Geoscientific Model Development

Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, 2024
We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.

Numerical stabilization methods for level-set-based ice front migration
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, 2024
We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.

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., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, 2024
This paper presents the experimental 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.

Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, 2024
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.

PIBM 1.0: An individual-based model for simulating phytoplankton acclimation, diversity, and evolution in the ocean
Iria Sala and Bingzhang Chen
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-130,2024
Preprint under review for GMD (discussion: open, 0 comments)
Phytoplankton, tiny photosynthetic organisms, produce nearly half of Earth's oxygen. To analyze their physiology, diversity, and evolution in the ocean, we developed a model that treats phytoplankton as individual particles. Moreover, our model considers phytoplankton size, temperature, and light traits, and allows for mutations in phytoplankton cells. Thus, our model provides a valuable tool for advancing the study of phytoplankton physiology, diversity, and evolution.

Presentation, Calibration and Testing of the DCESS II Earth System Model of Intermediate Complexity (version 1.0)
Esteban Fernández and Gary Shaffer
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-122,2024
Preprint under review for GMD (discussion: open, 0 comments)
Here we describe, calibrate and test DCESS II, a new, broad, adaptable and fast Earth System Model. DCESS II has been designed for global simulations over time scales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II should prove to be a useful, computational-friendly tool for simulations of past climates as well as for future Earth System projections.

The DOE E3SM Version 2.1: Overview and Assessment of the Impacts of Parameterized Ocean Submesoscales
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-149,2024
Preprint under review for GMD (discussion: open, 0 comments)
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.

The MESSy DWARF (based on MESSy v2.55.2)
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-117,2024
Preprint under review for GMD (discussion: open, 0 comments)
This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.

FINAM – is not a model (v1.0): a new Python-based model coupling framework
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-144,2024
Preprint under review for GMD (discussion: open, 1 comment)
This study presents FINAM ("FINAM Is Not A Model"), a new coupling framework written in Python to dynamically link independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.

Evaluation of atmospheric rivers in reanalyses and climate models in a new metrics framework
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-142,2024
Preprint under review for GMD (discussion: open, 0 comments)
1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the north and south Atlantic (south Pacific and Indian Ocean).

Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, 2024
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.

ShellSet v1.1.0 parallel dynamic neotectonic modelling: a case study using Earth5-049
Jon B. May, Peter Bird, and Michele M. C. Carafa
Geosci. Model Dev., 17, 6153–6171, https://doi.org/10.5194/gmd-17-6153-2024, 2024
ShellSet is a combination of well-known geoscience software packages. It features a simple user interface and is optimised through the addition of a grid search input option (automatically searching for optimal models within a defined N-dimensional parameter space) and the ability to run multiple models in parallel. We show that for each number of models tested there is a performance benefit to parallel running, while two examples demonstrate a use case by improving an existing global model.

A Bayesian method for predicting background radiation at environmental monitoring stations
Jens Peter K. W. Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-137,2024
Preprint under review for GMD (discussion: open, 0 comments)
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known `anomalous’ event.

Model calibration and streamflow simulations for the extreme drought event of 2018 on the Rhine River Basin using WRF-Hydro 5.2.0
Andrea L. Campoverde, Uwe Ehret, Patrick Ludwig, and Joaquim G. Pinto
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-134,2024
Preprint under review for GMD (discussion: open, 0 comments)
We looked at how well the model WRF-Hydro performed during the 2018 drought event in the River Rhine basin, even though it is typically used for floods. We used the meteorological ERA5 reanalysis dataset to simulate River Rhine’s streamflow and adjusted the model using parameters and actual discharge measurements. We focused on Lake Constance, a key part of the basin, but found issues with the model’s lake outflow simulation. By removing the lake module, we obtained more accurate results.

Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-150,2024
Preprint under review for GMD (discussion: open, 0 comments)
As the health impact of ultrafine particles is better understood, modeling the size distribution and the number concentration becomes increasingly important. A new analytic formulation is presented to compute coagulation partition coefficients, allowing to lower down the numerical diffusion associated to the resolution of aerosol dynamics. The significance of this effect is assessed over Greater Paris with a chemistry transport model, using different size resolution of the particle distribution.

Modelling chemical advection during magma ascent
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024, 2024
Predicting the behaviour of magmatic systems is important for understanding Earth's matter and heat transport. Numerical modelling is a technique that can predict complex systems at different scales of space and time by solving equations using various techniques. This study tests four algorithms to find the best way to transport the melt composition. The "weighted essentially non-oscillatory" algorithm emerges as the best choice, minimising errors and preserving system mass well.

Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, 2024
Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.

Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, 2024
A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.

A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, 2024
Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.

TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, 2024
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.