Articles | Volume 12, issue 6
Geosci. Model Dev., 12, 2523–2538, 2019
https://doi.org/10.5194/gmd-12-2523-2019
Geosci. Model Dev., 12, 2523–2538, 2019
https://doi.org/10.5194/gmd-12-2523-2019
Development and technical paper
28 Jun 2019
Development and technical paper | 28 Jun 2019

Vertically nested LES for high-resolution simulation of the surface layer in PALM (version 5.0)

Sadiq Huq et al.

Related authors

Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation
Charlotte Rahlves, Frank Beyrich, and Siegfried Raasch
Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022,https://doi.org/10.5194/amt-15-2839-2022, 2022
Short summary
Wake properties and power output of very large wind farms for different meteorological conditions and turbine spacings: a large-eddy simulation case study for the German Bight
Oliver Maas and Siegfried Raasch
Wind Energ. Sci., 7, 715–739, https://doi.org/10.5194/wes-7-715-2022,https://doi.org/10.5194/wes-7-715-2022, 2022
Short summary
Options to correct local turbulent flux measurements for large-scale fluxes using an approach based on large-eddy simulation
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021,https://doi.org/10.5194/amt-14-7835-2021, 2021
Short summary
Novel approach to observing system simulation experiments improves information gain of surface–atmosphere field measurements
Stefan Metzger, David Durden, Sreenath Paleri, Matthias Sühring, Brian J. Butterworth, Christopher Florian, Matthias Mauder, David M. Plummer, Luise Wanner, Ke Xu, and Ankur R. Desai
Atmos. Meas. Tech., 14, 6929–6954, https://doi.org/10.5194/amt-14-6929-2021,https://doi.org/10.5194/amt-14-6929-2021, 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

Related subject area

Atmospheric sciences
An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application
Haibo Wang, Ting Yang, Zifa Wang, Jianjun Li, Wenxuan Chai, Guigang Tang, Lei Kong, and Xueshun Chen
Geosci. Model Dev., 15, 3555–3585, https://doi.org/10.5194/gmd-15-3555-2022,https://doi.org/10.5194/gmd-15-3555-2022, 2022
Short summary
Earth system modeling of mercury using CESM2 – Part 1: Atmospheric model CAM6-Chem/Hg v1.0
Peng Zhang and Yanxu Zhang
Geosci. Model Dev., 15, 3587–3601, https://doi.org/10.5194/gmd-15-3587-2022,https://doi.org/10.5194/gmd-15-3587-2022, 2022
Short summary
Conservation laws in a neural network architecture: enforcing the atom balance of a Julia-based photochemical model (v0.2.0)
Patrick Obin Sturm and Anthony S. Wexler
Geosci. Model Dev., 15, 3417–3431, https://doi.org/10.5194/gmd-15-3417-2022,https://doi.org/10.5194/gmd-15-3417-2022, 2022
Short summary
On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions
Michael Weger, Holger Baars, Henriette Gebauer, Maik Merkel, Alfred Wiedensohler, and Bernd Heinold
Geosci. Model Dev., 15, 3315–3345, https://doi.org/10.5194/gmd-15-3315-2022,https://doi.org/10.5194/gmd-15-3315-2022, 2022
Short summary
Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022,https://doi.org/10.5194/gmd-15-3281-2022, 2022
Short summary

Cited articles

Anastopoulos, N., Nikunen, P., and Weinberg, V.: Best Practice Guide – SuperMUC v1.0. PRACE – Partnership for Advanced Computing in Europe 2013, available at: http://www.prace-ri.eu/best-practice-guide-supermuc-html (last access: 24 June 2019), 2013. a
Basu, S. and Lacser, A.: A Cautionary Note on the Use of Monin–Obukhov Similarity Theory in Very High-Resolution Large-Eddy Simulations, Bound.-Lay. Meteorol., 163, 351–355, https://doi.org/10.1007/s10546-016-0225-y, 2017. a
Boersma, B. J., Kooper, M. N., Nieuwstadt, F. T. M., and Wesseling, P.: Local grid refinement in large-eddy simulations, J. Eng. Math., 32, 161–175, https://doi.org/10.1023/A:1004283921077, 1997. a
Clark, T. L. and Farley, R. D.: Severe downslope windstorm calculations in two and three spatial dimensions using anelastic interactive grid nesting: A possible mechanism for gustiness, J. Atmos. Sci., 41, 329–350, https://doi.org/10.1175/1520-0469(1984)041<0329:SDWCIT>2.0.CO;2, 1984. a, b
Clark, T. L. and Hall, W. D.: Multi-domain simulations of the time dependent Navier Stokes equation: Benchmark error analyses of nesting procedures, J. Comput. Phys., 92, 456–481, https://doi.org/10.1016/0021-9991(91)90218-A, 1991. a, b, c
Download
Short summary
To study turbulence in heterogeneous terrain, high-resolution LES is desired. However, the desired resolution is often restricted by computational constraints. We present a two-way interactive vertical grid nesting technique that enables high-resolution LES of the surface layer. By employing a finer grid only close to the surface layer, the total computational memory requirement is reduced. We demonstrate the accuracy and performance of the method for a convective boundary layer simulation.