Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 10, issue 8
Geosci. Model Dev., 10, 3145–3165, 2017
https://doi.org/10.5194/gmd-10-3145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 3145–3165, 2017
https://doi.org/10.5194/gmd-10-3145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

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

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 Discuss., https://doi.org/10.5194/tc-2019-252,https://doi.org/10.5194/tc-2019-252, 2019
Preprint under review for TC
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
The benefits of spatial resolution increase in global simulations of the hydrological cycle evaluated for the Rhine and Mississippi basins
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci., 23, 1779–1800, https://doi.org/10.5194/hess-23-1779-2019,https://doi.org/10.5194/hess-23-1779-2019, 2019
Short summary
Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018,https://doi.org/10.5194/hess-22-3275-2018, 2018
Short summary
An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-473,https://doi.org/10.5194/hess-2017-473, 2017
Revised manuscript not accepted
Short summary

Related subject area

Atmospheric Sciences
Local fractions – a method for the calculation of local source contributions to air pollution, illustrated by examples using the EMEP MSC-W model (rv4_33)
Peter Wind, Bruce Rolstad Denby, and Michael Gauss
Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020,https://doi.org/10.5194/gmd-13-1623-2020, 2020
Short summary
An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2
Vincent Huijnen, Kazuyuki Miyazaki, Johannes Flemming, Antje Inness, Takashi Sekiya, and Martin G. Schultz
Geosci. Model Dev., 13, 1513–1544, https://doi.org/10.5194/gmd-13-1513-2020,https://doi.org/10.5194/gmd-13-1513-2020, 2020
Short summary
PM2.5 ∕ PM10 ratio prediction based on a long short-term memory neural network in Wuhan, China
Xueling Wu, Ying Wang, Siyuan He, and Zhongfang Wu
Geosci. Model Dev., 13, 1499–1511, https://doi.org/10.5194/gmd-13-1499-2020,https://doi.org/10.5194/gmd-13-1499-2020, 2020
Short summary
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 1: Model physics and numerics
Arnau Folch, Leonardo Mingari, Natalia Gutierrez, Mauricio Hanzich, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 13, 1431–1458, https://doi.org/10.5194/gmd-13-1431-2020,https://doi.org/10.5194/gmd-13-1431-2020, 2020
Short summary
Overview of the PALM model system 6.0
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020,https://doi.org/10.5194/gmd-13-1335-2020, 2020
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.
Publications Copernicus
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.
MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the...
Citation