Publications

Publications

Höhlein, K., Weiss, S., Necker, T., Weissmann, M., Miyoshi, T., & Westermann, R. (2022). Evaluation of Volume Representation Networks for Meteorological Ensemble Compression. In VMV 2022: Vision, Modeling, and Visualization https://doi.org/10.2312/vmv.20221198

Geiss, S., Scheck, L., de Lozar, A., & Weissmann, M. (2021). Understanding the model representation of clouds based on visible and infrared satellite observations. Atmospheric Chemistry and Physics, 21(16), 12273-12290. https://doi.org/10.5194/acp-21-12273-2021

Martin, A., Weissmann, M., Reitebuch, O., Rennie, M., Geiss, A., & Cress, A. (2021). Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents. Atmospheric Measurement Techniques, 14(3), 2167-2183. https://doi.org/10.5194/amt-14-2167-2021

Neggers, R. A. J., & Griewank, P. J. (2021). A Binomial Stochastic Framework for Efficiently Modeling Discrete Statistics of Convective Populations. Journal of Advances in Modeling Earth Systems, 13(3), Article e2020MS002229. https://doi.org/10.1029/2020MS002229

Strauss, L., Serafin, S., & Dorninger, M. (2020). Skill and Potential Economic Value of Forecasts of Ice Accretion on Wind Turbines. Journal of Applied Meteorology and Climatology, 59(11), 1845–1864. https://doi.org/10.1175/JAMC-D-20-0025.1

Schröttle, J., Weissmann, M., Scheck, L., & Hutt, A. (2020). Assimilating visible and infrared radiances in idealized simulations of deep convection. Monthly Weather Review, 148(11), 4357-4375. https://doi.org/10.1175/MWR-D-20-0002.1

Scheck, L., Weissmann, M., & Bach, L. (2020). Assimilating visible satellite images for convective‐scale numerical weather prediction: A case‐study. Quarterly Journal of the Royal Meteorological Society, 146(732), 3165-3186. https://doi.org/10.1002/qj.3840

Necker, T., Geiss, S., Weissmann, M., Ruiz , J., Miyoshi, T., & Lien, GY. (2020). A convective‐scale 1,000‐member ensemble simulation and potential applications. Quarterly Journal of the Royal Meteorological Society, 146(728), 1423-1442. https://doi.org/10.1002/qj.3744

Hutt, A., Schraff, C., Anlauf, H., Bach, L., Baldauf, M., Bauernschubert, E., Cress, A., Faulwetter, R., Fundel, F., Köpken-Watts, C., Reich, H., Schomburg, A., Schröttle, J., Stephan, K., Stiller, O., Weissmann, M., & Potthast, R. (2020). Assimilation of SEVIRI Water Vapor Channels With an Ensemble Kalman Filter on the Convective Scale. Frontiers in Earth Science, 8, Article 70. https://doi.org/10.3389/feart.2020.00070

Necker, T., Weissmann, M., Ruckstuhl, Y., Anderson, J., & Miyoshi, T. (2020). Sampling Error Correction Evaluated Using a Convective-Scale 1000-Member Ensemble. Monthly Weather Review, 148(3), 1229–1249. https://doi.org/10.1175/MWR-D-19-0154.1

Schindler, M., Weissmann, M., Schäfler, A., & Radnoti, G. (2020). The Impact of Dropsonde and Extra Radiosonde Observations during NAWDEX in Autumn 2016. Monthly Weather Review, 148(2), 809-824. https://doi.org/10.1175/MWR-D-19-0126.1

Bachmann, K., Weissmann, M., Keil, C., Craig, G. C., & Welzbacher, C. A. (2020). Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography, and Synoptic Weather Regime. Monthly Weather Review, 148(1), 63-81. https://doi.org/10.1175/MWR-D-19-0045.1

Baars, H., Geiss, A., Wandinger, U., Herzog, A., Engelmann, R., Bühl, J., Radenz, M., Seifert, P., Ansmann, A., Martin, A., Leinweber, R., Lehmann, V., Weissmann, M., Cress, A., Filioglou, M., Komppula, M., & Reitebuch, O. (2020). First Results from the German Cal/Val Activities for Aeolus. The European physical journal. Web of conferences : proceedings, 237. https://doi.org/10.1051/epjconf/202023701008