Publikationen
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Krüger, K., Schäfler, A., Wirth, M., Weissmann, M., & Craig, G. C. (2022). Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes. Atmospheric Chemistry and Physics, 22(23), 15559-15577. https://doi.org/10.5194/acp-22-15559-2022
Neggers, R., & Griewank, P. J. (2022). A decentralized approach for modeling organized convection based on thermal populations on microgrids. Journal of Advances in Modeling Earth Systems, 14(10), Artikel e2022MS003042. https://doi.org/10.1002/essoar.10510525.1, https://doi.org/10.1029/2022MS003042
Manzato, A., Serafin, S., Miglietta, M. M., Kirshbaum, D. J., & Schulz, W. (2022). A pan-Alpine climatology of lightning and convective initiation. Monthly Weather Review, 150(9), 2213-2230. https://doi.org/10.1175/MWR-D-21-0149.1
Strauss, L., Serafin, S., & Dorninger, M. (2022). Probability forecasts of ice accretion on wind turbines derived from multiphysics and neighbourhood ensembles. Quarterly Journal of the Royal Meteorological Society, 148(746), 2446-2467. https://doi.org/10.1002/qj.4311
Craig, G. C., Puh, M., Keil, C., Tempest, K., Necker, T., Ruiz , J., Weissmann, M., & Miyoshi, T. (2022). Distributions and convergence of forecast variables in a 1000 member convection-permitting ensemble. Quarterly Journal of the Royal Meteorological Society, 148(746), 2325-2343. https://doi.org/10.1002/qj.4305
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), Artikel 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), Artikel 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
Höhlein, K., Weiss, S., Necker, T., Weissmann, M., Miyoshi, T., & Westermann, R. (2022). Evaluation of Volume Representation Networks for Meteorological Ensemble Compression. Beitrag in VMV 2022, Vision, Modeling, and Visualization. The Eurographics Association., Konstanz, Deutschland. 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), Artikel 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, Artikel 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
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