Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2571-2019
© Author(s) 2019. 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-12-2571-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
28 Jun 2019
Methods for assessment of models |
| 28 Jun 2019
Quantitative stratigraphic analysis in a source-to-sink numerical framework
Basin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia
Tristan Salles
Basin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia
Nicolas Flament
School of Earth and Environmental Science, University of Wollongong, Wollongong, NSW 2522, Australia
Patrice Rey
Basin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia
Related authors
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
EGUsphere, https://doi.org/10.5194/egusphere-2023-53, https://doi.org/10.5194/egusphere-2023-53, 2023
Short summary
Short summary
Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea-level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport and sea-level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
Thomas Frasson, Stéphane Labrosse, Henri-Claude Nataf, Nicolas Coltice, and Nicolas Flament
EGUsphere, https://doi.org/10.5194/egusphere-2023-1782, https://doi.org/10.5194/egusphere-2023-1782, 2023
Short summary
Short summary
Heat flux heterogeneities at the bottom of Earth's mantle plays an important role in the dynamic of the underlying core. Here, we study how these heterogeneities are affected by the global rotation of the Earth called true polar wander (TPW), which has to be considered to relate mantle dynamics with core dynamics. We find that TPW can greatly modify the large scales of the heat flux heterogeneities, notably at short time scales. We provide representative maps of these heterogeneities.
Carole Petit, Tristan Salles, Vincent Godard, Yann Rolland, and Laurence Audin
Earth Surf. Dynam., 11, 183–201, https://doi.org/10.5194/esurf-11-183-2023, https://doi.org/10.5194/esurf-11-183-2023, 2023
Short summary
Short summary
We present new tools in the landscape evolution model Badlands to simulate 10Be production, erosion and transport. These tools are applied to a source-to-sink system in the SW French Alps, where the model is calibrated. We propose a model that fits river incision rates and 10Be concentrations in sediments, and we show that 10Be in deep marine sediments is a signal with multiple contributions that cannot be easily interpreted in terms of climate forcing.
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
EGUsphere, https://doi.org/10.5194/egusphere-2023-53, https://doi.org/10.5194/egusphere-2023-53, 2023
Short summary
Short summary
Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea-level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport and sea-level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
R. Dietmar Müller, Nicolas Flament, John Cannon, Michael G. Tetley, Simon E. Williams, Xianzhi Cao, Ömer F. Bodur, Sabin Zahirovic, and Andrew Merdith
Solid Earth, 13, 1127–1159, https://doi.org/10.5194/se-13-1127-2022, https://doi.org/10.5194/se-13-1127-2022, 2022
Short summary
Short summary
We have built a community model for the evolution of the Earth's plate–mantle system. Created with open-source software and an open-access plate model, it covers the last billion years, including the formation, breakup, and dispersal of two supercontinents, as well as the creation and destruction of numerous ocean basins. The model allows us to
seeinto the Earth in 4D and helps us unravel the connections between surface tectonics and the
beating heartof the Earth, its convecting mantle.
Claire A. Mallard and Tristan Salles
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-89, https://doi.org/10.5194/esurf-2021-89, 2021
Preprint withdrawn
Short summary
Short summary
Using landscape evolution models integrating mantle dynamics, climate, eustatism and surface processes, we break down a previous idea that considers mantle flow as the main driver of the pulse of sedimentation in the Orange Basin, SA, over the last 30 Ma. Instead, climate impact seems to be a predominant mechanism. We also show that sediment flux and landscape evolution in the region is the product of interlinked processes accounting for both lithology variations, mantle dynamics and climate.
Gilles Brocard, Jane Kathrin Willenbring, Tristan Salles, Michael Cosca, Axel Guttiérez-Orrego, Noé Cacao Chiquín, Sergio Morán-Ical, and Christian Teyssier
Earth Surf. Dynam., 9, 795–822, https://doi.org/10.5194/esurf-9-795-2021, https://doi.org/10.5194/esurf-9-795-2021, 2021
Short summary
Short summary
The rise of a mountain affects the circulation of water, both in the atmosphere and over the land surface, thereby affecting the erosion of the land surface. We document how the rise of a mountain in central Guatemala has affected the erosion of an older range nearby. The new range intercepts precipitation formerly delivered to the older range. River response to the uplift of the new range has decreased incision across the older one. Both have reduced hillslope erosion over the old range.
Ömer F. Bodur and Patrice F. Rey
Solid Earth, 10, 2167–2178, https://doi.org/10.5194/se-10-2167-2019, https://doi.org/10.5194/se-10-2167-2019, 2019
Short summary
Short summary
Convection in the deep Earth dynamically changes the elevation of plates. Amplitudes of those vertical motions predicted from numerical models are significantly higher than observations. We find that at small wavelengths (< 1000 km) this misfit can be due to the oversimplification in viscosity of rocks. By a suite of numerical experiments, we show that considering the non–Newtonian rheology of the mantle results in predictions in amplitude of dynamic topography consistent with observations.
Tristan Salles, Patrice Rey, and Enrico Bertuzzo
Earth Surf. Dynam., 7, 895–910, https://doi.org/10.5194/esurf-7-895-2019, https://doi.org/10.5194/esurf-7-895-2019, 2019
Short summary
Short summary
Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Tristan Salles
Geosci. Model Dev., 12, 4165–4184, https://doi.org/10.5194/gmd-12-4165-2019, https://doi.org/10.5194/gmd-12-4165-2019, 2019
Short summary
Short summary
This paper presents a new numerical model able to simulate for the first time the evolution of Earth's surface at a global scale under different precipitation, sea level, and tectonic conditions. This is significant as it can help to bridge the gap between local- and global-scale predictions of Earth's past and future variations.
Tristan Salles, Jodie Pall, Jody M. Webster, and Belinda Dechnik
Geosci. Model Dev., 11, 2093–2110, https://doi.org/10.5194/gmd-11-2093-2018, https://doi.org/10.5194/gmd-11-2093-2018, 2018
Short summary
Short summary
We present a 1-D model of coral reefs' evolution over centennial to millennial timescales. The model enables us to estimate the effects of environmental conditions (such as oceanic variability, sedimentation rate, sea-level fluctuations or tectonics) and ecological coral competition on reef vertical accretion and stratigraphic succession. The tool can quantitatively test carbonate platform development and efficiently interpret vertical growth under various forcing scenarios.
Wenchao Cao, Sabin Zahirovic, Nicolas Flament, Simon Williams, Jan Golonka, and R. Dietmar Müller
Biogeosciences, 14, 5425–5439, https://doi.org/10.5194/bg-14-5425-2017, https://doi.org/10.5194/bg-14-5425-2017, 2017
Short summary
Short summary
We present a workflow to link paleogeographic maps to alternative plate tectonic models, alleviating the problem that published global paleogeographic maps are generally presented as static maps and tied to a particular plate model. We further develop an approach to improve paleogeography using paleobiology. The resulting paleogeographies are consistent with proxies of eustatic sea level change since ~400 Myr ago. We make the digital global paleogeographic maps available as an open resource.
Nicholas Barnett-Moore, Rakib Hassan, Nicolas Flament, and Dietmar Müller
Solid Earth, 8, 235–254, https://doi.org/10.5194/se-8-235-2017, https://doi.org/10.5194/se-8-235-2017, 2017
Short summary
Short summary
We use 3D mantle flow models to investigate the evolution of the Iceland plume in the North Atlantic. Results show that over the last ~ 100 Myr a remarkably stable pattern of flow in the lowermost mantle beneath the region resulted in the formation of a plume nucleation site. At the surface, a model plume compared to published observables indicates that its large plume head, ~ 2500 km in diameter, arriving beneath eastern Greenland in the Palaeocene, can account for the volcanic record and uplift.
Related subject area
Climate and Earth system modeling
The Canadian Atmospheric Model version 5 (CanAM5.0.3)
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Simulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wiso
Rainbows and climate change: a tutorial on climate model diagnostics and parameterization
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications
IceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learning
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model
The Regional Aerosol Model Intercomparison Project (RAMIP)
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change
Recalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?
Description and evaluation of the JULES-ES set-up for ISIMIP2b
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Modeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regression
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
A new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Deep learning for stochastic precipitation generation – deep SPG v1.0
Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress
Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0
The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
SMLFire1.0: a stochastic machine learning (SML) model for wildfire activity in the western United States
LandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources
Conservation of heat and mass in P-SKRIPS version 1: the coupled atmosphere–ice–ocean model of the Ross Sea
Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53
Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System: RRTMGP-NN 2.0
Differentiable programming for Earth system modeling
Evaluation of CMIP6 model performances in simulating fire weather spatiotemporal variability on global and regional scales
Data-driven aeolian dust emission scheme for climate modelling evaluated with EMAC 2.55.2
Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning
An improved method of the Globally Resolved Energy Balance model by the Bayesian networks
Assessing predicted cirrus ice properties between two deterministic ice formation parameterizations
Various ways of using empirical orthogonal functions for climate model evaluation
C-Coupler3.0: an integrated coupler infrastructure for Earth system modelling
FEOTS v0.0.0: a new offline code for the fast equilibration of tracers in the ocean
Pace v0.2: a Python-based performance-portable atmospheric model
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water
The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework
The analysis of large-volume multi-institute climate model output at a Central Analysis Facility (PRIMAVERA Data Management Tool V2.10)
Structural k-means (S k-means) and clustering uncertainty evaluation framework (CUEF) for mining climate data
The emergence of the Gulf Stream and interior western boundary as key regions to constrain the future North Atlantic carbon uptake
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
Short summary
Short summary
The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
Short summary
Short summary
Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382, https://doi.org/10.5194/gmd-16-5365-2023, https://doi.org/10.5194/gmd-16-5365-2023, 2023
Short summary
Short summary
This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
Short summary
Short summary
Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
Short summary
Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
Short summary
Short summary
A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
Short summary
Short summary
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
Short summary
Short summary
Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
Short summary
Short summary
Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
Short summary
Short summary
To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
Short summary
Short summary
The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616, https://doi.org/10.5194/gmd-16-4599-2023, https://doi.org/10.5194/gmd-16-4599-2023, 2023
Short summary
Short summary
This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519, https://doi.org/10.5194/gmd-16-4501-2023, https://doi.org/10.5194/gmd-16-4501-2023, 2023
Short summary
Short summary
How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
Short summary
Short summary
Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366, https://doi.org/10.5194/gmd-16-4331-2023, https://doi.org/10.5194/gmd-16-4331-2023, 2023
Short summary
Short summary
This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
Short summary
Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329, https://doi.org/10.5194/gmd-16-4315-2023, https://doi.org/10.5194/gmd-16-4315-2023, 2023
Short summary
Short summary
A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
Short summary
Short summary
This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247, https://doi.org/10.5194/gmd-16-4233-2023, https://doi.org/10.5194/gmd-16-4233-2023, 2023
Short summary
Short summary
Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136, https://doi.org/10.5194/gmd-16-4113-2023, https://doi.org/10.5194/gmd-16-4113-2023, 2023
Short summary
Short summary
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112, https://doi.org/10.5194/gmd-16-4083-2023, https://doi.org/10.5194/gmd-16-4083-2023, 2023
Short summary
Short summary
Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
Short summary
Short summary
Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
Short summary
Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
Short summary
Short summary
A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
Short summary
Short summary
Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
Short summary
Short summary
Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
Short summary
Short summary
This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Jatan Buch, A. Park Williams, Caroline S. Juang, Winslow D. Hansen, and Pierre Gentine
Geosci. Model Dev., 16, 3407–3433, https://doi.org/10.5194/gmd-16-3407-2023, https://doi.org/10.5194/gmd-16-3407-2023, 2023
Short summary
Short summary
We leverage machine learning techniques to construct a statistical model of grid-scale fire frequencies and sizes using climate, vegetation, and human predictors. Our model reproduces the observed trends in fire activity across multiple regions and timescales. We provide uncertainty estimates to inform resource allocation plans for fuel treatment and fire management. Altogether the accuracy and efficiency of our model make it ideal for coupled use with large-scale dynamical vegetation models.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev., 16, 3375–3406, https://doi.org/10.5194/gmd-16-3375-2023, https://doi.org/10.5194/gmd-16-3375-2023, 2023
Short summary
Short summary
We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent so that users can make their own decisions on how to resolve these should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Alena Malyarenko, Alexandra Gossart, Rui Sun, and Mario Krapp
Geosci. Model Dev., 16, 3355–3373, https://doi.org/10.5194/gmd-16-3355-2023, https://doi.org/10.5194/gmd-16-3355-2023, 2023
Short summary
Short summary
Simultaneous modelling of ocean, sea ice, and atmosphere in coupled models is critical for understanding all of the processes that happen in the Antarctic. Here we have developed a coupled model for the Ross Sea, P-SKRIPS, that conserves heat and mass between the ocean and sea ice model (MITgcm) and the atmosphere model (PWRF). We have shown that our developments reduce the model drift, which is important for long-term simulations. P-SKRIPS shows good results in modelling coastal polynyas.
Feijia Yin, Volker Grewe, Federica Castino, Pratik Rao, Sigrun Matthes, Katrin Dahlmann, Simone Dietmüller, Christine Frömming, Hiroshi Yamashita, Patrick Peter, Emma Klingaman, Keith P. Shine, Benjamin Lührs, and Florian Linke
Geosci. Model Dev., 16, 3313–3334, https://doi.org/10.5194/gmd-16-3313-2023, https://doi.org/10.5194/gmd-16-3313-2023, 2023
Short summary
Short summary
This paper describes a newly developed submodel ACCF V1.0 based on the MESSy 2.53.0 infrastructure. The ACCF V1.0 is based on the prototype algorithmic climate change functions (aCCFs) v1.0 to enable climate-optimized flight trajectories. One highlight of this paper is that we describe a consistent full set of aCCFs formulas with respect to fuel scenario and metrics. We demonstrate the usage of the ACCF submodel using AirTraf V2.0 to optimize trajectories for cost and climate impact.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
Short summary
Short summary
Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
Geosci. Model Dev., 16, 3123–3135, https://doi.org/10.5194/gmd-16-3123-2023, https://doi.org/10.5194/gmd-16-3123-2023, 2023
Short summary
Short summary
Differential programming is a technique that enables the automatic computation of derivatives of the output of models with respect to model parameters. Applying these techniques to Earth system modeling leverages the increasing availability of high-quality data to improve the models themselves. This can be done by either using calibration techniques that use gradient-based optimization or incorporating machine learning methods that can learn previously unresolved influences directly from data.
Carolina Gallo, Jonathan M. Eden, Bastien Dieppois, Igor Drobyshev, Peter Z. Fulé, Jesús San-Miguel-Ayanz, and Matthew Blackett
Geosci. Model Dev., 16, 3103–3122, https://doi.org/10.5194/gmd-16-3103-2023, https://doi.org/10.5194/gmd-16-3103-2023, 2023
Short summary
Short summary
This study conducts the first global evaluation of the latest generation of global climate models to simulate a set of fire weather indicators from the Canadian Fire Weather Index System. Models are shown to perform relatively strongly at the global scale, but they show substantial regional and seasonal differences. The results demonstrate the value of model evaluation and selection in producing reliable fire danger projections, ultimately to support decision-making and forest management.
Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 16, 3013–3028, https://doi.org/10.5194/gmd-16-3013-2023, https://doi.org/10.5194/gmd-16-3013-2023, 2023
Short summary
Short summary
Desert dust has significant impacts on climate, public health, infrastructure and ecosystems. An impact assessment requires numerical predictions, which are challenging because the dust emissions are not well known. We present a novel approach using satellite observations and machine learning to more accurately estimate the emissions and to improve the model simulations.
Anna Denvil-Sommer, Erik T. Buitenhuis, Rainer Kiko, Fabien Lombard, Lionel Guidi, and Corinne Le Quéré
Geosci. Model Dev., 16, 2995–3012, https://doi.org/10.5194/gmd-16-2995-2023, https://doi.org/10.5194/gmd-16-2995-2023, 2023
Short summary
Short summary
Using outputs of global biogeochemical ocean model and machine learning methods, we demonstrate that it will be possible to identify linkages between surface environmental and ecosystem structure and the export of carbon to depth by sinking organic particles using real observations. It will be possible to use this knowledge to improve both our understanding of ecosystem dynamics and of their functional representation within models.
Zhenxia Liu, Zengjie Wang, Jian Wang, Zhengfang Zhang, Dongshuang Li, Zhaoyuan Yu, Linwang Yuan, and Wen Luo
Geosci. Model Dev., 16, 2939–2955, https://doi.org/10.5194/gmd-16-2939-2023, https://doi.org/10.5194/gmd-16-2939-2023, 2023
Short summary
Short summary
This study introduces an improved method of the Globally Resolved Energy Balance (GREB) model by the Bayesian network. The improved method constructs a coarse–fine structure that combines a dynamical model with a statistical model based on employing the GREB model as the global framework and utilizing Bayesian networks as the local optimization. The results show that the improved model has better applicability and stability on a global scale and maintains good robustness on the timescale.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
Short summary
Short summary
A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
Short summary
Short summary
A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Li Liu, Chao Sun, Xinzhu Yu, Hao Yu, Qingu Jiang, Xingliang Li, Ruizhe Li, Bin Wang, Xueshun Shen, and Guangwen Yang
Geosci. Model Dev., 16, 2833–2850, https://doi.org/10.5194/gmd-16-2833-2023, https://doi.org/10.5194/gmd-16-2833-2023, 2023
Short summary
Short summary
C-Coupler3.0 is an integrated coupler infrastructure with new features, i.e. a series of parallel-optimization technologies, a common halo-exchange library, a common module-integration framework, a common framework for conveniently developing a weakly coupled ensemble data assimilation system, and a common framework for flexibly inputting and outputting fields in parallel. It is able to handle coupling under much finer resolutions (e.g. more than 100 million horizontal grid cells).
Joseph Schoonover, Wilbert Weijer, and Jiaxu Zhang
Geosci. Model Dev., 16, 2795–2809, https://doi.org/10.5194/gmd-16-2795-2023, https://doi.org/10.5194/gmd-16-2795-2023, 2023
Short summary
Short summary
FEOTS aims to enhance the value of data produced by state-of-the-art climate models by providing a framework to diagnose and use ocean transport operators for offline passive tracer simulations. We show that we can capture ocean transport operators from a validated climate model and employ these operators to estimate water mass budgets in an offline regional simulation, using a small fraction of the compute resources required to run a full climate simulation.
Johann Dahm, Eddie Davis, Florian Deconinck, Oliver Elbert, Rhea George, Jeremy McGibbon, Tobias Wicky, Elynn Wu, Christopher Kung, Tal Ben-Nun, Lucas Harris, Linus Groner, and Oliver Fuhrer
Geosci. Model Dev., 16, 2719–2736, https://doi.org/10.5194/gmd-16-2719-2023, https://doi.org/10.5194/gmd-16-2719-2023, 2023
Short summary
Short summary
It is hard for scientists to write code which is efficient on different kinds of supercomputers. Python is popular for its user-friendliness. We converted a Fortran code, simulating Earth's atmosphere, into Python. This new code auto-converts to a faster language for processors or graphic cards. Our code runs 3.5–4 times faster on graphic cards than the original on processors in a specific supercomputer system.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
EGUsphere, https://doi.org/10.5194/egusphere-2023-549, https://doi.org/10.5194/egusphere-2023-549, 2023
Short summary
Short summary
The present paper introduces a floodplains scheme for a high resolution Land Surface Model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land atmosphere fluxes and highlights the potential impact of floodplains on land-atmosphere interactions and the importance of integrating this module in coupled simulations.
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottlé, and Jérôme Servonnat
Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023, https://doi.org/10.5194/gmd-16-2583-2023, 2023
Short summary
Short summary
The proposed graphs of hydrological sub-grid elements for atmospheric models allow us to integrate the topographical elements needed in land surface models for a realistic representation of horizontal water and energy transport. The study demonstrates the numerical properties of the automatically built graphs and the simulated water flows.
Magnus Hieronymus
Geosci. Model Dev., 16, 2343–2354, https://doi.org/10.5194/gmd-16-2343-2023, https://doi.org/10.5194/gmd-16-2343-2023, 2023
Short summary
Short summary
A statistical model called the sea level simulator is presented and made freely available. The sea level simulator integrates mean sea level rise and sea level extremes into a joint probabilistic framework that is useful for flood risk estimation. These flood risk estimates are contingent on probabilities given to different emission scenarios and the length of the planning period. The model is also useful for uncertainty quantification and in decision and adaptation problems.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-46, https://doi.org/10.5194/gmd-2023-46, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a Central Analysis Facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large data set. We believe that similar, multi institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Quang-Van Doan, Toshiyuki Amagasa, Thanh-Ha Pham, Takuto Sato, Fei Chen, and Hiroyuki Kusaka
Geosci. Model Dev., 16, 2215–2233, https://doi.org/10.5194/gmd-16-2215-2023, https://doi.org/10.5194/gmd-16-2215-2023, 2023
Short summary
Short summary
This study proposes (i) the structural k-means (S k-means) algorithm for clustering spatiotemporally structured climate data and (ii) the clustering uncertainty evaluation framework (CUEF) based on the mutual-information concept.
Nadine Goris, Klaus Johannsen, and Jerry Tjiputra
Geosci. Model Dev., 16, 2095–2117, https://doi.org/10.5194/gmd-16-2095-2023, https://doi.org/10.5194/gmd-16-2095-2023, 2023
Short summary
Short summary
Climate projections of a high-CO2 future are highly uncertain. A new study provides a novel approach to identifying key regions that dynamically explain the model uncertainty. To yield an accurate estimate of the future North Atlantic carbon uptake, we find that a correct simulation of the upper- and interior-ocean volume transport at 25–30° N is key. However, results indicate that models rarely perform well for both indicators and point towards inconsistencies within the model ensemble.
Cited articles
Abreu, V., Pederson, K., Neal, J., and Bohacs, K.: A simplified guide for sequence stratigraphy: nomenclature, definitions and method, in: William Smith Meeting, 22–23 September 2014, The Geological Society, Burlington House, London, Paper number: 4, 2014. a
Ainsworth, B. R., McArthur, J. B., Lang, S. C., and Vonk, A. J.: Quantitative
sequence stratigraphy, AAPG Bull., 102, 1913–1939, 2018. a
Bond, G. C., Kominz, M. A., Steckler, M. S., and Grotzinger, J. P.: Role of thermal subsidence, flexure, and eustasy in the evolution of early Paleozoic passive-margin carbonate platforms, in: Controls on Carbonate Platform and Basin Development, SEPM, Special Publication, 44, 39–61, 1989. a
Braun, J.: The many surface expressions of mantle dynamics, Nat. Geosci., 3, 825–833, 2010. a
Burgess, P. M. and Gurnis, M.: Mechanisms for the formation of cratonic stratigraphic sequences, Earth Planet. Sc. Lett., 136, 647–663, 1995. a
Burgess, P. M. and Prince, G. D.: Non-unique stratal geometries: implications for sequence stratigraphic interpretations, Basin Res., 27, 351–365, 2015. a
Burgess, P. M., Gurnis, M., and Moresi, L.: Formation of sequences in the cratonic interior of North America by interaction between mantle, eustatic, and stratigraphic processes, Geol. Soc. Am. Bull., 109, 1515–1535, 1997. a
Carvajal, C. and Steel, R.: Shelf-edge architecture and bypass of sand to deep water: influence of shelf-edge processes, sea level, and sediment supply, J. Sediment. Res., 79, 652–672, 2009. a
Catuneanu, O., Abreu, V., Bhattacharya, J., Blum, M., Dalrymple, R., Eriksson, P., Fielding, C. R., Fisher, W., Galloway, W., Gibling, M., Giles, K. A., Holbrook, J. M., Jordan, R., Kendall C. G. St. C., Macurda, B., Martinsen, O. J., Miall, A. D., Neal, J. E., Nummedal, D., Pomar, L., Posamentier, H. W., Pratt, B. R., Sarg, J. F.,
Shanley, K. W., Steel, R. J., Strasser, A., Tucker, M. E., and Winker, C.: Towards the standardization of sequence stratigraphy, Earth-Sci. Rev., 92, 1–33, 2009. a
Csato, I., Catuneanu, O., and Granjeon, D.: Millennial-scale sequence stratigraphy: numerical simulation with Dionisos, J. Sediment. Res., 84, 394–406, 2014. a
Flament, N., Gurnis, M., and Müller, R. D.: A review of observations and
models of dynamic topography, Lithosphere, 5, 189–210, 2013. a
Galloway, W. E.: Genetic stratigraphic sequences in basin analysis I:
architecture and genesis of flooding-surface bounded depositional units, AAPG
Bull., 73, 125–142, 1989. a
Granjeon, D., Martinius, A., Ravnas, R., Howell, J., Steel, R., and Wonham, J.: 3D forward modelling of the impact of sediment transport and base level
cycles on continental margins and incised valleys, Depositional Systems to
Sedimentary Successions on the Norwegian Continental Margin: International
Association of Sedimentologists, Special Publication, 46, 453–472, 2014. a, b
Harris, A. D., Carvajal, C., Covault, J., Perlmutter, M., and Sun, T.: Numerical stratigraphic modeling of climatic controls on basin-scale sedimentation, in: AAPG Annual Convention and Exhibition, 31 May–3 June 2015, Denver, Colorado, USA, 2015. a
Harris, A. D., Covault, J. A., Madof, A. S., Sun, T., Sylvester, Z., and Granjeon, D.: Three-dimensional numerical modeling of eustatic control on continental-margin sand distribution, J. Sediment. Res., 86, 1434–1443, 2016. a
Jervey, M.: Quantitative geological modeling of siliciclastic rock sequences
and their seismic expression, Spec. Publ. SEPM, 42, 47–69, 1988. a
Jordan, T. and Flemings, P.: Large-scale stratigraphic architecture, eustatic variation, and unsteady tectonism: A theoretical evaluation, J. Geophys. Res., 96, 6681–6699, 1991. a
Kim, W.: Decoupling allogenic and autogenic processes in experimental stratigraphy, AGU Fall Meeting Abstracts, EP53A-0609, 2009. a
Kim, W., Paola, C., Voller, V. R., and Swenson, J. B.: Experimental measurement of the relative importance of controls on shoreline migration, J. Sediment. Res., 76, 270–283, 2006. a
Li, Q., Gasparini, N. M., and Straub, K. M.: Some signals are not the same as they appear: How do erosional landscapes transform tectonic history into sediment flux records?, Geology, 46, 407–410, https://doi.org/10.1130/G40026.1, 2018. a
Miall, A. D.: Empiricism and model building in stratigraphy: the historical
roots of present-day practices, Stratigraphy, 1, 3–25, 2004. a
Mitchum Jr., R. M.: Seismic stratigraphy and global changes of sea level: Part 11. Glossary of terms used in seismic stratigraphy: Section 2. Application of seismic reflection configuration to stratigraphic interpretation, Mem. Amer. Assoc. Petrol. Geol., 26, 205–212, 1977. a
Mountain, G. S., Burger, R. L., Delius, H., Fulthorpe, C. S., Austin, J. A., Goldberg, D. S., Steckler, M. S., McHugh, C. M., Miller, K. G., Monteverde, D. H., Orange, D. L., and Pratson, L. F.: The long-term stratigraphic record on continental margins, Continental margin sedimentation: From sediment transport to sequence stratigraphy: International Association of Sedimentologists Special Publication, 37, 381–458, 2007. a
Muto, T. and Steel, R. J.: Principles of regression and transgression: the nature of the interplay between accommodation and sediment supply: perspectives, J. Sediment. Res., 67, 994–1000, 1997. a
Muto, T., Steel, R. J., and Burgess, P. M.: Contributions to sequence stratigraphy from analogue and numerical experiments, J. Geol. Soc. London, 173, 837–844, 2016. a
Paola, C.: Quantitative models of sedimentary basin filling, Sedimentology, 47, 121–178, 2000. a
Paola, C., Straub, K., Mohrig, D., and Reinhardt, L.: The “unreasonable effectiveness” of stratigraphic and geomorphic experiments, Earth-Sci. Rev., 97, 1–43, 2009. a
Patruno, S., Hampson, G. J., and Jackson, C. A.: Quantitative characterisation of deltaic and subaqueous clinoforms, Earth-Sci. Rev., 142, 79–119, 2015. a
Payton, C. E. et al.: Seismic stratigraphy: applications to hydrocarbon exploration, American Association of Petroleum Geologists Tulsa, OK, 26, 1–516, 1977. a
Pitman, W. C.: Relationship between eustacy and stratigraphic sequences of passive margins, GSA Bulletin, 89, 1389–1403, 1978. a
Posamentier, H. and Vail, P.: Eustatic controls on clastic deposition II – Sequence and systems tract models, in: Sea-Level Changes: an Integrated Approach, edited by: Wilgus, C. K., Hastings, B. S.,
Posamentier, H., Van Wagoner, J., Ross, C. A., and St. C. Kendall, C. G., Spec. Publ. Soc. Econ. Paleont. Miner., 42, 125–154, 1988. a
Posamentier, H., Jervey, M., and Vail, P.: Eustatic controls on clastic deposition I – Conceptual frameworks, in: Sea-Level Changes: an Integrated Approach, edited by:
Wilgus, C. K., Hastings, B. S., St. C. Kendall, C. G., Posamentier, H. W., Ross, C. A., and Van Wagoner, J. C., Spec. Publ. Soc. Econ. Paleont. Miner., 42, 109–124, 1988. a
Posamentier, H. W., Allen, G. P., James, D. P., and Tesson, M.: Forced regressions in a sequence stratigraphic framework: concepts, examples, and exploration significance (1), AAPG bulletin, 76, 1687–1709, 1992. a
Reynolds, D. J., Steckler, M. S., and Coakley, B. J.: The role of the sediment load in sequence stratigraphy: The influence of flexural isostasy and compaction, J. Geophys. Res., 96, 6931–6949, 1991. a
Rouby, D., Braun, J., Robin, C., Dauteuil, O., and Deschamps, F.: Long-term
stratigraphic evolution of Atlantic-type passive margins: A numerical
approach of interactions between surface processes, flexural isostasy and 3D thermal subsidence, Tectonophysics, 604, 83–103, 2013. a
Ruetenik, G. A., Moucha, R., and Hoke, G. D.: Landscape response to changes in dynamic topography, Terra Nova, 28, 289–296, https://doi.org/10.1111/ter.12220, 2016. a
Salles, T.: Badlands: A parallel basin and landscape dynamics model, SoftwareX, 5, 195–202, 2016. a
Salles, T. and Hardiman, L.: Badlands: An open-source, flexible and parallel framework to study landscape dynamics, Comput. Geosci., 91, 77–89, 2016. a
Salles, T., Flament, N., and Müller, D.: Influence of mantle flow on the
drainage of eastern Australia since the Jurassic Period, Geochem. Geophy. Geosy., 18, 280–305, 2017. a
Salles, T., Ding, X., and Brocard, G.: pyBadlands: A framework to simulate
sediment transport, landscape dynamics and basin stratigraphic evolution
through space and time, PloS one, 13, e0195557, https://doi.org/10.1371/journal.pone.0195557, 2018. a
Schlager, W.: Accommodation and supply – a dual control on stratigraphic sequences, Sediment. Geol., 86, 111–136, 1993. a
Steckler, M., Reynolds, D., Coakley, B., Swift, B., and Jarrard, R.: Modelling passive margin sequence stratigraphy, in: Sequence stratigraphy and facies associations, edited by: Posamentier, H. W., Summerhayes, C. P., Haq, B. U., and Allen, G. P., International Association of Sedimentologists Special Publication 18, Blackwell Sientific Publications, Oxford, UK, 19–41, 1993. a, b
Sylvester, Z., Cantelli, A., and Pirmez, C.: Stratigraphic evolution of
intraslope minibasins: Insights from surface-based model, AAPG Bulletin, 99, 1099–1129, 2015. a
Vail, P. R., Mitchum Jr., R., and Thompson III, S.: Seismic stratigraphy and
global changes of sea level: Part 3. Relative changes of sea level from
coastal onlap: section 2. Application of seismic reflection configuration to stratigrapic interpretation, Mem. Amer. Assoc. Petrol. Geol., 26, 63–81, 1977a. a
van der Beek, P., Andriessen, P., and Cloetingh, S.: Morphotectonic evolution
of rifted continental margins: Inferences from a coupled tectonic-surface
processes model and fission track thermochronology, Tectonics, 14, 406–421, 1995. a
Van Heijst, M., Postma, G., Meijer, X., Snow, J., and Anderson, J.: Quantitative analogue flume-model study of river-shelf systems: principles and verification exemplified by the Late Quaternary Colorado river-delta evolution, Basin Res., 13, 243–268, 2001. a
Watts, A. and Steckler, M.: Subsidence and eustasy at the continental margin of eastern North America, in: Deep Drilling Results in the Atlantic Ocean: Continental Margins and Paleoenvironment, edited by: Talwani, M., Hay, W., and Ryan, W. B., AGU, 3, 218–234, 1979. a
Short summary
This work introduced a quantitative stratigraphic framework within a source-to-sink numerical code, pyBadlands, and evaluated two stratigraphic interpretation techniques. This quantitative framework allowed us to quickly construct the strata formations and automatically produce strata interpretations. We further showed that the accommodation succession method, compared with the trajectory analysis method, provided more reliable interpretations as it is independent of time-dependent processes.
This work introduced a quantitative stratigraphic framework within a source-to-sink numerical...
