Articles | Volume 8, issue 6
https://doi.org/10.5194/gmd-8-1677-2015
https://doi.org/10.5194/gmd-8-1677-2015
Model description paper
 | 
09 Jun 2015
Model description paper |  | 09 Jun 2015

libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

S. Arabas, A. Jaruga, H. Pawlowska, and W. W. Grabowski

Related authors

Breakups are complicated: an efficient representation of collisional breakup in the superdroplet method
Emily de Jong, John Ben Mackay, Oleksii Bulenok, Anna Jaruga, and Sylwester Arabas
Geosci. Model Dev., 16, 4193–4211, https://doi.org/10.5194/gmd-16-4193-2023,https://doi.org/10.5194/gmd-16-4193-2023, 2023
Short summary
On numerical broadening of particle-size spectra: a condensational growth study using PyMPDATA 1.0
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022,https://doi.org/10.5194/gmd-15-3879-2022, 2022
Short summary
On the CCN (de)activation nonlinearities
Sylwester Arabas and Shin-ichiro Shima
Nonlin. Processes Geophys., 24, 535–542, https://doi.org/10.5194/npg-24-535-2017,https://doi.org/10.5194/npg-24-535-2017, 2017
Short summary
libmpdata++ 1.0: a library of parallel MPDATA solvers for systems of generalised transport equations
A. Jaruga, S. Arabas, D. Jarecka, H. Pawlowska, P. K. Smolarkiewicz, and M. Waruszewski
Geosci. Model Dev., 8, 1005–1032, https://doi.org/10.5194/gmd-8-1005-2015,https://doi.org/10.5194/gmd-8-1005-2015, 2015
Short summary

Related subject area

Atmospheric sciences
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024,https://doi.org/10.5194/gmd-17-759-2024, 2024
Short summary
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024,https://doi.org/10.5194/gmd-17-685-2024, 2024
Short summary
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024,https://doi.org/10.5194/gmd-17-651-2024, 2024
Short summary
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024,https://doi.org/10.5194/gmd-17-587-2024, 2024
Short summary
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024,https://doi.org/10.5194/gmd-17-607-2024, 2024
Short summary

Cited articles

Ahnert, K. and Mulansky, M.: Boost.Numeric.Odeint: solving ordinary differential equations, in: Boost Library Documentation, available at: http://www.boost.org/doc/libs/ (last access: 15 November 2014), 2013.
Andrejczuk, M., Reisner, J., Henson, B., Dubey, M., and Jeffery, C.: The potential impacts of pollution on a nondrizzling stratus deck: does aerosol number matter more than type?, J. Geophys. Res., 113, D19204, https://doi.org/10.1029/2007JD009445, 2008.
Andrejczuk, M., Grabowski, W., Reisner, J., and Gadian, A.: Cloud-aerosol interactions for boundary layer stratocumulus in the Lagrangian Cloud Model, J. Geophys. Res., 115, D22214, https://doi.org/10.1029/2010JD014248, 2010.
Arabas, S. and Pawlowska, H.: Adaptive method of lines for multi-component aerosol condensational growth and CCN activation, Geosci. Model Dev., 4, 15–31, https://doi.org/10.5194/gmd-4-15-2011, 2011.
Download
Short summary
This paper introduces a free and open-source C++ library of algorithms for representing cloud microphysics in numerical models. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionalities and complexities ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations.