Geoscientific Model Development

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-73,2024
Preprint under review for GMD (discussion: open, 0 comments)
Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.

Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, 2024
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.

Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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.

Multivariate adjustment of drizzle bias using machine learning in European climate projections
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, 2024
This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.

Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, 2024
We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.

StraitFlux – precise computations of water strait fluxes on various modeling grids
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, 2024
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.

Comprehensive Air Quality Model With Extensions, v7.20: Formulation and Evaluation for Ozone and Particulate Matter Over the US
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-48,2024
Preprint under review for GMD (discussion: open, 0 comments)
We describe the Comprehensive Air quality Model with extensions (CAMx) and evaluate a model simulation during 2016 over nine U.S. climate zones. For ozone, the model statistically replicates measured concentrations better than most other past models and applications. For small inhalable particulates, the model replicates concentrations consistent with most other past models and applications subject to common uncertainties associated with sources, weather, and chemical interactions.

Development of the MPAS-CMAQ Coupled System (V1.0) for Multiscale Global Air Quality Modeling
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-52,2024
Preprint under review for GMD (discussion: open, 0 comments)
This work describe how we linked meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction in a global scale. This new model scales well on high performance computing environment and performs well with respect to ground surface networks in terms of ozone and PM2.5.

EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, 2024
The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.

A general comprehensive evaluation method for cross-scale precipitation forecasts
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, 2024
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.

sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-16,2024
Preprint under review for GMD (discussion: open, 0 comments)
Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface wave driven processes. In this study, a new model sedInterFoam allows to reproduce numerically complex configurations to investigate coastal sediment transport applications dominated by surface waves and gain insight into the complex physical processes associated with breaking waves and morphodynamics.

Impact of horizontal resolution and model time step on European precipitation extremes in the OpenIFS 43r3 atmosphere model
Yingxue Liu, Joakim Kjellsson, Abhishek Savita, and Wonsun Park
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-66,2024
Preprint under review for GMD (discussion: open, 0 comments)
The impact of horizontal resolution and model time step on extreme precipitation over Europe is examined in OpenIFS. We find that the biases are reduced with increasing horizontal resolution, but not with reducing time step. The large-scale precipitation is more sensitive to the horizontal resolution, however, the convective precipitation is more sensitive to the model time step. Increasing horizontal resolution is more important for extreme precipitation simulation that reducing time step.

A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, 2024
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.

Remote sensing-based high-resolution mapping of the forest canopy height: some models are useful, but might they be even more if combined?
Nikola Besic, Nicolas Picard, Cédric Vega, Lionel Hertzog, Jean-Pierre Renaud, Fajwel Fogel, Agnès Pellissier-Tanon, Gabriel Destouet, Milena Planells-Rodriguez, and Philippe Ciais
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-95,2024
Preprint under review for GMD (discussion: open, 0 comments)
The creation of advanced mapping models for forest attributes, utilizing remote sensing data and incorporating machine or deep learning methods, has become a key area of interest in the domain of forest observation and monitoring. This paper introduces a method where we blend and collectively interpret five models dedicated to estimating forest canopy height. We achieve this through Bayesian model averaging, offering a comprehensive approach to height estimation in forest ecosystems.

Software sustainability of global impact models
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-97,2024
Preprint under review for GMD (discussion: open, 1 comment)
Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.

Short-term effects of hurricanes on nitrate-nitrogen runoff loading: a case study of Hurricane Ida using E3SM land model (v2.1)
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-70,2024
Preprint under review for GMD (discussion: open, 0 comments)
Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.

Enhanced Land Subsidence Interpolation through a Hybrid Deep Convolutional Neural Network and InSAR Time Series
Zahra Azarm, Hamid Mehrabi, and Saeed Nadi
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-15,2024
Preprint under review for GMD (discussion: open, 0 comments)
The article introduces a new method using deep CNN and PSInSAR to estimate land subsidence, addressing the limitations of traditional methods. It focuses on Isfahan province, demonstrating substantial improvement over traditional techniques. The deep CNN method showed a 70 % enhancement in subsidence prediction, with the study area experiencing over 38 cm of subsidence between 2014 and 2020.

AI-NAOS: An AI-Based Nonspherical Aerosol Optical Scheme for Chemical Weather Model GRAPES_Meso5.1/CUACE
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-51,2024
Preprint under review for GMD (discussion: open, 0 comments)
An AI-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of aerosol direct radiation effect (DRE). The AI-NAOS scheme considers BC as fractal aggregates and SD as super-spheroids, encapsulated with hygroscopic aerosols. The AI-NAOS scheme was coupled online with a chemical weather model. Real-case simulations emphasize the necessity of accurately representing nonpsherical and inhomogeneous aerosols in chemical weather models.

Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-92,2024
Preprint under review for GMD (discussion: open, 0 comments)
We explore a high-level programming model for GPU porting of NWP model codes, based on the Python domain-specific library GT4Py. We present a Python rewrite with GT4Py of the ECMWF cloud microphysics scheme and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive performance and robust execution on diverse CPU and GPU architectures. The additional advantages in terms of maintainability, productivity and readability are also highlighted.

Amending the algorithm of aerosol-radiation interaction in WRF-Chem (v4.4)
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-69,2024
Preprint under review for GMD (discussion: open, 0 comments)
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that the new method significantly changes the estimated aerosols' properties and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol-radiation interactions in models.