Waves to Weather
print


Breadcrumb Navigation


Content

Publications

  • Peer-reviewed articles and theses (PhD, MSc, BSc) published within the framework of W2W are listed below.
  • Peer-reviewed articles by W2W researchers published before W2W started (i.e. before July 1st, 2015) that are relevant to W2W are listed in "Previous publications" below.
  • Peer-reviewed articles by W2W researchers published during W2W that are relevant to W2W but that are not within the framework of W2W are listed in "Other publications" below.
--> Browse the AMS special collection "W2W" to read W2W articles published in AMS journals.
--> Browse the Special Online Collection "W2W" in QJRMS to read W2W articles published in the Quarterly Journal of the Royal Meteorological Society.

2024

  • Borne, M., Knippertz, P., Weissmann, M., Witschas, B., Flamant, C., Rios-Berrios, R., Veals, P.: Validation of Aeolus L2B products over the tropical Atlantic using radiosondes, Atmos. Meas. Tech., 17, 561–581, doi:10.5194/amt-17-561-2024. (Link to online article)
  • Höhlein, K., B. Schulz, R. Westermann, S. Lerch: Postprocessing of ensemble weather forecasts using permutation-invariant neural networks, Artificial Intelligence for the Earth Systems, 3 (1), e230070, doi: 10.1175/AIES-D-23-0070.1. (Link to online article)
  • Spaeth, J., Rupp, P., Garny, H., Birner, T.: Stratospheric impact on subseasonal forecast uncertainty in the Northern extratropics, Commun. Earth Environ., 5, 126, doi: 10.1038/s43247-024-01292-z. (Link to online article)

2023

  • Ageet, S., A. H. Fink, M. Maranan, and B. Schulz: Predictability of Rainfall over Equatorial East Africa in the ECMWF Ensemble Hindcast on short to medium-range time scales, Wea. Forecast, in press, doi: 10.1175/WAF-D-23-0093.1. (Link to online article)
  • Barrett, A. I., and Hoose, C.: Microphysical Pathways Active within Thunderstorms and Their Sensitivity to CCN Concentration and Wind Shear, J. Geophys. Res.: Atmospheres, 128, e2022JD036965, doi: 10.1029/2022JD036965. (Link to online article)
  • Beckert, A. A., Eisenstein, L., Oertel, A., Hewson, T., Craig, G. C., and Rautenhaus, M.: The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models, Geosci. Model Dev., 16, 4427–4450, doi: 10.5194/gmd-16-4427-2023. (Link to online article)
  • Borne, M., Knippertz, P., Weissmann, M., Martin, A., Rennie, M., and Cress, A.: Impact of Aeolus wind lidar observations on the representation of the West African monsoon circulation in the ECMWF and DWD forecasting systems, Quart. J. Roy. Meteorol. Soc., 149(752), 933–958, doi:10.1002/qj.4442. (Link to online article).
  • Chen, I., J. Berner, C. Keil, Y. Kuo, and G. Craig: Classification of Warm-Season Precipitation in High-Resolution Rapid Refresh (HRRR) Model Forecasts over the Contiguous United States, Mon. Wea. Rev., 152, 187–201, doi:10.1175/MWR-D-23-0108.1. (Link to online article)
  • Chertock, A., A. Kurganov, M. Lukácová-Medvidová, P. Spichtinger, and B. Wiebe: Stochastic Galerkin method for cloud simulation. Part II: a fully random Navier-Stokes-cloud model, J. Comput. Phys., 111987, doi: 10.1016/j.jcp.2023.111987. (Link to online article)
  • de Mourgues M., Emde C., Mayer B.: Optimized Wavelength Sampling for Thermal Radiative Transfer in Numerical Weather Prediction Models, Atmosphere, 14(2):332, doi: 10.3390/atmos14020332. (Link to online article)
  • Eisenstein, L., Schulz, B., Pinto, J. G., and Knippertz, P.: Identification of high-wind features within extratropical cyclones using a probabilistic random forest – Part 2: Climatology over Europe, Weather Clim. Dynam., 4, 981–999, doi: 10.5194/wcd-4-981-2023. (Link to online article)
  • Farokhmanesh, F., K. Höhlein, C. Neuhauser and R. Westermann: Neural Fields for Interactive Visualization of Statistical Dependencies in 3D Simulation Ensembles, Vision, Modeling, and Visualization, doi: 10.2312/vmv.20231229. (Link to online article)
  • Farokhmanesh, F., K. Höhlein, and R. Westermann: Deep Learning-based Parameter Transfer in Meteorological Data, Artificial Intelligence for the Earth Systems, 2(1), e220024, doi: 10.1175/AIES-D-22-0024.1. (Link to online article)
  • Gneiting, T., S. Lerch, B. Schulz: Probabilistic solar forecasting: Benchmarks, post-processing, verification, Solar Energy, 252, 72-80, doi: 10.1016/j.solener.2022.12.054. (Link to online article)
  • Gneiting, T., D. Wolffram, J. Resin, K. Kraus, J. Bracher, T. Dimitriadis, V. Hagenmeyer, A. I. Jordan, S. Lerch, K. Phipps, and M. Schienle: Model diagnostics and forecast evaluation for quantiles, Annu. Rev. Stat. Appl., 10, pre‐published, doi: 10.1146/annurev‐statistics‐032921‐020240. (Link to online article)
  • Groot, E. and Tost, H.: Evolution of squall line variability and error growth in an ensemble of LES, Atmos. Chem. Phys., 23, 565–585, doi: 10.5194/acp-23-565-2023. (Link to online article).
  • Groot, E. and Tost, H.: Divergent convective outflow in large-eddy simulations, Atmos. Chem. Phys., 23, 6065–6081, doi: 10.5194/acp-23-6065-2023. (Link to online article)
  • Hauser, S., Teubler, F., Riemer, M., Knippertz, P., and Grams, C. M.: Towards a holistic understanding of blocked regime dynamics through a combination of complementary diagnostic perspectives, Weather Clim. Dynam., 4, 399–425, doi: 10.5194/wcd-4-399-2023. (Link to online article)
  • Hauser, S., S. Mueller, X. Chen, T.-C. Chen, J. G. Pinto, and C. M. Grams: The Linkage of Serial Cyclone Clustering in Western Europe and Weather Regimes in the North Atlantic-European Region in Boreal Winter, Geophys. Res.Lett., 50(2), e2022GL101900, doi: 10.1029/2022GL101900. (Link to online article)
  • Hirt, M., Craig, G., C., Klein R.: Scale interactions between the meso- and synoptic scales and the impact of diabatic heating, Quart. J. Roy. Meteor. Soc., 149 (753), 1319-1334, doi: 10.1002/qj.4456. (Link to online article)
  • Janjic, T., M. Lukácová-Medvid’ová, Y. Ruckstuhl, and B. Wiebe: Comparison of un-certainty quantification methods for cloud simulation, Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.4537. (Link to online article)
  • Jung, H., Knippertz, P., Ruckstuhl, Y., Redl, R., Janjic, T., Hoose, C.: Understanding the dependence of mean precipitation on convective treatment and horizontal resolution in tropical aquachannel experiments, Wea. Clim. Dyn., 4, 1111-1134, doi:10.5194/wcd-4-1111-2023. (Link to online article)
  • Jung, H. and P. Knippertz: Link between the time-space behavior of rainfall and 3D dynamical structures of equatorial waves in global convection-permitting simulations, Geophys. Res. Lett., 49, doi:10.1029/2022GL100973, e2022GL100973. (Link to online article)
  • Keshtgar, B., A. Voigt, C. Hoose, M. Riemer, and B. Mayer: Cloud-radiative impact on the dynamics and predictability of an idealized extratropical cyclone, Weather Clim. Dynam., 4, 115–132, doi: 10.5194/wcd-4-115-2023. (Link to online article)
  • Kiefer, S. M., S. Lerch, P. Ludwig, and J. G. Pinto: Can Machine Learning Models be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Timescales?. Artif. Intell. Earth Syst., in press, doi: 10.1175/AIES-D-23-0020.1. (Link to online article)
  • Li, J, Y. Li, J. Steppeler, A. Laurian, F. Fang, and D. Knapp: Meeting Summary: Challenges and Prospects for Numerical Techniques in Atmospheric Modeling, Bull. Amer. Meteorol. Soc., early online release, doi: 10.1175/BAMS-D-22-0269.1. (Link to online article)
  • Lukáčová-Medvid’ová, M., Schömer: A. Compressible Navier–Stokes Equations with Potential Temperature Transport: Stability of the Strong Solution and Numerical Error Estimates, J. Math. Fluid Mech., 25, 1, doi: 10.1007/s00021-022-00733-z. (Link to online article)
  • Martin, A., Weissmann, M., and Cress, A.: Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts, Weather Clim. Dynam., 4, 249–264, doi: 10.5194/wcd-4-249-2023. (Link to online article).
  • Matsunobu, T., J. F. Quinting, C. M. Grams, M. Matsueda: Regional extreme precipitation events in wintertime Japan facilitated by East-Asian large-scale flow patterns, SOLA, 19, 253-260, doi: 10.2151/sola.2023-033. (Link to online article)
  • Mayer A., and Wirth V.: Lagrangian description of the atmospheric flow from Eulerian tracer advection with relaxation, Quart. J. Roy. Meteor. Soc., 149 (753), 1271-1292, doi: 10.1002/qj.4453.
    (Link to online article)
  • Neuhauser C., Hieronymus M., Kern M., Rautenhaus M., Oertel A., Westermann R.: Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1), Geoscientific Model Development, 16, 4617–4638, doi: 10.5194/gmd-16-4617-2023. (Link to online article)
  • Oertel, A., Pickl, M., Quinting, J. F., Hauser, S., Wandel, J., Magnusson, L., M. Balmaseda, F. Vitart, C. M. Grams: Everything hits at once: How remote rainfall matters for the prediction of the 2021 North American heat wave, Geophys. Res. Lett., 50, e2022GL100958, doi: 10.1029/2022GL100958. (Link to online article)
  • Oertel, A., Miltenberger, A. K., Grams, C. M., and Hoose, C.: Interaction of microphysics and dynamics in a warm conveyor belt simulated with the ICOsahedral Nonhydrostatic (ICON) model, Atmos. Chem. Phys., 23, 8553–8581, doi: 10.5194/acp-23-8553-2023. (Link to online article)
  • Polster, C., and V. Wirth: A New Atmospheric Background State to Diagnose Local Waveguidability, Geophys. Res. Letters, 50, e2023GL106166, doi:10.1029/2023GL106166. (Link to online article)
  • Polster, C., and V. Wirth: The Onset of a Blocking Event as a "Traffic Jam": Characterization with Ensemble Sensitivity Analysis, J. Atmos. Sci., doi:10.1175/JAS-D-21-0312.1. (Link to online article)
  • Punge, H. J., Bedka, K. M., Kunz, M., Bang, S. D., and Itterly, K. F.: Characteristics of hail hazard in South Africa based on satellite detection of convective storms, Nat. Hazards Earth Syst. Sci., 23, 1549–1576, doi: 10.5194/nhess-23-1549-2023. (Link to online article)
  • Rasheeda Satheesh, A., P. Knippertz, A. H. Fink, E.-M. Walz, T. Gneiting: Sources of predictability of synoptic-scale rainfall during the West African summer monsoon, Quart. J. Roy. Met. Soc., early online release, doi:  10.1002/qj.4581. (Link to online article)
  • Rupp, P., J. Späth, H. Garny, T. Birner: Enhanced Polar Vortex Predictability Following Sudden Stratospheric Warming Events, Geophys. Res. Lett., 50(17), e2023GL104057, doi: 10.1029/2023GL104057.
    (Link to online article)
  • Schäfler, A., and M. Rautenhaus: Interactive 3D Visual Analysis of Weather Predic-tion Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment, Bull. Amer. Meteorol. Soc., 104 (8), E1426–E1434, doi: 10.1175/BAMS-D-22-0103.1. (Link to online article)
  • Schäfler, A., Sprenger, M., Wernli, H., Fix, A., and Wirth, M.: Case study on the influence of synoptic-scale processes on the paired H2O-O3 distribution in the UTLS across a North Atlantic jet stream, Atmos. Chem. Phys., 23, 999-1018, doi: 10.5194/acp-23-999-2023. (Link to online article).
  • Selz, T. and G.C. Craig: Can Artificial Intelligence-Based Weather Prediction Models Simulate the Butterfly Effect? Geophys. Res. Lett., 50(20), e2023GL105747, doi: 10.1029/2023GL105747 (Link to online article)
  • Spichtinger, P., Marschalik, P., and Baumgartner, M.: Impact of formulations of the homogeneous nucleation rate on ice nucleation events in cirrus, Atmos. Chem. Phys., 23, 2035–2060, doi: 10.5194/acp-23-2035-2023. (Link to online article).
  • Teubler, F., Riemer, M., Polster, C., Grams, C. M., Hauser, S., and Wirth, V.: Similarity and variability of blocked weather-regime dynamics in the Atlantic–European region, Weather Clim. Dynam., 4, 265–285, doi: 10.5194/wcd-4-265-2023. (Link to online article)
  • Thomas, J., Barrett, A., and Hoose, C.: Temperature and cloud condensation nuclei (CCN) sensitivity of orographic precipitation enhanced by a mixed-phase seeder–feeder mechanism: a case study for the 2015 Cumbria flood, Atmos. Chem. Phys., 23, 1987–2002, doi: 10.5194/acp-23-1987-2023. (Link to online article).
  • Ward, N., A. H. Fink, R. J. Keane, and D. J. Parker: Upper-level winter troughs near 40 degrees North have an amplified low-latitude linkage over Africa, Atmos. Sci. Lett., 24, e1129, doi: 10.1002/asl.1129. (Link to online article)

PhD theses - 2023

  • Groot, Edward: An analysis of variability and predictability of organised deep convection and its divergent upper tropospheric outflow. Dissertation, Johannes Gutenberg-Universität Mainz: FB 08 Physik, Mathematik u. Informatik, doi: 10.25358/openscience-9115. (Link to online document)

2022

  • Barthlott, C., Zarboo, A., Matsunobu, T., and Keil, C.: Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimes, Atmos. Chem. Phys., 22, 10841-10860, doi: 10.5194/acp-22-10841-2022. (Link to online article)
  • Barthlott, C., Zarboo, A., Matsunobu, T., and Keil, C.: Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation, Atmos. Chem. Phys., 22, 2153-2172, doi: 10.5194/acp-22-2153-2022. (Link to online article)
  • Baumgartner M., C. Rolf, J.-U. Grooß, J. Schneider, T. Schorr, O. Möhler, P. Spichtinger, and M. Krämer: New investigations on homogeneous ice nucleation: the ef-fects of water activity and water saturation formulations, Atmos. Chem. Phys., 22, 65–91, doi: 10.5194/acp-22-65-2022. (Link to online article)
  • Baur, F., C. Keil, and C. Barthlott: Combined effects of soil moisture and microphysical perturbations on convective clouds and precipitation for a locally forced case over Central Europe, Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.4295. (Link to online article)
  • Becker, F. N., A. H. Fink, J. G. Pinto, and P. Bissolli: Towards a more comprehensive assessment of the intensity of European heat waves (1979-2019), Atmos. Sci. Lett., e1120. DOI: 10.1002/asl.1120. (Link to online article)
  • Chapman, W. E., L. Delle Monache, S. Alessandrini, A. C. Subramanian, F. M. Ralph, S.-P. Xie, S. Lerch, and N. Hayatbini: Probabilistic Predictions from Deterministic Atmospheric River Forecasts with Deep Learning, Mon. Wea. Rev., 150, 215–234, doi: 10.1175/MWR-D-21-0106.1. (Link to online article)
  • Craig, G., M. Puh, C. Keil, K. Tempest, T. Necker, J. Ruiz, M. Weissmann, and T. Miyoshi: Distributions and convergence of forecast variables in a 1000 member convection-permitting ensemble, Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.4305. (Link to online article)
  • Eisenstein, L., Schulz, B., Qadir, G. A., Pinto, J. G., and Knippertz, P.: Objective identification of high‐wind features within extratropical cyclones using a probabilistic random forest (RAMEFI). Part I: Method and illustrative case studies, Weather Clim. Dynam. Discuss., 3, 1157-1182, doi: 10.5194/wcd-3-1157-202. (Link to online article)
  • Feireisl, E., M. Lukácová-Medvid’ová, S. Schneider, and B. She: Approximating viscosity solutions of the Euler system, Mathematics of Computations, in press, doi:10.1090/mcom/3738. (Link to online article)
  • Feireisl, E., M. Lukácová-Medvid’ová, B. She, and Y. Yuan: Convergence and error analysis of compressible fluid flows with random data: Monte Carlo method, Mathematical Models and Methods in Applied Sciences, doi: 10.1142/S0218202522500671. (Link to online article)
  • Fischer, C., A. H. Fink, E. Schömer, R. van der Linden, M. Maier-Gerber, M. Rautenhaus, and M. Riemer: A novel method for objective identification of 3-D potential vorticity anomalies, Geosci. Model Dev. Discuss., 15, 4447–4468, doi: 10.5194/gmd-2021-424. (Link to online article)
  • Gleiter, T., T. Janjić, N. Chen: Ensemble Kalman filter based data assimilation for tropical waves in the MJO skeleton model, Quart. J. Roy. Meteor. Soc., 148, 1035-1056, doi: 10.1002/qj.4245. (Link to online article)
  • Gneiting, T., and Vogel, P.: Receiver operating characteristic (ROC) curves: equivalences, beta model, and minimum distance estimation, Mach. Learn., 111, 2147–2159, doi:10.1007/s10994-021-06115-2. (Link to online article)
  • Gneiting, T., and Walz, E.-M.: Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA), Mach. Learn., 111, 2769-2797, doi: 10.1007/s10994-021-06114-3. (Link to online article)
  • Hieronymus, M., M. Baumgartner, A. Miltenberger, and A. Brinkmann: Algorithmic Differentiation for Sensitivity Analysis in Cloud Microphysics, J. Adv. Model. Earth Syst., 14(7), doi: 10.1029/2021MS002849. (Link to online article)
  • Höhlein, K., S. Weiss, and R. Westermann: Evaluation of Volume Representation Networks for Meteorological Ensemble Compression, in Vision, Modeling, and Visualization, doi: 10.2312/vmv.20221198. (Link to online article)
  • Kautz L.A., Martius O., Pfahl S., Pinto J.G., Ramos A.M., Sousa P.M., and Woollings T.: Atmospheric Blocking and Weather Extremes over the Euro-Atlantic Sector - A Review, Weather Clim. Dynam., 3, 305-336, doi: 10.5194/wcd-3-305-2022. (Link to online article)
  • Knippertz, P., Gehne, M., Kiladis, G. N., Kikuchi, K., Rasheeda Satheesh, A., Roundy, P. E., Yang, G.-Y., Žagar, N., Dias, J., Fink, A. H., Methven, J., Schlueter, A., Sielmann, F., Wheeler, M. C.: The intricacies of identifying equatorial waves, Quart. J. Roy. Meteorol. Soc., 148, 2814-2852, doi:10.1002/qj.4338. (Link to online article)
  • Kriegmair, R.Y. Ruckstuhl, S. Rasp, and G. Craig: Using neural networks to improve simulations in the gray zone, Nonlin. Processes Geophys., 29, 171–181, doi:10.5194/npg-29-171-2022. (Link to online article)
  • Krüger, K., Schäfler, A., Wirth, M., Weissmann, M., and Craig, G.: Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes, Atmos. Chem. Phys., 22, 15559-15577, doi: 10.5194/acp-2022-505. (Link to online article).
  • Legler, S. and T. Janjic: Combining data assimilation and machine learning to estimate parameters of a convective-scale model, Quart. J. Roy. Meteor. Soc., 148 (743), 860– 874, doi: 10.1002/qj.4235. (Link to inline article)
  • Lemburg, A. and A. H. Fink: Identifying causes of short-range forecast errors in maximum temperature during recent Central European heatwaves using the ECMWF-IFS ensemble, Wea. Forecast., 37, 1885-1902, doi: 10.1175/WAF-D-22-0033.1. (Link to online article)
  • Lukáčová-Medvid’ová, M., Schömer, A.: Existence of Dissipative Solutions to the Compressible Navier-Stokes System with Potential Temperature Transport, J. Math. Fluid Mech., 24, 82, doi: 10.1007/s00021-022-00713-3. (Link to online article)
  • Lukacova-Medvidova, M., B. She, Y. Yuan: Error estimate of the Godunov method for multidimensional compressible Euler equations, J. Sci. Comput., 91:71, doi: 10.1007/s10915-022-01843-6. (Link to online article)
  • Matsunobu, T., C. Keil, and C. Barthlott: The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty during different synoptic control, Weather and Clim. Dyn., 1–25, doi: 10.5194/wcd‐ 2022‐ 17. (Link to online article)
  • Muller, C., D. Yang, G. Craig, T. Cronin, B. Fildier, J. O. Haerter, C. Hohenegger, B. Mapes, D. Randall, S. Shamekh, and S. C. Sherwood: Spontaneous Aggregation of Convective Storms, Annu. Rev. Fluid Mech.54:1, 33-157, doi: 10.1146/annurev-fluid-022421-011319. (Link to online article)
  • Phipps, K., Lerch, S., Andersson, M., Mikut, R., Hagenmeyer, V. and Ludwig, N.: Evaluating ensemble post-processing for wind power forecasts, Wind Energy, Early Online, doi: 10.1002/we.2736. (Link to online article)
  • Quinting, J. F. and Grams, C. M.: EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 1: Development of deep learning model, Geosci. Model Dev., 15, 715–730, doi:10.5194/gmd-15-715-2022. (Link to online article)
  • Quinting, J. F., Grams, C. M., Oertel, A., and Pickl, M.: EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 2: Model application to different datasets, Geosci. Model Dev., 15, 731–744, doi:10.5194/gmd-15-731-2022. (Link to online article)
  • Rupp, P., S. Loeffel, H. Garny, X. Chen, J. G. Pinto, T. Birner: Potential links between tropospheric and stratospheric circulation extremes during early 2020, J. Geophys. Res., doi: 10.1029/2021JD035667. (Link to online article)
  • Schulz, B. and Lerch, S.: Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison, Mon. Weather Rev., 150 (1), 235-257, doi: 10.1175/MWR-D-21-0150.1. (Link to online article)
  • Selz, T., M. Riemer, and G.Craig: The transition from practical to intrinsic predictability of midlatitude weather, J. Atmos. Sci., doi:10.1175/JAS-D-21-0271.1. (Link to online article)
  • Spaeth, J. and T. Birner: Stratospheric Modulation of Arctic Oscillation Extremes as Represented by Extended‐Range Ensemble Forecasts, Weather Clim. Dyn., 3, 883–903, doi: 10.5194/wcd‐3‐883‐2022. (Link to online article)
  • Stumpfegger, J., K. Höhlein, G. Craig, and R. Westermann: GPU accelerated scalable parallel coordinates plots,
    Computers & Graphics, 109, 111-120, doi: 10.1016/j.cag.2022.10.008. (Link to online article).
  • Tempest, K. I., G. C. Craig, J. R. Brehmer: Convergence of forecast distributions in a 100,000 member idealised convective-scale ensemble, Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.4410. (Link to online article)
  • White, R. H., K. Kornhuber, O. Martius, and V. Wirth: From atmospheric waves to heatwaves: A waveguide perspective for understanding and predicting concurrent, persistent and extreme extratropical weather. Bull. Am. Meteorol. Soc., 103, E923–E935, doi: 10.1175/BAMS-D-21-0170.1. (Link to online article)

Master's theses - 2022

  • Bardachova, T.: Tropical Waves and Predictability in Simulations with a Stochastic Convection Scheme. Master thesis. LMU. (Link to online document)
  • Butz, K.: The radiative impact of clouds on idealized extratropical cyclones. MSc Thesis. University of Vienna, doi: 10.25365/thesis.71895. (Link to online document)
  • Kriening, M.: The 3-D Potential Vorticity Development during the Tropical Transition of Hurricane Leslie (2018) and
    Paulette (2020) over the North Atlantic Ocean. (Link to online document)
  • Mockert F.: Forecasting Forecast skill. Karlsruhe Institute of Technology. (Link to online document)

2021

  • Ageet, S., A. H. Fink, M. Maranan, J. Diem, J. Hartter, A. L. Ssali and P. Ayabagabo: Validation of Satellite Rainfall Estimates over Equatorial East Africa, J. Hydromet., 23, 129–151, doi: 10.1175/JHM-D-21-0145.1. (Link to online article)
  • Baran, A., Lerch, S., El Ayari, M. and Baran, S.: Machine learning for total cloud cover prediction, Neural Comput. and Applic., 33, 2605–2620, doi: 10.1007/s00521-020-05139-4. (Link to online article)
  • Caldas-Alvarez, A., Khodayar, S., and Knippertz, P.: The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6, Weather Clim. Dynam., 2, 561–580, doi:10.5194/wcd-2-561-2021. (Link to online article)
  • Craig, G. C., A. H. Fink, C. Hoose, T. Janjić, P. Knippertz, A. Laurian, S. Lerch, B. Mayer, A. Miltenberger, R. Redl, M. Riemer, K. I. Tempest, and V. Wirth: Waves to Weather: Exploring the limits of predictability of weather, Bull. Amer. Meteor. Soc.102 (11), E2151–E2164, doi:10.1175/BAMS-D-20-0035.1. (Link to online article
  • Črnivec, N. and Mayer, B.: Towards an improved treatment of cloud–radiation interaction in weather and climate models: exploring the potential of the Tripleclouds method for various cloud types using libRadtran 2.0.4, Geosci. Model Dev., 14, 3663–3682, doi:10.5194/gmd-14-3663-2021. (Link to online article)
  • Dimitriadis, T., T. Gneiting, A. I. Jordan: Stable reliability diagrams for probabilistic classifiers, Proc. Natl. Acad. Sci., 118 (8) e2016191118, doi:10.1073/pnas.2016191118. (Link to online article)
  • Feireisl, E., M. Lukáčová-Medvid’ová, H. Mizerová, B. She: Numerical Analysis of Compressible Flows, monograph, Vol. 20 Modeling, Simulation and Applications, Springer, ISSN: 2037-5255, 481 pages, doi: 10.1007/978-3-030-73788-7. (Link to online document)
  • Feireisl, E., M. Lukáčová-Medvid’ová, B. She, Y. Wang: Computing oscillatory solutions of the Euler system via K-convergence, M3AS Math. Mod. & Methods Appl. Sci., 31, 537-576, doi:10.1142/S0218202521500123. (Link to online article)
  • Flaounas, E., Gray, S. L., and Teubler, F.: A process-based anatomy of Mediterranean cyclones: from baroclinic lows to tropical-like systems, Weather Clim. Dynam., 2, 255–279, doi:10.5194/wcd-2-255-2021. (Link to online article)
  • Grazzini, F., G. Fragkoulidis, F. Teubler, V. Wirth and G. C. Craig: Extreme precipitation events over northern-central Italy. Part (II): Dynamical precursors, Quart. J. Roy. Meteor. Soc., 147, 1237-1257, doi: 10.1002/qj.3969 (Link to online article
  • Haupt, S.E., Chapman, W., Adams, S.V., Kirkwood, C., Hosking, J.S., Robinson, N.H., Lerch, S., and Subramanian, A.C.: Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop, Phil. Trans. R. Soc. A., 379, 20200091, doi: 10.1098/rsta.2020.0091. (Link to online article)
  • Hirt, M. and Craig, G.C.: A cold pool perturbation scheme to improve convective initiation in convection‐permitting models, Quart. J. Roy. Meteor. Soc., 147, 2429-2447, doi: 10.1002/qj.4032. (Link to online article)
  • Hochman A., Messori G., Quinting J.F., Pinto J.G., Grams C.M.: Do Atlantic- Europe-an weather regimes physically exist? Geophys. Res. Lett., 48:e2021GL095574, doi: 10.1029/2021GL095574. (Link to online article)
  • Janjić, T., Ruckstuhl, Y., Toint, P.L.: A data assimilation algorithm for predicting rain, Quart. J. Roy. Meteor. Soc., 1– 15, doi:10.1002/qj.4004. (Link to online article)
  • Krüger, F., Lerch, S., Thorarinsdottir, T.L., and Gneiting, T.: Predictive Inference Based on Markov Chain Monte Carlo Output, International Statistical Review, 89, 274-301, doi:10.1111/insr.12405. (Link to online article
  • Kučera, V., Lukáčová-Medvid’ová, M., Noelle, S., and Schütz, J.: Asymptotic properties of a class of linearly implicit schemes for weakly compressible Euler equations, Numer. Math., 42, doi: 10.1007/s00211-021-01240-5. (Link to online article)
  • Kumpf, A., J. Stumpfegger, P. F. Hartl, and R. Westermann: Visual Analysis of Multi-Parameter Distributions across Ensembles of 3D Fields, IEEE Transactions on Visualization and Computer Graphics, 1-16, doi: 10.1109/TVCG.2021.3061925. (Link to online article)
  • Leonard, L., Höhlein, K. and Westermann, R.: Learning Multiple-Scattering Solutions for Sphere-Tracing of Volumetric Subsurface Effects, Computer Graphics Forum, 40(2), 165-178, doi: 10.1111/cgf.142623. (Link to online article)
  • Maier-Gerber, M., A. H. Fink, M. Riemer, E. Schömer, C. Fischer, and B. Schulz: Statistical-Dynamical Forecasting of Sub-Seasonal North Atlantic Tropical Cyclone Occurrence, Wea. Forecast., 36 (6), 2127-2142, doi: 10.1175/WAF-D-21-0020.1. (Link to online article)
  • Meyer, M., Polkova, I., Modali, K. R., Schaffer, L., Baehr, J., Olbrich, S., and Rautenhaus, M.: Interactive 3-D visual analysis of ERA5 data: improving diagnostic indices for marine cold air outbreaks and polar lows, Weather Clim. Dynam., 2, 867–891, doi:10.5194/wcd-2-867-2021. (Link to online article)
  • Nicholson, S. E., A. H. Fink, C. Funk, D. Klotter, and A. Rasheeda Satheesh: Meteorological causes of the catastrophic rains of October/November 2019 in equatorial Africa, Global and Planetary Change, doi: 10.1016/j.gloplacha.2021.103687. (Link to online article)
  • Quinting, J. F., and C. M. Grams: Toward a Systematic Evaluation of Warm Conveyor Belts in Numerical Weather Prediction and Climate Models. Part I: Predictor Selection and Logistic Regression Model, J. Atmos. Sci., 78, 1465–1485, doi:10.1175/JAS-D-20-0139.1. (Link to online article)
  • Ruckstuhl Y., T. Janjić, and S. Rasp: Training a convolutional neural network to conserve mass in data assimilation, Nonlin. Processes Geophys., 28, 111–119, doi: 10.5194/npg-28-111-2021. (Link to online article)
  • Rupp, P., and T. Birner: Tropospheric eddy feedback to different stratospheric conditions in idealised baroclinic life cycles, Weather Clim. Dynam., 2, 111–128, doi: 10.5194/wcd-2-111-2021. (Link to online article)
  • Schulz, B., M. El Ayari, S. Lerch, and S. Baran: Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting, Solar Energy220, 1016-1031, doi: 10.1016/j.solener.2021.03.023. (Link to online article)
  • Teubler, F., and M. Riemer: Potential-vorticity dynamics of troughs and ridges within Rossby wave packets during a 40-year reanalysis period, Weather Clim. Dynam., 2, 535–559, doi:10.5194/wcd-2-535-2021. (Link to online article) 
  • Vogel, P., P. Knippertz, T. Gneiting, A. H. Fink, M. Klar, and A. Schlueter: Statistical forecasts for the occurrence of precipitation outperform global models over northern Tropical Africa, Geophys. Res. Lett., 48, e2020GL091022, doi:10.1029/2020GL091022. (Link to online article)
  • Walz, E-M., M. Maranan, R. van der Linden, A. H. Fink and P. Knippertz: An IMERG-Based Optimal Extended Probabilistic Climatology (EPC) as a Benchmark Ensemble Forecast for Precipitation in the Tropics and Subtropics, Wea. Forecasting, 36, 1561-1573, doi: 10.1175/WAF-D-20-0233.1. (Link to online article)
  • Wandel, J., Quinting, J., and C. M. Grams: Toward a Systematic Evaluation of Warm Conveyor Belts in Numerical Weather Prediction and Climate Models. Part II: Verification of Operational Reforecasts, J. Atmos. Sci., 78, 3965-3982, doi: 10.1175/JAS-D-20-0385.1. (Link to online article)
  • Wang, Y., Guang J. Zhang, S. Xie, W. Lin, G. C. Craig, Q. Tang, and H.-Y. Ma: Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model, Geosci. Model Dev., 14, 1575–1593. doi: 10.5194/gmd-14-1575-2021. (Link to online article)
  • Ward, N., A. H. Fink, R. J. Keane, F. Guichard, J. H. Marsham, D. J. Parker, C. M. Taylor: Synoptic timescale linkage between midlatitude winter troughs, Sahara temperature patterns and northern Congo rainfall: A building block of regional climate variability, Int. J. Climatol., 41, 3153-3173, doi: 10.1002/joc.7011. (Link to online article)
  • Wirth, V., and C. Polster: The problem of diagnosing jet waveguidability in the presence of large-amplitude eddies, J. Atmos. Sci., doi: 10.1175/JAS-D-20-0292.1. (Link to online article)
  • Zheng, B. and F. Sadlo: Uncertainty in Continuous Scatterplots, Continuous Parallel Coordinates, and Fibers, IEEE Transactions on Visualization and Computer Graphics, 27, 1819-1828, doi: 10.1109/TVCG.2020.3030466. (Link to online article)
PhD theses - 2021
  • Grazzini, Federico: Extreme precipitation in Northern Italy: genesis, classification and predictability. Dissertation, LMU München: Fakultät für Physik, doi: 10.5282/edoc.28219. (Link to online document)
  • Kremer, Tobias: Automatisierte Detektion kohärenter Strömungen und interaktive Exploration von Sturmstrukturen im Kontext des außertropischen Übergangs tropischer Zyklone, Johannes Gutenberg-Universität Mainz. (Link to online document)
Master's theses - 2021
  • Gleiter T.: Improving Data Assimilation for MJO Prediction based on Experiments with the
    Skeleton Model for Tropical Intraseasonal Variability. Ludwig-Maximilians-Universität. (Link to online document)
  • Legler, S.: Combining Data Assimilation and Machine Learning to Estimate Parameters of a Convective-Scale Model. Ludwig-Maximilians-Universität. (Link to online document)
  • Müller S.: The linkage between serial cyclone clustering and weather regimes. Karlsruhe Institute of Technology. (Link to online document)

2020

  • Baldwin, M. P., B. Ayarzagüena, T. Birner, N. Butchart, A. J. Charlton-Perez, A. H. Butler, D. 
I. V. Domeisen, C. I. Garfinkel, H. Garny, E. P. Gerber, M. I. Hegglin, U. Langematz, N. M. Pedatella: Sudden stratospheric warmings, Rev. Geophys., doi: 10.1029/2020RG000708. (Link to online article)
  • Baran, A., Lerch, S., El Ayari, M. and Baran, S.: Machine learning for total cloud cover prediction, Neural Computing and Applications, early online release. (Link to online article)
  • Barthlott, C. and Barrett, A. I.: Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany, Weather Clim. Dynam., 1, 207–224, doi: 10.5194/wcd-1-207-2020. (Link to online article)
  • Baumgartner, M., R. Weigel, A. H. Harvey, F. Plöger, U. Achatz, and P. Spichtinger: Reappraising the appropriate calculation of a common meteorological quantity: Potential Temperature, Atmos. Chem. Phys. Diss., 20, 15585–15616, doi:10.5194/acp-2020-361. (Link to online article)
  • Črnivec, N. and Mayer, B.: The incorporation of the Tripleclouds concept into the δ-Eddington two-stream radiation scheme: solver characterization and its application to shallow cumulus clouds, Atmos. Chem. Phys., 20,
    10733-10755, doi: 10.5194/acp-20-10733-2020. (Link to online article).
  • Dacre H.F., Pinto J.G.: Serial clustering of extratropical cyclones: a review of where, when and why it occurs, npj Clim. Atmos. Sci., 3, doi:10.1038/s41612-020-00152-9. (Link to online article)
  • Feireisl, E., M. Lukáčová-Medvid’ová, H. Mizerová, B. She: Convergence of a finite volume scheme for the compressible Navier-Stokes system, ESAIM: Math. Model. Num., 53, 1957-1979, doi: 10.1051/m2an/2019043. (Link to online article)
  • Feireisl, E., M. Lukacova-Medvidova, H. Mizerova, B. She: On the convergence of a finite volume method for the Navier-Stokes-Fourier system, IMA J. Num. Anal., 1-35, doi:10.1093/imanum/draa060. (Link to online article)
  • Fragkoulidis, G. and V. Wirth: Local Rossby Wave Packet Amplitude, Phase Speed, and Group Velocity: Seasonal Variability and their Role in Temperature Extremes, J. Clim., 33, 1–53, doi: 10.1175/JCLI-D-19-0377.1. (Link to online article)
  • Ghinassi P., M. Baumgart, F. Teubler, M. Riemer, and V. Wirth: A budget equation for the amplitude of Rossby wave packets based on finite amplitude local wave activity, J. Atmos. Sci., 77, 277–296, doi:10.1175/JAS-D-19-0149.1. (Link to online article)
  • Grazzini, F., Fragkoulidis, G., Pavan, V., Antolini, G.: The 1994 Piedmont flood: an archetype of extreme precipitation events in Northern Italy, Bull. of Atmos. Sci.& Technol., doi:10.1007/s42865-020-00018-1. (Link to online article)
  • Hanke, M. and N. Porz: Unique Solvability of a System of Ordinary Differential Equations Modeling a Warm Cloud Parcel, SIAM J. Appl. Math., 80, 706-724, doi: 10.1137/19M1267751. (Link to online article)
  • Harvey, B., J. Methven, C. Sanchez, and A. Schäfler: Diabatic generation of negative potential vorticity and its impact on the North Atlantic jet stream, Quart. J. Roy. Meteor. Soc., 146, 14771497, doi:10.1002/qj.3747. (Link to online article)
  • Hauser S., Grams C.M., Reeder M.J., McGregor S., Fink A.H., Quinting J.F.: A weather system perspective on winter–spring rainfall variability in southeastern Australia during El Niño, Q. J. Royal Meteorol. Soc., 1-20, doi: 10.1002/qj.3808. (Link to online article)
  • Hirt, M., G. C. Craig, S. A. K. Schäfer, J.Savre, and R. Heinze: Cold pool driven convective initiation: using causal graph analysis to determine what convection permitting models are missing, Q. J. Royal Meteorol. Soc., doi: 10.1002/qj.3788. (Link to online article)
  • Höhlein, K., Kern, M., Hewson, T., Westermann, R.: A comparative study of convolutional neural network models for wind field downscaling, Meteorol Appl., 27:e1961, doi:10.1002/met.1961. (Link to online article)
  • Keil, C., L. Chabert, O. Nuissier, and L. Raynaud: Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control, Atmos. Chem. Phys., 20, 15851–15865, doi: 10.5194/acp-20-15851-2020. (Link to online article)
  • Kern, M., Neuhauser, C., Maack, T., Han, M., Usher, W., and Westermann, R.: A Comparison of Rendering Techniques for 3D Line Sets with Transparency, IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2020.2975795. (Link to online article)
  • Klinger, C. and Mayer, B.: Neighboring column approximation – An improved 3D thermal radiative transfer approximation for non-rectangular grids, J. Adv. Model. Earth Syst., 12, doi: 10.1029/2019MS001843. (Link to online article)
  • Kremer, T., E. Schömer, C. Euler, and M. Riemer: Cluster analysis tailored to structure change of tropical cyclones using a very large number of trajectories, Mon. Wea. Rev., 148, 1-59, doi: 10.1175/MWR-D-19-0408.1.
    (Link to online article)
  • Lang, M. N., Lerch, S., Mayr, G. J., Simon, T., Stauffer, R., and Zeileis, A.: Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression, Nonlinear Process. Geophys., 27, 23–34, doi: 10.5194/npg-27-23-2020. (Link to online article).
  • Lerch, S., Baran, S., Möller, A., Groß, J., Schefzik, R., Hemri, S., and M. Graeter: Simulation-based comparison of multivariate ensemble post-processing methods, Nonlin. Processes Geophys., 27, 349–371, doi:10.5194/npg-27-349-2020. (Link to online article)
  • Lukacova-Medvidova, M.: K-convergence of finite volume solutions of the Euler equations, Finite Volumes for Complex Applications IX, Springer Proceedings in Mathematics & Statistics, Ed. Klöfkorn et al., 25-37, doi: 10.1007/978-3-030-43651-3_2. (Link to chapter)
  • Maranan, M., A. H. Fink, P. Knippertz, L. Amekudzi ,W. Atiah, and M. Stengel: A process-based validation of GPM IMERG and its sources using a mesoscale rain gauge network in the West African forest zone, J. Hydromet., 21, 729–749, doi: 10.1175/JHM-D-19-0257.1. (Link to online article)
  • Miltenberger, A. K., P. R. Field, A. H. Hill, and A. J. Heymsfield: Vertical redistribution of moisture and aerosol in orographic mixed-phase clouds, Atmos. Chem. Phys.20, 7979–8001, doi: 10.5194/acp-20-7979-2020. (Link to online article)
  • Miltenberger, A.K., Lüttmer, T., Siewert, C.: Secondary Ice Formation in Idealised Deep Convection—Source of Primary Ice and Impact on Glaciation, Atmosphere, 11, 542, doi: 10.3390/atmos11050542. (Link to online article)
  • Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D.I.V., Feser, F., Koszalka, I., Kreibich, H., Pantillon, F., Parolai, S., Pinto, J.G., Punge, H.J., Rivalta, E., Schröter, K., Strehlow, K., Weisse, R., and Wurpts, A.: Impact Forecasting to Support Emergency Management of Natural Hazards, Rev. Geophys., 58, doi: 10.1029/2020RG000704. (Link to online article)
  • Necker, T., M. Weissmann, Y. Ruckstuhl, J. Anderson, and T. Miyoshi: Sampling Error Correction Evaluated Using a Convective-Scale 1000-Member Ensemble, Mon. Wea. Rev., 148, 1229–1249, doi: 10.1175/MWR-D-19-0154.1. (Link to online article)
  • Necker, T., S. Geiss, M. Weissmann, J. Ruiz, T. Miyoshi, and G.‐Y. Lien: A convective‐scale 1,000‐member ensemble simulation and potential applications, Q. J. Royal Meteorol. Soc., 146, 1423-1442, doi:10.1002/qj.3744. (Link to online article)
  • Papavasileiou, G., A. Voigt, and P. Knippertz: The role of observed cloud‐radiative anomalies for the dynamics of the North Atlantic Oscillation on synoptic time‐scales, Q. J. Royal Meteorol. Soc., doi:10.1002/qj.3768. (Link to online article)
  • Rosemeier, J. and P. Spichtinger: Pattern formation in clouds via Turing instabilities, Math. Clim. Weather Forecast., 6, 75-96, doi: 10.1515/mcwf-2020-0104. (Link to online article)
  • Ruckstuhl, Y., and T. Janjić: Combined state-parameter estimation with the LETKF for convective-scale weather forecasting, Mon. Weather Rev., 148, 1607–1628, doi:10.1175/MWR-D-19-0233.1. (Link to online article)
  • Schäfler, A., B. Harvey, J. Methven, J.D. Doyle, S. Rahm, O. Reitebuch, F. Weiler, and B. Witschas: Observation of jet stream winds during NAWDEX and characterization of systematic meteorological analysis errors, Mon. Wea. Rev., 148, 2889-2907, doi:10.1175/MWR-D-19-0229.1. (Link to online article)
  • Schlueter, A.: Synoptic to intraseasonal variability of african rainfall. In Oxford Research Encyclopedia of Climate Science. Oxford University Press, online ISBN 9780190228620, doi: 10.1093/acrefore/9780190228620.013.522. (Link to online chapter)
  • Schultz, D. M., H. Volkert, B. Antonescu, and H. C. Davies: Defender and Expositor of the Bergen Methods of Synoptic Analysis: Significance, History, and Translation of Bergeron’s (1928) “Three-Dimensionally Combining Synoptic Analysis”, Bull. Amer. Meteorol. Soc., doi: 10.1175/BAMS-D-20-0021.1. (Link to online article)
  • Spensberger, C., Madonna, E., Boettcher, M., Grams, C.M., Papritz, L., Quinting, J.F., Röthlisberger, M., Sprenger, M. and Zschenderlein, P.: Dynamics of concurrent and sequential Central European and Scandinavian heatwaves, Q. J. Royal Meteorol. Soc., Accepted Author Manuscript, doi:10.1002/qj.3822. (Link to online article)
  • Vannitsem, S., Bremnes, J. B., Demaeyer, J., Evans, G. R., Flowerdew, J., Hemri, S., Lerch, S., Roberts, N., Theis, S., Ben Bouallègue, A. A. Z., Bhend, J., Dabernig, M., De Cruz, L., Hieta, L., Mestre, O., Moret, L., Odak Plenković, I., Schmeits, M., Taillardat, M., Van den Bergh, J., Van Schaeybroeck, B., Whan, K., and Ylhaisi,  J.:  Statistical Postprocessing for Weather Forecasts – Review, Challenges and Avenues in a Big Data World, Bull. Amer. Meteor. Soc., doi: 10.1175/BAMS-D-19-0308.1. (Link to online article
  • Vogel, P.Knippertz, P., Fink, A. H., Schlueter, A., Gneiting, T.: Skill of global raw and postprocessed ensemble predictions of rainfall in the tropics, Wea. Forecasting, 35(6), 2367–2385, doi:10.1175/WAF-D-20-0082.1. (Link to online article)
  • Wellmann, C., Barrett, A. I., Johnson, J. S., Kunz, M., Vogel, B., Carslaw, K. S., Hoose, C.: Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail, Atmos. Chem. Phys., 20 (4), 2201–2219. doi:10.5194/acp-20-2201-2020. (Link to online article)
  • Wilhelm J., S. Mohr, H.J. Punge, B. Mühr, M. Schmidberger, J.E. Daniell, K.M. Bedka, and M. Kunz: Severe thunderstorms with large hail across Germany in June 2019, Weather, doi:10.1002/wea.3886. (Link to online article)
  • Wirth, V.: Waveguidability of idealized midlatitude jets and the limitations of ray tracing theory, Weather Clim. Dynam., 1, 111–125, doi: 10.5194/wcd–1–111–2020. (Link to online article)
  • Zeifang, J., J. Schütz, K. Kaiser, A. Beck, M. Lukáčová-Medvid’ová, S. Noelle: A novel full-Euler low Mach number IMEX splitting, Commun. Comput. Phys., 27, 292–320, doi: 10.4208/cicp.OA-2018-0270. (Link to online article)
  • Zeng, Y., T. Janjić, A. de Lozar, S. Rasp, U. Blahak, A. Seifert, and G.C. Craig: Comparison of Methods Accounting for Subgrid-Scale Model Error in Convective-Scale Data Assimilation, Mon. Wea. Rev., 148, 2457–2477, doi:10.1175/MWR-D-19-0064.1. (Link to online article)
  • Zschenderlein, P., Pfahl, S., Wernli, H., and Fink, A. H.: A Lagrangian analysis of upper-tropospheric anticyclones associated with heat waves in Europe, Weather Clim. Dynam., 1, 191–206, doi: 10.5194/wcd-1-191-2020. (Link to online article)
PhD theses - 2020
  • Barekzai M.: On the impact of thermal radiation and turbulence on drizzle development. Ludwig-Maximilians-Universität, doi: 10.5282/edoc.26924. (Link to online document)
  • Baumgart, M.: Processes governing the amplification of forecast errors and forecast uncertainty in a quantitative potential-vorticity framework. Johannes Gutenberg Universität. (Link to online document)
  • Črnivec, N.: Towards an improved treatment of unresolved cloud-radiation interaction in weather and climate models. Ludwig-Maximilians-Universität, doi: 10.5282/edoc.27502. (Link to online document)
  • Ghinassi, P.: Investigating the dynamics of Rossby wave packets using Local Finite Amplitude Wave Activity. Johannes Gutenberg Universität. (Link to online document)
  • Hirt, M.: Convective initiation - relevant processes and their representation in convection-permitting models. Ludwig-Maximilians-Universität. (Link to online document)
  • Kumpf A.: Data-driven Ensemble Visualization. Technische Universität München. (Link to online document)
  • Rosemeier J.: Strukturbildung in Wolken. Johannes Gutenberg Universität. (Link to online document)
  • Zschenderlein, P.: Lagrangian Dynamics of European dynamics. Karlsruhe Institute of Technology. (Link to online document)

Master's theses - 2020

  • Kiefer S.: Characteristics of Selected Major Sudden Stratospheric Warming Events and their Links to European Cold Waves in Extended Range Ensemble Forecasts. Karlsruhe Institute of Technology. (Link to online document
  • Puh, M.: Distributions of Forecast Variables in a Convective‐scale 1000‐member Ensemble. Master thesis. LMU. (Link to online document)

2019

  • Bachmann, K., C. Keil, G. Craig, M. Weissmann, and C. A. Welzbacher: Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography and Synoptic Weather Regime, Mon. Weather Rev., 148, 63–81, doi:10.1175/MWR-D-19-0045.1. (Link to online article)
  • Barrett, A., C. Wellmann, A. Seifert, C. Hoose, B. Vogel, and M. Kunz: One Step at a Time: How Model Time Step Significantly Affects Convection‐Permitting Simulations, J. Adv. Model. Earth Sy., 11(3), 641-658, doi: 10.1029/2018MS001418. (Link to online article)
  • Baumgart, M. A. and M. Riemer: Processes governing the amplification of ensemble spread in a medium-range forecast with large forecast uncertainty, Q. J. Royal Meteorol. Soc., doi:10.1002/qj.3617. (Link to online article)
  • Baumgart, M., P. GhinassiV. Wirth, T. Selz, G. C. Craig, and M. Riemer: Quantitative view on the processes governing the upscale error growth up to the planetary scale using a stochastic convection scheme, Mon. Weather Rev., 147, 1713-1731, doi:10.1175/MWR-D-18-0292.1. (Link to online article)
  • Baumgartner, M., M. Sagebaum, N. R. Gauger, P. Spichtinger, and A. Brinkmann: Algorithmic differentiation for cloud schemes (IFS cy43r3) using CoDiPack (v1.8.1), Geosci. Model Dev., 12 (12), 5197–5212, doi: 10.5194/gmd-12-5197-2019. (Link to online article)
  • Baumgartner, M. and P. Spichtinger: Homogeneous nucleation from an asymptotic point of view, Theor. Comput. Fluid Dyn., 33, 83-106, doi:10.1007/s00162-019-00484-0. (Link to online article)
  • Bermann, J., and R. Torn: The Impact of Initial Condition and Warm Conveyor Belt Forecast Uncertainty on Variability in the Downstream Waveguide in an ECWMF Case Study, Mon. Weather Rev., 147, 4071-4089, doi: 10.1175/MWR-D-18-0333.1. (Link to online article)
  • Chertock, A., A. Kurganov, M. Lukáčová-Medvid’ová, P. Spichtinger, and B. Wiebe: Stochastic Galerkin method for cloud simulation, Math. Clim. Weather Forecast, 5, 65-106, doi: 10.1515/mcwf-2019-0005. (Link to online article)
  • Crnivec, N., and B. Mayer: Quantifying the bias of radiative heating rates in numerical weather prediction models for shallow cumulus clouds, Atmos. Chem. Phys., 19, 8083-8100, doi: 10.5194/acp-19-8083-2019. (Link to online article)
  • Di Muzio, E., M. Riemer, A. H. Fink, and M. Maier-Gerber: Assessing the predictability of Medicanes in ECMWF ensemble forecasts using an object‐based approach, Q. J. Royal Meteorol. Soc., 145, 1202-1217, doi:10.1002/qj.3489. (Link to online article)
  • Eisenstein, L., F. Pantillon, and P. Knippertz: Dynamics of sting‐jet storm "Egon" over continental Europe: impact of surface properties and model resolution, Q. J. Royal Meteorol. Soc., doi: 10.1002/qj.3666. (Link to online article)
  • Euler, C., M. Riemer, T. Kremer, and E. Schömer: Lagrangian Description of Air Masses Associated with Latent Heat Release in Tropical Storm Karl (2016) during Extratropical Transition, Mon. Weather Rev., 147, 2657-2676, doi:10.1175/MWR-D-18-0422.1. (Link to online article)
  • Feireisl, E., M. Lukáčová-Medvid’ová, H. Mizerová: K-convergence as a new tool in numerical analysis, IMA J. Num. Anal., 40, 2227–2255, doi: 10.1093/imanum/drz045. (Link to online article)
  • Feireisl, E., M. Lukáčová-Medvid’ová, H. Mizerová: A finite volume scheme for the Euler system inspired by the two velocities approach, Num. Math., 144, 89-132, doi: 10.1007/s00211-019-01078-y. (Link to online article)
  • Feireisl, E., M. Lukáčová-Medvid’ová, H. Mizerová: Convergence of finite volume schemes for the Euler equations via dissipative measure–valued solutions, Found. Comput. Math., 20, 923-966, doi: 10.1007/s10208-019-09433-z. (Link to online article)
  • Grazzini, F., Craig G.C., Keil C., Antolini G., and Pavan V: Extreme precipitation events over Northern Italy. Part (I): a systematic classification with machine learning techniques, Q. J. Royal Meteorol. Soc., 1–17, doi: 10.1002/qj.3635. (Link to online article)
  • Hirt, M., S. Rasp, U. Blahak, and G.C. Craig: Stochastic Parameterization of Processes Leading to Convective Initiation in Kilometer-Scale Models. Mon. Wea. Rev., 147, 3917–3934, doi: 10.1175/MWR-D-19-0060.1. (Link to online article)
  • Jordan, A., F. Krüger, and S. Lerch: Evaluating probabilistic forecasts with scoring Rules, J. Stat. Softw., 90, 1-37, doi: 10.18637/jss.v090.i12. (Link to online article)
  • Kautz, L.-A., Polichtchouk, I., Birner, T., Garny, H., Pinto, J. G.: Enhanced extended‐range predictability of the 2018 late‐winter Eurasian cold spell due to the stratosphere, Quart. J. Roy. Meteor. Soc., 146, 1040-1055, doi:10.1002/qj.3724. (Link to online article)
  • Keil, C., Baur, F., Bachmann, K., Rasp, S., Schneider, L., and Barthlott, C.: Relative contribution of soil moisture, boundary layer and microphysical perturbations on convective predictability in different weather regimes, Q. J. Royal Meteorol. Soc., Accepted Author Manuscript, doi:10.1002/qj.3607. (Link to online article)
  • Keller, J. H., C. M. Grams, M. Riemer, H. M. Archambault, L. Bosart, J. D. Doyle, J. L. Evans, T. J. Galarneau, K. Griffin, P. A. Harr, N. Kitabatake, R. McTaggart-Cowan, F. Pantillon, J. F. Quinting, C. A. Reynolds, E. A. Ritchie, R. D. Torn, and F. F. Zhang: The Extratropical Transition of Tropical Cyclones Part II: Interaction with the midlatitude flow, downstream impacts, and implications for predictability, Mon. Weather Rev., 147, 1077-1106, doi: 10.1175/MWR-D-17-0329.1. (Link to online article)
  • Kern, M. and R. Westermann: Clustering Ensembles of 3D Jet-Stream Core Lines, to appear in Proceedings of the Conference on Vision, Modeling, and Visualization 2019, doi: 10.2312/vmv.20191321. (Link to online article)
  • Kumpf, A., M. Rautenhaus, M. Riemer, and R. Westermann: Visual Analysis of the Temporal Evolution of Ensemble Forecast Sensitivities, IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/tvcg.2018.2864901. (Link to online article)
  • Kumpf, A., J. Stumpfegger, and R. Westermann: Cluster-based Analysis of Multi-Parameter Distributions in Cloud Simulation Ensembles, Vision, Modeling, and Visualization, accepted.
  • Maier-Gerber, M., Riemer, M., Fink, A. H., Knippertz P., Di Muzio E., McTaggart-Cowan R.: Tropical Transition of Hurricane Chris (2012) over the North Atlantic Ocean: A Multi-Scale Investigation of Predictability, Mon. Weather Rev., doi:10.1175/MWR-D-18-0188.1. (Link to online article)
  • Pantillon, F., Adler B., Corsmeier U., Knippertz P., Wieser A., and Hansen A.: Formation of Wind Gusts in an Extratropical Cyclone in the Light of Doppler Lidar Observations and Large-Eddy Simulations, Mon. Weather Rev., doi:10.1175/MWR-D-19-0241.1. (Link to online article)
  • Pinto J.G., Pantillon F., Ludwig P., Déroche M.S., Leoncini G., Raible C.C., Shaffrey L.C., Stephenson D.B.: From Atmospheric Dynamics to Insurance Losses – an Interdisciplinary Workshop on European Windstorms, Bull. Amer. Meteorol. Soc., doi:10.1175/ BAMS-D-19-0026.1 (Link to online article)
  • Reinbold, C., A. Kumpf, and R. Westermann: Visualizing the Stability of 2D Point Sets from Dimensionality Reduction Techniques, Comput. Graph. Forum, doi:10.1111/cgf.13806. (Link to online article)
  • Schindler, M., M. Weissmann, A. Schäfler, and G. Radnoti: The impact of dropsonde and extra radiosonde observations during NAWDEX in autumn 2016. Mon. Wea. Rev., doi: 10.1175/MWR-D-19-0126.1. (Link to online article)
  • Schlüter, A., A. H. Fink, P. Knippertz, and P. Vogel: A systematic comparison of tropical waves over northern Africa. Part I: Influence on rainfall, J. Clim., 32, 1501-1523, doi: 10.1175/JCLI-D-18-0173.1. (Link to online article)
  • Schlüter, A., A. H. Fink, and P. Knippertz: A systematic comparison of tropical waves over northern Africa. Part II: Dynamics and thermodynamics, J. Clim., 32, 2605–2625, doi: 10.1175/JCLI-D-18-0651.1. (Link to online article)
  • Schneider, L., C. Barthlott, C. Hoose, and A. I. Barrett: Relative impact of aerosol, soil moisture, and orography perturbations on deep convection, Atmos. Chem. Phys., 19, 12343–12359, doi:10.5194/acp-19-12343-2019. (Link to online article)
  • Schultz, D.M., L.F. Bosart, B.A. Colle, H.C. Davies, C. Dearden, D. Keyser, O. Martius, P.J. Roeber, W.J. Steenburgh, H. Volkert, and A.C. Winters: Extratropical Cyclones: A century of research on meteorology's centerpiece, Chapter 16 in G. McFarquhar et al.: A century of progress in atmospheric and related sciences: celebrating the American Meteorological Society centennial, Meteorol. Monographs, 59, 16.1-16.56, doi: 10.11752/AMSMONOGRAPHS-D-18-0015.1. (Link to online article)
  • Selz, T., L. Bierdel, and G. C. Craig: Estimation of the variability of mesoscale energy spectra with three years of COSMO-DE analyses, J. Atmos. Sci., 76, 627-637, doi: 10.1175/JAS-D-18-0155.1. (Link to online article)
  • Zeifang, J., J. Schütz, K. Kaiser, A. Beck, M. Lukacova-Medvidova, and S. Noelle: A novel full-Euler low Mach number IMEX splitting, accepted in Commun. Comput. Phys., 27, 292-320, doi: 10.4208/cicp.OA-2018-0270. (Link to online article)
  • Zschenderlein, P. , Fink, A. H., Pfahl, S. and Wernli, H.: Processes determining heat waves across different European climates, Q. J. Royal Meteorol. Soc., 145, 2973–2989, doi: 10.1002/qj.3599. (Link to online article)

PhD theses - 2019

  • Baur, F.:  Soil moisture-precipitation coupling over Central Europe: relative impact of surface heterogeneity on deep convection. Ludwig-Maximilians-Universität. (Link to online document)
  • Di Muzio, E.: Predictability of Medicanes in the ECMWF ensemble forecast system. Karlsruhe Institute of Technology. (Link to online document)
  • Fragkoulidis, G.: Rossby Wave Packets and their Role in Temperature Extremes. Johannes Gutenberg Universität. (Link to online document)
  • Rasp, S.: Statistical methods and machine learning in weather and climate modeling. Ludwig-Maximilians-Universität. (Link to online document)
  • Ruckstuhl, Y.: Joint state and parameter estimation to address model error in convective scale numerical weather prediction systems. (Link to online document)
  • Schlueter, A.: Tropical waves and rainfall over Africa: Variability, mechanisms and potential for forecasting, doi:10.5445/IR/1000094145. (Link to online document)
  • Vogel, P.: Assessing Predictive Performance: From Precipitation Forecasts over the Tropics to Receiver Operating Characteristic Curves and Back. Karlsruhe Institute of Technology. (Link to online document)
  • Wellmann, C.: Using Statistical Emulation for Sensitivity Studies of Deep Convective Clouds. Karlsruhe Institute of Technology. (Link to online document)

2018

  • Arnault, J., T. Rummler, F. Baur, S. Lerch, S. Wagner, B. Fersch, Z. Zhang, N. Kerandi, C. Keil, and H. Kunstmann: Precipitation sensitivity to the uncertainty of terrestrial water flow in WRF-Hydro – An ensemble analysis for Central Europe, J. Hydrometeorol., 19, 1007-1025, doi: 10.1175/jhm-d-17-0042.1. (Link to online article)
  • Bachmann K., C. Keil, and M. Weissmann: Impact of Radar Data Assimilation and Orography on Predictability of Deep Convection, Q. J. Royal Meteorol. Soc., doi: 10.1002/qj.3412. (Link to online article)
  • Baran, S., and S. Lerch: Combining predictive distributions for the statistical post-processing of ensemble forecasts, Int. J. Forecast., 34, 477-496, doi: 10.1016/j.ijforecast.2018.01.005. (Link to online article)
  • Barthlott, C. and C. Hoose: Aerosol effects on clouds and precipitation over central Europe in different weather regimes, J. Atmos. Sci., doi: 10.1175/jas-d-18-0110.1. (Link to online article)
  • Baumgart, M., M. Riemer, V. Wirth, F. Teubler, S. T. K. Lang: Potential-vorticity dynamics of forecast errors: A quantitative case study, Mon. Weather Rev., 146, 1405-1425, doi:10.1175/MWR-D-17-0196.1. (Link to online article)
  • Baur, F. , C. Keil, and G. C. Craig: Soil Moisture - Precipitation Coupling over Central Europe: Interactions between surface anomalies at different scales and its dynamical implication, Q. J. Royal Meteorol. Soc., doi: 10.1002/qj.3415. (Link to online article)
  • Bierdel, L., T. Selz, and G. C. Craig: Theoretical aspects of upscale error growth on the mesoscales: Idealized numerical simulations, Q. J. Royal Meteorol. Soc., 144, 682-694, doi: 10.1002/qj.3236. (Link to online article)
  • Chertock, A., M. Dudzinski, A. Kurganov, and M. Lukáčová-Medvid’ová: Well-balanced schemes for the shallow water equations with Coriolis forces, Num. Math., 939–973, doi: 10.1007/s00211-017-0928-0. (Link to online article)
  • Craig, G. C., and T. Selz: Mesoscale dynamical regimes in the midlatitudes, Geophys. Res. Lett., 45, 410-417, doi:10.1002/2017GL076174. (Link to online article)
  • Fragkoulidis, G., Wirth, V., Bossmann, P. and Fink, A.H.: Linking Northern Hemisphere temperature extremes to Rossby wave packets, Q. J. Royal Meteorol. Soc., 144, 553-566, doi:10.1002/qj.3228. (Link to online article)
  • Gentine, P., M. Pritchard, S. Rasp, G. Reinaudi and G. Yacalis, 2018: Could machine learning break the convection parameterization deadlock?, Geophys. Res. Lett.45, 5742-5751, doi: 10.1029/2018gl078202. (Link to online article)
  • Ghinassi, P., G. Fragkoulidis, and V. Wirth: Local Finite Amplitude Wave Activity as a diagnostic for Rossby wave packets, Mon. Weather Rev., doi:10.1175/MWR-D-18-0068.1. (Link to online article)
  • Gustafsson, N., Janjic, T., Schraff, C., Leuenberger, D., Weissman, M., Reich, H., Brousseau, P., Montmerle, T., Wattrelot, E., Bučánek, A., Mile, M., Hamdi, R., Lindskog, M., Barkmeijer, J., Dahlbom, M., Macpherson, B., Ballard, S., Inverarity, G., Carley, J., Alexander, C., Dowell, D., Liu, S., Ikuta, Y. and Fujita, T.: Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres, Q. J. Royal Meteorol. Soc., 144, 1218-1256, doi:10.1002/qj.3179. (Link to online article)
  • Hanser, K., O. Klein, B. Rieck, B. Wiebe, T. Selz, M. Piatkowski, A. Sagrista, B. Zheng, M. Lukacova, G. Craig, H. Leitte, and F. Sadlo: Visualization of Parameter Sensitivity of 2D Time-Dependent Flow. In Lecture notes in computer science: advances in visual computing (proceedings of international symposium on visual computing). Springer Berlin Heidelberg, 359-370, doi: 10.1007/978-3-030-03801-4_32. (Link to online article)
  • Janjić, T., Bormann, N., Bocquet, M., Carton, J. A., Cohn, S. E., Dance, S. L., Losa, S. N., Nichols, N. K., Potthast, R., Waller, J. A. and Weston, P.: On the representation error in data assimilation, Q. J. Royal Meteorol. Soc., 144, 1257-1278, doi:10.1002/qj.3130. (Link to online article)
  • Kerandi, N., J. Arnault, P. Laux, S. Wagner, J. Kitheka, and H. Kunstmann: Joint atmospheric-terrestrial water balances for East Africa: A WRF-Hydro case study for the upper Tana River basin, Theor. Appl. Climatol., 131, 1337–1355, doi:10.1007/s00704-017-2050-8. (Link to online article)
  • Kern, M., T. Hewson, F. Sadlo, R. Westermann and M. Rautenhaus: Robust detection and visualization of jet-stream core lines in atmospheric flow, IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2017.2743989. (Link to online article)
  • Kern M., T. Hewson, A. Schäfler, R. Westermann, and M. Rautenhaus: Interactive 3D Visual Analysis of Atmospheric Fronts, IEEE Transactions on Visualization and Computer Graphics, doi:10.1109/tvcg.2018.2864806. (Link to online article)
  • Knippertz, P., F. Pantillon, and A.H. Fink: The devil in the details of storms, Environ. Res. Lett., 13, 051001, doi: 10.1088/1748-9326/aabd3e. (Link to online article)
  • Kumpf, A., B. Tost, M. Baumgart, M. Riemer, R. Westermann, and M. Rautenhaus: Visualizing confidence in cluster-based ensemble weather forecast analyses, IEEE Transactions on Visualization and Computer Graphics, 24, 109-119, doi: 10.1109/TVCG.2017.2745178. (Link to online article)
  • Lentik, H.S., C.M. Grams, M. Riemer, and S. C. Jones: The effects of orography on the extratropical transition of tropical cyclones: a case study of typhoon Sinlaku (2008), Mon. Weather Rev., 146, 4231-4246, doi: 10.1175/MWR-D-18-0150.1. (Link to online article)
  • Pantillon, F., Lerch, S., Knippertz, P. and Corsmeier, U.: Forecasting wind gusts in winter storms using a calibrated convection‐permitting ensemble, Q. J. Royal Meteorol. Soc., 1-18, doi:10.1002/qj.3380. (Link to online article)
  • Pantillon, F., Wieser, A., Adler, B., Corsmeier, U., Knippertz, P.: Overview and first results of the Wind and Storms Experiment (WASTEX): a field campaign to observe the formation of gusts using a Doppler lidar, Adv. Sci. Res., 15, 91–97, doi:10.5194/asr-15-91-2018. (Link to online article)
  • Porz, N., M. Hanke, M. Baumgartner, and P. Spichtinger: A model for warm
    clouds with implicit droplet activation, avoiding saturation adjustment, Math. Clim. Weather Forecast., 4, 50-78, doi: 10.1515/mcwf-2018-0003. (Link to online article)
  • Rasp, S. and S. Lerch: Neural networks for post-processing ensemble weather forecasts, Mon. Weather Rev., doi: 10.1175/mwr-d-18-0187.1. (Link to online article)
  • Rasp, S., M. S. Pritchard, and P. Gentine: Deep learning to represent sub-grid processes in climate models. Proc. Natl. Acad. Sci., doi: 10.1073/pnas.1810286115. (Link to online article)
  • Rautenhaus, M., M. Böttinger, S. Siemen, R. Hoffman, R.M. Kirby, M. Mirzargar, N. Röber, and R. Westermann: Visualization in Meteorology - A Survey of Techniques and Tools for Data Analysis Tasks, IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2017.2779501 (Link to online article
  • Riboldi, J., C. M. Grams, and M. Riemer, and H. M. Archambault: A phase-locking perspective on Rossby wave amplification and atmospheric blocking downstream of recurving western North Pacific tropical cyclones, Mon. Weather Rev., doi: 10.1175/MWR-D-18-0271.1. (Link to online article)
  • Rosemeier, J., M. Baumgartner, and P. Spichtinger: Intercomparison of Warm-Rain Bulk Microphysics Schemes using Asymptotics, Math. Clim. Weather Forecast., 4, 104-124, doi:10.1515/mcwf-2018-0005. (Link to online article)
  • Ruckstuhl, Y. and Janjić, T.: Parameter and state estimation with ensemble Kalman filter based algorithms for convective scale applications, Q. J. Royal Meteorol. Soc., 144, 826-841, doi:10.1002/qj.3257. (Link to online article)
  • Schäfler, A., G. Craig, H. Wernli, P. Arbogast, J.D. Doyle, R. McTaggart-Cowan, J. Methven, G. Rivière, F. Ament, M. Boettcher, M. Bramberger, Q. Cazenave, R. Cotton, S. Crewell, J. Delanoë, A. Dörnbrack, A. Ehrlich, F. Ewald, A. Fix, C.M. Grams, S.L. Gray, H. Grob, S. Groß, M. Hagen, B. Harvey, L. Hirsch, M. Jacob, T. Kölling, H. Konow, C. Lemmerz, O. Lux, L. Magnusson, B. Mayer, M. Mech, R. Moore, J. Pelon, J. Quinting, S. Rahm, M. Rapp, M. Rautenhaus, O. Reitebuch, C.A. Reynolds, H. Sodemann, T. Spengler, G. Vaughan, M. Wendisch, M. Wirth, B. Witschas, K. Wolf, and T. Zinner: The North Atlantic Waveguide and Downstream Impact Experiment, Bull. Amer. Meteor. Soc., 99, 1607-1637, doi: 10.1175/BAMS-D-17-0003.1. (Link to online article)
  • Schneider, L., C. Barthlott, A.I. Barrett, C. Hoose: The precipitation response to variable terrain forcing over low mountain ranges in different weather regimes, Q. J. Royal Meteorol. Soc., 144, 970-989, doi:10.1002/qj.3250. (Link to online article)
  • Selz, T.: Estimating the intrinsic limit of predictability using a stochastic convection scheme. J. Atmospheric Sci., doi: 10.1175/JAS-D-17-0373.1. (Link to online article
  • Taylor, C. M., A. H. Fink, D. J. Parker, C. Klein, F. Guichard, P. P. Harris, and K. R. Knapp: Earlier seasonal onset of intense Mesoscale Convective Systems in the Congo Basin since 1999, Geophys. Res. Lett., 45, doi: 10.1029/2018GL080516. (Link to online article)
  • van der Does, M., P. Knippertz, P. Zschenderlein, R. Giles Harrison, J.-B. W. Stuut: The mysterious long-range transport of giant mineral dust particles, Sci. Adv., 4, doi: 10.1126/sciadv.aau2768. (Link to online article)
  • Vogel, P., P. Knippertz, A. Fink, A. Schlueter, and T. Gneiting: Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa, Wea. Forecasting., 33, 369-388, doi:10.1175/WAF-D-17-0127.1. (Link to online article)
  • Wellmann, C., A.I. Barrett, J.S Johnson, M. Kunz, B. Vogel, K.S Carslaw, and C. Hoose: Using emulators to understand the sensitivity of deep convective clouds and hail to environmental conditions, J. Adv. Model. Earth Syst., doi:10.1029/2018MS001465. (Link to online article)
  • Wirth, V., M. Riemer, E. K. M. Chang, O. Martius: Rossby Wave Packets on the Midlatitude Waveguide - A Review, Mon. Weather Rev., 146, 1965-2001, doi:10.1175/MWR-D-16-0483.1. (Link to online article)
  • Zeng, Y., Janjic, T., de Lozar, A., Blahak, U., Reich, H., Keil, C., and Seifert, A.: Representation of model error in convective-scale data assimilation: additive noise, relaxation methods and combinations, J. Adv. Model. Earth Syst. doi:10.1029/2018MS001375. (Link to online article)
  • Zschenderlein, P., G. Fragkoulidis, A. H. Fink, and V. Wirth: Large-scale Rossby wave and synoptic-scale dynamic analyses of the unusually late 2016 heat wave over Europe. Weather, 73(9), 275-283, doi: 10.1002/wea.3278. (Link to online article)

PhD theses - 2018

  • Schneider, L.: Relative Impact of Surface and Aerosol Heterogeneities on Deep Convection. Karlsruhe Institute of Technologie. (Link to online document)

2017

  • Barthlott, C., B. Mühr, and C. Hoose: Sensitivity of the 2014 Pentecost storms over Germany to different model grids and microphysics schemes, Q. J. Royal Meteorol. Soc., 143, 1485-1503, doi:10.1002/qj.3019. (Link to online article)
  • Bierdel, L., T. Selz, and G. C. Craig: Theoretical aspects of upscale error growth through the mesoscales: an analytical model, Q. J. Royal Meteorol. Soc., 143, 3048-3059, doi: 10.1002/qj.3160. (Link to online article)
  • Bispen, G., M. Lukacova-Medvidova, L. Yelash: Asymptotic preserving IMEX finite volume schemes for low Mach number Euler equations with gravitation. J. Comp. Phys., 335, 222-248, doi: 10.1016/j.jcp.2017.01.020. (Link to online article)
  • Engel, T., A.H. Fink, P. Knippertz, G. Pante, and Jan Bliefernicht: Extreme precipitation in the West African cities of Dakar and Ouagadougou – atmospheric dynamics and implications for flood risk assessments, J. Hydromet, 18, 2937-2957, doi: 10.1175/JHM-D-16-0218.1. (Link to online article)
  • Evans, C., K. M. Wood, S. D. Aberson, H. M. Archambault, S. M. Milrad, L. F. Bosart, K. L. Corbosiero, C. A. Davis, J. R. D. Pinto, J. Doyle, C. Fogarty, T. J. Galarneau, C. M. Grams, K. S. Griffin, J. Gyakum, R. E. Hart, N. Kitabatake, H. S. Lentink, R. McTaggart- Cowan, W. Perrie, J. F. D. Quinting, C. A. Reynolds, M. Riemer, E. A. Ritchie, Y. Sun, and F. Zhang: The extratropical transition of tropical cyclones. Part I: Cyclone evolution and direct impacts, Mon. Weather Rev., 145, 4317-4344, doi: 10. 1175/MWR-D-17-0027.1. (Link to online article)
  • Feireisl, E., and M. Lukacova-Medvidova: Convergence of a mixed finite element finite volume scheme for the isentropic Navier-Stokes system via dissipative measure-valued solutions, Found. Comput. Math., 18(3), 703-730. (Link to online article)
  • Feireisl, E., M. Lukacova-Medvidova, S. Necasova, A. Novotny, and B. She: Asymptotic preserving error estimates for numerical solutions of compressible Navier-Stokes equations in the low Mach number regime, Multiscale Model. Simul., 16(1), 150-183, doi:10.1137/16M1094233. (Link to online article)
  • Jung, P., Hausner, P., Pilz, L., Stern, J., Euler, C., Riemer, M., and Sadlo, F.: Tumble-vortex core line extraction. In Proceedings of sibgrapi wvis. (Link to online article)
  • Klinger, C., B. Mayer, F. Jakub, T. Zinner, S.-B. Park, and P. Gentine: Effects of 3-D thermal radiation on the development of a shallow cumulus cloud field, Atmos. Chem. Phys., 17, 5477-5500, doi: 10.5194/acp-17-5477-2017. (Link to online article)
  • Knippertz P., A.H. Fink, A. Deroubaix, E. Morris, F. Tocquer, M.J. Evans, C. Flamant, M. Gaetani, C. Lavaysse, C. Mari, J.H. Marsham, R. Meynadier, A. Affo-Dogo, T. Bahaga, F. Brosse, K. Deetz, R. Guebsi, I. Latifou, M. Maranan, P.D. Rosenberg, and A. Schlüter: A meteorological and chemical overview of the DACCIWA field campaign in West Africa in June–July 2016, Atmos. Chem. Phys., 17, 10893-10918, doi: 10.5194/acp-17-10893-2017. (Link to online article)
  • Lange, H., G.C. Craig, G. C., and T. Janjić: Characterizing noise and spurious convection in convective data assimilation, Q. J. Royal Meteorol. Soc., 143(709), 3060–3069, doi:10.1002/qj.3162. (Link to online article)
  • Lerch, S., and S. Baran: Similarity-based semilocal estimation of post-processing models, J. Roy. Statist. Soc., Ser. C (Applied Statistics), 66(1), 29-51, doi: 10.1111/rssc.12153. (Link to online article)
  • Lukacova-Medvidova, M., J. Rosemeier, P. Spichtinger, and B. Wiebe: IMEX finite volume methods for cloud simulation, in: Clement Cances, Pascal Omnes (eds.) Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic and Parabolic Problems, 179-187. (Link to online chapter)
  • Maier-Gerber, M., F. Pantillon, E. di Muzio, M. Riemer, A. H. Fink, and P. Knippertz: Birth of the Biscane, Weather, 72 (8), 236-241, doi:10.1002/wea.2995. (Link to the online article)
  • Pantillon, F., P. Knippertz, and U. Corsmeier: Revisiting the synoptic-scale predictability of severe European winter storms using ECMWF ensemble reforecasts, Nat. Hazards Earth Syst. Sci., 17, 1795-1810, doi:10.5194/nhess-2017-122. (Link to online article)
  • Rasp, S., Selz, T., and Craig, G.C.: Variability and clustering of mid-latitude summertime convection: Testing the Craig and Cohen (2006) theory in a convection-permitting ensemble with stochastic boundary layer perturbations, J. Atmos. Sci., 75, 691-706, doi: 10.1175/JAS-D-17-0258.1. (Link to online article)
  • Sagrista, A., S. Jordan, A. Just, F. Dias, L.G. Nonato, and F. Sadlo: Topological Analysis of Inertial Dynamics, IEEE Transactions on Visualization & Computer Graphics, 950-959, doi:10.1109/TVCG.2016.2599018. (Link to online article)
  • Selz, T., L. Fischer, and G. C. Craig: Structure function analysis of water vapor simulated with a convection-permitting model and comparison to airborne lidar observations. J. Atmos. Sci., 74, 1201-1210, doi: 10.1175/JAS-D-16-0160.1. (Link to online article)
  • Spreitzer, E.J., Marschalik, M.P., and Spichtinger, P.: Subvisible cirrus clouds – a dynamical system approach. Nonlin. Processes Geophys., 24, 307-328, doi:10.5194/npg-24-307-2017. (Link to online article)
  • Sprenger, M., Fragkoulidis, G., Binder, H., Croci-Maspoli, M., Graf, P., Grams, C. M., Knippertz, P., Madonna, E., Schemm, S., Škerlak, B. and Wernli, H.: Global climatologies of Eulerian and Lagrangian flow features based on ERA-Interim, Bull. Amer. Meteor. Soc., 98, 1739–1748, doi: 10.1175/BAMS-D-15-00299.1. (Link to inline article)
  • van der Linden, R., A. Fink, J. Pinto, and T. Phan-Van: The Dynamics of an Extreme Precipitation Event in Northeastern Vietnam in 2015 and its Predictability in the ECMWF Ensemble Prediction System, Wea. Forecasting, 32, 1041-1056, doi: 10.1175/WAF-D-16-0142.1. (Link to online article)
  • Volkert, H.: Putting faces to names: Snapshots of two committee meetings, 95 years apart, emphasize continuous international cooperation in the atmospheric sciences, Adv. Atmos. Sci., 34, 571-576, doi:10.1007/s00376-017-6329-6. (Link to online article)
  • Wolf, G., and V. Wirth: Diagnosing the horizontal propagation of Rossby wave packets along the midlatitude waveguide, Mon. Weather Rev., doi:10.1175/MWR-D-16-0355.1, 145, 3247-3264. (Link to online article)
  • Zeng, Y., T. Janjic, Y. Ruckstuhl, and M. Verlaan: Ensemble-Type Kalman Filter Algorithm conserving Mass, Total Energy and Enstrophy, Q. J. Royal Meteorol. Soc., 143(708), 2902-2914, doi: 10.1002/qj.3142. (Link to online article)

PhD theses - 2017

  • Bierdel, L.: On the relevance of rotational and divergent modes of motion to mesoscale dynamics and upscale error growth. Ludwig-Maximilians-Universität. (Link to online document)

2016

  • Kober, K., and G. C. Craig: Physically-based stochastic perturbations (PSP) in the boundary layer to represent uncertainty in convective initiation, J. Atmos. Sci., 73, 2893-2911, doi:10.1175/JAS-D-15-0144.1. (Link to online article)
  • Rasp, S., T. Selz, and G.C. Craig: Convective and slantwise trajectory ascent in convection-permitting simulations of mid-latitude cyclones, Mon. Weather Rev., 144, 3961-3976, doi: 10.1175/MWR-D-16-0112.1. (Link to online article)
  • Volkert, H.: Aerological data spurred dynamical meteorology: Richard Scherhag's contribution of 1934 as an early milestone, Meteorol. Z., 25, 521-526, doi: 10.1127/metz/2016/0784. (Link to online article)

PhD theses - 2016

  • Lerch, S.: Probabilistic forecasting and comparative model assessment, with focus on extreme events. Karlsruhe Institute of Technology. (Link to online document)