Jeremy Gibbs

Dr. Jeremy Gibbs


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 August 2020 in Boundary-Layer Meteorology
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Journal Article
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RSRob Stoll
Rob Stoll
JGJeremy Gibbs
Jeremy Gibbs
SSScott T. Salesky
Scott T. Salesky
WAWilliam Anderson
William Anderson
MCMarc Calaf
Marc Calaf

28 August 2017 in Geoscientific Model Development
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Journal Article
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CHChiel C. van Heerwaarden
Chiel C. van Heerwaarden
BSBart J. H. van Stratum
Bart J. H. van Stratum
THThijs Heus
Thijs Heus
JGJeremy Gibbs
Jeremy Gibbs
EFEvgeni Fedorovich
Evgeni Fedorovich
JMJuan Pedro Mellado
Juan Pedro Mellado
This paper describes MicroHH 1.0, a new and open-source (www.microhh.org) computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is primarily made for direct numerical simulation but also supports large-eddy simulation (LES). The paper covers the description of the governing equations, their numerical implementation, and the parameterizations included in the code. Furthermore, the paper presents the validation of the dynamical core in the form of convergence and conservation tests, and comparison of simulations of channel flows and slope flows against well-established test cases. The full numerical model, including the associated parameterizations for LES, has been tested for a set of cases under stable and unstable conditions, under the Boussinesq and anelastic approximations, and with dry and moist convection under stationary and time-varying boundary conditions. The paper presents performance tests showing good scaling from 256 to 32 768 processes. The graphical processing unit (GPU)-enabled version of the code can reach a speedup of more than an order of magnitude for simulations that fit in the memory of a single GPU.

1 December 2011 in Journal of Applied Meteorology and Climatology
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Journal Article
Closed access
JGJeremy Gibbs
Jeremy Gibbs
EFEvgeni Fedorovich
Evgeni Fedorovich
AEAlexander M. J. van Eijk
Alexander M. J. van Eijk
Weather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern Great Plains (SGP). The first studied case exhibited a dryline passage during the simulation window, and the second studied case was used to examine the CBL in a post-cold-frontal environment. The model runs were conducted with three boundary layer parameterization schemes (Yonsei University, Mellor–Yamada–Janjić, and asymmetrical convective) commonly employed within the WRF model environment to represent effects of small-scale turbulent transport. A study domain was centered over the Atmospheric Radiation Measurement Program SGP site in Lamont, Oklahoma. Results show that near-surface flow and turbulence parameters are predicted reasonably well with all tested horizontal grid spacings (1, 2, and 4 km) and that value added through refining grid spacing was minimal at best for conditions considered in this study. In accord with this result, it was suggested that the 16-fold increase in computing overhead associated with changing from 4- to 1-km grid spacing was not justified. Therefore, only differences among schemes at 4-km spacing were presented in detail. WRF model predictions generally overestimated the contribution to turbulence generation by mechanical forcing over buoyancy forcing in both studied CBL cases. Nonlocal parameterization schemes were found to match observational data more closely than did the local scheme, although differences among the predictions with all three schemes were relatively small.

9 January 2015 in Boundary-Layer Meteorology
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CWCharlotte E. Wainwright
Charlotte E. Wainwright
TBTimothy A. Bonin
Timothy A. Bonin
PCPhillip B. Chilson
Phillip B. Chilson
JGJeremy Gibbs
Jeremy Gibbs
EFEvgeni Fedorovich
Evgeni Fedorovich
RPRobert D. Palmer
Robert D. Palmer

1 March 2021 in Environmental Modelling & Software
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Journal Article
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BBBehnam Bozorgmehr
Behnam Bozorgmehr
PWPete Willemsen
Pete Willemsen
JGJeremy Gibbs
Jeremy Gibbs
RSRob Stoll
Rob Stoll
JKJae-Jin Kim
Jae-Jin Kim
EPEric Pardyjak
Eric Pardyjak

1 February 2014 in Journal of Applied Meteorology and Climatology
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Journal Article
Closed access
JGJeremy Gibbs
Jeremy Gibbs
EFEvgeni Fedorovich
Evgeni Fedorovich
As computing capabilities expand, operational and research environments are moving toward the use of finescale atmospheric numerical models. These models are attractive for users who seek an accurate description of small-scale turbulent motions. One such numerical tool is the Weather Research and Forecasting (WRF) model, which has been extensively used in synoptic-scale and mesoscale studies. As finer-resolution simulations become more desirable, it remains a question whether the model features originally designed for the simulation of larger-scale atmospheric flows will translate to adequate reproductions of small-scale motions. In this study, turbulent flow in the dry atmospheric convective boundary layer (CBL) is simulated using a conventional large-eddy-simulation (LES) code and the WRF model applied in an LES mode. The two simulation configurations use almost identical numerical grids and are initialized with the same idealized vertical profiles of wind velocity, temperature, and moisture. The respective CBL forcings are set equal and held constant. The effects of the CBL wind shear and of the varying grid spacings are investigated. Horizontal slices of velocity fields are analyzed to enable a comparison of CBL flow patterns obtained with each simulation method. Two-dimensional velocity spectra are used to characterize the planar turbulence structure. One-dimensional velocity spectra are also calculated. Results show that the WRF model tends to attribute slightly more energy to larger-scale flow structures as compared with the CBL structures reproduced by the conventional LES. Consequently, the WRF model reproduces relatively less spatial variability of the velocity fields. Spectra from the WRF model also feature narrower inertial spectral subranges and indicate enhanced damping of turbulence on small scales.