Articles | Volume 13, issue 4
https://doi.org/10.5194/gmd-13-2073-2020
© 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-13-2073-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)
Giovanni Denaro
CNR-IRIB, Consiglio Nazionale delle Ricerche – Istituto per la Ricerca e l'Innovazione Biomedica, Via Ugo La Malfa 153, 90146 Palermo, Italy
Daniela Salvagio Manta
CNR-IAS, National Research Council of Italy – Institute of Anthropic Impacts and Sustainability in marine environment, ex Complesso Roosevelt, Lungomare Cristoforo Colombo, 4521, Loc. Addaura, Palermo, Italy
Alessandro Borri
CORRESPONDING AUTHOR
CNR-IASI Biomathematics Laboratory, Consiglio Nazionale delle Ricerche – Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Via dei Taurini 19, 00185 Rome, Italy
Maria Bonsignore
CNR-IAS, National Research Council of Italy – Institute of Anthropic Impacts and Sustainability in marine environment, U.O.S di Capo Granitola, Via del Faro 3, 91020 Campobello di Mazara (TP), Italy
Davide Valenti
CNR-IRIB, Consiglio Nazionale delle Ricerche – Istituto per la Ricerca e l'Innovazione Biomedica, Via Ugo La Malfa 153, 90146 Palermo, Italy
Dipartimento di Fisica e Chimica “Emilio Segrè”, Università di Palermo, Group of Interdisciplinary Theoretical Physics and CNISM, Unità di Palermo, Viale delle Scienze, Ed. 18, 90128 Palermo, Italy
Enza Quinci
CNR-IAS, National Research Council of Italy – Institute of Anthropic Impacts and Sustainability in marine environment, U.O.S di Capo Granitola, Via del Faro 3, 91020 Campobello di Mazara (TP), Italy
Andrea Cucco
CNR-IAS, Consiglio Nazionale delle Ricerche – Istituto per lo studio degli impatti Antropici e Sostenibilità in ambiente marino, U.O.S. di Oristano, località Sa Mardini, 09072 Torregrande (OR), Italy
Bernardo Spagnolo
Dipartimento di Fisica e Chimica “Emilio Segrè”, Università di Palermo, Group of Interdisciplinary Theoretical Physics and CNISM, Unità di Palermo, Viale delle Scienze, Ed. 18, 90128 Palermo, Italy
Radiophysics Department, National Research Lobachevsky State University of Nizhni Novgorod, 23 Gagarin Avenue, Nizhni Novgorod 603950, Russia
Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Via S. Sofia 64, 90123 Catania, Italy
Mario Sprovieri
CNR-IAS, National Research Council of Italy – Institute of Anthropic Impacts and Sustainability in marine environment, U.O.S di Capo Granitola, Via del Faro 3, 91020 Campobello di Mazara (TP), Italy
Andrea De Gaetano
CNR-IASI Biomathematics Laboratory, Consiglio Nazionale delle Ricerche – Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Via dei Taurini 19, 00185 Rome, Italy
Related authors
No articles found.
Alberto Ribotti, Antonio Bussani, Milena Menna, Andrea Satta, Roberto Sorgente, Andrea Cucco, and Riccardo Gerin
Earth Syst. Sci. Data, 15, 4651–4659, https://doi.org/10.5194/essd-15-4651-2023, https://doi.org/10.5194/essd-15-4651-2023, 2023
Short summary
Short summary
Over 100 experiments were realized between 1998 and 2022 in the Mediterranean Sea using surface coastal and offshore Lagrangian drifters. Raw data were initially unified and pre-processed. Then, the integrity of the received data packages was checked and incomplete ones were discarded. Deployment information was retrieved and integrated into the PostgreSQL database. Data were interpolated at defined time intervals, providing a dataset of 158 trajectories, available in different formats.
Roberto Sorgente, Federica Pessini, Aldo Francis Drago, Alberto Ribotti, Simona Genovese, Marco Barra, Angelo Perilli, Giovanni Quattrocchi, Andrea Cucco, Ignazio Fontana, Giovanni Giacalone, Gualtiero Basilone, and Angelo Bonanno
EGUsphere, https://doi.org/10.5194/egusphere-2023-2193, https://doi.org/10.5194/egusphere-2023-2193, 2023
Preprint withdrawn
Short summary
Short summary
Presence and interannual variability of water masses on the continental shelf around Sardinia are studied by CTD data from three cruises carried out between 2019 and 2021. For the first time the analyses are identifying the water mass phenomenology on the south-western Sardinia shelf characterized by the presence of the Atlantic Water driven by Algerian eddies. On the southern and eastern shelves, the presence of the Atlantic Water the water column is affected by the South East Sardinia Gyre.
Alberto Ribotti, Roberto Sorgente, Federica Pessini, Andrea Cucco, Giovanni Quattrocchi, and Mireno Borghini
Earth Syst. Sci. Data, 14, 4187–4199, https://doi.org/10.5194/essd-14-4187-2022, https://doi.org/10.5194/essd-14-4187-2022, 2022
Short summary
Short summary
Over 1468 hydrological vertical profiles were acquired in 21 years in the Mediterranean Sea. This allowed us to follow the diffusion of the Western Mediterranean Transient along all western seas or make some important repetitions across straits, channels, or at defined locations. These data are now available in four open-access online datasets, including profiles of water temperature, conductivity, dissolved oxygen, chlorophyll α fluorescence, and, after 2004, turbidity and pH.
Georg Umgiesser, Marco Bajo, Christian Ferrarin, Andrea Cucco, Piero Lionello, Davide Zanchettin, Alvise Papa, Alessandro Tosoni, Maurizio Ferla, Elisa Coraci, Sara Morucci, Franco Crosato, Andrea Bonometto, Andrea Valentini, Mirko Orlić, Ivan D. Haigh, Jacob Woge Nielsen, Xavier Bertin, André Bustorff Fortunato, Begoña Pérez Gómez, Enrique Alvarez Fanjul, Denis Paradis, Didier Jourdan, Audrey Pasquet, Baptiste Mourre, Joaquín Tintoré, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, https://doi.org/10.5194/nhess-21-2679-2021, 2021
Short summary
Short summary
The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.
Andrea Cucco, Giovanni Quattrocchi, Antonio Olita, Leopoldo Fazioli, Alberto Ribotti, Matteo Sinerchia, Costanza Tedesco, and Roberto Sorgente
Nat. Hazards Earth Syst. Sci., 16, 1553–1569, https://doi.org/10.5194/nhess-16-1553-2016, https://doi.org/10.5194/nhess-16-1553-2016, 2016
Short summary
Short summary
This work explored the importance of considering the tidal dynamics when modelling the general circulation in the Messina Strait, a narrow passage connecting the Tyrrhenian and the Ionian Sea sub-basins in the Western Mediterranean Sea. The results highlight that tidal dynamics deeply impact the reproduction of the instantaneous and residual circulation pattern, waters thermohaline properties and transport dynamics both inside the Messina Strait and in the surrounding coastal and open waters.
Related subject area
Biogeosciences
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
The community-centered aquatic biogeochemistry model unified RIVE v1.0: a unified version for water column
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water and nitrogen perturbations
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
A Novel Eulerian Reaction-Transport Model to Simulate Age and Reactivity Continua Interacting with Mixing Processes
AgriCarbon-EO: v1.0.1: Large Scale and High Resolution Simulation of Carbon Fluxes by Assimilation of Sentinel-2 and Landsat-8 Reflectances using a Bayesian approach
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling
Impact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02
FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics
Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0)
Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon
SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level
Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation
Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP)
CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5)
The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0
A validation standard for area of habitat maps for terrestrial birds and mammals
Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9
Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
A map of global peatland extent created using machine learning (Peat-ML)
Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)
ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-135, https://doi.org/10.5194/gmd-2023-135, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of aquatic biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganisms’ activities to describe full biogeochemical cycles in the water column (e.g. carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams, and public services.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-107, https://doi.org/10.5194/gmd-2023-107, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-74, https://doi.org/10.5194/gmd-2023-74, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We develop a machine learning based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a lightweight way.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-66, https://doi.org/10.5194/gmd-2023-66, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
EGUsphere, https://doi.org/10.5194/egusphere-2023-46, https://doi.org/10.5194/egusphere-2023-46, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, bottom trawling, etc. We derive equations for simulating the effect of mixing on central moments that describe the distributions. Then, we demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Rémy Fieuzal, and Eric Ceschia
EGUsphere, https://doi.org/10.5194/egusphere-2023-48, https://doi.org/10.5194/egusphere-2023-48, 2023
Short summary
Short summary
Quantification of Carbon fluxes of crops is an essential brick for the construction of a Monitoring, Reporting and Verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates through an efficient Bayesian approach, high resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in-situ flux towers, yield maps, and analysed at regional scale.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
Short summary
Short summary
We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
Short summary
Short summary
To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
Short summary
Short summary
Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
Short summary
Short summary
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
Short summary
Short summary
The coastal marine environment serves as a transition zone in the land–ocean continuum and is susceptible to episodic phenomena such as flash floods, which cause massive organic matter deposition. Here, we present a model of sediment early diagenesis that explicitly describes this type of deposition while also incorporating unique flood deposit characteristics. This model can be used to investigate the temporal evolution of marine sediments following abrupt changes in environmental conditions.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022, https://doi.org/10.5194/gmd-15-6863-2022, 2022
Short summary
Short summary
Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
Short summary
Short summary
Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Marcus Falls, Raffaele Bernardello, Miguel Castrillo, Mario Acosta, Joan Llort, and Martí Galí
Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, https://doi.org/10.5194/gmd-15-5713-2022, 2022
Short summary
Short summary
This paper describes and tests a method which uses a genetic algorithm (GA), a type of optimisation algorithm, on an ocean biogeochemical model. The aim is to produce a set of numerical parameters that best reflect the observed data of particulate organic carbon in a specific region of the ocean. We show that the GA can provide optimised model parameters in a robust and efficient manner and can also help detect model limitations, ultimately leading to a reduction in the model uncertainties.
Julien Ruffault, François Pimont, Hervé Cochard, Jean-Luc Dupuy, and Nicolas Martin-StPaul
Geosci. Model Dev., 15, 5593–5626, https://doi.org/10.5194/gmd-15-5593-2022, https://doi.org/10.5194/gmd-15-5593-2022, 2022
Short summary
Short summary
A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
Short summary
Short summary
We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
Short summary
Short summary
In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
Short summary
Short summary
Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jiaying Zhang, Rafael L. Bras, Marcos Longo, and Tamara Heartsill Scalley
Geosci. Model Dev., 15, 5107–5126, https://doi.org/10.5194/gmd-15-5107-2022, https://doi.org/10.5194/gmd-15-5107-2022, 2022
Short summary
Short summary
We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105, https://doi.org/10.5194/gmd-15-5093-2022, https://doi.org/10.5194/gmd-15-5093-2022, 2022
Short summary
Short summary
This paper describes the validation of area of habitat (AOH) maps produced for terrestrial birds and mammals. The main objective was to assess the accuracy of the maps based on independent data. We used open access data from repositories, such as ebird and gbif to check if our maps were a better reflection of species' distribution than random. When points were not available we used logistic models to validate the AOH maps. The majority of AOH maps were found to have a high accuracy.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
Short summary
Short summary
Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
Short summary
Short summary
We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
Short summary
Short summary
Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Qianyu Li, Shawn P. Serbin, Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and Alistair Rogers
Geosci. Model Dev., 15, 4313–4329, https://doi.org/10.5194/gmd-15-4313-2022, https://doi.org/10.5194/gmd-15-4313-2022, 2022
Short summary
Short summary
Stomatal conductance is the rate of water release from leaves’ pores. We implemented an optimal stomatal conductance model in a vegetation model. We then tested and compared it with the existing empirical model in terms of model responses to key environmental variables. We also evaluated the model with measurements at a tropical forest site. Our study suggests that the parameterization of conductance models and current model response to drought are the critical areas for improving models.
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, https://doi.org/10.5194/gmd-15-3901-2022, 2022
Short summary
Short summary
We describe the coupled bio-physical model ECOSMO II(CHL), which is used for regional configurations for the North Atlantic and the Arctic hind-casting and operational purposes. The model is consistent with the large-scale climatological nutrient settings and is capable of representing regional and seasonal changes, and model primary production agrees with previous measurements. For the users of this model, this paper provides the underlying science, model evaluation and its development.
Cited articles
Bagnato, E., Sprovieri, M., Barra, M., Bitetto, M., Bonsignore, M., Calabrese,
S., Di Stefano, V., Oliveri, E., Parello, F., and Mazzola, S.: The sea-air
exchange of mercury (Hg) in the marine boundary layer of the Augusta basin
(southern Italy): Concentrations and evasion flux, Chemosphere, 93,
2024–2032, https://doi.org/10.1016/j.chemosphere.2013.07.025, 2013. a, b, c, d, e, f, g, h, i, j
Bellucci, L. G., Giuliani, S., Romano, S., Albertazzi, S., Mugnai, C., and
Frignani, M.: An integrated approach to the assessment of pollutant delivery
chronologies to impacted areas: Hg in the Augusta Bay (Italy), Environ. Sci.
Technol., 46, 2040–2046, https://doi.org/10.1021/es203054c, 2012. a
Bianchi, F., Dardanoni, G., Linzalone, N., and Pierini, A.: Malformazioni
congenite nei nati residenti nel Comune di Gela (Sicilia, Italia), Epidemiol.
Prev., 30, 19–26, 2006. a
Bonsignore, M., Manta, D. S., Oliveri, E., Sprovieri, M., Basilone, G.,
Bonanno, A., Falco, F., Traina, A., and Mazzola, S.: Mercury in fishes from
Augusta Bay (southern Italy): risk assessment and health implication, Food
Chem. Toxicol., 56, 184–194, https://doi.org/10.1016/j.fct.2013.02.025, 2013. a
Bonsignore, M., Tamburrino, S., Oliveri, E., Marchetti, A., Durante, C., Berni,
A., Quinci, E., and Sprovieri, M.: Tracing mercury pathways in Augusta Bay
(southern Italy) by total concentration and isotope determination, Environ.
Pollut., 205, 178–185, https://doi.org/10.1016/j.envpol.2015.05.033, 2015. a
Bonsignore, M., Andolfi, N., Barra, M., Madeddu, M., Tisano, F., Ingallinella,
V., Castorina, M., and Sprovieri, M.: Assessment of mercury exposure in human
populations: a status report from Augusta Bay (southern Italy), Environ. Res., 150, 592–599,
https://doi.org/10.1016/j.envres.2016.01.016, 2016. a
Bryant, L. D., McGinnis, D. F., Lorrai, C., Brand, A., Little, J. C., and
Wüest, A.: Evaluating oxygen fluxes using microprofiles from both sides
of the sediment–water interface, Limnol. Oceanogr.-Meth., 8, 610–627,
https://doi.org/10.4319/lom.2010.8.610, 2010. a
Budillon, F., Ferraro, L., Hopkins, T. S., Iorio, M., Lubritto, C., Sprovieri,
M., Bellonia, A., Marzaioli, F., and Tonielli, R.: Effects of intense
anthropogenic settlement of coastal areas on seabed and sedimentary systems:
a case study from the Augusta Bay (southern Italy), Rend. Online Soc. Geol.
Italy, 3, 142–143, 2008. a
Burchard, H. and Petersen, O.: Models of turbulence in the marine environment,
A comparative study of two-equation turbulence models, J. Marine Syst.,
21, 23–53, https://doi.org/10.1016/S0924-7963(99)00004-4, 1999. a
Canu, D. and Rosati, G.: Long-term scenarios of mercury budgeting and exports
for a Mediterranean hot spot (Marano-Grado Lagoon, Adriatic Sea), Estuar.
Coast. Shelf S., 198, 518–528,
https://doi.org/10.1016/j.ecss.2016.12.005, 2017. a, b, c, d
Cossa, D. and Coquery, M.: The Handbook of Environmental Chemistry, Vol. 5,
Part K: The Mediterranean Mercury Anomaly, a Geochemical or a
Biologocal Issue, Springer-Verlag Berlin Heidelberg, 177–208, 2005. a
Covelli, S., Faganeli, J., Horvat, M., and Bramati, A.: Porewater Distribution
and Benthic Flux Measurements of Mercury and Methylmercury in the Gulf of
Trieste (Northern Adriatic Sea), Estuar. Coast. Shelf S., 48, 415–428,
https://doi.org/10.1006/ecss.1999.0466, 1999. a, b, c
Cucco, A., Quattrocchi, G., Olita, A., Fazioli, L., Ribotti, A., Sinerchia, M., Tedesco, C., and Sorgente, R.: Hydrodynamic modelling of coastal seas: the role of tidal dynamics in the Messina Strait, Western Mediterranean Sea, Nat. Hazards Earth Syst. Sci., 16, 1553–1569, https://doi.org/10.5194/nhess-16-1553-2016, 2016a. a, b, c
Cucco, A., Quattrocchi, G., Satta, A., Antognarelli, F., De Biasio, F.,
Cadau, E., Umgiesser, G., and Zecchetto, S.: Predictability of wind-induced
sea surface transport in coastal areas, J. Geophys. Res.-Oceans, 121,
5847–5871, https://doi.org/10.1002/2016JC011643, 2016b. a, b
Cucco, A., Quattrocchi, G., and Zecchetto, S.: The role of temporal resolution
in modeling the wind induced sea surface transport in coastal seas, J. Marine
Syst., 193, 46–58, https://doi.org/10.1016/j.jmarsys.2019.01.004,
2019. a, b
De Marchis, M., Freni, G., and Napoli, E.: Three-dimensional numerical
simulations on wind- and tide-induced currents: The case of Augusta Harbour
(Italy), Comput. Geosci., 72, 65–75, 2014. a
Denaro, G. and Borri, A.: Spatio-temporal dynamic model of mercury concentration – version 1, Zenodo, https://doi.org/10.5281/zenodo.3384784, 2019. a
Denaro, G., Valenti, D., La Cognata, A., Spagnolo, B., Bonanno, A., Basilone,
G., Mazzola, S., Zgozi, S., Aronica, S., and Brunet, C.: Spatio-temporal
behaviour of the deep chlorophyll maximum in Mediterranean Sea:
Development of a stochastic model for picophytoplankton dynamics, Ecol.
Complex., 13, 21–34, https://doi.org/10.1016/j.ecocom.2012.10.002, 2013a. a, b, c, d
Denaro, G., Valenti, D., Spagnolo, B., Basilone, G., Mazzola, S., Zgozi, S.,
Aronica, S., and Bonanno, A.: Dynamics of two picophytoplankton groups in
Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a
stochastic advection-reaction-diffusion model, PLoS ONE, 8, e66765,
https://doi.org/10.1371/journal.pone.0066765, 2013b. a, b, c
Denaro, G., Valenti, D., Spagnolo, B., Bonanno, A., Basilone, G., Mazzola, S.,
Zgozi, S., and Aronica, S.: Stochastic dynamics of two picophytoplankton
populations in a real marine ecosystem, Acta Phys. Pol. B, 44, 977–990,
https://doi.org/10.5506/APhysPolB.44.977, 2013c. a, b, c, d
Denman, K. L. and Gargett, A. E.: Time and space scales of vertical mixing and
advection of phytoplankton in the upper ocean, Limnol. Oceanogr., 28,
801–815, https://doi.org/10.4319/lo.1983.28.5.0801, 1983. a, b
Driscoll, C. T., Mason, R. P., Chan, H. M., Jacob, D. J., and Pirrone, N.:
Mercury as a Global Pollutant: Sources, Pathways, and Effects, Environ. Sci.
Technol., 47, 4967–4983, https://doi.org/10.1021/es305071v, 2013. a
Dutkiewicz, S., Follows, M. J., and Bragg, J. G.: Modeling the coupling of
ocean ecology and biogeochemistry., Global Biogeochem. Cy., 23, GB4017,
https://doi.org/10.1029/2008GB003405, 2009. a, b, c
Ferrarin, C., Bajo, M., Bellafiore, D., Cucco, A., De Pascalis, F., and
Ghezzo, M.: Toward homogenization of Mediterranean lagoons and their loss of
hydrodiversity, Geophys. Res. Lett., 41, 5935–5941,
https://doi.org/10.1002/2014GL060843, 2014. a
Fiasconaro, A., Valenti, D., and Spagnolo, B.: Nonmonotonic Behaviour of
Spatiotemporal Pattern Formation in a Noisy Lotka-Volterra System, Acta Phys.
Pol. B, 35, 1491–1500, 2004. a
Han, S., Lehman, R. D., Choe, K. Y., and Gill, A.: Chemical and physical
speciation of mercury in Offatts Bayou: A seasonally anoxic bayou in
Galveston Bay, Limnol. Oceanogr., 52, 1380–1392,
https://doi.org/10.4319/lo.2007.52.4.1380, 2007. a
Hines, M. E., Potrait, E. N., Covelli, S., Faganeli, J., Emili, A., Zizek, E.,
and Horvat, M.: Mercury methylation and demethylation in Hg-contaminated
lagoon sediments (Marano and Grado Lagoon, Italy), Estuar. Coast. Shelf S.,
113, 85–95, https://doi.org/10.1016/j.ecss.2011.12.021, 2012. a
Horvat, M., Kotnik, J., Logar, M., Fajon, V., Zvoranic, T., and Pirrone, N.:
Speciation of mercury in surface and deep-sea waters in the Mediterranean
Sea, Atmos. Environ., 37, S93–S108,
https://doi.org/10.1016/S1352-2310(03)00249-8, 2003. a, b, c
La Barbera, A. and Spagnolo, B.: Spatio-Temporal Patterns in Population
Dynamics, Physica A, 314, 120–124, https://doi.org/10.1016/S0378-4371(02)01173-1,
2002. a
Lee, C. S. and Fischer, N. S.: Bioaccumulation of methylmercury in a marine
copepod, Environ. Toxicol. Chem., 36, 1287–1293, https://doi.org/10.1002/etc.3660,
2017. a, b
Lehnherr, I., St. Louis, V. L., Hintelmann, H., and Kirk, J. L.: Methylation
of inorganic mercury in polar marine waters, Nat. Geosci., 4, 298–302,
https://doi.org/10.1038/ngeo1134, 2011. a, b, c
Liu, G., Cai, J., and O'Driscoll, N.: Environmental Chemistry and
Toxycology of Mercury, John Wiley and Sons, Inc., Hoboken, New Jersey,
2012. a
Mason, R. P., Choi, A. L., Fitzgerald, W. F., Hammerschimidt, C. R., Lamborg,
C. H., Soerensen, A. L., and Sunderland, E. M.: Mercury biogeochemical
cycling in the ocean and policy implications, Environ. Res., 112, 101–117,
https://doi.org/10.1016/j.envres.2012.03.013, 2012. a
Melaku Canu, D., Rosati, G., Solidoro, C., Heimbürger, L., and Acquavita,
A.: A comprehensive assessment of the mercury budget in the Marano-Grado
Lagoon (Adriatic Sea) using a combined observational modeling approach, Mar.
Chem., 177, 742–752, https://doi.org/10.1016/j.marchem.2015.10.013, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o
Monperrus, M., Tessier, E., Amouroux, D., Leynaert, A., Huonnic, P., and
Donard, O. F. X.: Mercury methylation, demethylation and reduction rates in
coastal and marine surface waters of the Mediterranean Sea, Mar. Chem., 107,
49–63, https://doi.org/10.1016/j.marchem.2007.01.018, 2007a. a, b
Monperrus, M., Tessier, E., Point, D., Vidimova, K., Amouroux, D., Guyoneaud,
R., Leynaert, A., Grall, J., Chauvaud, L., Thouzeau, G., and Donard, O.
F. X.: The biogeochemistry of mercury at the sediment-water interface in the
Thau Lagoon. 2. Evaluation of mercury methylation potential in both surface
sediment and the column, Estuar. Coast. Shelf S., 72, 485–486,
https://doi.org/10.1016/j.ecss.2006.11.014, 2007b. a, b
Morozov, A., Arashkevich, E., Nikishina, A., and Solovyev, K.: Nutrient-rich
plankton communities stabilized via predator-prey interactions: revisiting
the role of vertical heterogeneity, Math. Med. Biol., 28, 185–215,
https://doi.org/10.1093/imammb/dqq010, 2010. a, b
Morozov, A., Denaro, G., Spagnolo, B., and Valenti, D.: Revisiting the role of
top-down and bottom-up controls in stabilisation of nutrient-rich plankton
communities, Commun. Nonlinear Sci., 79, 104885,
https://doi.org/10.1016/j.cnsns.2019.104885, 2019. a, b
Ogrinc, N., Monperrus, M., Kotnik, J., Fajon, V., Vidimova, K., Amouroux, D.,
Kocman, D., Tessier, E., Zizek, S., and Horvat, M.: Distribution of mercury
and methylmercury in deep-sea surficial sediments of the Mediterranean Sea,
Mar. Chem., 107, 31–48, https://doi.org/10.1016/j.marchem.2007.01.019,
2007. a, b, c
Oliveri, E., Manta, D. S., Bonsignore, M., Cappello, S., Tranchida, G.,
Bagnato, E., Sabatino, N., Santisi, S., and Sprovieri, M.: Mobility of
mercury in contaminated marine sediments: Biogeochemical pathways, Mar.
Chem., 186, 1–10, https://doi.org/10.1016/j.marchem.2016.07.002, 2016. a, b, c, d, e, f, g, h
Pacanowski, R. and Philander, S. G. H.: Parameterization of Vertical Mixing in
Numerical Models of Tropical Oceans, J. Phys. Oceanogr., 11, 1443–1451,
https://doi.org/10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2, 1981. a
Pakhomova, S. V., Yakushev, E. V., Protsenko, E. A., Rigaud, S., Cossa, D.,
Knoery, J., Couture, R. M., Radakovitch, O., Yakubov, S. K., Krzeminska, D.,
and Newton, A.: Modeling the Influence of Eutrophication and Redox Conditions
on Mercury Cycling at the Sediment-Water Interface in the Berre Lagoon,
Front. Mar. Sci., 5, https://doi.org/10.3389/fmars.2018.00291, 2018. a, b, c, d, e
Pickhardt, P. C. and Fischer, N. S.: Accumulation of Inorganic and
Methylmercury by Freshwater Phytoplankton in Two Contrasting Water Bodies,
Environ. Sci. Technol., 41, 125–131, https://doi.org/10.1021/es060966w, 2007. a, b, c
Qureshi, A., O'Driscoll, N. J., MacLeod, M., Neuhold, Y. M., and
Hungerbuhler, K.: Photoreactions of mercury in surface ocean water: gross
reaction kinetics and possible pathways, Environ. Sci. Technol., 44,
644–649, https://doi.org/10.1021/es9012728, 2010. a
Roache, P. J.: Fundamentals of Computational Fluid Dynamics, Hermosa
Publishers, Albuquerque, New Mexico, 1998. a
Rosati, G., Heimbürger, L. E., Melaku Canu, D., Lagane, C., Rijkenberg,
M. J. A., Gerringa, L. J. A., Solidoro, C., Gencarelli, C. N., Hedgecock,
I. M., De Baar, H. J. W., and Sonke, J. E.: Mercury in the Black Sea: New
Insights From Measurements and Numerical Modeling, Global Biogeochem. Cy.,
32, 529–550, https://doi.org/10.1002/2017GB005700, 2018. a, b, c, d, e
Salvagio Manta, D., Bonsignore, M., Oliveri, E., Barra, M., Tranchida, G.,
Giaramita, L., Mazzola, S., and Sprovieri, M.: Fluxes and the mass balance of
mercury in Augusta Bay (Sicily, southern Italy), Estuar. Coast. Shelf S.,
181, 134–143, https://doi.org/10.1016/j.ecss.2016.08.013, 2016. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s
Soerensen, A. L., Sunderland, E. M., Holmes, C. D., Jacob, D. J., Yantosca,
R. M., Skov, H., Christensen, J. H., Strode, S. A., and Mason, R. P.: An
improved global model for air-sea exchange of mercury: High concentrations
over the north Atlantic, Environ. Sci. Technol., 44, 8574–8580,
https://doi.org/10.1021/es102032g, 2010. a
Soerensen, A. L., Schartup, A. T., Gustafsson, E., Gustafsson, B. G., Undeman,
E., and Björn, E.: Eutrophication Increases Phytoplankton Methylmercury
Concentrations in a Coastal Sea – A Baltic Sea Case Study, Environ. Sci.
Technol., 50, 11787–11796, https://doi.org/10.1021/acs.est.6b02717, 2016. a, b, c, d
Sprovieri, M., Oliveri, E., Di Leonardo, R., Romano, E., Ausili, A.,
Gabellini, M., Barra, M., Tranchida, G., Bellanca, A., Neri, R., Budillon,
F., Saggiomo, R., Mazzola, S., and Saggiomo, V.: The key role played by the
Augusta basin (southern Italy) in the mercury contamination of the
Mediterranean Sea, J. Environ. Monitor., 13, 1753–1760,
https://doi.org/10.1039/C0EM00793E, 2011. a, b, c, d, e, f, g, h
Strode, S., Jaeglè, L., and Emerson, S.: Vertical transport of
anthropogenic mercury in the ocean, Global Biogeochem. Cy., 24, GB4014,
https://doi.org/10.1029/2009GB003728, 2010. a
Sunderland, E. M., Gobas, F. A. P. C., Branfireum, B. A., and Heyes, A.:
Environmental controls on the speciation and distribtuion of mercury in
coastal sediments, Mar. Chem., 102, 111–123,
https://doi.org/10.1016/j.marchem.2005.09.019, 2006. a
Thi, N. N. P., Huisman, J., and Sommeijer, B. P.: Simulation of
three-dimensional phytoplankton dynamics: competition in light-limited
environments, J. Comput. Appl. Math., 174, 57–77,
https://doi.org/10.1016/j.cam.2004.03.023, 2005. a
Tomasello, B., Copat, C., Pulvirenti, V., Ferrito, V., Ferrante, M., Renis, M.,
Sciacca, S., and Tigano, C.: Biochemical and bioaccumulation approaches for
investigating marine pollution using Mediterranean rainbow wrasse, Coris
julis (Linneaus 1798), Ecotox. Environ. Safe., 86, 168–175,
https://doi.org/10.1016/j.ecoenv.2012.09.012, 2012. a, b
Umgiesser, G., Canu, D. M., Cucco, A., and Solidoro, C.: A finite element model
for the Venice Lagoon. Development, set up, calibration and validation, J.
Marine Syst., 51, 123–145, https://doi.org/10.1016/j.jmarsys.2004.05.009, 2004. a, b
Umgiesser, G., Ferrarin, C., Cucco, A., De Pascalis, F., Bellafiore, D.,
Ghezzo, M., and Bajo, M.: Comparative hydrodynamics of 10 Mediterranean
lagoons by means of numerical modeling, J. Geophys. Res.-Oceans, 119,
2212–2226, https://doi.org/10.1002/2013JC009512, 2014. a, b
Valenti, D., Fiasconaro, A., and Spagnolo, B.: Pattern formation and spatial
correlation induced by the noise in two competing species, Acta Phys. Pol. B,
35, 1481–1489, 2004. a
Valenti, D., Tranchina, L., Cosentino, C., Brai, M., Caruso, A., and Spagnolo,
B.: Environmental Metal Pollution Considered as Noise: Effects on the Spatial
Distribution of Benthic Foraminifera in two Coastal Marine Areas of Sicily
(Southern Italy), Ecol. Model., 213, 449–462,
https://doi.org/10.1016/j.ecolmodel.2008.01.023, 2008. a
Valenti, D., Denaro, G., La Cognata, A., Spagnolo, B., Bonanno, A., Mazzola,
S., Zgozi, S., and Aronica, S.: Picophytoplankton dynamics in noisy marine
environment, Acta Phys. Pol. B, 43, 1227–1240,
https://doi.org/10.5506/APhysPolB.43.1227, 2012. a, b, c
Valenti, D., Denaro, G., Conversano, F., Brunet, C., Bonanno, A., Basilone, G.,
Mazzola, S., and Spagnolo, B.: The role of noise on the steady state
distributions of phytoplankton populations, J. Stat. Mech., 2016, 054044,
https://doi.org/10.1088/1742-5468/2016/05/054044, 2016a. a, b, c, d
Valenti, D., Denaro, G., Spagnolo, B., Mazzola, S., Basilone, G., Conversano,
F., Brunet, C., and Bonanno, A.: Stochastic models for phytoplankton dynamics
in Mediterranean Sea, Ecol. Complex., 27, 84–103,
https://doi.org/10.1016/j.ecocom.2015.06.001, 2016b. a, b, c, d
Valenti, D., Giuffrida, A., Denaro, G., Pizzolato, N., Curcio, L., Mazzola, S.,
Basilone, G., Bonanno, A., and Spagnolo, B.: Noise Induced Phenomena in the
Dynamics of Two Competing Species, Math. Model. Nat. Pheno., 11,
158–174, https://doi.org/10.1051/mmnp/201611510, 2016c.
a, b, c
Valenti, D., Denaro, G., Ferreri, R., Genovese, S., Aronica, S., Mazzola, S.,
Bonanno, A., Basilone, G., and Spagnolo, B.: Spatio-temporal dynamics of a
planktonic system and chlorophyll distribution in a 2D spatial domain:
matching model and data, Sci. Rep., 7, 220,
https://doi.org/10.1038/s41598-017-00112-z, 2017. a, b, c, d, e, f, g, h
Williams, J. J., Dutton, J., Chen, C. Y., and Fischer, N. S.: Metal (As, Cd,
Hg, and CH3Hg) bioaccumulation from water and food by the benthic amphypod
Leptocheirus Plumulosus, Environ. Toxicol. Chem., 29, 1755–1761,
https://doi.org/10.1002/etc.207, 2010. a, b
Yakushev, E. V., Protsenko, E. A., Bruggeman, J., Wallhead, P., Pakhomova, S. V., Yakubov, S. Kh., Bellerby, R. G. J., and Couture, R.-M.: Bottom RedOx Model (BROM v.1.1): a coupled benthic–pelagic model for simulation of water and sediment biogeochemistry, Geosci. Model Dev., 10, 453–482, https://doi.org/10.5194/gmd-10-453-2017, 2017. a, b
Zagar, D., Petkovsek, G., Rajar, R., Sirnik, N., Horvat, M., Voudouri, A.,
Kallos, G., and Cetina, M.: Modelling of mercury transport and
transformations in the water compartment of the Mediterranean Sea, Mar.
Chem., 107, 64–88, https://doi.org/10.1016/j.marchem.2007.02.007,
2007. a, b, c, d, e, f, g, h
Zagar, D., Sirnik, N., Cetina, M., Horvat, M., Kotnik, J., Ogrinc, N.,
Hedgecock, I. M., Cinnirella, S., De Simone, F., Gencarelli, C. N., and
Pirrone, N.: Mercury in the Mediterranean. Part 2: processes and mass
balance, Environ. Sci. Pollut. R., 21, 4081–4094,
https://doi.org/10.1007/s11356-013-2055-5, 2014. a
Zhu, S., Zhang, Z., and Zagar, D.: Mercury transport and fate models in aquatic
systems: A review and synthesis, Sci. Total Environ., 639, 538–549,
https://doi.org/10.1016/j.scitotenv.2018.04.397, 2018. a
Short summary
The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in seawater and marine sediments, of three mercury species (elemental, inorganic, and organic mercury) in a highly polluted marine environment (Augusta Bay, southern Italy). The model shows fair agreement with the experimental data collected during six different oceanographic cruises and can possibly be used for a detailed exploration of the effects of climate change on mercury distribution.
The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in...