Dr. M.Sc.
tobias.necker(at)univie.ac.at
Josef-Holaubek-Platz 2 (UZA II), 1090 Vienna
Roomnumber: 2G504
Phone: +43-1-4277-537 14
© Tobias Necker
Curriculum vitae
03/2020 - 05/2024: Visiting Scientist at RIKEN (R-CCS, Kobe, Japan)
02/2020 - 04/2024: Postdoctoral Researcher at University of Vienna
08/2019 - 12/2019: Postdoctoral Researcher at Ludwig-Maximilians-University Munich
06/2015 - 07/2019: PhD at Ludwig-Maximilians-University Munich
Hans-Ertel-Zentrum (HErZ) for Weather Research, Data Assimilation Branch
10/2012 - 03/2015: M.Sc. in Meteorology at Ludwig-Maximilians-University Munich
10/2008 - 09/2012: B.Sc. in Physics plus minor in Meteorology at Ludwig-Maximilians-University Munich
Stays Abroad
01/2019 - 02/2019: RIKEN Student Trainee (R-CCS, Kobe, Japan)
06/2018 - 07/2018: RIKEN Student Trainee (R-CCS, Kobe, Japan)
11/2015 - 01/2016: COSMO Activity / Intern at MeteoSwiss (Zurich, Switzerland)
Research Interests
- Data assimilation
- Numerical weather prediction
- Large ensembles, sampling errors and localization
- Impact of observations in numerical weather prediction
- Probabilistic forecasting
- Verification methods
- Machine Learning
- Satellite data assimilation
Teaching
Recent Publications
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
Griewank, PJ, 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, vol. 149, no. 754, pp. 1546-1571. https://doi.org/10.1002/qj.4464
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, vol. 30, no. 1, pp. 13-29. https://doi.org/10.5194/npg-30-13-2023
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, vol. 149, no. 750, pp. 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, vol. 2, no. 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, 27/09/23 - 29/09/23. https://doi.org/10.2312/vmv.20231229
Craig, GC, 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, vol. 148, no. 746, pp. 2325-2343. https://doi.org/10.1002/qj.4305
Höhlein, K, Weiss, S, Necker, T, Weissmann, M, Miyoshi, T & Westermann, R 2022, 'Evaluation of Volume Representation Networks for Meteorological Ensemble Compression', Paper presented at VMV 2022, Vision, Modeling, and Visualization. The Eurographics Association., Konstanz, Germany, 23/09/22 - 30/09/22. https://doi.org/10.2312/vmv.20221198
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, vol. 146, no. 728, pp. 1423-1442. https://doi.org/10.1002/qj.3744
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, vol. 148, no. 3, pp. 1229–1249. https://doi.org/10.1175/MWR-D-19-0154.1