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

Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations

Tue, 12/19/2023 - 19:00
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, 2023
In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.

Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)

Tue, 12/19/2023 - 19:00
Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)
Octavi Gómez-Novell, Bruno Pace, Francesco Visini, Joanna Faure Walker, and Oona Scotti
Geosci. Model Dev., 16, 7339–7355, https://doi.org/10.5194/gmd-16-7339-2023, 2023
Knowing the rate at which earthquakes happen along active faults is crucial to characterize the hazard that they pose. We present an approach (Paleoseismic EArthquake CHronologies, PEACH) to correlate and compute seismic histories using paleoseismic data, a type of data that characterizes past seismic activity from the geological record. Our approach reduces the uncertainties of the seismic histories and overall can improve the knowledge on fault rupture behavior for the seismic hazard.

Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization

Tue, 12/19/2023 - 19:00
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, 2023
Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.

Getting the leaves right matters for estimating temperature extremes

Tue, 12/19/2023 - 16:37
Getting the leaves right matters for estimating temperature extremes
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.

Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2

Mon, 12/18/2023 - 18:56
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, 2023
Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.

Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)

Mon, 12/18/2023 - 18:56
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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.

How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?

Mon, 12/18/2023 - 18:56
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-209,2023
Preprint under review for GMD (discussion: open, 0 comments)
This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.

RCEMIP-II: Mock-Walker Simulations as Phase II of the Radiative-Convective Equilibrium Model Intercomparison Project

Mon, 12/18/2023 - 18:56
RCEMIP-II: Mock-Walker Simulations as Phase II of the Radiative-Convective Equilibrium Model Intercomparison Project
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-235,2023
Preprint under review for GMD (discussion: open, 6 comments)
This paper presents the experiment design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.

Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods

Fri, 12/15/2023 - 18:56
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, 2023
This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.

Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1

Fri, 12/15/2023 - 18:56
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-202,2023
Preprint under review for GMD (discussion: open, 0 comments)
Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.

A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes

Thu, 12/14/2023 - 15:39
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, 2023
The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.

RoadSurf 1.1: open-source road weather model library

Thu, 12/14/2023 - 15:39
RoadSurf 1.1: open-source road weather model library
Virve Eveliina Karsisto
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-175,2023
Preprint under review for GMD (discussion: open, 0 comments)
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities to do salting and ploughing operations at the right time and to keep roads safe for drivers.

The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations

Tue, 12/12/2023 - 19:05
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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 simple way.

Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections

Mon, 12/11/2023 - 19:05
Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, 2023
We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.

An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields

Fri, 12/08/2023 - 19:05
An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, 2023
This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.

Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations

Fri, 12/08/2023 - 19:05
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, 2023
We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.

A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes

Thu, 12/07/2023 - 19:05
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.

HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model

Thu, 12/07/2023 - 19:05
HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-229,2023
Preprint under review for GMD (discussion: open, 0 comments)
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model, its large selection of different assimilation algorithms and its modularity with respect to the combination of different types of observations, states and parameters.

A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)

Wed, 12/06/2023 - 19:05
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, 2023
Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.

GCAM-GLORY v1.0: Representing Global Reservoir Water Storage in a Multisector Human-Earth System Model

Wed, 12/06/2023 - 19:05
GCAM-GLORY v1.0: Representing Global Reservoir Water Storage in a Multisector Human-Earth System Model
Mengqi Zhao, Thomas B. Wild, Neal T. Graham, Son Kim, Matthew Binsted, A. F. M. Kamal Chowdhury, Siwa Msangi, Pralit L. Patel, Chris R. Vernon, Hassan Niazi, Hong-Yi Li, and Guta W. Abeshu
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2023-204,2023
Preprint under review for GMD (discussion: open, 0 comments)
The Global Change Analysis Model (GCAM) simulates interactions among the world’s climate, land, energy, and water systems, but its reservoir representation is limited. We developed the GLObal Reservoir Yield (GLORY) model to provide GCAM with information on the cost to supply water based on reservoir construction costs, climate and demand conditions, and reservoir expansion potential. GLORY enhances our understanding of future reservoir capacity needs to meet human demands in a changing climate.

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