References

[AGRG10]

M. Andrejczuk, W. W. Grabowski, J. Reisner, and A. Gadian. Cloud-aerosol interactions for boundary layer stratocumulus in the lagrangian cloud model. Journal of Geophysical Research: Atmospheres, 115(D22):, 2010. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2010JD014248, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2010JD014248, doi:https://doi.org/10.1029/2010JD014248.

[ARH+08]

M. Andrejczuk, J. M. Reisner, B. Henson, M. K. Dubey, and C. A. Jeffery. The potential impacts of pollution on a nondrizzling stratus deck: does aerosol number matter more than type? Journal of Geophysical Research: Atmospheres, 113(D19):, 2008. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2007JD009445, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007JD009445, doi:https://doi.org/10.1029/2007JD009445.

[AJPG15]

S. Arabas, A. Jaruga, H. Pawlowska, and W. W. Grabowski. Libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in c++. Geoscientific Model Development, 8(6):1677–1707, 2015. URL: https://gmd.copernicus.org/articles/8/1677/2015/, doi:10.5194/gmd-8-1677-2015.

[AS17]

S. Arabas and S. Shima. On the ccn (de)activation nonlinearities. Nonlinear Processes in Geophysics, 24(3):535–542, 2017. URL: https://npg.copernicus.org/articles/24/535/2017/, doi:10.5194/npg-24-535-2017.

[AS13]

Sylwester Arabas and Shin-ichiro Shima. Large-eddy simulations of trade wind cumuli using particle-based microphysics with monte carlo coalescence. Journal of the Atmospheric Sciences, 70(9):2768 – 2777, 2013. URL: https://journals.ametsoc.org/view/journals/atsc/70/9/jas-d-12-0295.1.xml, doi:10.1175/JAS-D-12-0295.1.

[BA21]

Piotr Bartman and Sylwester Arabas. On the design of monte-carlo particle coagulation solver interface: a cpu/gpu super-droplet method case study with pysdm. In Maciej Paszynski, Dieter Kranzlmüller, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, and Peter M. A. Sloot, editors, Computational Science – ICCS 2021, 16–30. Cham, 2021. Springer International Publishing.

[DWP19]

P. Dziekan, M. Waruszewski, and H. Pawlowska. University of warsaw lagrangian cloud model (uwlcm) 1.0: a modern large-eddy simulation tool for warm cloud modeling with lagrangian microphysics. Geoscientific Model Development, 12(6):2587–2606, 2019. URL: https://gmd.copernicus.org/articles/12/2587/2019/, doi:10.5194/gmd-12-2587-2019.

[ETS14]

H. Carter Edwards, Christian R. Trott, and Daniel Sunderland. Kokkos: enabling manycore performance portability through polymorphic memory access patterns. Journal of Parallel and Distributed Computing, 74(12):3202 – 3216, 2014. Domain-Specific Languages and High-Level Frameworks for High-Performance Computing. URL: http://www.sciencedirect.com/science/article/pii/S0743731514001257, doi:https://doi.org/10.1016/j.jpdc.2014.07.003.

[GMS+19]

Wojciech W. Grabowski, Hugh Morrison, Shin-Ichiro Shima, Gustavo C. Abade, Piotr Dziekan, and Hanna Pawlowska. Modeling of cloud microphysics: can we do better? Bulletin of the American Meteorological Society, 100(4):655 – 672, 2019. URL: https://journals.ametsoc.org/view/journals/bams/100/4/bams-d-18-0005.1.xml, doi:10.1175/BAMS-D-18-0005.1.

[LL82]

T. B. Low and Roland List. Collision, coalescence and breakup of raindrops. part i: experimentally established coalescence efficiencies and fragment size distributions in breakup. Journal of Atmospheric Sciences, 39(7):1591 – 1606, 1982. URL: https://journals.ametsoc.org/view/journals/atsc/39/7/1520-0469_1982_039_1591_ccabor_2_0_co_2.xml, doi:https://doi.org/10.1175/1520-0469(1982)039<1591:CCABOR>2.0.CO;2.

[McF04]

Greg M. McFarquhar. A new representation of collision-induced breakup of raindrops and its implications for the shapes of raindrop size distributions. Journal of the Atmospheric Sciences, 61(7):777 – 794, 2004. URL: https://journals.ametsoc.org/view/journals/atsc/61/7/1520-0469_2004_061_0777_anrocb_2.0.co_2.xml, doi:https://doi.org/10.1175/1520-0469(2004)061<0777:ANROCB>2.0.CO;2.

[MvLWF+20]

Hugh Morrison, Marcus van Lier-Walqui, Ann M. Fridlind, Wojciech W. Grabowski, Jerry Y. Harrington, Corinna Hoose, Alexei Korolev, Matthew R. Kumjian, Jason A. Milbrandt, Hanna Pawlowska, Derek J. Posselt, Olivier P. Prat, Karly J. Reimel, Shin-Ichiro Shima, Bastiaan van Diedenhoven, and Lulin Xue. Confronting the challenge of modeling cloud and precipitation microphysics. Journal of Advances in Modeling Earth Systems, 12(8):e2019MS001689, 2020. e2019MS001689 2019MS001689. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019MS001689, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001689, doi:https://doi.org/10.1029/2019MS001689.

[SSJ+19]

M. Satoh, B. Stevens, F. Judt, M. Khairoutdinov, S. Lin, W. Putman, and P. Düben. Global cloud-resolving models. Curr Clim Change Rep, pages 172–184, 2019. doi:https://doi.org/10.1007/s40641-019-00131-0.

[SBW+19]

Thomas C. Schulthess, Peter Bauer, Nils Wedi, Oliver Fuhrer, Torsten Hoefler, and Christoph Schär. Reflecting on the goal and baseline for exascale computing: a roadmap based on weather and climate simulations. Computing in Science and Engineering, 21(1):30–41, 2019. doi:10.1109/MCSE.2018.2888788.

[SS23]

Hauke Schulz and Bjorn Stevens. Evaluating large-domain, hecto-meter, large-eddy simulations of trade-wind clouds using eurec4a data. Journal of Advances in Modeling Earth Systems, 15(10):e2023MS003648, 2023. e2023MS003648 2023MS003648. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023MS003648, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2023MS003648, doi:https://doi.org/10.1029/2023MS003648.

[SKK+09]

S. Shima, K. Kusano, A. Kawano, T. Sugiyama, and S. Kawahara. The super-droplet method for the numerical simulation of clouds and precipitation: a particle-based and probabilistic microphysics model coupled with a non-hydrostatic model. Quarterly Journal of the Royal Meteorological Society, 135(642):1307–1320, 2009. URL: https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.441, arXiv:https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.441, doi:https://doi.org/10.1002/qj.441.

[STT02]

Martin Simmel, Thomas Trautmann, and Gerd Tetzlaff. Numerical solution of the stochastic collection equation—comparison of the linear discrete method with other methods. Atmospheric Research, 61(2):135–148, 2002. URL: https://www.sciencedirect.com/science/article/pii/S0169809501001314, doi:https://doi.org/10.1016/S0169-8095(01)00131-4.

[SSAea19]

B. Stevens, M. Satoh, L. Auger, and et al. DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Prog Earth Planet Sci, 6:61, 2019. doi:https://doi.org/10.1186/s40645-019-0304-z.

[TBVP+21]

Christian Trott, Luc Berger-Vergiat, David Poliakoff, Sivasankaran Rajamanickam, Damien Lebrun-Grandie, Jonathan Madsen, Nader Al Awar, Milos Gligoric, Galen Shipman, and Geoff Womeldorff. The kokkos ecosystem: comprehensive performance portability for high performance computing. Computing in Science Engineering, 23(5):10–18, 2021. doi:10.1109/MCSE.2021.3098509.

[TLGA+22]

Christian R. Trott, Damien Lebrun-Grandié, Daniel Arndt, Jan Ciesko, Vinh Dang, Nathan Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy S. Hollman, Dan Ibanez, Nevin Liber, Jonathan Madsen, Jeff Miles, David Poliakoff, Amy Powell, Sivasankaran Rajamanickam, Mikael Simberg, Dan Sunderland, Bruno Turcksin, and Jeremiah Wilke. Kokkos 3: programming model extensions for the exascale era. IEEE Transactions on Parallel and Distributed Systems, 33(4):805–817, 2022. doi:10.1109/TPDS.2021.3097283.

[vSN+11]

Margreet C vanZanten, Bjorn Stevens, Louise Nuijens, A Pier Siebesma, A. S. Ackerman, F. Burnet, A. Cheng, F. Couvreux, H. Jiang, M. Khairoutdinov, Y. Kogan, D. C. Lewellen, D. Mechem, K. Nakamura, A. Noda, B. J. Shipway, J. Slawinska, S. Wang, and A. Wyszogrodzki. Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during rico. Journal of Advances in Modeling Earth Systems, 3(2):, 2011. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2011MS000056, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011MS000056, doi:https://doi.org/10.1029/2011MS000056.

[SlingoJBatesPBauerPaeal22]

Slingo, J., Bates, P., Bauer, P. and et al. Ambitious partnership needed for reliable climate prediction. Nat Clim Chang, 12:499–503, 2022. doi:https://doi.org/10.1038/s41558-022-01384-8.