Articles | Volume 13, issue 1
https://doi.org/10.5194/gmd-13-121-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-121-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
16 Jan 2020
Model description paper |
| 16 Jan 2020
| 16 Jan 2020
A model of Black Sea circulation with strait exchange (2008–2018)
Institute of Marine Sciences and Technology, Dokuz Eylül University, İzmir, Turkey
Emin Özsoy
Institute of Marine Sciences, Middle East Technical University, Erdemli, Mersin, Turkey
Eurasia Earth Science Institute, İstanbul Technical University, İstanbul, Turkey
Robinson Hordoir
Institute of Marine Research, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Related authors
M. Gunduz and E. Özsoy
Ocean Sci., 10, 459–471, https://doi.org/10.5194/os-10-459-2014, https://doi.org/10.5194/os-10-459-2014, 2014
Imke Sievers, Andrea M. U. Gierisch, Till A. S. Rasmussen, Robinson Hordoir, and Lars Stenseng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-84, https://doi.org/10.5194/tc-2022-84, 2022
Preprint withdrawn
Short summary
Short summary
To predict Arctic sea ice models are used. Many ice models exists. They all are skill full, but give different results. Often this differences result from forcing as for example air temperature. Other differences result from the way the physical equations are solved in the model. In this study two commonly used models are compared under equal forcing, to find out how much the models differ under similar external forcing. The results are compared to observations and to eachother.
Filippa Fransner, Agneta Fransson, Christoph Humborg, Erik Gustafsson, Letizia Tedesco, Robinson Hordoir, and Jonas Nycander
Biogeosciences, 16, 863–879, https://doi.org/10.5194/bg-16-863-2019, https://doi.org/10.5194/bg-16-863-2019, 2019
Short summary
Short summary
Although rivers carry large amounts of organic material to the oceans, little is known about what fate it meets when it reaches the sea. In this study we are investigating the fate of the carbon in this organic matter by the use of a numerical model in combination with ship measurements from the northern Baltic Sea. Our results suggests that there is substantial remineralization taking place, transforming the organic carbon into CO2, which is released to the atmosphere.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Sofia Saraiva, H. E. Markus Meier, Helén Andersson, Anders Höglund, Christian Dieterich, Robinson Hordoir, and Kari Eilola
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2018-16, https://doi.org/10.5194/esd-2018-16, 2018
Revised manuscript not accepted
Short summary
Short summary
Uncertainties are estimated in Baltic Sea climate projections by performing scenarios combining 4 Global Climate Models, 2 future gas emissions (RCP4.5, RCP8.5) and 3 nutrient load scenarios. Results on primary production, nitrogen fixation, and hypoxic areas show that uncertainties caused by the nutrients loads are greater than uncertainties due to GCMs and RCPs. In all scenarios, nutrient load abatement strategy, Baltic Sea Action Plan, will lead to an improvement in the environmental state.
Per Pemberton, Ulrike Löptien, Robinson Hordoir, Anders Höglund, Semjon Schimanke, Lars Axell, and Jari Haapala
Geosci. Model Dev., 10, 3105–3123, https://doi.org/10.5194/gmd-10-3105-2017, https://doi.org/10.5194/gmd-10-3105-2017, 2017
Short summary
Short summary
The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive ecosystem. Understanding the sea-ice pack is important for climate effect studies and forecasting. A NEMO-LIM3.6-based model setup for the North Sea/Baltic Sea is introduced, including a method for ice in the coastal zone. We evaluate different sea-ice parameters and overall find that the model agrees well with the observation though deformed ice is more challenging to capture.
M. Gunduz and E. Özsoy
Ocean Sci., 10, 459–471, https://doi.org/10.5194/os-10-459-2014, https://doi.org/10.5194/os-10-459-2014, 2014
P. Malanotte-Rizzoli, V. Artale, G. L. Borzelli-Eusebi, S. Brenner, A. Crise, M. Gacic, N. Kress, S. Marullo, M. Ribera d'Alcalà, S. Sofianos, T. Tanhua, A. Theocharis, M. Alvarez, Y. Ashkenazy, A. Bergamasco, V. Cardin, S. Carniel, G. Civitarese, F. D'Ortenzio, J. Font, E. Garcia-Ladona, J. M. Garcia-Lafuente, A. Gogou, M. Gregoire, D. Hainbucher, H. Kontoyannis, V. Kovacevic, E. Kraskapoulou, G. Kroskos, A. Incarbona, M. G. Mazzocchi, M. Orlic, E. Ozsoy, A. Pascual, P.-M. Poulain, W. Roether, A. Rubino, K. Schroeder, J. Siokou-Frangou, E. Souvermezoglou, M. Sprovieri, J. Tintoré, and G. Triantafyllou
Ocean Sci., 10, 281–322, https://doi.org/10.5194/os-10-281-2014, https://doi.org/10.5194/os-10-281-2014, 2014
Related subject area
Numerical methods
Fast approximate Barnes interpolation: illustrated by Python-Numba implementation fast-barnes-py v1.0
Strategies for conservative and non-conservative monotone remapping on the sphere
Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)
A mixed finite-element discretisation of the shallow-water equations
Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN
Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes
The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning
ISMIP-HOM benchmark experiments using Underworld
spyro: a Firedrake-based wave propagation and full-waveform-inversion finite-element solver
A Comparison of 3-D Spherical Shell Thermal Convection results at Low to Moderate Rayleigh Number using ASPECT (version 2.2.0) and CitcomS (version 3.3.1)
Spatial filtering in a 6D hybrid-Vlasov scheme to alleviate adaptive mesh refinement artifacts: a case study with Vlasiator (versions 5.0, 5.1, and 5.2.1)
LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations
A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1
A fast, single-iteration ensemble Kalman smoother for sequential data assimilation
Characterizing uncertainties of Earth system modeling with heterogeneous many-core architecture computing
Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models
Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics
Islet: interpolation semi-Lagrangian element-based transport
Multi-dimensional hydrological–hydraulic model with variational data assimilation for river networks and floodplains
Assessing the robustness and scalability of the accelerated pseudo-transient method
Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation
University of Warsaw Lagrangian Cloud Model (UWLCM) 2.0: adaptation of a mixed Eulerian–Lagrangian numerical model for heterogeneous computing clusters
Prediction error growth in a more realistic atmospheric toy model with three spatiotemporal scales
On numerical broadening of particle-size spectra: a condensational growth study using PyMPDATA 1.0
Lossy checkpoint compression in full waveform inversion: a case study with ZFPv0.5.5 and the overthrust model
Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
Improved double Fourier series on a sphere and its application to a semi-implicit semi-Lagrangian shallow-water model
SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python
Flow-Py v1.0: a customizable, open-source simulation tool to estimate runout and intensity of gravitational mass flows
Emulation of high-resolution land surface models using sparse Gaussian processes with application to JULES
A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations
Implementation of a Gaussian Markov random field sampler for forward uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19
A method for assessment of the general circulation model quality using the K-means clustering algorithm: a case study with GETM v2.5
An explicit GPU-based material point method solver for elastoplastic problems (ep2-3De v1.0)
MagIC v5.10: a two-dimensional message-passing interface (MPI) distribution for pseudo-spectral magnetohydrodynamics simulations in spherical geometry
Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets
Recalculation of error growth models' parameters for the ECMWF forecast system
How biased are our models? – a case study of the alpine region
B-flood 1.0: an open-source Saint-Venant model for flash-flood simulation using adaptive refinement
A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea
SymPKF (v1.0): a symbolic and computational toolbox for the design of parametric Kalman filter dynamics
NDCmitiQ v1.0.0: a tool to quantify and analyse greenhouse gas mitigation targets
Combining ensemble Kalman filter and reservoir computing to predict spatiotemporal chaotic systems from imperfect observations and models
The Coastline Evolution Model 2D (CEM2D) V1.1
An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3
Ocean Plastic Assimilator v0.2: assimilation of plastic concentration data into Lagrangian dispersion models
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
Short summary
Short summary
We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
Short summary
Short summary
Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
Short summary
Short summary
In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
Short summary
Short summary
This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
Short summary
Short summary
This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
Short summary
Short summary
We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
Short summary
Short summary
We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
Short summary
Short summary
In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
Short summary
Short summary
While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
Short summary
Short summary
A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
Short summary
Short summary
Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
Short summary
Short summary
Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Grant Thomas Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott David King
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-252, https://doi.org/10.5194/gmd-2022-252, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
Due to the increasing availability of high-performance computing over the past decades numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously-known information to modern methodologies.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
Short summary
Short summary
Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-259, https://doi.org/10.5194/gmd-2022-259, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
This paper describes a new release for LISFLOOD-FP model for fast and efficient flood simulations. The model features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPU) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
Short summary
Short summary
Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
Short summary
Short summary
Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
Short summary
Short summary
To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
Short summary
Short summary
Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
Short summary
Short summary
Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
Short summary
Short summary
Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Léo Pujol, Pierre-André Garambois, and Jérôme Monnier
Geosci. Model Dev., 15, 6085–6113, https://doi.org/10.5194/gmd-15-6085-2022, https://doi.org/10.5194/gmd-15-6085-2022, 2022
Short summary
Short summary
This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
Short summary
Short summary
Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
Meriem Krouma, Pascal Yiou, Céline Déandreis, and Soulivanh Thao
Geosci. Model Dev., 15, 4941–4958, https://doi.org/10.5194/gmd-15-4941-2022, https://doi.org/10.5194/gmd-15-4941-2022, 2022
Short summary
Short summary
We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.
Piotr Dziekan and Piotr Zmijewski
Geosci. Model Dev., 15, 4489–4501, https://doi.org/10.5194/gmd-15-4489-2022, https://doi.org/10.5194/gmd-15-4489-2022, 2022
Short summary
Short summary
Detailed computer simulations of clouds are important for understanding Earth's atmosphere and climate. The paper describes how the UWLCM has been adapted to work on supercomputers. A distinctive feature of UWLCM is that air flow is calculated by processors at the same time as cloud droplets are modeled by graphics cards. Thanks to this, use of computing resources is maximized and the time to complete simulations of large domains is not affected by communications between supercomputer nodes.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 15, 4147–4161, https://doi.org/10.5194/gmd-15-4147-2022, https://doi.org/10.5194/gmd-15-4147-2022, 2022
Short summary
Short summary
A scale-dependent error growth described by a power law or by a quadratic hypothesis is studied in Lorenz’s system with three spatiotemporal levels. The validity of power law is extended by including a saturation effect. The quadratic hypothesis can only serve as a first guess. In addition, we study the initial error growth for the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 days.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
Short summary
Short summary
In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, John Washbourne, Paul H. J. Kelly, and Gerard J. Gorman
Geosci. Model Dev., 15, 3815–3829, https://doi.org/10.5194/gmd-15-3815-2022, https://doi.org/10.5194/gmd-15-3815-2022, 2022
Short summary
Short summary
Full waveform inversion (FWI) is a partial-differential equation (PDE)-constrained optimization problem that is notorious for its high computational load and memory footprint. In this paper we present a method that combines recomputation with lossy compression to accelerate the computation with minimal loss of precision in the results. We show this using experiments running FWI with a variety of compression settings on a popular academic dataset.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
Short summary
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Romit Maulik, Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil Constantinescu, Bethany Lusch, Prasanna Balaprakash, Ian Foster, and Rao Kotamarthi
Geosci. Model Dev., 15, 3433–3445, https://doi.org/10.5194/gmd-15-3433-2022, https://doi.org/10.5194/gmd-15-3433-2022, 2022
Short summary
Short summary
In numerical weather prediction, data assimilation is frequently utilized to enhance the accuracy of forecasts from equation-based models. In this work we use a machine learning framework that approximates a complex dynamical system given by the geopotential height. Instead of using an equation-based model, we utilize this machine-learned alternative to dramatically accelerate both the forecast and the assimilation of data, thereby reducing need for large computational resources.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
Short summary
Short summary
This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Mirko Mälicke
Geosci. Model Dev., 15, 2505–2532, https://doi.org/10.5194/gmd-15-2505-2022, https://doi.org/10.5194/gmd-15-2505-2022, 2022
Short summary
Short summary
I preset SciKit-GStat, a well-documented and tested Python package for variogram estimation. The variogram is the core means of geostatistics, which almost all other methods rely on. Geostatistical interpolation and field generation are widely spread in geoscience, i.e., for data assimilation or modeling.
While SciKit-GStat focuses on effective and intuitive variogram estimation, it can interface with other prominent packages and make its variograms available for a multitude of methods.
Christopher J. L. D'Amboise, Michael Neuhauser, Michaela Teich, Andreas Huber, Andreas Kofler, Frank Perzl, Reinhard Fromm, Karl Kleemayr, and Jan-Thomas Fischer
Geosci. Model Dev., 15, 2423–2439, https://doi.org/10.5194/gmd-15-2423-2022, https://doi.org/10.5194/gmd-15-2423-2022, 2022
Short summary
Short summary
The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
Evan Baker, Anna B. Harper, Daniel Williamson, and Peter Challenor
Geosci. Model Dev., 15, 1913–1929, https://doi.org/10.5194/gmd-15-1913-2022, https://doi.org/10.5194/gmd-15-1913-2022, 2022
Short summary
Short summary
We have adapted machine learning techniques to build a model of the land surface in Great Britain. The model was trained using data from a very complex land surface model called JULES. Our model is faster at producing simulations and predictions and can investigate many different scenarios, which can be used to improve our understanding of the climate and could also be used to help make local decisions.
Daichun Wang, Wei You, Zengliang Zang, Xiaobin Pan, Yiwen Hu, and Yanfei Liang
Geosci. Model Dev., 15, 1821–1840, https://doi.org/10.5194/gmd-15-1821-2022, https://doi.org/10.5194/gmd-15-1821-2022, 2022
Short summary
Short summary
This paper presents a 3D variational data assimilation system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, which was developed for a size-resolved sectional model in WRF-Chem. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was designed. The results show that Himawari-8 AOT assimilation can significantly improve model aerosol analyses and forecasts.
Kevin Bulthuis and Eric Larour
Geosci. Model Dev., 15, 1195–1217, https://doi.org/10.5194/gmd-15-1195-2022, https://doi.org/10.5194/gmd-15-1195-2022, 2022
Short summary
Short summary
We present and implement a stochastic solver to sample spatially and temporal varying uncertain input parameters in the Ice-sheet and Sea-level System Model, such as ice thickness or surface mass balance. We represent these sources of uncertainty using Gaussian random fields with Matérn covariance function. We generate random samples of this random field using an efficient computational approach based on solving a stochastic partial differential equation.
Urmas Raudsepp and Ilja Maljutenko
Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, https://doi.org/10.5194/gmd-15-535-2022, 2022
Short summary
Short summary
A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 14, 7749–7774, https://doi.org/10.5194/gmd-14-7749-2021, https://doi.org/10.5194/gmd-14-7749-2021, 2021
Short summary
Short summary
We propose an implementation of the material point method using graphical processing units (GPUs) to solve elastoplastic problems in three-dimensional configurations, such as the granular collapse or the slumping mechanics, i.e., landslide. The computational power of GPUs promotes fast code executions, compared to a traditional implementation using central processing units (CPUs). This allows us to study complex three-dimensional problems tackling high spatial resolution.
Rafael Lago, Thomas Gastine, Tilman Dannert, Markus Rampp, and Johannes Wicht
Geosci. Model Dev., 14, 7477–7495, https://doi.org/10.5194/gmd-14-7477-2021, https://doi.org/10.5194/gmd-14-7477-2021, 2021
Short summary
Short summary
In this work we discuss a two-dimensional distributed parallelization of MagIC, an open-source code for the numerical solution of the magnetohydrodynamics equations. Such a parallelization involves several challenges concerning the distribution of work and data. We detail our algorithm and compare it with the established, optimized, one-dimensional distribution in the context of the dynamo benchmark and discuss the merits of both implementations.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
Short summary
Short summary
This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) 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.
Hynek Bednář, Aleš Raidl, and Jiří Mikšovský
Geosci. Model Dev., 14, 7377–7389, https://doi.org/10.5194/gmd-14-7377-2021, https://doi.org/10.5194/gmd-14-7377-2021, 2021
Short summary
Short summary
Forecast errors in numerical weather prediction systems grow in time. To quantify the impacts of this growth, parametric error growth models may be employed. This study recalculates and newly defines parameters for several statistic models approximating error growth in the ECMWF forecasting system. Accurate values of parameters are important because they are used to evaluate improvements of the forecasting systems or to estimate predictability.
Denise Degen, Cameron Spooner, Magdalena Scheck-Wenderoth, and Mauro Cacace
Geosci. Model Dev., 14, 7133–7153, https://doi.org/10.5194/gmd-14-7133-2021, https://doi.org/10.5194/gmd-14-7133-2021, 2021
Short summary
Short summary
In times of worldwide energy transitions, an understanding of the subsurface is increasingly important to provide renewable energy sources such as geothermal energy. To validate our understanding of the subsurface we require data. However, the data are usually not distributed equally and introduce a potential misinterpretation of the subsurface. Therefore, in this study we investigate the influence of measurements on temperature distribution in the European Alps.
Geoffroy Kirstetter, Olivier Delestre, Pierre-Yves Lagrée, Stéphane Popinet, and Christophe Josserand
Geosci. Model Dev., 14, 7117–7132, https://doi.org/10.5194/gmd-14-7117-2021, https://doi.org/10.5194/gmd-14-7117-2021, 2021
Short summary
Short 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 shallow-water equations and adaptive mesh refinement.
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-5957-2021, https://doi.org/10.5194/gmd-14-5957-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-5695-2021, https://doi.org/10.5194/gmd-14-5695-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-5623-2021, https://doi.org/10.5194/gmd-14-5623-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-5507-2021, https://doi.org/10.5194/gmd-14-5507-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-5107-2021, https://doi.org/10.5194/gmd-14-5107-2021, 2021
Short summary
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, https://doi.org/10.5194/gmd-14-4769-2021, https://doi.org/10.5194/gmd-14-4769-2021, 2021
Short summary
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.
Cited articles
Arkhipkin, V. and Berezhnoi, V. Y.: Steric oscillations of the Black Sea level,
Oceanology of the Russian Academy of Sciences, 35, 735–741, 1995. a
Aydoğdu, A., Hoar, T. J., Vukicevic, T., Anderson, J. L., Pinardi, N., Karspeck, A., Hendricks, J., Collins, N., Macchia, F., and Özsoy, E.: OSSE for a sustainable marine observing network in the Sea of Marmara, Nonlin. Processes Geophys., 25, 537–551, https://doi.org/10.5194/npg-25-537-2018, 2018a. a
Aydoğdu, A., Pinardi, N., Özsoy, E., Danabasoglu, G., Gürses, Ö., and Karspeck, A.: Circulation of the Turkish Straits System under interannual atmospheric forcing, Ocean Sci., 14, 999–1019, https://doi.org/10.5194/os-14-999-2018,
2018b. a
Beşiktepe, Ş., Özsoy, E., and Ünlüata, Ü.: Filling
of the Marmara Sea by the Dardanelles lower layer inflow, Deep-Sea Res.
Pt. I, 40, 1815–1838, 1993. a
Beşiktepe, Ş. T., Sur, H. İ., Özsoy, E., Latif, M. A.,
Oǧuz, T., and Ünlüata, Ü.: The circulation and hydrography of
the Marmara Sea, Prog. Oceanogr., 34, 285–334, 1994. a
Blanke, B. and Delecluse, P.: Variability of the tropical Atlantic Ocean
simulated by a general circulation model with two different mixed-layer
physics, J. Phys. Oceanogr., 23, 1363–1388, 1993. a
Bondar, C.: Considerations on water balance of the Black Sea. Report on the
chemistry of seawater, in: Proceedings of the XXXIII International Conference
on Chemical and Physical Oceanography of the Black Sea, 2–4, 1986. a
Capet, A., Stanev, E. V., Beckers, J.-M., Murray, J. W., and Grégoire, M.: Decline of the Black Sea oxygen inventory, Biogeosciences, 13, 1287–1297, https://doi.org/10.5194/bg-13-1287-2016, 2016. a
Delfanti, R., Özsoy, E., Kaberi, H., Schirone, A., Salvi, S., Conte, F.,
Tsabaris, C., and Papucci, C.: Evolution and fluxes of 137Cs in the black
sea/turkish straits system/north aegean sea, J. Marine Syst., 135,
117–123, 2014. a
Dorrell, R. M., Peakall, J., Sumner, E., Parsons, D., Darby, S., Wynn, R.,
Özsoy, E., and Tezcan, D.: Flow dynamics and mixing processes in
hydraulic jump arrays: Implications for channel-lobe transition zones, Mar.
Geol., 381, 181–193, 2016. a
Dorrell, R. M., Peakall, J., Darby, S. E., Parsons, D. R., Johnson, J., Sumner,
E. J., Wynn, R. B., Özsoy, E., and Tezcan, D.: Self-sharpening induces
jet-like structure in seafloor gravity currents, Nat. Commun., 10,
1381, https://doi.org/10.1038/s41467-019-09254-2, 2019. a
Falina, A., Sarafanov, A., Özsoy, E., and Turunçoğlu, U. U.:
Observed basin-wide propagation of Mediterranean water in the Black Sea,
J. Geophys. Res.-Oceans, 122, 3141–3151, 2017. a
Farmer, D. M. and Armi, L.: Maximal two-layer exchange over a sill and through
the combination of a sill and contraction with barotropic flow, J.
Fluid Mech., 164, 53–76, 1986. a
Farmer, D. M. and Armi, L.: The flow of Atlantic water through the Strait of
Gibraltar, Prog. Oceanogr., 21, 1–103, 1988. a
Federico, I., Pinardi, N., Coppini, G., Oddo, P., Lecci, R., and Mossa, M.: Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas, Nat. Hazards Earth Syst. Sci., 17, 45–59, https://doi.org/10.5194/nhess-17-45-2017, 2017. a
Ferrarin, C., Bellafiore, D., Sannino, G., Bajo, M., and Umgiesser, G.: Tidal
dynamics in the inter-connected Mediterranean, Marmara, Black and Azov seas,
Prog. Oceanogr., 161, 102–115, 2018. a
Gregg, M. C. and Özsoy, E.: Flow, water mass changes, and hydraulics in the
Bosphorus, J. Geophys. Res.-Oceans, 107, https://doi.org/10.1029/2000JC000485, 2002. a, b
Grinevetsky, S. R., Zonn, I. S., Zhiltsov, S. S., Kosarev, A. N., and
Kostianoy, A. G.: The Black Sea Encyclopedia, Springer, Berlin Heidelberg,
2002. a
Ilıcak, M., Özgökmen, T. M., Özsoy, E., and Fischer, P. F.:
Non-hydrostatic modeling of exchange flows across complex geometries, Ocean
Model., 29, 159–175, 2009. a
Jarosz, E., Teague, W. J., Book, J. W., and Beşiktepe, Ş.: On flow
variability in the Bosphorus Strait, J. Geophys. Res.-Oceans,
116, C08038, https://doi.org/10.1029/2010JC006861, 2011a. a, b
Jordà, G., Von Schuckmann, K., Josey, S. A., Caniaux, G.,
García-Lafuente, J., Sammartino, S., Özsoy, E., Polcher, J.,
Notarstefano, G., Poulain, P.-M., Adloff, F., Salat, J., C., N., Schroeder,
K., Chiggiato, J., Sannino, G., and Macías, D.: The Mediterranean Sea heat
and mass budgets: Estimates, uncertainties and perspectives, Prog.
Oceanogr., 156, 174–208, 2017. a
Kelley, D. E., Fernando, H. J. S., Gargett, A. E., Tanny, J., and Özsoy,
E.: The diffusive regime of double-diffusive convection, Prog.
Oceanogr., 56, 461–481, 2003. a
Kosarev, A. N.: The Black Sea Environment, vol. 5, Springer, 2007. a
Latif, M. A., Özsoy, E., Oğuz, T., and Ünlüata, Ü.:
Observations of the Mediterranean inflow into the Black Sea, Deep-Sea
Res. Pt. I, 38, S711–S723, 1991. a
Madec, G.: NEMO ocean engine, Note du Pole de modélisation, Institut
Pierre-Simon Laplace (IPSL), France, No 27, Tech. rep., ISSN-1288-1619, 2008. a
Miladinova, S., Stips, A., Garcia-Gorriz, E., and Moy, D. M.: Formation and
changes of the Black Sea cold intermediate layer, Prog. Oceanogr.,
167, 11–23, 2018. a
Murray, J. W., Top, Z., and Özsoy, E.: Hydrographic properties and
ventilation of the Black Sea, Deep-Sea Res. Pt. I, 38, S663–S689, 1991. a
NEMO: The OPA9 Ocean Engine: Note du Pole de Modelisation Institut Pierre-Simon Laplace, No. 27, ISSN 1288-1619, available at: https://www.nemo-ocean.eu/wp-content/uploads/NEMO_book.pdf (last access: 11 January 2020), 2016 a
Oğuz, T. and Malanotte-Rizzoli, P.: Seasonal variability of wind and
thermohaline-driven circulation in the Black Sea: Modeling studies, J. Geophys. Res.-Oceans, 101, 16551–16569, 1996. a
Oğuz, T., Tuğrul, S., Kıdeys, A. E., Ediger, V., and Kubilay,
N.: Physical and biogeochemical characteristics of the Black Sea, The Sea,
14, 1331–1369, 2005. a
Özsoy, E. and Altıok, H.: A review of water fluxes across the Turkish
Straits System, The Sea of Marmara – Marine Biodiversity, Fisheries,
Conservation and Governance, Turkish Marine Research Foundation (TÜDAV)
Publication 42, 42–61, 2016b. a
Özsoy, E., Top, Z., White, G., and Murray, J. W.: Double diffusive
intrusions, mixing and deep sea convection processes in the Black Sea, in:
Black Sea Oceanography, 17–42, Springer, 1991. a
Özsoy, E., Ünlüata, Ü., and Top, Z.: The Mediterranean water
evolution, material transport by double diffusive intrusions, and interior
mixing in the Black Sea, Prog. Oceanogr., 31, 275–320, 1993. a
Özsoy, E., Rank, D., and Salihoğlu, İ.: Pycnocline and deep
mixing in the Black Sea: stable isotope and transient tracer measurements,
Estuarine, Coast. Shelf Sci., 54, 621–629, 2002. a
Özsoy, E., Çagatay, M., Balkıs, N., Balkıs, N., and
Öztürk, B.: The Sea of Marmara, Marine Biodiversity, Fisheries,
Conservation and Governance, Turkish Marine Research Foundation (TUDAV), Publication No: 42, Istanbul, Turkey, 2016. a
Peneva, E., Stanev, E., Belokopytov, V., and Le Traon, P.-Y.: Water transport
in the Bosphorus Straits estimated from hydro-meteorological and altimeter
data: seasonal to decadal variability, J. Marine Syst., 31, 21–33,
2001. a
Rank, D., Özsoy, E., and Salihoǧlu, İ.: Oxygen-18, deuterium and
tritium in the Black Sea and the Sea of Marmara, J. Environ.
Radioactiv., 43, 231–245, 1999. a
Sannino, G., Sözer, A., and Özsoy, E.: Recent advancements on modelling
the exchange flow dynamics through the Turkish Straits System, Black
Sea/Mediterranean Environment, p. 110, 2014. a
Sarkisyan, A. S. and Sündermann, J. E.: Modelling Climate Variability of
Selected Shelf Seas, Springer, 2009. a
Schroeder, K., Garcìa-Lafuente, J., Josey, S. A., Artale, V., Nardelli, B. B., Carrillo, A., Gačić, M., Gasparini, G. P., Herrmann, M., Lionello, P., Ludwig, W., Millot, C., Özsoy, E., Pisacane, G., Sánchez-Garrido, J. C., Sannino, G., Santoleri, R., Somot, S., Struglia, M., Stanev, E., Taupier-Letage, I., Tsimplis, M. N., Vargas-Yáñez, M., Zervakis, V., and Zodiatis, G.: Circulation of the Mediterranean Sea and its variability, The climate
of the Mediterranean region, edited by: Lionello, P., Elsevier, 187–256, https://doi.org/10.1016/B978-0-12-416042-2.00003-3,
2012. a
Simonov, A. and Altman, E.: Hydrometeorology and hydrochemistry of seas of
USSR. IV, Black Sea, pt. 1, Hydrometeorological conditions, 1991. a
Song, Y. and Haidvogel, D.: A semi-implicit ocean circulation model using a
generalized topography-following coordinate system, J. Comput.
Phys., 115, 228–244, 1994. a
Sorokin, I.: The Black Sea: Ecology and Oceanography, Biology of inland waters,
Backhuys Pub., 2002. a
Sözer, A. and Özsoy, E.: Modeling of the Bosphorus exchange flow
dynamics, Ocean Dynam., 67, 321–343, 2017a. a
Sözer, A. and Özsoy, E.: Water Exchange through Canal İstanbul and
Bosphorus Strait, Mediterr. Mar. Sci., 18, 77–86,
2017b. a
Stanev, E., Grashorn, S., and Zhang, Y.: Cascading ocean basins: numerical
simulations of the circulation and interbasin exchange in the
Azov-Black-Marmara-Mediterranean Seas system, Ocean Dynam., 67, https://doi.org/10.1007/s10236-017-1071-2, 2017. a, b
Stanev, E. V.: On the mechanisms of the Black Sea circulation, Earth-Sci.
Rev., 28, 285–319, 1990. a
Stanev, E. V.: Understanding Black Sea dynamics: Overview of recent numerical
modeling, Oceanography, 18, 56–75, 2005. a
Stanev, E. V., Bowman, M. J., Peneva, E. L., and Staneva, J. V.: Control of
Black Sea intermediate water mass formation by dynamics and topography:
Comparison of numerical simulations, surveys and satellite data, J.
Mar. Res., 61, 59–99, 2003. a
Stanev, E. V., Peneva, E., and Chtirkova, B.: Climate change and regional ocean
water mass disappearance: case of the Black Sea, J. Geophys.
Res.-Oceans, 124, 4803–4819,
https://doi.org/10.1029/2019JC015076, 2019. a
Sur, H. İ., Özsoy, E., and Ünlüata, Ü.: Boundary current
instabilities, upwelling, shelf mixing and eutrophication processes in the
Black Sea, Prog. Oceanogr., 33, 249–302, 1994. a
Tsimplis, M., Josey, S., Rixen, M., and Stanev, E.: On the forcing of sea level
in the Black Sea, J. Geophys. Res.-Oceans, 109, C08015,
https://doi.org/10.1029/2003JC002185, 2004.
a
Vespremeanu, E. and Golumbeanu, M.: The Black Sea: Physical, Environmental and
Historical Perspectives, Springer, 2017. a
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.
The Bosphorus exchange is of critical importance for hydrodynamics and hydroclimatology of the...
