Publications

Publications

Rotach, M. W., Serafin, S., Ward, H. C., Arpagaus, M., Colfescu, I., Cuxart, J., De Wekker, S. F. J., Grubisic, V., Karl, T., Kirshbaum, D. J., Lehner, M., Mobbs, S. D., Paci, A., Palazzi, E., Bailey, A., Schmidli, J., Wittmann, C., Wohlfahrt, G., & Zardi, D. (2022). A collaborative effort to better understand, measure and model atmospheric exchange processes over mountains. Bulletin of the American Meteorological Society, 103(5), E1282-E1295. https://doi.org/10.1175/BAMS-D-21-0232.1

Pepin, N. C., Arnone, E., Gobiet, A., Haslinger, K., Kotlarski, S., Notarnicola, C., Palazzi, E., Seibert, P., Serafin, S., Schöner, W., Terzago, S., Thornton, J. M., Vuille, M., & Adler, C. (2022). Climate changes and their elevational patterns in the mountains of the world. Reviews of Geophysics, 60(1), [e2020RG000730]. https://doi.org/10.1029/2020RG000730

Griewank, P. J., Heus, T., & Neggers, R. A. J. (2022). Size‐Dependent Characteristics of Surface‐Rooted Three‐Dimensional Convective Objects in Continental Shallow Cumulus Simulations. Journal of Advances in Modeling Earth Systems, 14(3), [e2021MS002612]. https://doi.org/10.1029/2021MS002612

Göbel, M., Serafin, S., & Rotach, M. W. (2022). Numerically consistent budgets of potential temperature, momentum, and moisture in Cartesian coordinates: application to the WRF model. Geoscientific Model Development, 15(2), 669-681. https://doi.org/10.5194/gmd-15-669-2022

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), [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, [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