Articles | Volume 8, issue 10
Geosci. Model Dev., 8, 3131–3150, 2015
https://doi.org/10.5194/gmd-8-3131-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Isaac Newton Institute programme on multiscale numerics for...
Model description paper 07 Oct 2015
Model description paper | 07 Oct 2015
DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility
T. Dubos et al.
Related authors
Nicholas K.-R. Kevlahan and Thomas Dubos
Geosci. Model Dev., 12, 4901–4921, https://doi.org/10.5194/gmd-12-4901-2019, https://doi.org/10.5194/gmd-12-4901-2019, 2019
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WAVETRISK-1.0 is a new adaptive dynamical core for global climate modelling. It uses multiscale adaptive wavelet methods to adjust the grid resolution of the model at each time to guarantee error and make optimal use of computational resources. This technique has the potential to make climate simulations more accurate and allow much higher local resolutions. This "zoom" capability could also be used to focus on significant phenomena (such as hurricanes) or particular regions of the Earth.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
Geosci. Model Dev., 10, 4477–4509, https://doi.org/10.5194/gmd-10-4477-2017, https://doi.org/10.5194/gmd-10-4477-2017, 2017
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Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
N. K.-R. Kevlahan, T. Dubos, and M. Aechtner
Geosci. Model Dev., 8, 3891–3909, https://doi.org/10.5194/gmd-8-3891-2015, https://doi.org/10.5194/gmd-8-3891-2015, 2015
Short summary
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In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method.
J. Thuburn, C. J. Cotter, and T. Dubos
Geosci. Model Dev., 7, 909–929, https://doi.org/10.5194/gmd-7-909-2014, https://doi.org/10.5194/gmd-7-909-2014, 2014
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, Victor Estella-Perez, Christian Ethé, Frédéric Fluteau, Marie-Alice Foujols, Guillaume Gastineau, Josefine Ghattas, Didier Hauglustaine, Frédéric Hourdin, Masa Kageyama, Myriam Khodri, Olivier Marti, Yann Meurdesoif, Juliette Mignot, Anta-Clarisse Sarr, Jérôme Servonnat, Didier Swingedouw, Sophie Szopa, and Delphine Tardif
Geosci. Model Dev., 13, 3011–3053, https://doi.org/10.5194/gmd-13-3011-2020, https://doi.org/10.5194/gmd-13-3011-2020, 2020
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Our paper describes IPSL-CM5A2, an Earth system model that can be integrated for long (several thousands of years) climate simulations. We describe the technical aspects, assess the model computing performance and evaluate the strengths and weaknesses of the model, by comparing pre-industrial and historical runs to the previous-generation model simulations and to observations. We also present a Cretaceous simulation as a case study to show how the model simulates deep-time paleoclimates.
Nicholas K.-R. Kevlahan and Thomas Dubos
Geosci. Model Dev., 12, 4901–4921, https://doi.org/10.5194/gmd-12-4901-2019, https://doi.org/10.5194/gmd-12-4901-2019, 2019
Short summary
Short summary
WAVETRISK-1.0 is a new adaptive dynamical core for global climate modelling. It uses multiscale adaptive wavelet methods to adjust the grid resolution of the model at each time to guarantee error and make optimal use of computational resources. This technique has the potential to make climate simulations more accurate and allow much higher local resolutions. This "zoom" capability could also be used to focus on significant phenomena (such as hurricanes) or particular regions of the Earth.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
Geosci. Model Dev., 10, 4477–4509, https://doi.org/10.5194/gmd-10-4477-2017, https://doi.org/10.5194/gmd-10-4477-2017, 2017
Short summary
Short summary
Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
Habib Senghor, Éric Machu, Frédéric Hourdin, and Amadou Thierno Gaye
Atmos. Chem. Phys., 17, 8395–8410, https://doi.org/10.5194/acp-17-8395-2017, https://doi.org/10.5194/acp-17-8395-2017, 2017
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This work focus on the distribution of dust particles emitted in western Africa and having consequences on human health and marine ecosystems. The understanding of their fate requires a better understanding of the processes governing their variability. Using satellite observations and ground measurements, we present the seasonality of their distribution and explain the processes responsible for this distribution as well as their transition from the African continent towards the Atlantic Ocean.
N. K.-R. Kevlahan, T. Dubos, and M. Aechtner
Geosci. Model Dev., 8, 3891–3909, https://doi.org/10.5194/gmd-8-3891-2015, https://doi.org/10.5194/gmd-8-3891-2015, 2015
Short summary
Short summary
In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method.
F. Hourdin, M. Gueye, B. Diallo, J.-L. Dufresne, J. Escribano, L. Menut, B. Marticoréna, G. Siour, and F. Guichard
Atmos. Chem. Phys., 15, 6775–6788, https://doi.org/10.5194/acp-15-6775-2015, https://doi.org/10.5194/acp-15-6775-2015, 2015
Short summary
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New parameterizations of the convective boundary layer are used to better represent the diurnal cycle of near-surface wind over Sahara and Sahel in a climate model and the associated emission of dust.
R. Locatelli, P. Bousquet, F. Hourdin, M. Saunois, A. Cozic, F. Couvreux, J.-Y. Grandpeix, M.-P. Lefebvre, C. Rio, P. Bergamaschi, S. D. Chambers, U. Karstens, V. Kazan, S. van der Laan, H. A. J. Meijer, J. Moncrieff, M. Ramonet, H. A. Scheeren, C. Schlosser, M. Schmidt, A. Vermeulen, and A. G. Williams
Geosci. Model Dev., 8, 129–150, https://doi.org/10.5194/gmd-8-129-2015, https://doi.org/10.5194/gmd-8-129-2015, 2015
J. Thuburn, C. J. Cotter, and T. Dubos
Geosci. Model Dev., 7, 909–929, https://doi.org/10.5194/gmd-7-909-2014, https://doi.org/10.5194/gmd-7-909-2014, 2014
P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh
Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, https://doi.org/10.5194/gmd-7-105-2014, 2014
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Necessary conditions for algorithmic tuning of weather prediction models using OpenIFS as an example
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Efficient multi-scale Gaussian process regression for massive remote sensing data with satGP v0.1.2
PDE-NetGen 1.0: from symbolic partial differential equation (PDE) representations of physical processes to trainable neural network representations
Simple algorithms to compute meridional overturning and barotropic streamfunctions on unstructured meshes
Development of a two-way-coupled ocean–wave model: assessment on a global NEMO(v3.6)–WW3(v6.02) coupled configuration
Surrogate-assisted Bayesian inversion for landscape and basin evolution models
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A one-dimensional model of turbulent flow through “urban” canopies (MLUCM v2.0): updates based on large-eddy simulation
Slate: extending Firedrake's domain-specific abstraction to hybridized solvers for geoscience and beyond
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Geosci. Model Dev., 14, 377–389, https://doi.org/10.5194/gmd-14-377-2021, https://doi.org/10.5194/gmd-14-377-2021, 2021
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Resetting of non-significant figures (precision trimming) enables efficient data compression and helps to avoid excessive use of storage space and network bandwidth while having well-constrained distortion to the data. The paper analyses accuracy losses and artifacts caused by trimming methods and by the widely used linear packing method. The paper presents several methods with implementation, evaluation, and illustrations and includes subroutines directly usable in geoscientific models.
Bertrand Bessagnet, Laurent Menut, and Maxime Beauchamp
Geosci. Model Dev., 14, 91–106, https://doi.org/10.5194/gmd-14-91-2021, https://doi.org/10.5194/gmd-14-91-2021, 2021
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This paper presents a new interpolator useful for geophysics applications. It can explore N-dimensional meshes, grids or look-up tables. The code accepts irregular but structured grids. Written in Fortran, it is easy to implement in existing codes and very fast and portable. We have compared it with a Python library. Python is convenient but suffers from portability and is sometimes not optimized enough. As an application case, this method is applied to atmospheric sciences.
Oksana Guba, Mark A. Taylor, Andrew M. Bradley, Peter A. Bosler, and Andrew Steyer
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Anna Wirbel and Alexander Helmut Jarosch
Geosci. Model Dev., 13, 6425–6445, https://doi.org/10.5194/gmd-13-6425-2020, https://doi.org/10.5194/gmd-13-6425-2020, 2020
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We present an open-source numerical tool to simulate the free-surface evolution of gravity-driven flows (e.g. glaciers) constrained by bed topography. No ad hoc post-processing is required to enforce positive ice thickness and mass conservation. We utilise finite elements, define benchmark tests, and showcase glaciological examples. In addition, we provide a thorough analysis of the applicability and robustness of different spatial stabilisation and time discretisation methods.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 13, 6265–6284, https://doi.org/10.5194/gmd-13-6265-2020, https://doi.org/10.5194/gmd-13-6265-2020, 2020
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In this work, we present an efficient and fast material point method (MPM) implementation in MATLAB. We first discuss the vectorization strategies to adapt this numerical method to a MATLAB implementation. We report excellent agreement of the solver compared with classical analysis among the MPM community, such as the cantilever beam problem. The solver achieves a performance gain of 28 compared with a classical iterative implementation.
Lauri Tuppi, Pirkka Ollinaho, Madeleine Ekblom, Vladimir Shemyakin, and Heikki Järvinen
Geosci. Model Dev., 13, 5799–5812, https://doi.org/10.5194/gmd-13-5799-2020, https://doi.org/10.5194/gmd-13-5799-2020, 2020
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This paper presents general guidelines on how to utilise computer algorithms efficiently in order to tune weather models so that they would produce better forecasts. The main conclusions are that the computer algorithms work most efficiently with a suitable cost function, certain forecast length and ensemble size. We expect that our results will facilitate the use of algorithmic methods in the tuning of weather models.
Tarandeep S. Kalra, Neil K. Ganju, and Jeremy M. Testa
Geosci. Model Dev., 13, 5211–5228, https://doi.org/10.5194/gmd-13-5211-2020, https://doi.org/10.5194/gmd-13-5211-2020, 2020
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The paper covers the description of a 3-D open-source model that dynamically couples the biophysical interactions between submerged aquatic vegetation (SAV), hydrodynamics (currents, waves), sediment dynamics, and nutrient loading. Based on SAV growth model, SAV can use growth or dieback while contributing and sequestering nutrients from the water column (modifying the biological environment) and subsequently affect the hydrodynamics and sediment transport (modifying the physical environment).
Xiaoshuang Li, Richard Garth James Bellerby, Jianzhong Ge, Philip Wallhead, Jing Liu, and Anqiang Yang
Geosci. Model Dev., 13, 5103–5117, https://doi.org/10.5194/gmd-13-5103-2020, https://doi.org/10.5194/gmd-13-5103-2020, 2020
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We have developed an ANN model to predict pH using 11 cruise datasets from 2013 to 2017,
demonstrated its reliability using three cruise datasets during 2018 and applied it to
retrieve monthly pH for the period 2000 to 2016 on the East China Sea shelf using the
ANN model in combination with input variables from the Changjiang biology Finite-Volume
Coastal Ocean Model. This approach may be a valuable tool for understanding the seasonal
variation of pH in poorly observed regions.
Christopher Subich, Pierre Pellerin, Gregory Smith, and Frederic Dupont
Geosci. Model Dev., 13, 4379–4398, https://doi.org/10.5194/gmd-13-4379-2020, https://doi.org/10.5194/gmd-13-4379-2020, 2020
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This work presents a semi-Lagrangian advection module for the NEMO (OPA) ocean model. Semi-Lagrangian advection transports fluid properties (temperature, salinity, velocity) between time steps by following fluid motion and interpolating from upstream locations of fluid parcels.
This method is commonly used in atmospheric models to extend time step size, but it has not previously been applied to operational ocean models. Overcoming this required a new approach for solid boundaries (coastlines).
Jouni Susiluoto, Alessio Spantini, Heikki Haario, Teemu Härkönen, and Youssef Marzouk
Geosci. Model Dev., 13, 3439–3463, https://doi.org/10.5194/gmd-13-3439-2020, https://doi.org/10.5194/gmd-13-3439-2020, 2020
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We describe a new computer program that is able produce maps of carbon dioxide or other quantities based on data collected by satellites that orbit the Earth. When working with such data there is often too much data in one area and none in another. The program is able to describe the fields even when data is not available. To be able to do so, new computational methods were developed. The program is also able to describe how uncertain the estimated carbon dioxide or other fields are.
Olivier Pannekoucke and Ronan Fablet
Geosci. Model Dev., 13, 3373–3382, https://doi.org/10.5194/gmd-13-3373-2020, https://doi.org/10.5194/gmd-13-3373-2020, 2020
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Learning physics from data using a deep neural network is a challenge that requires an appropriate but unknown network architecture. The package introduced here helps to design an architecture by translating known physical equations into a network, which the experimenter completes to capture unknown physical processes. A test bed is introduced to illustrate how this learning allows us to focus on truly unknown physical processes in the hope of making better use of data and digital resources.
Dmitry Sidorenko, Sergey Danilov, Nikolay Koldunov, Patrick Scholz, and Qiang Wang
Geosci. Model Dev., 13, 3337–3345, https://doi.org/10.5194/gmd-13-3337-2020, https://doi.org/10.5194/gmd-13-3337-2020, 2020
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Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then be artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense.
Xavier Couvelard, Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Fabrice Ardhuin, Rachid Benshila, and Gurvan Madec
Geosci. Model Dev., 13, 3067–3090, https://doi.org/10.5194/gmd-13-3067-2020, https://doi.org/10.5194/gmd-13-3067-2020, 2020
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Within the framework of the Copernicus Marine Environment Monitoring Service (CMEMS), an objective is to demonstrate the contribution of coupling the high-resolution analysis and forecasting system with a wave model. This study describes the necessary steps and discusses the various choices made for coupling a wave model and an oceanic model for global-scale applications.
Rohitash Chandra, Danial Azam, Arpit Kapoor, and R. Dietmar Müller
Geosci. Model Dev., 13, 2959–2979, https://doi.org/10.5194/gmd-13-2959-2020, https://doi.org/10.5194/gmd-13-2959-2020, 2020
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Forward landscape and sedimentary basin evolution models pose a major challenge in the development of efficient inference and optimization methods. Bayesian inference provides a methodology for estimation and uncertainty quantification of free model parameters. In this paper, we present an application of a surrogate-assisted Bayesian parallel tempering method where that surrogate mimics a landscape evolution model. We use the method for parameter estimation and uncertainty quantification.
Juliette Mignot, Carlos Mejia, Charles Sorror, Adama Sylla, Michel Crépon, and Sylvie Thiria
Geosci. Model Dev., 13, 2723–2742, https://doi.org/10.5194/gmd-13-2723-2020, https://doi.org/10.5194/gmd-13-2723-2020, 2020
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The most robust representation of climate is usually obtained by averaging a large number of simulations, thereby cancelling individual model errors. Here, we work towards an objective way of selecting the least biased models over a certain region, based on physical parameters. This statistical method based on a neural classifier and multi-correspondence analysis is illustrated here for the Senegalo-Mauritanian region, but it could potentially be developed for any other region or process.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 13, 2611–2630, https://doi.org/10.5194/gmd-13-2611-2020, https://doi.org/10.5194/gmd-13-2611-2020, 2020
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Stochastic simulations are key tools to generate complex spatial structures uses as input in geoscientific models. In this paper, we present a new open-source tool that enables to simulate complex structures in a straightforward and efficient manner, based on analogues. The method is tested on a variety of use cases to demonstrate the generality of the framework.
Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 13, 2245–2258, https://doi.org/10.5194/gmd-13-2245-2020, https://doi.org/10.5194/gmd-13-2245-2020, 2020
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A full Stokes subgrid scheme in two dimensions for the grounding line migration problem is presented in the open-source finite-element framework Elmer/ICE. This method can achieve comparable results to previous research using a more than 20 times larger mesh size, which can be used to improve the efficiency in marine ice sheet simulations.
Colin Grudzien, Marc Bocquet, and Alberto Carrassi
Geosci. Model Dev., 13, 1903–1924, https://doi.org/10.5194/gmd-13-1903-2020, https://doi.org/10.5194/gmd-13-1903-2020, 2020
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All scales of a dynamical physical process cannot be resolved accurately in a multiscale, geophysical model. The behavior of unresolved scales of motion are often parametrized by a random process to emulate their effects on the dynamically resolved variables, and this results in a random–dynamical model. We study how the choice of a numerical discretization of such a system affects the model forecast and estimation statistics, when the random–dynamical model is unbiased in its parametrization.
Theo Baracchini, Philip Y. Chu, Jonas Šukys, Gian Lieberherr, Stefan Wunderle, Alfred Wüest, and Damien Bouffard
Geosci. Model Dev., 13, 1267–1284, https://doi.org/10.5194/gmd-13-1267-2020, https://doi.org/10.5194/gmd-13-1267-2020, 2020
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Lake physical processes occur at a wide range of spatiotemporal scales. 3D hydrodynamic lake models are the only information source capable of solving those scales; however, they still need observations to be calibrated and to constrain their uncertainties. The optimal combination of a 3D hydrodynamic model, in situ measurements, and remote sensing observations is achieved through data assimilation. Here we present a complete data assimilation experiment for lakes using open-source tools.
Negin Nazarian, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 13, 937–953, https://doi.org/10.5194/gmd-13-937-2020, https://doi.org/10.5194/gmd-13-937-2020, 2020
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We present an update to the Multi-Layer Urban Canopy Model by revisiting the parameterization of length scales based on high-resolution and validated large-eddy simulations. Additionally, the inclusion of dispersive fluxes in the parameterization schemes are also discussed. The results demonstrate that updated parameterizations improve the accuracy of the vertical exchange of momentum in the street canyon.
Thomas H. Gibson, Lawrence Mitchell, David A. Ham, and Colin J. Cotter
Geosci. Model Dev., 13, 735–761, https://doi.org/10.5194/gmd-13-735-2020, https://doi.org/10.5194/gmd-13-735-2020, 2020
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Galerkin finite element discretizations for atmospheric modeling often require the solution of ill-conditioned, saddle point equations which can be efficiently solved using a hybridized method. By extending Firedrake's domain-specific abstraction, we provide a mechanism for the rapid implementation of hybridization methods for a wide class of methods. In this paper, we show that hybridization is an effective alternative to traditional block solvers for simulating geophysical flows.
Murat Gunduz, Emin Özsoy, and Robinson Hordoir
Geosci. Model Dev., 13, 121–138, https://doi.org/10.5194/gmd-13-121-2020, https://doi.org/10.5194/gmd-13-121-2020, 2020
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The Bosphorus exchange is of critical importance for hydrodynamics and hydroclimatology of the Black Sea. In this study, we report on the development of a medium-resolution circulation model of the Black Sea, making use of surface atmospheric forcing with high space and time resolution, climatic river fluxes and strait exchange, enabled by adding elementary details of strait and coastal topography and seasonal hydrology specified in an artificial box on the Marmara Sea side.
Ewan Pinnington, Tristan Quaife, Amos Lawless, Karina Williams, Tim Arkebauer, and Dave Scoby
Geosci. Model Dev., 13, 55–69, https://doi.org/10.5194/gmd-13-55-2020, https://doi.org/10.5194/gmd-13-55-2020, 2020
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We present LAVENDAR, a mathematical method for combining observations with models of the terrestrial environment. Here we use it to improve estimates of crop growth in the UK Met Office land surface model. However, the method is model agnostic, requires no modification to the underlying code and can be applied to any part of the model. In the example application we improve estimates of maize yield by 74 % by assimilating observations of leaf area, crop height and photosynthesis.
Xavier Delaunay, Aurélie Courtois, and Flavien Gouillon
Geosci. Model Dev., 12, 4099–4113, https://doi.org/10.5194/gmd-12-4099-2019, https://doi.org/10.5194/gmd-12-4099-2019, 2019
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This research aimed at finding a compression method suitable for the ground processing of CFOSAT and SWOT satellite datasets. Lossless algorithms did not allow enough compression. That is why we began studying lossy alternatives. This work introduces the digit rounding algorithm which reduces the volume of scientific datasets keeping only the significant digits in each sample value. The number of digits kept is relative to each sample so that both small and high values are similarly preserved.
Richard Scalzo, David Kohn, Hugo Olierook, Gregory Houseman, Rohitash Chandra, Mark Girolami, and Sally Cripps
Geosci. Model Dev., 12, 2941–2960, https://doi.org/10.5194/gmd-12-2941-2019, https://doi.org/10.5194/gmd-12-2941-2019, 2019
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Producing 3-D models of structures under the Earth's surface based on sensor data is a key problem in geophysics (for example, in mining exploration). There may be multiple models that explain the data well. We use the open-source Obsidian software to look at the efficiency of different methods for exploring the model space and attaching probabilities to models, leading to less biased results and a better idea of how sensor data interact with geological assumptions.
Anna Denvil-Sommer, Marion Gehlen, Mathieu Vrac, and Carlos Mejia
Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, https://doi.org/10.5194/gmd-12-2091-2019, 2019
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This work is dedicated to a new model that reconstructs the surface ocean partial pressure of carbon dioxide (pCO2) over the global ocean on a monthly 1°×1° grid. The model is based on a feed-forward neural network and represents the nonlinear relationships between pCO2 and the ocean drivers. Reconstructed pCO2 has a satisfying accuracy compared to independent observational data and shows a good agreement in seasonal and interannual variability with three existing mapping methods.
Alexey Androsov, Vera Fofonova, Ivan Kuznetsov, Sergey Danilov, Natalja Rakowsky, Sven Harig, Holger Brix, and Karen Helen Wiltshire
Geosci. Model Dev., 12, 1009–1028, https://doi.org/10.5194/gmd-12-1009-2019, https://doi.org/10.5194/gmd-12-1009-2019, 2019
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We present a description of a coastal ocean circulation model designed to work on variable-resolution meshes made of triangular and quadrilateral cells. This hybrid mesh functionality allows for higher numerical performance and less dissipative solutions.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
Geosci. Model Dev., 12, 879–892, https://doi.org/10.5194/gmd-12-879-2019, https://doi.org/10.5194/gmd-12-879-2019, 2019
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We summarize the results of the Dynamical Core Model Intercomparison Project's idealized supercell test case. Supercells are storm-scale weather phenomena that are a key target for next-generation, non-hydrostatic weather prediction models. We show that the dynamical cores of most global numerical models converge between approximately 1 and 0.5 km grid spacing for this test, although differences in final solution exist, particularly due to differing grid discretizations and numerical diffusion.
Christian Kühnlein, Willem Deconinck, Rupert Klein, Sylvie Malardel, Zbigniew P. Piotrowski, Piotr K. Smolarkiewicz, Joanna Szmelter, and Nils P. Wedi
Geosci. Model Dev., 12, 651–676, https://doi.org/10.5194/gmd-12-651-2019, https://doi.org/10.5194/gmd-12-651-2019, 2019
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We present a novel finite-volume dynamical core formulation considered for future numerical weather prediction at ECMWF. We demonstrate that this formulation can be competitive in terms of solution quality and computational efficiency to the proven spectral-transform dynamical core formulation currently operational at ECMWF, while providing a local, more scalable discretization, conservative and monotone advective transport, and flexible meshes.
Ramadan Abdelaziz, Broder J. Merkel, Mauricio Zambrano-Bigiarini, and Sreejesh Nair
Geosci. Model Dev., 12, 167–177, https://doi.org/10.5194/gmd-12-167-2019, https://doi.org/10.5194/gmd-12-167-2019, 2019
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The paper presents a robust tool to estimate the thermodynamic surface complexation parameter for the sorption of uranium(VI) onto quartz surfaces. The optimization package hydroPSO R is coupled with the geochemical speciation code PHREEQC. hydroPSO used the m parameter estimation tool for geochemical modeling with PHREEQC. Coupled hydroPSO with PHREEQC proved to be a robust tool to estimate surface complexation constants for uranium(VI) species on quartz.
Miguel de la Varga, Alexander Schaaf, and Florian Wellmann
Geosci. Model Dev., 12, 1–32, https://doi.org/10.5194/gmd-12-1-2019, https://doi.org/10.5194/gmd-12-1-2019, 2019
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GemPy is an open-source Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. GemPy is implemented in the programming language Python, making use of a highly efficient underlying library, Theano, for efficient code generation that performs automatic differentiation. This enables the link to probabilistic machine-learning and Bayesian inference frameworks.
Tianfeng Chai, Ariel Stein, and Fong Ngan
Geosci. Model Dev., 11, 5135–5148, https://doi.org/10.5194/gmd-11-5135-2018, https://doi.org/10.5194/gmd-11-5135-2018, 2018
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While model predictions depend on release parameters, model uncertainties in inverse modeling should also vary with the source terms. In this paper, model uncertainties that will change with the source terms are introduced in a weak-constraint inverse modeling system. Tests using HYSPLIT model and CAPTEX observations show that adding such model uncertainty terms improves release rate estimates. A cost function normalization scheme introduced to avoid spurious solutions proves to be effective.
Christopher J. Skinner, Tom J. Coulthard, Wolfgang Schwanghart, Marco J. Van De Wiel, and Greg Hancock
Geosci. Model Dev., 11, 4873–4888, https://doi.org/10.5194/gmd-11-4873-2018, https://doi.org/10.5194/gmd-11-4873-2018, 2018
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Landscape evolution models are computer models used to understand how the Earth’s surface changes over time. Although designed to look at broad changes over very long time periods, they could potentially be used to predict smaller changes over shorter periods. However, to do this we need to better understand how the models respond to changes in their set-up – i.e. their behaviour. This work presents a method which can be applied to these models in order to better understand their behaviour.
Gary L. Russell, David H. Rind, and Jeffrey Jonas
Geosci. Model Dev., 11, 4637–4656, https://doi.org/10.5194/gmd-11-4637-2018, https://doi.org/10.5194/gmd-11-4637-2018, 2018
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This paper presents the Fortran 90 source code for one-layer model GISS:IB on an icosahedral grid. The model solves the shallow water equations on the sphere using three symmetric horizontal components of angular momentum instead of velocity. One-layer shallow water models are a basic building block used in complex global weather and climate models.
Istvan Z. Reguly, Daniel Giles, Devaraj Gopinathan, Laure Quivy, Joakim H. Beck, Michael B. Giles, Serge Guillas, and Frederic Dias
Geosci. Model Dev., 11, 4621–4635, https://doi.org/10.5194/gmd-11-4621-2018, https://doi.org/10.5194/gmd-11-4621-2018, 2018
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We present the VOLNA-OP2 tsunami simulation code, built on the OP2 library. It is unique among such solvers in its support for several high-performance computing platforms: CPUs, the Intel Xeon Phi, and GPUs. This is achieved in a way that the scientific code is kept separate from various parallel implementations, enabling easy maintainability. Scalability and efficiency are demonstrated on three supercomputers built with CPUs, Xeon Phi's, and GPUs.
Joakim Beck, Sören Wolfers, and Gerald P. Roberts
Geosci. Model Dev., 11, 4383–4397, https://doi.org/10.5194/gmd-11-4383-2018, https://doi.org/10.5194/gmd-11-4383-2018, 2018
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Seismic hazard assessment requires records of earthquake recurrence with many slip events. Current data from paleoseismology on individual faults are sparse and do not provide stable estimates of earthquake recurrence. We propose a statistical model-based method to study timings of earthquakes over the past few millennia. The results agree with historical earthquakes for faults in the Italian Apennines, and can aid future studies of fault interactions over multiple earthquake cycles.
Peter D. Dueben and Peter Bauer
Geosci. Model Dev., 11, 3999–4009, https://doi.org/10.5194/gmd-11-3999-2018, https://doi.org/10.5194/gmd-11-3999-2018, 2018
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We discuss the question of whether weather forecast models that are based on deep learning and trained on atmospheric data can compete with conventional weather and climate models that are based on physical principles and the basic equations of motion. We discuss the question in the context of global weather forecasts. A toy model for global weather predictions will be presented and used to identify challenges and fundamental design choices for a forecast system based on neural networks.
Anthony P. Walker, Ming Ye, Dan Lu, Martin G. De Kauwe, Lianhong Gu, Belinda E. Medlyn, Alistair Rogers, and Shawn P. Serbin
Geosci. Model Dev., 11, 3159–3185, https://doi.org/10.5194/gmd-11-3159-2018, https://doi.org/10.5194/gmd-11-3159-2018, 2018
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Large uncertainty is inherent in model predictions due to imperfect knowledge of how to describe the processes that a model is intended to represent. Yet methods to quantify and evaluate this model hypothesis uncertainty are limited. To address this, the multi-assumption architecture and testbed (MAAT) automates the generation of all possible models by combining multiple representations of multiple processes. MAAT provides a formal framework for quantification of model hypothesis uncertainty.
Matthias Rauter, Andreas Kofler, Andreas Huber, and Wolfgang Fellin
Geosci. Model Dev., 11, 2923–2939, https://doi.org/10.5194/gmd-11-2923-2018, https://doi.org/10.5194/gmd-11-2923-2018, 2018
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We present a physical model for the simulation of dense snow avalanches and other gravitational mass flows. The model is solved with OpenFOAM, a popular open-source toolkit for the numerical solution of partial differential equations. The solver has a modular design and is easy to extend. Therefore, it represents an ideal platform for implementing and testing new model approaches.
Zhixuan Cao, Abani Patra, Marcus Bursik, E. Bruce Pitman, and Matthew Jones
Geosci. Model Dev., 11, 2691–2715, https://doi.org/10.5194/gmd-11-2691-2018, https://doi.org/10.5194/gmd-11-2691-2018, 2018
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Plume-SPH provides the first particle-based simulation of volcanic plumes. Smooth particle hydrodynamics used here has several advantages over mesh-based methods for multiphase free boundary flows like volcanic plumes. This tool will provide more accurate eruption source terms to users of volcanic ash transport and dispersion models, greatly improving volcanic ash forecasts. The Plume-SPH code incorporates several newly developed techniques in SPH-needed multiphase compressible turbulent flow.
Sabine Hittmeir, Anne Philipp, and Petra Seibert
Geosci. Model Dev., 11, 2503–2523, https://doi.org/10.5194/gmd-11-2503-2018, https://doi.org/10.5194/gmd-11-2503-2018, 2018
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Model output of quantities such as precipitation usually represents integrals, for example sums over 3 h. It is not trivial to interpolate a time series of such integral values to instantaneous precipitation rates conserving the integral values. A piecewise linear reconstruction is presented which fulfils the conservation, is non-negative, and is continuous at interval boundaries. It will be used in the FLEXPART Lagrangian dispersion model but has many other possible applications.
Richard M. Gorman and Hilary J. Oliver
Geosci. Model Dev., 11, 2153–2173, https://doi.org/10.5194/gmd-11-2153-2018, https://doi.org/10.5194/gmd-11-2153-2018, 2018
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We describe an optimisation suite ("Cyclops") that can be used to apply a selection of nonlinear optimisation algorithms to "tune" the parameters of a geophysical model. Based on the Cylc workflow engine, Cyclops can be used to calibrate any modelling system that has itself been implemented as a (separate) Cylc model suite, provided it includes computation and output of the desired scalar cost function.
David J. Gardner, Jorge E. Guerra, François P. Hamon, Daniel R. Reynolds, Paul A. Ullrich, and Carol S. Woodward
Geosci. Model Dev., 11, 1497–1515, https://doi.org/10.5194/gmd-11-1497-2018, https://doi.org/10.5194/gmd-11-1497-2018, 2018
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As the computational power of supercomputing systems increases, and models for simulating the fluid flow of the Earth's atmosphere operate at higher resolutions, new approaches for advancing these models in time will be necessary. In order to produce the best possible result in the least amount of time, we evaluate a number of splittings, methods, and solvers on two test cases. Based on these results, we identify the most accurate and efficient approaches for consideration in production models.
Philippe Delandmeter, Jonathan Lambrechts, Vincent Legat, Valentin Vallaeys, Jaya Naithani, Wim Thiery, Jean-François Remacle, and Eric Deleersnijder
Geosci. Model Dev., 11, 1161–1179, https://doi.org/10.5194/gmd-11-1161-2018, https://doi.org/10.5194/gmd-11-1161-2018, 2018
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The discontinuous Galerkin (DG) finite element method is well suited for the modelling of three-dimensional flows exhibiting strong density gradients. Here, a vertical adaptive mesh method is developed for DG finite element methods and implemented into SLIM 3D. This technique increases drastically the accuracy of simulations including strong stratification, without affecting the simulation cost. SLIM 3D is then used to simulate the thermocline oscillations of Lake Tanganyika.
Thomas Rößler, Olaf Stein, Yi Heng, Paul Baumeister, and Lars Hoffmann
Geosci. Model Dev., 11, 575–592, https://doi.org/10.5194/gmd-11-575-2018, https://doi.org/10.5194/gmd-11-575-2018, 2018
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In this study, we performed an assessment of truncation errors and computational efficiency of trajectory calculations using six popular numerical integration schemes of the Runge–Kutta family. More than 5000 transport simulations for different seasons and regions of the free troposphere and stratosphere were conducted, driven by the latest version of ECMWF operational analyses and forecasts. The study provides guidelines to achieve the most accurate and efficient trajectory calculations.
Koen Hilgersom, Marcel Zijlema, and Nick van de Giesen
Geosci. Model Dev., 11, 521–540, https://doi.org/10.5194/gmd-11-521-2018, https://doi.org/10.5194/gmd-11-521-2018, 2018
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This study models the local inflow of groundwater at the bottom of a stream with large density gradients between the groundwater and surface water. Modelling salt and heat transport in a water body is very challenging, as it requires large computation times. Due to the circular local groundwater inflow and a negligible stream discharge, we assume axisymmetry around the inflow, which is easily implemented in an existing model, largely reduces the computation times, and still performs accurately.
Tarandeep S. Kalra, Alfredo Aretxabaleta, Pranay Seshadri, Neil K. Ganju, and Alexis Beudin
Geosci. Model Dev., 10, 4511–4523, https://doi.org/10.5194/gmd-10-4511-2017, https://doi.org/10.5194/gmd-10-4511-2017, 2017
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The paper details the sensitivity of vegetation properties that are input to a 3-D submerged aquatic vegetation model within a coupled hydrodynamics and wave model. It describes a novel strategy to perform sensitivity analysis efficiently by using a combination of the Effective Quadratures method and Sobol' indices. This method reduces the number of simulations to understand the sensitivity patterns and also quantifies the amount of sensitivity.
Yanan Fan, Roman Olson, and Jason P. Evans
Geosci. Model Dev., 10, 2321–2332, https://doi.org/10.5194/gmd-10-2321-2017, https://doi.org/10.5194/gmd-10-2321-2017, 2017
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We develop a novel and principled Bayesian statistical approach to computing model weights in climate change projection ensembles of regional climate models. The approach accounts for uncertainty in model bias, trend and internal variability. The weights are easily interpretable and the ensemble weighted models are shown to provide the correct coverage and improve upon existing methods in terms of providing narrower confidence intervals for climate change projections.
Darren Engwirda
Geosci. Model Dev., 10, 2117–2140, https://doi.org/10.5194/gmd-10-2117-2017, https://doi.org/10.5194/gmd-10-2117-2017, 2017
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A new algorithm for the generation of very high-quality staggered unstructured grids for multi-resolution ocean and atmospheric modelling is described. Through use of unstructured triangulation and grid-optimisation techniques, it is shown that meshes satisfying a number of important a priori grid-quality constraints can be constructed. This new algorithm is expected to be of interest to both developers and users of unstructured general circulation models.
Cited articles
Arakawa, A.: Computational design for long-term numerical integration of the equations of fluid motion: Two-dimensional incompressible flow. P}art {I, J. Comput. Phys, 1, 119–143, 1966.
Arakawa, A. and Lamb, V. R.: A Potential Enstrophy and Energy Conserving Scheme for the Shallow Water Equations, Mon. Weather Rev., 109, 18–36, 1981.
Arnold, V. I.: Conditions for non-linear stability of plane steady curvilinear flows of an ideal fluid, Dokl. Akad. Nauk Sssr, 162, 773–777, 1965.
Audusse, E., Bouchut, F., Bristeau, M.-O., Klein, R., and Perthame, B.: A Fast and Stable Well-Balanced Scheme with Hydrostatic Reconstruction for Shallow Water Flows, SIAM J. Sci. Comput., 25, 2050–2065, 2004.
Augenbaum, J. M. and Peskin, C. S.: On the construction of the Voronoi mesh on a sphere, J. Comput. Phys, 59, 177–192, 1985.
Bokhove, O.: Eulerian Variational Principles for Stratified Hydrostatic Equations, J. Atmos. Sci, 59, 1619–1628, 2002.
Bonaventura, L. and Ringler, T.: Analysis of Discrete Shallow-Water Models on Geodesic Delaunay Grids with C-Type Staggering, Mon. Weather Rev., 133, 2351–2373, 2005.
Botta, N., Klein, R., Langenberg, S., and Lützenkirchen, S.: Well balanced finite volume methods for nearly hydrostatic flows, J. Comput. Phys, 196, 539–565, 2004.
Cotter, C. J. and Thuburn, J.: A finite element exterior calculus framework for the rotating shallow-water equations, J. Comput. Phys, 257, 1506–1526, 2014.
Du, Q., Faber, V., and Gunzburger, M.: Centroidal Voronoi Tessellations: Applications and Algorithms, SIAM Rev., 41, 637–676, 1999.
Du, Q., Emelianenko, M., and Ju, L.: Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations, SIAM J. Numer. Anal., 44, 102–119, 2006.
Dubey, S., Dubos, T., Hourdin, F., and Upadhyaya, H. C.: On the inter-comparison of two tracer transport schemes on icosahedal grids, Appl. Math. Model., 39, 4828–4847, https://doi.org/10.1016/j.apm.2015.04.015, 2015.
Dubos, T. and Tort, M.: Equations of Atmospheric Motion in Non-Eulerian Vertical Coordinates: Vector-Invariant Form and Quasi-Hamiltonian Formulation, Mon. Weather Rev., 142, 3860–3880, 2014.
Dukowicz, J. K. and Kodis, J. W.: Accurate Conservative Remapping (Rezoning) for Arbitrary Lagrangian-Eulerian Computations, SIAM J. Sci. Stat. Comp., 8, 305–321, 1987.
Easter, R. C.: Two Modified Versions of Bott's Positive-Definite Numerical Advection Scheme, Mon. Weather Rev., 121, 297–304, 1993.
Gary, J. M.: Estimate of Truncation Error in Transformed Coordinate, Primitive Equation Atmospheric Models, J. Atmos. Sci., 30, 223–233, 1973.
Gassmann, A.: Inspection of hexagonal and triangular C-grid discretizations of the shallow water equations, J. Comput. Phys, 230, 2706–2721, 2011.
Gassmann, A.: A global hexagonal C-grid non-hydrostatic dynamical core (ICON-IAP) designed for energetic consistency, Q. J. Roy. Meteor. Soc., 139, 152–175, 2013.
Held, I. M. and Suarez, M. J.: A Proposal for the Intercomparison of the Dynamical Cores of Atmospheric General Circulation Models, B. Am. Meteorol. Soc., 75, 1825–1830, 1994.
Holm, D. D., Marsden, J. E., and Ratiu, T. S.: The Euler-Poincaré Equations in Geophysical Fluid Dynamics, 251–299, Cambridge University Press, Cambridge, 2002.
Hourdin, F.: Transport de l'énergie dans le modèle du LMD, internal report, IPSL, available at: http://lmdz.lmd.jussieu.fr/developpeurs/notes-techniques/ressources/energy.pdf (last access: 5 October 2015) 1994.
Hourdin, F. and Armengaud, A.: The Use of Finite-Volume Methods for Atmospheric Advection of Trace Species. Part I: Test of Various Formulations in a General Circulation Model, Mon. Weather Rev., 127, 822–837, 1999.
Hourdin, F., Grandpeix, J.-Y., Rio, C., Bony, S., Jam, A., Cheruy, F., Rochetin, N., Fairhead, L., Idelkadi, A., Musat, I., Dufresne, J.-L., Lahellec, A., Lefebvre, M.-P., and Roehrig, R.: LMDZ5B}: the atmospheric component of the {IPSL climate model with revisited parameterizations for clouds and convection, Clim. Dynam., 40, 2193–2222, 2013.
Jablonowski, C. and Williamson, D. L.: A baroclinic instability test case for atmospheric model dynamical cores, Q. J. Roy. Meteor. Soc., 132, 2943–2975, 2006.
Jiménez, J.: Hyperviscous vortices, J. Fluid Mech., 279, 169–176, 2006.
Kent, J., Ullrich, P. A., and Jablonowski, C.: Dynamical core model intercomparison project: Tracer transport test cases, Q. J. Roy. Meteor. Soc., 140, 1279–1293, 2014.
Kinnmark, I. P. E. and Gray, W. G.: One step integration methods of third-fourth order accuracy with large hyperbolic stability limits, Math. Comput. Simulat., 26, 181–188, 1984a.
Kinnmark, I. P. E. and Gray, W. G.: One step integration methods with maximum stability regions, Math. Comput. Simulat., 26, 87–92, 1984b.
Koren, B., Abgrall, R., Bochev, P., Frank, J., and Perot, B.: Physics-compatible numerical methods, J. Comput. Phys., 257, 1039, https://doi.org/10.1016/j.jcp.2013.10.015, 2014.
Laprise, R.: The Euler Equations of Motion with Hydrostatic Pressure as an Independent Variable, Mon. Weather Rev., 120, 197–207, 1992.
Lauritzen, P. H., Jablonowski, C., Taylor, M. A., and Nair, R. D.: Rotated Versions of the Jablonowski Steady-State and Baroclinic Wave Test Cases: A Dynamical Core Intercomparison, J. Adv. Model. Earth Syst., 2, 15, https://doi.org/10.3894/james.2010.2.15, 2010.
Lauritzen, P. H., Skamarock, W. C., Prather, M. J., and Taylor, M. A.: A standard test case suite for two-dimensional linear transport on the sphere, Geosci. Model Dev., 5, 887–901, https://doi.org/10.5194/gmd-5-887-2012, 2012.
Lauritzen, P. H., Bacmeister, J. T., Dubos, T., Lebonnois, S., and Taylor, M. A.: Held-Suarez simulations with the Community Atmosphere Model Spectral Element (CAM-SE) dynamical core: A global axial angular momentum analysis using Eulerian and floating Lagrangian vertical coordinates, J. Adv. Model. Earth Syst., 6, 129–140, 2014a.
Lauritzen, P. H., Ullrich, P. A., Jablonowski, C., Bosler, P. A., Calhoun, D., Conley, A. J., Enomoto, T., Dong, L., Dubey, S., Guba, O., Hansen, A. B., Kaas, E., Kent, J., Lamarque, J.-F., Prather, M. J., Reinert, D., Shashkin, V. V., Skamarock, W. C., Sørensen, B., Taylor, M. A., and Tolstykh, M. A.: A standard test case suite for two-dimensional linear transport on the sphere: results from a collection of state-of-the-art schemes, Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, 2014b.
Lebonnois, S., Hourdin, F., Eymet, V., Crespin, A., Fournier, R., and Forget, F.: Superrotation of Venus' atmosphere analyzed with a full general circulation model, J. Geophys. Res., 115, E06006, https://doi.org/10.1029/2009je003458, 2010.
Lebonnois, S., Covey, C., Grossman, A., Parish, H., Schubert, G., Walterscheid, R., Lauritzen, P., and Jablonowski, C.: Angular momentum budget in General Circulation Models of superrotating atmospheres: A critical diagnostic, J. Geophys. Res., 117, https://doi.org/10.1029/2012je004223, 2012.
Mittal, R. and Skamarock, W. C.: Monotonic Limiters for a Second-Order Finite-Volume Advection Scheme Using Icosahedral-Hexagonal Meshes, Mon. Weather Rev., 138, 4523–4527, 2010.
Miura, H.: An Upwind-Biased Conservative Advection Scheme for Spherical Hexagonal-Pentagonal Grids, Mon. Weather Rev., 135, 4038–4044, 2007.
Miura, H. and Kimoto, M.: A Comparison of Grid Quality of Optimized Spherical Hexagonal-Pentagonal Geodesic Grids, Mon. Weather Rev., 133, 2817–2833, 2005.
Ringler, T. D., Thuburn, J., Klemp, J. B., and Skamarock, W. C.: A unified approach to energy conservation and potential vorticity dynamics for arbitrarily-structured C-grids, J. Comput. Phys, 229, 3065–3090, 2010.
Ripa, P.: Conservation laws for primitive equations models with inhomogeneous layers, Geophys. Astrophys. Fluid, 70, 85–111, 1993.
Rípodas, P., Gassmann, A., Förstner, J., Majewski, D., Giorgetta, M., Korn, P., Kornblueh, L., Wan, H., Zängl, G., Bonaventura, L., and Heinze, T.: Icosahedral Shallow Water Model (ICOSWM): results of shallow water test cases and sensitivity to model parameters, Geosci. Model Dev., 2, 231–251, https://doi.org/10.5194/gmd-2-231-2009, 2009.
Sadourny, R.: Conservative Finite-Difference Approximations of the Primitive Equations on Quasi-Uniform Spherical Grids, Mon. Weather Rev., 100, 136–144, 1972.
Sadourny, R.: The Dynamics of Finite-Difference Models of the Shallow-Water Equations, J. Atmos. Sci, 32, 680–689, 1975a.
Sadourny, R.: Compressible Model Flows on the Sphere, J. Atmos. Sci, 32, 2103–2110, 1975b.
Sadourny, R., Arakawa, A. K. I. O., and Mintz, Y. A. L. E.: Integration of the nondivergent barotropic vorticity equation with an icosahedral-hexagonal grid for the Sphere1, Mon. Weather Rev., 96, 351–356, 1968.
Salmon, R.: Practical use of Hamilton's principle, J. Fluid Mech., 132, 431–444, 1983.
Salmon, R.: Poisson-Bracket Approach to the Construction of Energy- and Potential-Enstrophy}-Conserving Algorithms for the {Shallow-Water Equations, J. Atmos. Sci, 61, 2016–2036, 2004.
Satoh, M., Matsuno, T., Tomita, H., Miura, H., Nasuno, T., and Iga, S.: Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations, J. Comput. Phys., 227, 3486–3514, 2008.
Simmons, A. J. and Burridge, D. M.: An Energy and Angular-Momentum Conserving Vertical Finite-Difference Scheme and Hybrid Vertical Coordinates, Mon. Weather Rev., 109, 758–766, 1981.
Skamarock, W. C. and Gassmann, A.: Conservative Transport Schemes for Spherical Geodesic Grids: High-Order Flux Operators for ODE-Based Time Integration, Mon. Weather Rev., 139, 2962–2975, 2011.
Skamarock, W. C., Klemp, J. B., Duda, M. G., Fowler, L. D., Park, S.-H., and Ringler, T. D.: A Multiscale Nonhydrostatic Atmospheric Model Using Centroidal Voronoi Tesselations and C-Grid Staggering, Mon. Weather Rev., 140, 120402131411002–3105, https://doi.org/10.1175/mwr-d-11-00215.1, 2012.
Smagorinsky, J.: General circulation experiments with the primitive equations: I. The basic experiment*, Mon. Weather Rev., 91, 99–164, 1963.
Taylor, M. A. and Fournier, A.: A compatible and conservative spectral element method on unstructured grids, J. Comput. Phys, 229, 5879–5895, 2010.
Thuburn, J.: Numerical wave propagation on the hexagonal C-grid, J. Comput. Phys., 227, 5836–5858, 2008.
Thuburn, J. and Cotter, C. J.: A Framework for Mimetic Discretization of the Rotating Shallow-Water Equations on Arbitrary Polygonal Grids, SIAM J. Sci. Comput., 34, B203–B225, 2012.
Thuburn, J., Ringler, T. D., Skamarock, W. C., and Klemp, J. B.: Numerical representation of geostrophic modes on arbitrarily structured C-grids, J. Comput. Phys, 228, 8321–8335, 2009.
Thuburn, J., Cotter, C. J., and Dubos, T.: A mimetic, semi-implicit, forward-in-time, finite volume shallow water model: comparison of hexagonal–icosahedral and cubed-sphere grids, Geosci. Model Dev., 7, 909–929, https://doi.org/10.5194/gmd-7-909-2014, 2014.
Tomita, H., Tsugawa, M., Satoh, M., and Goto, K.: Shallow Water Model on a Modified Icosahedral Geodesic Grid by Using Spring Dynamics, J. Comput. Phys., 174, 579–613, 2001.
Tort, M. and Dubos, T.: Dynamically consistent shallow-atmosphere equations with a complete Coriolis force, Q. J. Roy. Meteor. Soc., 140, 2388–2392, 2014a.
Tort, M. and Dubos, T.: Usual Approximations to the Equations of Atmospheric Motion: A Variational Perspective, J. Atmos. Sci, 71, 2452–2466, 2014b.
Tort, M., Dubos, T., Bouchut, F., and Zeitlin, V.: Consistent shallow-water equations on the rotating sphere with complete Coriolis force and topography, J. Fluid Mech., 748, 789–821, 2014a.
Tort, M., Dubos, T., and Melvin, T.: An Energy-conserving Quasi-hydrostatic Deep-atmosphere Dynamical Core, Q. J. Roy. Meteor. Soc., accepted, 2014b.
Van Leer, B.: Towards the ultimate conservative difference scheme. IV. A new approach to numerical convection, J. Comput. Phys, 23, 276–299, 1977.
Wan, H., Giorgetta, M. A., Zängl, G., Restelli, M., Majewski, D., Bonaventura, L., Fröhlich, K., Reinert, D., Rípodas, P., Kornblueh, L., and Förstner, J.: The ICON-1.2 hydrostatic atmospheric dynamical core on triangular grids – Part 1: Formulation and performance of the baseline version, Geosci. Model Dev., 6, 735–763, https://doi.org/10.5194/gmd-6-735-2013, 2013.
Weller, H., Thuburn, J., and Cotter, C. J.: Computational Modes and Grid Imprinting on Five Quasi-Uniform Spherical C Grids, Mon. Weather. Rev., 140, 2734–2755, 2012.
White, A. A. and Bromley, R. A.: Dynamically consistent, quasi-hydrostatic equations for global models with a complete representation of the Coriolis force, Q. J. Roy. Meteor. Soc., 121, 399–418, 1995.
Williamson, D. L.: The Evolution of Dynamical Cores for Global Atmospheric Models, J. Meteor. Soc. Jpn., 85B, 241–269, 2007.
Short summary
The design of the icosahedral atmospheric dynamical core DYNAMICO is presented. The key contribution is to combine a strict separatation of kinematics from dynamics to a Hamiltonian formulation of the equations of motion in a non-Eulerian vertical coordinate to achieve energetic consistency. This approach allows for a unified treatment of various equations of motion: multi-layer shallow-water equations and hydrostatic primitive equations.
The design of the icosahedral atmospheric dynamical core DYNAMICO is presented. The key...