards the origin of ice-nucleating particles during melt season in the European Arctic up to 83.7° N, Atmos. Chem. Phys., 21, 11613–11636, https://doi.org/10.5194/acp-21-11613-2021, 2021.
2019
Kecorius, S., Vogl, T., Paasonen, P., Lampilahti, J., Rothenberg, D., Wex, H., Zeppenfeld, S., van Pinxteren, M., Hartmann, M., Henning, S., Gong, X., Welti, A., Kulmala, M., Stratmann, F., Herrmann, H., and Wiedensohler, A., 2019: New particle formation and its effect on cloud condensation nuclei abundance in the summer Arctic: a case study in the Fram Strait and Barents Sea, Atmos. Chem. Phys., 19, 14339–14364, https://doi.org/10.5194/acp-19-14339-2019
Kalesse, H., Vogl, T., Paduraru, C., and Luke, E., 2019: Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm, Atmos. Meas. Tech., 12, 4591–4617, https://doi.org/10.5194/amt-12-4591-2019
Wendisch, M., Macke, A., Ehrlich, A., Lüpkes, C., Mech, M., Chechin, D., Dethloff, K., Velasco, C. B., Bozem, H., Brückner, M., Clemen, H., Crewell, S., Donth, T., Dupuy, R., Ebell, K., Egerer, U., Engelmann, R., Engler, C., Eppers, O., Gehrmann, M., Gong, X., Gottschalk, M., Gourbeyre, C., Griesche, H., Hartmann, J., Hartmann, M., Heinold, B., Herber, A., Herrmann, H., Heygster, G., Hoor, P., Jafariserajehlou, S., Jäkel, E., Järvinen, E., Jourdan, O., Kästner, U., Kecorius, S., Knudsen, E. M., Köllner, F., Kretzschmar, J., Lelli, L., Leroy, D., Maturilli, M., Mei, L., Mertes, S., Mioche, G., Neuber, R., Nicolaus, M., Nomokonova, T., Notholt, J., Palm, M., van Pinxteren, M., Quaas, J., Richter, P., Ruiz-Donoso, E., Schäfer, M., Schmieder, K., Schnaiter, M., Schneider, J., Schwarzenböck, A., Seifert, P., Shupe, M. D., Siebert, H., Spreen, G., Stapf, J., Stratmann, F., Vogl, T., Welti, A., Wex, H., Wiedensohler, A., Zanatta, M., & Zeppenfeld, S., 2019. The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification. Bulletin of the American Meteorological Society, 100(5), 841-871. https://doi.org/10.1175/BAMS-D-18-0072.1