Articles | Volume 11, issue 11
Development and technical paper 19 Nov 2018
Development and technical paper | 19 Nov 2018
The VOLNA-OP2 tsunami code (version 1.5)
Istvan Z. Reguly et al.
No articles found.
Ryuichi Kanai, Masashi Kamogawa, Toshiyasu Nagao, Alan Smith, and Serge Guillas
Nat. Hazards Earth Syst. Sci. Discuss.,
Preprint under review for NHESSShort summary
The air pressure created by a tsunami causes a depression in the electron density in the ionosphere. The depression is measured at sparsely distributed, moving, GPS satellite locations. We provide an estimate of the volume of the depression. When applied to the 2011 Tohoku-Oki Earthquake in Japan, our method can warn of a tsunami event within 15 minutes of the earthquake, even when using only 5 % of the data. Thus satellite-based warnings could be implemented across the world with our approach.
Dimitra M. Salmanidou, Joakim Beck, and Serge Guillas
Nat. Hazards Earth Syst. Sci. Discuss.,
Revised manuscript under review for NHESSShort summary
The potential of large magnitude earthquakes in Cascadia poses a significant threat over a populous region of North America. We use statistical emulation to assess the probabilistic tsunami hazard from such events in the region of the city of Victoria, British Columbia. The emulators are built following a sequential design approach for information gain over the input space. To predict the hazard at coastal locations of the region, two families of potential seabed deformation are considered.
Maryam Ilyas, Douglas Nychka, Chris Brierley, and Serge Guillas
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMT
Emily Gleeson, Colm Clancy, Laura Zubiate, Jelena Janjić, Sarah Gallagher, and Frédéric Dias
Adv. Sci. Res., 16, 11–29,Short summary
The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In this study we investigated the influence of large scale atmospheric oscillations on waves in the Northeast Atlantic using a high resolution wave projection dataset.
Joakim Beck, Sören Wolfers, and Gerald P. Roberts
Geosci. Model Dev., 11, 4383–4397,Short summary
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.
Jelena Janjić, Sarah Gallagher, and Frédéric Dias
Adv. Sci. Res., 15, 145–157,Short summary
This study examines the synoptic conditions around Ireland during the winter of 2013/2014, which produced record-breaking sea states and severe coastal damage. Using a wave model, we analysed four of the most energetic storms providing an overview of the height, directionality and periodicity of the waves. This study provides important information for the development of renewable ocean energy extraction, where deployment location selection and survivability are a primary concern.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354,Short summary
The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
Laura O'Brien, Emiliano Renzi, John M. Dudley, Colm Clancy, and Frédéric Dias
Nat. Hazards Earth Syst. Sci., 18, 729–758,Short summary
This paper extends and updates the survey of extreme wave events in Ireland that was previously carried out by O'Brien et al. (2013). Events are categorised into storm waves, rogue waves, tsunamis and storm surges. Important questions regarding public safety, services and the influence of climate change are also highlighted. An interactive map that allows the reader to navigate through events can be found here.
Emily Gleeson, Sarah Gallagher, Colm Clancy, and Frédéric Dias
Adv. Sci. Res., 14, 23–33,Short summary
Large scale atmospheric oscillations, such as the North Atlantic Oscillation are known to have an influence on waves in the North Atlantic. This study investigated the influence of the NAO on the present and future wind and wave climate in the Northeast Atlantic near Ireland.
Sarah Gallagher, Emily Gleeson, Roxana Tiron, Ray McGrath, and Frédéric Dias
Adv. Sci. Res., 13, 75–80,Short summary
As an island located in the North Atlantic Ocean with a highly energetic wave and wind climate, Ireland is uniquely placed in terms of its ocean renewable energy resource. The socio-economic importance of this resource makes it a priority to quantify how the wave and wind climate may change in the future. We examine how surface winds in the North Atlantic Ocean may change towards the end of this century due to global climate change, and how these changes may affect Ireland's wave climate.
K.-L. Chang, S. Guillas, and V. E. Fioletov
Atmos. Meas. Tech., 8, 4487–4505,Short summary
The aim of this article is to analyze the total column ozone data from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) that consists of around 150 stations irregularly spaced over the globe. Our use of a new statistical spatial technique over the globe can greatly outperform the currently used spatial approximation of the total column ozone in terms of approximation. We feel that this technique could benefit the ozone science community.
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Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255,Short summary
One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Olivier Pannekoucke and Philippe Arbogast
Geosci. Model Dev., 14, 5957–5976,Short summary
This contributes to research on uncertainty prediction, which is important either for determining the weather today or estimating the risk in prediction. The problem is that uncertainty prediction is numerically very expensive. An alternative has been proposed wherein uncertainty is presented in a simplified form with only the dynamics of certain parameters required. This tool allows for the determination of the symbolic equations of these parameter dynamics and their numerical computation.
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730,Short summary
The mitigation components of the nationally determined contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested to limit global warming to 1.5–2 °C. The new and easy-to-update open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.
Futo Tomizawa and Yohei Sawada
Geosci. Model Dev., 14, 5623–5635,Short summary
A new method to predict chaotic systems from observation and process-based models is proposed by combining machine learning with data assimilation. Our method is robust to the sparsity of observation networks and can predict more accurately than a process-based model when it is biased. Our method effectively works when both observations and models are imperfect, which is often the case in geoscience. Therefore, our method is useful to solve a wide variety of prediction problems in this field.
Chloe Leach, Tom Coulthard, Andrew Barkwith, Daniel R. Parsons, and Susan Manson
Geosci. Model Dev., 14, 5507–5523,Short summary
Numerical models can be used to understand how coastal systems evolve over time, including likely responses to climate change. However, many existing models are aimed at simulating 10- to 100-year time periods do not represent a vertical dimension and are thus unable to include the effect of sea-level rise. The Coastline Evolution Model 2D (CEM2D) presented in this paper is an advance in this field, with the inclusion of the vertical coastal profile against which the water level can be altered.
Steven J. Phipps, Jason L. Roberts, and Matt A. King
Geosci. Model Dev., 14, 5107–5124,Short summary
Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.
Axel Peytavin, Bruno Sainte-Rose, Gael Forget, and Jean-Michel Campin
Geosci. Model Dev., 14, 4769–4780,Short summary
We present a new algorithm developed at The Ocean Cleanup to update ocean plastic models based on measurements from the field to improve future cleaning operations. Prepared in collaboration with MIT researchers, this initial study presents its use in several analytical and real test cases in which two observers in a flow field record regular observations to update a plastic forecast. We demonstrate this improves the prediction, even with inaccurate knowledge of the water flows driving plastic.
Kang Pan, Mei Qi Lim, Markus Kraft, and Epaminondas Mastorakos
Geosci. Model Dev., 14, 4509–4534,Short summary
A new moving point source (MPS) model was developed to simulate the dispersion of emissions generated by the moving ships. Compared to the commonly used line source (LS) or fixed point source (FPS) model, the MPS model provides more emission distribution details generated by the moving ships and matches reasonably with the measurements. Therefore, the MPS model should be a valuable alternative for the environmental society to evaluate the pollutant dispersion contributed from the moving ships.
Sebastian Springer, Heikki Haario, Jouni Susiluoto, Aleksandr Bibov, Andrew Davis, and Youssef Marzouk
Geosci. Model Dev., 14, 4319–4333,Short summary
Model predictions always contain uncertainty. But in some cases, such as weather forecasting or climate modeling, chaotic unpredictability increases the difficulty to say exactly how much uncertainty there is. We combine two recently proposed mathematical methods to show how the uncertainty can be analyzed in models that are simplifications of true weather models. The results can be extended in the future to show how forecasts from large-scale models can be improved.
Alexander Schaaf, Miguel de la Varga, Florian Wellmann, and Clare E. Bond
Geosci. Model Dev., 14, 3899–3913,Short summary
Uncertainty is an inherent property of any model of the subsurface. We show how geological topology information – how different regions of rocks in the subsurface are connected – can be used to train uncertain geological models to reduce uncertainty. More widely, the method demonstrates the use of probabilistic machine learning (Bayesian inference) to train structural geological models on auxiliary geological knowledge that can be encoded in graph structures.
Matthew Ozon, Aku Seppänen, Jari P. Kaipio, and Kari E. J. Lehtinen
Geosci. Model Dev., 14, 3715–3739,Short summary
Experimental research has provided large amounts of high-quality data on aerosol over the last 2 decades. However, inference of the process rates (e.g., the rates at which particles are generated) is still typically done by simple curve-fitting methods and does not assess the credibility of the estimation. The devised method takes advantage of the Bayesian framework to not only retrieve the state of the observed aerosol system but also to estimate the process rates (e.g., growth rate).
Colton J. Conroy and Einat Lev
Geosci. Model Dev., 14, 3553–3575,Short summary
Lava flows present a natural hazard to communities around volcanoes and are usually slow-moving (< 1-5 cm/s). Lava flows during the 2018 eruption of Kilauea volcano, Hawai’i, however, reached speeds as high as 11 m/s. To investigate these dynamics we develop a new lava flow computer model that incorporates a nonlinear expression for the fluid viscosity. Model results indicate that the lava flows at Site 8 of the eruption displayed shear thickening behavior due to the flow's high bubble content.
Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch
Geosci. Model Dev., 14, 3185–3214,Short summary
Large-eddy simulation (LES) of the urban atmospheric boundary layer involves a large separation of turbulent scales, leading to prohibitive computational costs. An online LES–LES nesting scheme is implemented into the PALM model system 6.0 to overcome this problem. Test results show that the accuracy within the high-resolution nest domains approach the non-nested high-resolution reference results. The nesting can reduce the CPU by time up to 80 % compared to the fine-resolution reference runs.
Yumeng Chen, Konrad Simon, and Jörn Behrens
Geosci. Model Dev., 14, 2289–2316,Short summary
Mesh adaptivity can reduce overall model error by only refining meshes in specific areas where it us necessary in the runtime. Here we suggest a way to integrate mesh adaptivity into an existing Earth system model, ECHAM6, without having to redesign the implementation from scratch. We show that while the additional computational effort is manageable, the error can be reduced compared to a low-resolution standard model using an idealized test and relatively realistic dust transport tests.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Mathieu Lachâtre
Geosci. Model Dev., 14, 2221–2233,Short summary
Representing the advection of thin polluted plumes in numerical models is a challenging task since these models usually tend to excessively diffuse these plumes in the vertical direction. This numerical diffusion process is the cause of major difficulties in representing such dense and thin polluted plumes in numerical models. We propose here, and test in an academic framework, a novel method to solve this problem through the use of an antidiffusive advection scheme in the vertical direction.
Daniel Otoo and David Hodgetts
Geosci. Model Dev., 14, 2075–2095,Short summary
The forward stratigraphic simulation method is used to predict lithofacies, porosity, and permeability in a reservoir model. The objective of using this approach is to enhance subsurface property modelling through geologic realistic 3-D stratigraphic patterns. Results show realistic stratigraphic sequences. Given this, we can derive spatial and geometric data as secondary data to constrain property simulation in a reservoir model. The approach can reduce the uncertainty of property modelling.
Denise Degen and Mauro Cacace
Geosci. Model Dev., 14, 1699–1719,Short summary
In this work, we focus on improving the understanding of subsurface processes with respect to interactions with climate dynamics. We present advanced, open-source mathematical methods that enable us to investigate the influence of various model properties on the final outcomes. By relying on our approach, we have been able to showcase their importance in improving our understanding of the subsurface and highlighting the current shortcomings of currently adopted models.
Geoffroy Kirstetter, Olivier Delestre, Pierre-Yves Lagrée, Stéphane Popinet, and Christophe Josserand
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
The development of forecasting tools may help to limit the impacts of flash floods. Our purpose here is to demonstrate the possibility of using B-flood which is a 2D tool based on the shallow water equations and adaptive mesh refinement.
Geosci. Model Dev., 14, 377–389,Short summary
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,Short summary
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
Geosci. Model Dev., 13, 6467–6480,
Anna Wirbel and Alexander Helmut Jarosch
Geosci. Model Dev., 13, 6425–6445,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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).
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
This study aims to replicate computationally expensive high-resolution large-eddy simulations (LES) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
Jouni Susiluoto, Alessio Spantini, Heikki Haario, Teemu Härkönen, and Youssef Marzouk
Geosci. Model Dev., 13, 3439–3463,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
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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.
We present the VOLNA-OP2 tsunami simulation code, built on the OP2 library. It is unique among...