Publications
Serafin, S. (2025). Mountain Waves and Lee Waves. In W. A. Robinson (Ed.), Encyclopedia of Atmospheric Sciences Elsevier. https://doi.org/10.1016/B978-0-323-96026-7.00123-5
Diefenbach, T., Scheck, L., Weissmann, M., & Craig, G. C. (2024). Diagnostics for Imbalance on the Convective Scale. Monthly Weather Review, 152(9), 2075-2088. https://doi.org/10.1175/MWR-D-23-0291.1
Necker, T., Wolfgruber, L., Kugler, L., Weissmann, M., Dorninger, M., & Serafin, S. (2024). The fractions skill score for ensemble forecast verification. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.4824
Krüger, K., Schäfler, A., Weissmann, M., & Craig, G. C. (2024). Influence of radiosonde observations on the sharpness and altitude of the midlatitude tropopause in the ECMWF IFS. Weather and Climate Dynamics, 5(2), 491–509. https://doi.org/10.5194/wcd-5-491-2024
Kugler, L., & Weissmann, M. (2024). The synergy of assimilating visible and infrared radiances and radar observations. Manuscript submitted for publication.
Borne, M., Knippertz, P., Weissmann, M., Witschas, B., Flamant, C., Rios-Berrios, R., & Veals, P. (2024). Validation of Aeolus L2B products over the tropical Atlantic using radiosondes. Atmospheric Measurement Techniques, 17(2), 561-581. https://doi.org/10.5194/amt-17-561-2024
Martin, A., Weissmann, M., & Cress, A. (2023). Impact of assimilating Aeolus observations in the global model ICON: A global statistical overview. Quarterly Journal of the Royal Meteorological Society, 149(756), 2962-2979. https://doi.org/10.1002/qj.4541
Weinkaemmerer, J., Göbel, M., Serafin, S., Ďurán, I. B., & Schmidli, J. (2023). Boundary-layer plumes over mountainous terrain in idealized large-eddy simulations. Quarterly Journal of the Royal Meteorological Society, 149(757), 3183-3197. https://doi.org/10.1002/qj.4551
Kugler, L., Anderson, J. L., & Weissmann, M. (2023). Potential impact of all-sky assimilation of visible and infrared satellite observations compared with radar reflectivity for convective-scale numerical weather prediction. Quarterly Journal of the Royal Meteorological Society, 149(757), 3623-3644. https://doi.org/10.1002/qj.4577
Göbel, M., Serafin, S., & Rotach, M. W. (2023). Adverse impact of terrain steepness on thermally driven initiation of orographic convection. Weather and Climate Dynamics, 4(3), 725-745. https://doi.org/10.5194/wcd-4-725-2023
Davy, R., & Griewank, P. (2023). Arctic amplification has already peaked. Environmental Research Letters, 18(8), [084003]. https://doi.org/10.1088/1748-9326/ace273
Griewank, P. J., Weissmann, M., Necker, T., Nomokonova, T., & Löhnert, U. (2023). Ensemble‐based estimates of the impact of potential observations. Quarterly Journal of the Royal Meteorological Society, 149(754), 1546-1571. https://doi.org/10.1002/qj.4464
Borne, M., Knippertz, P., Weissmann, M., Martin, A., Rennie, M., & Cress, A. (2023). Impact of Aeolus wind lidar observations on the representation of the West African monsoon circulation in the ECMWF and DWD forecasting systems. Quarterly Journal of the Royal Meteorological Society, 149(752), 933-958. https://doi.org/10.1002/qj.4442
Diefenbach, T., Craig, G., Keil, C., Scheck, L., & Weissmann, M. (2023). Partial Analysis Increments as Diagnostic for LETKF Data Assimilation Systems. Quarterly Journal of the Royal Meteorological Society, 149(752), 740-756. https://doi.org/10.1002/qj.4419
Martin, A., Weissmann, M., & Cress, A. (2023). Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts. Weather and Climate Dynamics, 4(1), 249–264. https://doi.org/10.5194/wcd-4-249-2023
Necker, T., Hinger, D., Griewank, P., Miyoshi, T., & Weissmann, M. (2023). Guidance on how to improve vertical covariance localization based on a 1000-member ensemble. Nonlinear Processes in Geophysics, 30(1), 13-29. https://doi.org/10.5194/npg-30-13-2023
Hu, G., Dance, S. L., Bannister, R. N., Chipilski, H. G., Guillet, O., Macpherson, B., Weissmann, M., & Yussouf, N. (2023). Progress, challenges, and future steps in data assimilation for convection-permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021. Atmospheric Science Letters, 24(1), [e1130]. https://doi.org/10.1002/asl.1130
Nomokonova, T., Griewank, P., Loehnert, U., Miyoshi, T., Necker, T., & Weissmann, M. (2023). Estimating the benefit of Doppler wind lidars for short-term low-level wind ensemble forecasts. Quarterly Journal of the Royal Meteorological Society, 149(750), 192-210. https://doi.org/10.1002/qj.4402
Farokhmanesh, F., Höhlein, K., Necker, T., & Weissmann, M. (2023). Deep Learning–Based Parameter Transfer in Meteorological Data. Artificial Intelligence for the Earth Systems, 2(1). https://doi.org/10.1175/AIES-D-22-0024.1
Farokhmanesh, F., Höhlein, K., Neuhauser, C., Necker, T., Weissmann, M., Miyoshi, T., & Westermann, R. (2023). Neural Fields for Interactive Visualization of Statistical Dependencies in 3D Simulation Ensembles. Paper presented at VMV 2023, Vision, Modeling, and Visualization. The Eurographics Association, Germany. https://doi.org/10.2312/vmv.20231229