Articles | Volume 10, issue 8
https://doi.org/10.5194/gmd-10-3145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
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
CORRESPONDING AUTHOR
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Max Planck Institute for Meteorology, Hamburg, Germany
Bart J. H. van Stratum
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Max Planck Institute for Meteorology, Hamburg, Germany
Thijs Heus
Cleveland State University, Cleveland, OH, USA
Jeremy A. Gibbs
Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA
Evgeni Fedorovich
University of Oklahoma, Norman, OK, USA
Juan Pedro Mellado
Max Planck Institute for Meteorology, Hamburg, Germany
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- Validating the Water Vapor Variance Similarity Relationship in the Interfacial Layer Using Observations and Large‐Eddy Simulations M. Osman et al. 10.1029/2019JD030653
- The Contributions of Shear and Turbulence to Cloud Overlap for Cumulus Clouds A. Sulak et al. 10.1029/2019JD032017
- Large-Eddy Simulations of the Steady Wintertime Antarctic Boundary Layer S. van der Linden et al. 10.1007/s10546-019-00461-4
- Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions A. Ražnjević et al. 10.5194/amt-15-3611-2022
- Numerical investigation of the influence of river flow on the atmospheric boundary layer under stably stratified conditions M. Hrebtov et al. 10.1088/1742-6596/1105/1/012028
- Direct Numerical Simulation of Turbulent Katabatic Slope Flows with an Immersed-Boundary Method C. Umphrey et al. 10.1007/s10546-017-0252-3
- Role of large eddies in the breakdown of the Reynolds analogy in an idealized mildly unstable atmospheric surface layer K. McColl et al. 10.1002/qj.3077
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65 citations as recorded by crossref.
- Galilean invariance of shallow cumulus convection large-eddy simulations O. Lamaakel & G. Matheou 10.1016/j.jcp.2020.110012
- The FastEddy®Resident‐GPU Accelerated Large‐Eddy Simulation Framework: Moist Dynamics Extension, Validation and Sensitivities of Modeling Non‐Precipitating Shallow Cumulus Clouds D. Muñoz‐Esparza et al. 10.1029/2021MS002904
- Toward Parametrization of Precipitating Shallow Cumulus Cloud Organization via Moisture Variance M. Thomas et al. 10.1029/2021JD034939
- Logarithmic profile of temperature in sheared and unstably stratified atmospheric boundary layers Y. Cheng et al. 10.1103/PhysRevFluids.6.034606
- Understanding wind-driven melt of patchy snow cover L. van der Valk et al. 10.5194/tc-16-4319-2022
- Intercomparison of Large-Eddy Simulations of the Antarctic Boundary Layer for Very Stable Stratification F. Couvreux et al. 10.1007/s10546-020-00539-4
- The Impact of Radiative Transfer at Reduced Spectral Resolution in Large‐Eddy Simulations of Convective Clouds M. Veerman et al. 10.1029/2023MS003699
- ProLB: A Lattice Boltzmann Solver of Large‐Eddy Simulation for Atmospheric Boundary Layer Flows Y. Feng et al. 10.1029/2020MS002107
- The FastEddy® Resident‐GPU Accelerated Large‐Eddy Simulation Framework: Model Formulation, Dynamical‐Core Validation and Performance Benchmarks J. Sauer & D. Muñoz‐Esparza 10.1029/2020MS002100
- Monitoring the Micrometeorology of a Coastal Site next to a Thermal Power Plant from the Surface to 140 m O. Acevedo et al. 10.1175/BAMS-D-17-0134.1
- The Benefits and Challenges of Downscaling a Global Reanalysis With Doubly‐Periodic Large‐Eddy Simulations B. van Stratum et al. 10.1029/2023MS003750
- Size dependence in chord characteristics from simulated and observed continental shallow cumulus P. Griewank et al. 10.5194/acp-20-10211-2020
- Improving the estimate of higher-order moments from lidar observations near the top of the convective boundary layer T. Rosenberger et al. 10.5194/amt-17-6595-2024
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- Inclusion of Building‐Resolving Capabilities Into the FastEddy® GPU‐LES Model Using an Immersed Body Force Method D. Muñoz‐Esparza et al. 10.1029/2020MS002141
- Structure Functions and Structure Parameters of Velocity Fluctuations in Numerically Simulated Atmospheric Convective Boundary Layer Flows J. Gibbs & E. Fedorovich 10.1175/JAS-D-20-0038.1
- The Time Scale of Shallow Convective Self‐Aggregation in Large‐Eddy Simulations Is Sensitive to Numerics M. Janssens et al. 10.1029/2022MS003292
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- Understanding the Moisture Variance in Precipitating Shallow Cumulus Convection T. Anurose et al. 10.1029/2019JD031178
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- An Evaluation of Algebraic Turbulence Length Scale Formulations S. Reilly et al. 10.3390/atmos13040605
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- A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids R. Neggers & P. Griewank 10.1029/2022MS003042
- A Review of Solar Forecasting Techniques and the Role of Artificial Intelligence K. Barhmi et al. 10.3390/solar4010005
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- A Graphics Processing Unit (GPU) Approach to Large Eddy Simulation (LES) for Transport and Contaminant Dispersion P. Bieringer et al. 10.3390/atmos12070890
- Numerical study of the interaction of vortex ring and background turbulence M. Hrebtov et al. 10.1134/S0869864319060040
- Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations A. Ražnjević et al. 10.5194/acp-22-6489-2022
- Logarithmic profiles of velocity in stably stratified atmospheric boundary layers Y. Cheng et al. 10.1103/PhysRevFluids.8.114602
- DUGKS-GPU: An efficient parallel GPU code for 3D turbulent flow simulations using Discrete Unified Gas Kinetic Scheme K. Karzhaubayev et al. 10.1016/j.cpc.2024.109216
- Towards exascale for wind energy simulations M. Min et al. 10.1177/10943420241252511
- Surface Moisture Exchange Under Vanishing Wind in Simulations of Idealized Tropical Convection W. Mol et al. 10.1029/2019GL085047
- Validating the Water Vapor Variance Similarity Relationship in the Interfacial Layer Using Observations and Large‐Eddy Simulations M. Osman et al. 10.1029/2019JD030653
- The Contributions of Shear and Turbulence to Cloud Overlap for Cumulus Clouds A. Sulak et al. 10.1029/2019JD032017
- Large-Eddy Simulations of the Steady Wintertime Antarctic Boundary Layer S. van der Linden et al. 10.1007/s10546-019-00461-4
- Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions A. Ražnjević et al. 10.5194/amt-15-3611-2022
- Numerical investigation of the influence of river flow on the atmospheric boundary layer under stably stratified conditions M. Hrebtov et al. 10.1088/1742-6596/1105/1/012028
3 citations as recorded by crossref.
- Direct Numerical Simulation of Turbulent Katabatic Slope Flows with an Immersed-Boundary Method C. Umphrey et al. 10.1007/s10546-017-0252-3
- Role of large eddies in the breakdown of the Reynolds analogy in an idealized mildly unstable atmospheric surface layer K. McColl et al. 10.1002/qj.3077
- Numerical Study of Nocturnal Low-Level Jets over Gently Sloping Terrain E. Fedorovich et al. 10.1175/JAS-D-17-0013.1
Discussed (preprint)
Latest update: 14 Dec 2024
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...