Publications

Papers

2024

Bishnoi, A., Stein, O., Meyer, C. I., Redler, R., Eicker, N., Haak, H., Hoffmann, L., Klocke, D., Kornblueh, L., and Suarez, E.: Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc, Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, 2024.

Clemens, J., Vogel, B., Hoffmann, L., Griessbach, S., Thomas, N., Fadnavis, S., Müller, R., Peter, T., and Ploeger, F.: A multi-scenario Lagrangian trajectory analysis to identify source regions of the Asian tropopause aerosol layer on the Indian subcontinent in August 2016, Atmos. Chem. Phys., 24, 763–787, https://doi.org/10.5194/acp-24-763-2024, 2024.

Herten, A. et al., „Application-Driven Exascale: The JUPITER Benchmark Suite,“ in 2024 SC24: International Conference for High Performance Computing, Networking, Storage and Analysis SC, Atlanta, GA, United States, 2024, pp. 468-512, doi: 10.1109/SC41406.2024.00038., 2024.

Liao, Y.; Deng, X.; Huang, M.; Liu, M.; Yi, J.; Hoffmann, L. Tracking Carbon Dioxide with Lagrangian Transport Simulations: Case Study of Canadian Forest Fires in May 2021. Atmosphere 2024, 15, 429. https://doi.org/10.3390/atmos15040429, 2024.

Liu, M., Hoffmann, L., Grooß, J.-U., Cai, Z., Grießbach, S., and Heng, Y.: Technical note: A comparative study of chemistry schemes for volcanic sulfur dioxide in Lagrangian transport simulations: a case study of the 2019 Raikoke eruption, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2596, 2024.

Nützel, M., Stecher, L., Jöckel, P., Winterstein, F., Dameris, M., Ponater, M., Graf, P., and Kunze, M.: Updating the radiation infrastructure in MESSy (based on MESSy version 2.55), Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, 2024.

Pérez-Invernón, F. J., Gordillo-Vázquez, F. J., Malagón-Romero, A., and Jöckel, P.: Global and regional chemical influence of sprites: reconciling modelling results and measurements, Atmos. Chem. Phys., 24, 3577–3592, https://doi.org/10.5194/acp-24-3577-2024, 2024.

Sonnabend, J., Grooß, j.-U., Ploeger, F., Hoffmann, L., Jöckel, P., Kern, B. and Müller, R.: Lagrangian transport based on the winds of the icosahedral nonhydrostatic model (ICON), Meteorologische Zeitschrift, 33(3), https://doi.org/10.1127/metz/2024/1207,2024.

Zou, L., Spang, R., Griessbach, S., Hoffmann, L., Khosrawi, F., Müller, R., and Tritscher, I.: Impact of mountain-wave-induced temperature fluctuations on the occurrence of polar stratospheric ice clouds: a statistical analysis based on MIPAS observations and ERA5 data, Atmos. Chem. Phys., 24, 11759–11774, https://doi.org/10.5194/acp-24-11759-2024, 2024.

2023

Clemens, J., Hoffmann, L., Vogel, B., Grießbach, S., and Thomas, N.: Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-214, 2023.

Döll, P., Sester, M., Feuerhake, U., Frahm, H. Fritzsch, B., Hezel, D. C., Kaus, B., Kolditz, O., Linxweiler, J., Müller Schmied, H., Nyenah, E., Risse, B., Schielein, U., Schlauch, T., Streck, T., and van den Oord, G.:Sustainable research software for high-quality computational research in the Earth System Sciences: Recommendations for universities, funders and the scientific community in Germany, http://dx.doi.org/10.23689/fidgeo-5805, 2023

Liu, M., Hoffmann, L., Griessbach, S., Cai, Z., Heng, Y., and Wu, X.: Improved representation of volcanic sulfur dioxide depletion in Lagrangian transport simulations: a case study with MPTRAC v2.4, Geosci. Model Dev., 16, 5197–5217, https://doi.org/10.5194/gmd-16-5197-2023, 2023.

Pérez-Invernón, F. J., Gordillo-Vázquez, F. J., Malagón-Romero, A., and Jöckel, P.: Gobal and regional chemical influence of sprites: Reconciling modeling results and measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2403, 2023.

Piotrowski, Z. P., Hokkanen, J., Caviedes-Voullieme, D., Stein, O., and Kollet, S.: Parflow 3.9: development of lightweight embedded DSLs for geoscientific models, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1079, 2023.

2022

Baumeister, P. F. and Hoffmann, L.: Fast infrared radiative transfer calculations using graphics processing units: JURASSIC-GPU v2.0, Geosci. Model Dev., 15, 1855–1874, https://doi.org/10.5194/gmd-15-1855-2022, 2022.

Becker, E., Vadas, S. L., Bossert, K., Harvey, V. L., Zülicke, C. and Hoffmann, L.: A High-resolution whole-atmosphere model with resolved gravity waves and specified large-scale dynamics in the troposphere and stratosphere. Journal of Geophysical Research: Atmospheres, 127, e2021JD035018. https://doi.org/10.1029/2021JD035018, 2022.

Cai, Z., Griessbach, S., and Hoffmann, L.: Improved estimation of volcanic SO₂ injections from satellite retrievals and Lagrangian transport simulations: the 2019 Raikoke eruption, Atmos. Chem. Phys., 22, 6787–6809,https://doi.org/10.5194/acp-22-6787-2022, 2022.

Caviedes-Voullième, D., Morales-Hernández, M., Norman, M. R., and Özgen-Xian, I.: SERGHEI (-SWE) v1.0: a performance portable HPC shallow water solver for hydrology and environmental hydraulics, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2022-208, in review, 2022.

Caviedes-Voullieme, D., Hokkanen, J., Kollet, S., Piotrowski, Z. P., and Stein, O.: Lightweight embedded DSLs for geoscientific models, in prep. for GMD, 2022.

Hoffmann, L., Baumeister, P. F., Cai, Z. et al.: Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on graphics processing units (GPUs). Geosci. Model Dev., 15, 2731–2762, https://gmd.copernicus.org/articles/15/2731/2022, 2022.

Konopka, P., Tao, M., von Hobe, M., Hoffmann, L., Kloss, C., Ravegnani, F., Volk, C. M., Lauther, V., Zahn, A., Hoor, P., and Ploeger, F.: Tropospheric transport and unresolved convection: numerical experiments with CLaMS 2.0/MESSy, Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, 2022.

Nützel, M., Brinkop, S., Dameris, M., Garny, H., Jöckel, P., Pan, L. L., and Park, M.: Climatology and variability of air mass transport from the boundary layer to the Asian monsoon anticyclone, Atmos. Chem. Phys., 22, 15659–15683, https://doi.org/10.5194/acp-22-15659-2022, 2022.

Pérez-Invernón, F. J., Huntrieser, H., Jöckel, P., and Gordillo-Vázquez, F. J.: A parameterization of long-continuing-current (LCC) lightning in the lightning submodel LNOX (version 3.0) of the Modular Earth Submodel System (MESSy, version 2.54), Geoscientific Model Development, 15, 1545–1565, doi: 10.5194/gmd-15-1545-2022, URL https://gmd.copernicus.org/articles/15/1545/2022, 2022.

Streffing, J., Sidorenko, D., Semmler, T., Zampieri, L., Scholz, P., Andrés-Martínez, M., Koldunov, N., Rackow, T., Kjellsson, J., Goessling, H., Athanase, M., Wang, Q., Hegewald, J., Sein, D. V., Mu, L., Fladrich, U., Barbi, D., Gierz, P., Danilov, S., Juricke, S., Lohmann, G., and Jung, T.: AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model, Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, 2022.

Uchida, T., Le Sommer, J., Stern, C., Abernathey, R. P., Holdgraf, C., Albert, A., Brodeau, L., Chassignet, E. P., Xu, X., Gula, J., Roullet, G., Koldunov, N., Danilov, S., Wang, Q., Menemenlis, D., Bricaud, C., Arbic, B. K., Shriver, J. F., Qiao, F., Xiao, B., Biastoch, A., Schubert, R., Fox-Kemper, B., Dewar, W. K., and Wallcraft, A.: Cloud-based framework for inter-comparing submesoscale-permitting realistic ocean models, Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, 2022.

Wright, C.J., Hindley, N.P., Alexander, M.J. et al. Surface-to-space atmospheric waves from Hunga Tonga–Hunga Ha’apai eruption. Nature, 609, 741–746, https://doi.org/10.1038/s41586-022-05012-5, 2022.

Zhang-Liu, Y., Müller, R., Grooß, J.-U. et al.: The impact of dehydration and initial HCl on HCl null cycles and ozone loss in the Antarctic lower stratosphere in the core of the
polar vortex, to be submitted to ACP, 2022.

2021

Danilov, S., Koldunov, N. V., Sidorenko, D., Scholz, P., and Wang, Q.: On the damping time scale of EVP sea ice dynamics. Journal of Advances in Modeling Earth Systems, 13, e2021MS002561. https://doi.org/10.1029/2021MS002561, 2021.

Franco, B., Blumenstock, T., Cho, C. et al. Ubiquitous atmospheric production of organic acids mediated by cloud droplets. Nature 593, 233–237, https://doi.org/10.1038/s41586-021-03462-x, 2021.

Hindley, N. P., Wright, C. J., Gadian, A. M., Hoffmann, L., Hughes, J. K., Jackson, D. R., King, J. C., Mitchell, N. J., Moffat-Griffin, T., Moss, A. C., Vosper, S. B., and Ross, A. N.: Stratospheric gravity waves over the mountainous island of South Georgia: testing a high-resolution dynamical model with 3-D satellite observations and radiosondes, Atmos. Chem. Phys., 21, 7695–7722, https://doi.org/10.5194/acp-21-7695-2021, 2021.

Hokkanen, J., Kollet, S., Kraus, J. et al.: Leveraging HPC accelerator architectures with modern techniques — hydrologic modeling on GPUs with ParFlow. Comput Geosci 25, 1579–1590, https://doi.org/10.1007/s10596-021-10051-4, 2021.

Stecher, L., Winterstein, F., Dameris, M., Jöckel, P., Ponater, M., and Kunze, M.: Slow feedbacks resulting from strongly enhanced atmospheric methane mixing ratios in a chemistry–climate model with mixed-layer ocean, Atmospheric Chemistry and Physics, 21, 731–754, https://acp.copernicus.org/articles/21/731/2021, 2021.

Weimer, M., Buchmüller, J., Hoffmann, L., Kirner, O., Luo, B., Ruhnke, R., Steiner, M., Tritscher, I., and Braesicke, P.: Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART, Atmos. Chem. Phys., 21, 9515–9543, https://doi.org/10.5194/acp-21-9515-2021, 2021.

Winterstein, F. & Jöckel, P.: Methane chemistry in a nutshell – the new submodels CH4 (v1.0) and TRSYNC (v1.0) in MESSy (v2.54.0), Geoscientific Model Development, 14, 661–674, doi: 10.5194/gmd-14-661-2021, URLhttps://gmd.copernicus.org/articles/14/661/2021, 2021.

Wu, X., Hoffmann, L., Wright, C. J., Hindley, N. P., Kalisch, S., Alexander, M. J., and Wang, Y.: Stratospheric gravity waves as a proxy for Hurricane intensification: A case study of weather research and forecast simulation for Hurricane Joaquin. Geophysical Research Letters, 49, e2021GL097010. https://doi.org/10.1029/2021GL097010, 2021.

2020

Garny, H., Walz, R., Nützel, M., and Birner, T.: Extending the Modular Earth Submodel System (MESSy v2.54) model hierarchy: the ECHAM/MESSy IdeaLized (EMIL) model setup, Geoscientific Model Development, 13, 5229–5257, https://gmd.copernicus.org/articles/13/5229/2020, 2020.

Nickl, A.-L., Mertens, M., Roiger, A., Fix, A., Amediek, A., Fiehn, A., Gerbig, C., Galkowski, M., Kerkweg, A., Klausner, T., Eckl, M., and Jöckel, P.: Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53), Geosci. Model Dev., 13, 1925–1943, https://doi.org/10.5194/gmd-13-1925-2020, 2020.

Righi, M., Hendricks, J., Lohmann, U., Beer, C. G., Hahn, V., Heinold, B., Heller, R., Krämer, M., Ponater, M., Rolf, C., Tegen, I., and Voigt, C.: Coupling aerosols to (cirrus) clouds in the global EMAC-MADE3 aerosol–climate model, Geoscientific Model Development, 13, 1635–1661, https://www.geosci-model-dev.net/13/1635/2020, 2020.

Sedona, R., Hoffmann, L., Spang, R., Cavallaro, G., Griessbach, S., Höpfner, M., Book, M., and Riedel, M.: Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds, Atmos. Meas. Tech., 13, 3661–3682, https://doi.org/10.5194/amt-13-3661-2020, 2020.

Semmler, T., S. Danilov, P. Gierz, H.F. Goessling, J. Hegewald, C. Hinrichs, N. Koldunov, N. Khosravi, L. Mu, T. Rackow, D. Sein, D. Sidorenko, Q. Wang and T. Jung: Simulations for CMIP6 with the AWI climate model AWI-CM-1-1. J. Adv. Model. Earth Sys., 12, https://doi.org/10.1029/2019MS002009, 2020.

Yamashita, H., Yin, F., Grewe, V., Jöckel, P., Matthes, S., Kern, B., Dahlmann, K., and Frömming, C.: Newly developed aircraft routing options for air traffic simulation in the chemistry–climate model EMAC 2.53: AirTraf 2.0, Geoscientific Model Development, 13, 4869–4890, https://gmd.copernicus.org/articles/13/4869/2020, 2020.

2019

Brinkop, S. and Jöckel, P.: ATTILA 4.0: Lagrangian advective and convective transport of passive tracers within the ECHAM5/MESSy (2.53.0) chemistry–climate model, Geoscientific Model Development, 12, 1991–2008, https://www.geosci-model-dev.net/12/1991/2019, 2019.

Koldunov, N., S. Danilov, D. Sidorenko, N. Hutter, M. Losch, H. Goessling, N. Rakowsky, P. Scholz, D. Sein, Q. Wang and T. Jung,: Fast EVP solutions in a high-resolution sea ice model, 11, 1269–1284, J. Adv. Model. Earth Sys., https://doi.org/10.1029/2018MS00148, 2019.

Koldunov, N. V., Aizinger, V., Rakowsky, N., Scholz, P., Sidorenko, D., Danilov, S., and Jung, T.: Scalability and some optimization of the Finite-volumE Sea ice–Ocean Model, Version 2.0 (FESOM2), Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, 2019.

Conference presentations

2022

Hartung, K. et al., Accelerating chemistry-climate simulations with MESSy, 10 Year Anniversary Workshop of NVIDIA Application Lab at Jülich, 2022.

Hoffmann, L. et al., MPTRAC: recent progress on Lagrangian transport simulations on GPUs, 10 Year Anniversary Workshop of NVIDIA Application Lab at Jülich, 2022.

Meyer, C. I. and the PilotLab ExaESM Team, The Pilot Lab Exascale Earth System Modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10919, https://doi.org/10.5194/egusphere-egu22-10919, https://meetingorganizer.copernicus.org/EGU22/EGU22-10919.html, 2022.

Holke, J. and Spataro, L., Lossy compression by adaptive mesh refinement. Exploiting data compression for climate science workflows in the exascale era, 01.-02. Feb 2022, Online, https://elib.dlr.de/148663, 2022.

2021

Holke, J., Exascale-ready adaptive mesh refinement and applications in Earth system modelling. In: 19th Workshop on high performance computing in meteorology. 19th Workshop on high performance computing in meteorology, 20.09.2021 – 24.09.2021, Europe, https://elib.dlr.de/144163, 2021.

Holke, J., Enabling dynamic adaptive mesh refinement (in MESSy) using t8code. In: 10th EMAC Symposium. 10th EMAC Symposium, 31.05.2021 – 02.06.2021, online, https://elib.dlr.de/146910, 2021.

Christoudias, T., Kirfel, T., Kerkweg, A. et al., GPU Optimizations for Atmospheric Chemical Kinetics, in The International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2021), Association for Computing Machinery, New York, NY, USA, 136–138, https://doi.org/10.1145/3432261.3439863, 2021.

Versick, S., Fischer, T., Kirner, O., Meisel, T., and Meyer, J., Accelerating I/O in ESMs using on demand filesystems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12209, https://doi.org/10.5194/egusphere-egu21-12209, 2021.

2020

Versick, S., Kirner, O., Meyer, J., Obermaier, H., and Soysal, M., Performance gains in an ESM using parallel ad-hoc file systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18121, https://doi.org/10.5194/egusphere-egu2020-18121, 2020.

Master theses

2022

Böing, N., Untersuchung von Präkonditionierern für implizite Löser für das Local DG-Verfahren zur Lösung der Advektions-Diffusionsgleichung, Universität zu Köln, https://elib.dlr.de/186347, 2022.

2021

Spataro, L., Lossy data compression for atmospheric chemistry using adaptive mesh coarsening, Technische Universität München, https://elib.dlr.de/144997, 2021.

Dreyer, L., The local discontinuous galerkin method for the advection-diffusion equation on adaptive meshes, Rheinische Friedrich-Wilhems-Universität Bonn, https://elib.dlr.de/143969, 2021.

Bachelor theses

2020

Vogelsang, J., A concept study of a flexible asynchronous scheduler for dynamic Earth System Model components on heterogeneous HPC systems, FH Aachen, https://juser.fz-juelich.de/record/888549, 2020.