Hier werden die Unterschiede zwischen zwei Versionen gezeigt.
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mitarbeiter_webseiten:ck [2019/11/11 12:47] keil [Veröffentlichungen] |
mitarbeiter_webseiten:ck [2024/04/15 08:13] (aktuell) keil [Veröffentlichungen] |
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| ===== Vorlesungen und Übungen ===== | ===== Vorlesungen und Übungen ===== | ||
| - | * [[ studium:vorlesungen:vorlesungsseiten:dynamische_meteorologie_i| Atmosphärische Dynamik I und II]] | + | * Numerische Modellierung |
| - | * Synoptik II | + | * Atmosphärische Dynamik I und II |
| - | * Theorie Seminar | + | * Synoptik II |
| - | * Bachelor Literaturseminar | + | * Theorie Seminar |
| - | * Master Literaturseminar | + | * Bachelor Literaturseminar |
| + | * Master Literaturseminar | ||
| ===== Aktuelle Forschung ===== | ===== Aktuelle Forschung ===== | ||
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| ===== Veröffentlichungen ===== | ===== Veröffentlichungen ===== | ||
| - | + | - Puh, M., Tempest, K., Keil, C., Craig, G. (2024): Flow dependence of forecast uncertainty in a large convection-permitting ensemble. Under review at Q. J. Roy. Meteorol. Soc. | |
| - | - Grazzini F., Craig G. C., Keil, C., Antolini G., Pavan V. (2019): Extreme precipitation events over Northern Italy. Part (I): a systematic classification with machine learning techniques. Quart. J. Roy. Meteor. Soc., doi:10.1002/qj.3635 | + | - Chen, I., J. Berner, C. Keil, G. Thompson, Y.-H. Kuo, G. Craig (2024): To which degree do the details of stochastic perturbation schemes matter for convective-scale and mesoscale error growth? Under review at Mon. Wea. Rev. |
| - | - Bachmann, K., C. Keil, G.C. Craig, M. Weissmann, C. Welzbacher (2019): Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography and Synoptic Weather Regime. Mon. Wea. Rev., doi:10.1175/MWR-D-19-0045.1 | + | - Tempest, K., Craig, G., Puh, M., Keil, C. (2024): Convergence of forecast distributions in weak and strong forcing convective weather regimes. Q. J. Roy. Meteorol. Soc., in press. |
| + | - Matsunobu, T., Puh, M., Keil, C. (2024): Quantifying flow- and scale-dependent spatial predictability of convective precipitation. Q. J. Roy. Meteorol. Soc., 1-18, http://doi.org/10.1002/qj.4713 | ||
| + | - Chen, I., J. Berner, C. Keil, Y. Kuo, and G. Craig (2023): Classification of Warm-Season Precipitation in High-Resolution Rapid Refresh (HRRR) Model Forecasts over the Contiguous United States. Mon. Wea. Rev., 152, 187–201, https://doi.org/10.1175/MWR-D-23-0108.1. | ||
| + | - Puh, M., C. Keil, C. Gebhardt, C. Marsigli, M. Hirt, F. Jakub, and G. C. Craig (2023): Physically based stochastic perturbations improve high‐resolution forecast of convection. Q. J. Roy. Meteorol. Soc., 149, 3582–3592. https://doi.org/10.1002/qj.4574 | ||
| + | - Diefenbach, T., Craig, G., Keil, C., Scheck, L. & Weissmann, M.(2023) Partial analysis increments as diagnostic for LETKF data assimilation systems. Q. J. Roy. Meteorol. Soc., 149, 740–756. https://doi.org/10.1002/qj.4419 | ||
| + | - Matsunobu, T., Keil, C., and Barthlott, C. (2022): The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control, Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022. | ||
| + | - Matsunobu, T., Keil, C., and Barthlott, C. (2022): ICON-D2 microphysically perturbed ensemble simulations including initial and boundary condition uncertainty. LMU Munich, Faculty of Physics. (Dataset). DOI: 10.57970/d1dn5-zwj06 | ||
| + | - Barthlott, C., Zarboo, A., Matsunobu, T., and Keil, C. (2022): Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-322. | ||
| + | - Craig, G. C., M. Puh, C. Keil, K. Tempest, T. Necker, J. Ruiz, M. Weissmann, and T. Miyoshi, (2022): Distributions and convergence of forecast variables in a 1,000-member convection-permitting ensemble. Q. J. Roy. Meteorol. Soc., 148, 2325–2343. Available from: https://doi.org/10.1002/qj.4305 | ||
| + | - Baur, F., Keil, C. & Barthlott, C. (2022) Combined effects of soil moisture and microphysical perturbations on convective clouds and precipitation for a locally forced case over Central Europe. Q. J. Roy. Meteorol. Soc., https://doi.org/10.1002/qj.4295 | ||
| + | - Barthlott, C., Zarboo, A., Matsunobu, T., and Keil, C.(2022): Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation, Atmos. Chem. Phys., https://doi.org/10.5194/acp-22-2153-2022 | ||
| + | - Keil, C., Chabert, L., Nuissier, O., and Raynaud, L. (2020): Dependence of Predictability of Precipitation in the Northwestern Mediterranean Coastal Region on the Strength of Synoptic Control, Atmos. Chem. Phys., 20, 15851–15865, https://doi.org/10.5194/acp-20-15851-2020 | ||
| + | - Grazzini F., Craig G. C., Keil, C., Antolini G., Pavan V. (2020): Extreme precipitation events over Northern Italy. Part (I): a systematic classification with machine learning techniques. Quart. J. Roy. Meteor. Soc., 146: 69-85. doi:10.1002/qj.3635 | ||
| + | - Bachmann, K., C. Keil, G.C. Craig, M. Weissmann, C. Welzbacher (2020): Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography and Synoptic Weather Regime. Mon. Wea. Rev., 148: 63-81. doi:10.1175/MWR-D-19-0045.1 | ||
| - Keil, C., F. Baur, K. Bachmann, S. Rasp, L. Schneider, C. Barthlott (2019): Relative contribution of soil moisture, boundary layer and microphysical perturbations on convective predictability in different weather regimes. Quart. J. Roy. Meteor. Soc., 145: 3102-3115. doi:10.1002/qj.3607 | - Keil, C., F. Baur, K. Bachmann, S. Rasp, L. Schneider, C. Barthlott (2019): Relative contribution of soil moisture, boundary layer and microphysical perturbations on convective predictability in different weather regimes. Quart. J. Roy. Meteor. Soc., 145: 3102-3115. doi:10.1002/qj.3607 | ||
| - Bachmann, K., C. Keil, M. Weissmann (2019): Impact of Radar Data Assimilation and Orography on Predictability of Deep Convection. Quart. J. Roy. Meteor. Soc., 145: 117-130. doi:10.1002/qj.3412 | - Bachmann, K., C. Keil, M. Weissmann (2019): Impact of Radar Data Assimilation and Orography on Predictability of Deep Convection. Quart. J. Roy. Meteor. Soc., 145: 117-130. doi:10.1002/qj.3412 | ||
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| - | //[[christian.keil@lmu.de|Christian Keil]] 26.07.2019// | + | //[[christian.keil@lmu.de|Christian Keil]] 15.04.2024// |