Geoscientific Model Development

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Combined list of the recent articles of the journal Geoscientific Model Development and the recent discussion forum Geoscientific Model Development Discussions
Updated: 1 day 16 hours ago

An emulation-based approach for interrogating reactive transport models

Tue, 12/05/2023 - 19:05
An emulation-based approach for interrogating reactive transport models
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, 2023
We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.

Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0

Tue, 12/05/2023 - 19:05
Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0
Jacquelyn K. Shuman, Rosie A. Fisher, Charles D. Koven, Ryan G. Knox, Lara M. Kueppers, and Chonggang Xu
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-191,2023
Preprint under review for GMD (discussion: open, 0 comments)
We adapt a fire-behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.

A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest

Tue, 12/05/2023 - 19:05
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-201,2023
Preprint under review for GMD (discussion: open, 1 comment)
In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.

Minimal variance-based outlier detection method using forward search model error in a leveling network

Tue, 12/05/2023 - 19:05
Minimal variance-based outlier detection method using forward search model error in a leveling network
Utkan Mustafa Durdağ
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-210,2023
Preprint under review for GMD (discussion: open, 1 comment)
This study introduces a novel approach to outlier detection in geodetic networks, challenging conventional and robust methods. By treating outliers as unknown parameters within the Gauss-Markov Model and exploring numerous outlier combinations, this approach prioritizes minimal variance and eliminates iteration dependencies. The Mean Success Rate (MSR) comparisons highlight its effectiveness, improving MSR by 40–45 % for multiple outliers.

Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter

Tue, 12/05/2023 - 18:55
Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter
Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-221,2023
Preprint under review for GMD (discussion: open, 1 comment)
We developed a snow assimilation system using satellite data based on a land surface model. The snow states produced by the assimilation system demonstrate high performance in all regions, including transition regions, compared to the satellite data and land model. As snow significantly influences energy and water balance at the atmosphere-land boundary, this approach allows for a more accurate prediction of atmospheric conditions by realistically representing atmosphere-land interactions.

Climate Model Downscaling in Central Asia: A Dynamical and a Neural Network Approach

Tue, 12/05/2023 - 18:55
Climate Model Downscaling in Central Asia: A Dynamical and a Neural Network Approach
Bijan Fallah, Christoph Menz, Emmanuele Russo, Paula Harder, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-227,2023
Preprint under review for GMD (discussion: open, 0 comments)
We tried to contribute to the local climate change impact study in Central Asia, a water-scarce and vulnerable region to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in Central Asia.

Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates

Mon, 12/04/2023 - 18:55
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, 2023
The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.

NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps

Fri, 12/01/2023 - 18:55
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-223,2023
Preprint under review for GMD (discussion: open, 0 comments)
Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion by either uniform erosion processes where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea level history, material properties, and the relative influence of different erosional processes.

AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing

Thu, 11/30/2023 - 17:06
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, 2023
Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.

AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity

Wed, 11/29/2023 - 18:23
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
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, 2023
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.

A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)

Wed, 11/29/2023 - 18:23
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, 2023
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.

GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling

Wed, 11/29/2023 - 17:06
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, 2023
Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.

A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)

Tue, 11/28/2023 - 16:26
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, 2023
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.

An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas

Tue, 11/28/2023 - 16:26
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
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, 2023
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.

Generalized spatiotemporally-decoupled framework for reconstructing the source of non-constant atmospheric radionuclide releases

Mon, 11/27/2023 - 19:09
Generalized spatiotemporally-decoupled framework for reconstructing the source of non-constant atmospheric radionuclide releases
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-173,2023
Preprint under review for GMD (discussion: open, 0 comments)
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge for nuclear emergency. Reconstruction via environmental observations is the only feasible way to identify the source. However, simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a strategy of spatiotemporally decoupled reconstruction that avoids these uncertainties and outperforms state-of-art methods with respect to the accuracy and uncertainty range.

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