Articles | Volume 10, issue 8
Geosci. Model Dev., 10, 3145–3165, 2017
https://doi.org/10.5194/gmd-10-3145-2017
Geosci. Model Dev., 10, 3145–3165, 2017
https://doi.org/10.5194/gmd-10-3145-2017

Model description paper 28 Aug 2017

Model description paper | 28 Aug 2017

MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows

Chiel C. van Heerwaarden et al.

Related authors

Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations
Anja Ražnjević, Chiel van Heerwaarden, Bart van Stratum, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, and Maarten Krol
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-614,https://doi.org/10.5194/acp-2021-614, 2021
Preprint under review for ACP
Short summary
Development of a large-eddy simulation subgrid model based on artificial neural networks: a case study of turbulent channel flow
Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021,https://doi.org/10.5194/gmd-14-3769-2021, 2021
Short summary
Understanding wind-driven melt of patchy snow cover
Luuk D. van der Valk, Adriaan J. Teuling, Luc Girod, Norbert Pirk, Robin Stoffer, and Chiel C. van Heerwaarden
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-171,https://doi.org/10.5194/tc-2021-171, 2021
Preprint under review for TC
Short summary
Using 3D turbulence-resolving simulations to understand the impact of surface properties on the energy balance of a debris-covered glacier
Pleun N. J. Bonekamp, Chiel C. van Heerwaarden, Jakob F. Steiner, and Walter W. Immerzeel
The Cryosphere, 14, 1611–1632, https://doi.org/10.5194/tc-14-1611-2020,https://doi.org/10.5194/tc-14-1611-2020, 2020
Short summary
Atmospheric boundary layer dynamics from balloon soundings worldwide: CLASS4GL v1.0
Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019,https://doi.org/10.5194/gmd-12-2139-2019, 2019
Short summary

Related subject area

Atmospheric sciences
Atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0: description and evaluation
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021,https://doi.org/10.5194/gmd-14-5525-2021, 2021
Short summary
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021,https://doi.org/10.5194/gmd-14-5487-2021, 2021
Short summary
Mesoscale nesting interface of the PALM model system 6.0
Eckhard Kadasch, Matthias Sühring, Tobias Gronemeier, and Siegfried Raasch
Geosci. Model Dev., 14, 5435–5465, https://doi.org/10.5194/gmd-14-5435-2021,https://doi.org/10.5194/gmd-14-5435-2021, 2021
Short summary
Multi-sensor analyses of the skin temperature for the assimilation of satellite radiances in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS, cycle 47R1)
Sebastien Massart, Niels Bormann, Massimo Bonavita, and Cristina Lupu
Geosci. Model Dev., 14, 5467–5485, https://doi.org/10.5194/gmd-14-5467-2021,https://doi.org/10.5194/gmd-14-5467-2021, 2021
Short summary
The Grell–Freitas (GF) convection parameterization: recent developments, extensions, and applications
Saulo R. Freitas, Georg A. Grell, and Haiqin Li
Geosci. Model Dev., 14, 5393–5411, https://doi.org/10.5194/gmd-14-5393-2021,https://doi.org/10.5194/gmd-14-5393-2021, 2021
Short summary

Cited articles

Bannon, P. R.: On the anelastic approximation for a compressible atmosphere, J. Atmos. Sci., 53, 3618–3628, 1996.
Beare, R. J., Macvean, M. K., Holtslag, A. A., Cuxart, J., Esau, I., Golaz, J. C., Jimenez, M. A., Khairoutdinov, M., Kosovic, B., Lewellen, D., and Lund, T. S.: An intercomparison of large-eddy simulations of the stable boundary layer, Bound.-Lay. Meteorol., 118, 247–272, 2006.
Betts, A. K.: Non-precipitating cumulus convection and its parameterization, Q. J. Roy. Meteor. Soc., 99, 178–196, 1973.
Boing, S. J.: The interaction of deep convective clouds and their environment, TU Delft, Delft University of Technology, the Netherlands, 2014.
Bou-Zeid, E., Meneveau, C., and Parlange, M.: A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows, Phys. Fluids, 17, 025105, https://doi.org/10.1063/1.1839152, 2005.
Download
Short summary
MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is made to simulate atmospheric flows up to the finest detail levels at very high resolution. It has been designed from scratch in C++ in order to use a modern design that allows the code to run on more than 10 000 cores, as well as on a graphical processing unit.