Publikationen am Institut für Meteorologie und Geophysik
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Boyce, A., Liddell, M. V., Pugh, S., Brown, J., McMurchie, E., Parsons, A., Esteve, C., Burdick, S., Darbyshire, F. A., Cottaar, S., Bastow, I. D., Schaeffer, A. J., Audet, P., Schutt, D. L., & Aster, R. C. (2023). A new P-wave Tomographic Model (CAP22) for North America: Implications for the Subduction and Cratonic Metasomatic Modification History of Western Canada and Alaska. Journal of Geophysical Research - Solid Earth, 128(3), Artikel e2022JB025745. https://doi.org/10.1029/2022JB025745
Gasparini, B., Quante, M., & Lohmann, U. (2023). Ausdünnung der Cirrusbewölkung um dem Klimawandel entgegenzuwirken? in J. L. Lozán, H. Graßl, S.-W. Breckle, D. Kasang, & M. Quante (Hrsg.), WARNSIGNAL-KLIMA: Hilft Technik gegen die Erderwärmung?: Climate Engineering in der Diskussion (S. 256-263). Wissenschaftliche Auswertungen in Kooperation mit GEO Magazin-Hamburg. https://doi.org/10.25592/warnsignal.klima.climate.engineering.39
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
Brunner, L., & Sippel, S. (2023). Identifying climate models based on their daily output using machine learning. Environmental Data Science, 2, Artikel e22. https://doi.org/10.1017/eds.2023.23
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. Beitrag in VMV 2023, Vision, Modeling, and Visualization. The Eurographics Association, Deutschland. https://doi.org/10.2312/vmv.20231229
Liu, Y., Yao, Y., Liu, D., & Zhang, C. (2023). Nuclear Magnetic Resonance Investigation of Forced Imbibitions in Longmaxi Shales: Consideration of Different Boundary Conditions. Energy & Fuels, 37(8), 5853-5866. https://doi.org/10.1021/acs.energyfuels.3c00404
Eckhardt, S., Pisso, I., Evangeliou, N., Groot Zwaaftink, C., Plach, A., McConnell, J. R., Sigl, M., Ruppel, M. M., Zdanowicz, C., Lim, S., Chellman, N. J., Opel, T., Meyer, H., Steffensen, J. P., Schwikowski, M., & Stohl, A. (2023). Revised historical Northern Hemisphere black carbon emissions based on inverse modeling of ice core records. Nature Communications, 14(1), Artikel 271. https://doi.org/10.1038/s41467-022-35660-0
Quante, M., Gasparini, B., & Belge, B. (2023). Vom Regenmachen zur Klimaintervention – Ein Blick auf die Ideen- und Entwicklungsgeschichte des Climate Engineering. in J. L. Lozán, H. Graßl, S.-W. Breckle, D. Kasang, & M. Quante (Hrsg.), WARNSIGNAL-KLIMA: Hilft Technik gegen die Erderwärmung?: Climate Engineering in der Diskussion (S. 34-42). Wissenschaftliche Auswertungen in Kooperation mit GEO Magazin-Hamburg. https://doi.org/10.25592/warnsignal.klima.climate.engineering.05
Liptai, N., Gráczer, Z., Szanyi, G., Cloetingh, S. A. P. L., Süle, B., Aradi, L., Falus, G., Bokelmann, G., Timkó, M., Timár, G., Szabó, C., Istvan, K., & AlpArray Working Group (2022). Seismic anisotropy in the mantle of a tectonically inverted extensional basin: A shear-wave splitting and mantle xenolith study on the western Carpathian-Pannonian region. Tectonics, 845, Artikel 229643. https://doi.org/10.1016/j.tecto.2022.229643
Baier, K., Dütsch, M., Mayer, M., Bakels, L., Haimberger, L., & Stohl, A. (2022). The Role of Atmospheric Transport for El Niño-Southern Oscillation Teleconnections. Geophysical Research Letters, 49(23), Artikel e2022GL100906. https://doi.org/10.1029/2022GL100906
Badgeley, J. A., Steig, E. J., & Dütsch, M. (2022). Uncertainty in Reconstructing Paleo‐Elevation of the Antarctic Ice Sheet From Temperature‐Sensitive Ice Core Records. Geophysical Research Letters, 49(23), Artikel e2022GL100334. https://doi.org/10.1029/2022GL100334
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
Vojta, M., Plach, A., Thompson, R. L., & Stohl, A. (2022). A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions. Geoscientific Model Development, 15(22), 8295-8323. Artikel 22. https://doi.org/10.5194/gmd-15-8295-2022
Braun, C., Voigt, A., Hoose, C., Ekman, A. M. L., & Pinto, J. G. G. (2022). Controls on Subtropical Cloud Reflectivity during a Waterbelt Scenario for the Cryogenian Glaciations. Journal of Climate, 35(21), 3457-3476. https://doi.org/10.1175/JCLI-D-22-0241.1
Villanueva, D., Possner, A., Neubauer, D., Gasparini, B., Lohmann, U., & Tesche, M. (2022). Mixed-phase regime cloud thinning could help restore sea ice. Environmental Research Letters, 17(11), Artikel 114057. https://doi.org/10.1088/1748-9326/aca16d
Choudhary, A., & Voigt, A. (2022). Impact of grid spacing, convective parameterization and cloud microphysics in ICON simulations of a warm conveyor belt. Weather and Climate Dynamics, 3(4), 1199-1214. https://doi.org/10.5194/wcd-3-1199-2022
Sullivan, S., Voigt, A., Miltenberger, A., Rolf, C., & Krämer, M. (2022). A Lagrangian Perspective of Microphysical Impact on Ice Cloud Evolution and Radiative Heating. Journal of Advances in Modeling Earth Systems, 14(11), Artikel e2022MS003226. https://doi.org/10.1029/2022MS003226
Voigt, A., Schwer, P., Rotberg, N. V., & Knopf, N. (2022). TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids. Geoscientific Model Development, 15(19), 7489-7504. https://doi.org/10.5194/gmd-15-7489-2022
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
Benavent, N., Mahajan, A. S., Li, Q., Cuevas, C. A., Schmale, J., Angot, H., Jokinen, T., Quelever, L. L. J., Blechschmidt, A.-M., Zilker, B., Richter, A., Serna, J. A., Garcia-Nieto, D., Fernandez, R. P., Skov, H., Dumitrascu, A., Pereira, P. S., Abrahamsson, K., Bucci, S., ... Saiz-Lopez, A. (2022). Substantial contribution of iodine to Arctic ozone destruction. Nature Geoscience, 15(10), 770-773. https://doi.org/10.1038/s41561-022-01018-w
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