Articles | Volume 14, issue 10
Geosci. Model Dev., 14, 5927–5955, 2021
https://doi.org/10.5194/gmd-14-5927-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 14, 5927–5955, 2021
https://doi.org/10.5194/gmd-14-5927-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
30 Sep 2021
Model evaluation paper
| 30 Sep 2021
Performance of the Adriatic Sea and Coast (AdriSC) climate component – a COAWST V3.3-based one-way coupled atmosphere–ocean modelling suite: ocean results
Petra Pranić et al.
Related authors
Cléa Denamiel, Petra Pranić, Damir Ivanković, Iva Tojčić, and Ivica Vilibić
Geosci. Model Dev., 14, 3995–4017, https://doi.org/10.5194/gmd-14-3995-2021, https://doi.org/10.5194/gmd-14-3995-2021, 2021
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The atmospheric results of the Adriatic Sea and Coast (AdriSC) climate simulation (1987–2017) are evaluated against available observational datasets in the Adriatic region. Generally, the AdriSC model performs better than regional climate models that have resolutions that are 4 times more coarse, except concerning summer temperatures, which are systematically underestimated. High-resolution climate models may thus provide new insights about the local impacts of global warming in the Adriatic.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Ángeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed A. Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-125, https://doi.org/10.5194/os-2021-125, 2022
Revised manuscript accepted for OS
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A survey was conducted in 2021 to tide gauge operators and sea level scientists in the Mediterranean and Black Seas. As a result, a detailed mapping of active tide gauges in this region, including relevant metadata and national contacts, is provided. The work is complemented with an assessment of tide gauge data availability in international programs, and a review of the fit-for-purpose status of the network for those coasts more threatened by sea level related hazards.
Emma Reyes, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Vanessa Cardin, Daniela Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadić, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Maria J. Fernández, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaž Ličer, Pablo Lorente, Marcello Magaldi, Carlo Mantovani, Hrvoje Mihanović, Anne Molcard, Baptiste Mourre, Adèle Révelard, Catalina Reyes-Suárez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquín Tintoré, Yaron Toledo, Marco Uttieri, Ivica Vilibić, Enrico Zambianchi, and Alejandro Orfila
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-115, https://doi.org/10.5194/os-2021-115, 2021
Revised manuscript accepted for OS
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This work reviews the existing advanced and emerging scientific and societal applications using HFR data, developed to address the major challenges identified in the Mediterranean coastal waters, organized around three main topics: maritime safety; extreme hazards and environmental transport processes. It also includes the discussion and a preliminary assessment of the capabilities of the existing HFR applications, finally providing a set of recommendations towards setting out future prospects.
Pablo Lorente, Eva Aguiar, Michele Bendoni, Maristella Berta, Carlo Brandini, Alejandro Cáceres-Euse, Fulvio Capodici, Daniella Cianelli, Giuseppe Ciraolo, Lorenzo Corgnati, Vlado Dadic, Bartolomeo Doronzo, Aldo Drago, Dylan Dumas, Pierpaolo Falco, Maria Fattorini, Adam Gauci, Roberto Gómez, Annalisa Griffa, Charles-Antoine Guérin, Ismael Hernández-Carrasco, Jaime Hernández-Lasheras, Matjaz Licer, Marcelo Magaldi, Carlo Mantovani, Hrvoje Mihanovic, Anne Molcard, Baptiste Mourre, Alejandro Orfila, Adèle Révelard, Emma Reyes, Jorge Sanchez, Simona Saviano, Roberta Sciascia, Stefano Taddei, Joaquin Tintoré, Yaron Toledo, Laura Ursella, Marco Uttieri, Ivica Vilibic, Enrico Zambianchi, and Vanessa Cardín
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-119, https://doi.org/10.5194/os-2021-119, 2021
Revised manuscript accepted for OS
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High-Frequency radar (HFR) is a land-based remote sensing technology that can provide maps of the surface circulation over broad coastal areas, along with wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network and present and future applications of this sensor for societal benefit such as search and rescue operations, safe vessel navigation, tracking of marine pollutants, the monitoring of extreme events.
Petra Zemunik, Jadranka Šepić, Havu Pellikka, Leon Ćatipović, and Ivica Vilibić
Earth Syst. Sci. Data, 13, 4121–4132, https://doi.org/10.5194/essd-13-4121-2021, https://doi.org/10.5194/essd-13-4121-2021, 2021
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A new global dataset – MISELA (Minute Sea-Level Analysis) – has been developed and contains quality-checked sea-level records from 331 tide gauges worldwide for a period from 2004 to 2019. The dataset is appropriate for research on atmospherically induced high-frequency sea-level oscillations. Research on these oscillations is important, as they can, like all sea-level extremes, seriously threaten coastal zone infrastructure and populations.
Iva Tojčić, Cléa Denamiel, and Ivica Vilibić
Nat. Hazards Earth Syst. Sci., 21, 2427–2446, https://doi.org/10.5194/nhess-21-2427-2021, https://doi.org/10.5194/nhess-21-2427-2021, 2021
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This study quantifies the performance of the Croatian meteotsunami early warning system (CMeEWS) composed of a network of air pressure and sea level observations developed in order to help coastal communities prepare for extreme events. The system would have triggered the warnings for most of the observed events but also set off some false alarms if it was operational during the multi-meteotsunami event of 11–19 May 2020 in the eastern Adriatic. Further development of the system is planned.
Cléa Denamiel, Petra Pranić, Damir Ivanković, Iva Tojčić, and Ivica Vilibić
Geosci. Model Dev., 14, 3995–4017, https://doi.org/10.5194/gmd-14-3995-2021, https://doi.org/10.5194/gmd-14-3995-2021, 2021
Short summary
Short summary
The atmospheric results of the Adriatic Sea and Coast (AdriSC) climate simulation (1987–2017) are evaluated against available observational datasets in the Adriatic region. Generally, the AdriSC model performs better than regional climate models that have resolutions that are 4 times more coarse, except concerning summer temperatures, which are systematically underestimated. High-resolution climate models may thus provide new insights about the local impacts of global warming in the Adriatic.
Ivica Vilibić, Petra Zemunik, Jadranka Šepić, Natalija Dunić, Oussama Marzouk, Hrvoje Mihanović, Clea Denamiel, Robert Precali, and Tamara Djakovac
Ocean Sci., 15, 1351–1362, https://doi.org/10.5194/os-15-1351-2019, https://doi.org/10.5194/os-15-1351-2019, 2019
Ivica Vilibić, Hrvoje Mihanović, Ivica Janeković, Cléa Denamiel, Pierre-Marie Poulain, Mirko Orlić, Natalija Dunić, Vlado Dadić, Mira Pasarić, Stipe Muslim, Riccardo Gerin, Frano Matić, Jadranka Šepić, Elena Mauri, Zoi Kokkini, Martina Tudor, Žarko Kovač, and Tomislav Džoić
Ocean Sci., 14, 237–258, https://doi.org/10.5194/os-14-237-2018, https://doi.org/10.5194/os-14-237-2018, 2018
H. Mihanović, I. Vilibić, S. Carniel, M. Tudor, A. Russo, A. Bergamasco, N. Bubić, Z. Ljubešić, D. Viličić, A. Boldrin, V. Malačič, M. Celio, C. Comici, and F. Raicich
Ocean Sci., 9, 561–572, https://doi.org/10.5194/os-9-561-2013, https://doi.org/10.5194/os-9-561-2013, 2013
S. Pasquet, I. Vilibić, and J. Šepić
Nat. Hazards Earth Syst. Sci., 13, 473–482, https://doi.org/10.5194/nhess-13-473-2013, https://doi.org/10.5194/nhess-13-473-2013, 2013
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Geosci. Model Dev., 15, 3923–3940, https://doi.org/10.5194/gmd-15-3923-2022, https://doi.org/10.5194/gmd-15-3923-2022, 2022
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This study uses a set of deep neural networks to learn a parameterization scheme from a superparameterized general circulation model (GCM). After being embedded in a realistically configurated GCM, the parameterization scheme performs stably in long-term climate simulations and reproduces reasonable climatology and climate variability. This success is the first for long-term stable climate simulations using machine learning parameterization under real geographical boundary conditions.
Xue Zheng, Qing Li, Tian Zhou, Qi Tang, Luke P. Van Roekel, Jean-Christophe Golaz, Hailong Wang, and Philip Cameron-Smith
Geosci. Model Dev., 15, 3941–3967, https://doi.org/10.5194/gmd-15-3941-2022, https://doi.org/10.5194/gmd-15-3941-2022, 2022
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We document the model experiments for the future climate projection by E3SMv1.0. At the highest future emission scenario, E3SMv1.0 projects a strong surface warming with rapid changes in the atmosphere, ocean, sea ice, and land runoff. Specifically, we detect a significant polar amplification and accelerated warming linked to the unmasking of the aerosol effects. The impact of greenhouse gas forcing is examined in different climate components.
Francine Schevenhoven and Alberto Carrassi
Geosci. Model Dev., 15, 3831–3844, https://doi.org/10.5194/gmd-15-3831-2022, https://doi.org/10.5194/gmd-15-3831-2022, 2022
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In this study, we present a novel formulation to build a dynamical combination of models, the so-called supermodel, which needs to be trained based on data. Previously, we assumed complete and noise-free observations. Here, we move towards a realistic scenario and develop adaptations to the training methods in order to cope with sparse and noisy observations. The results are very promising and shed light on how to apply the method with state of the art general circulation models.
Zhiang Xie, Dietmar Dommenget, Felicity S. McCormack, and Andrew N. Mackintosh
Geosci. Model Dev., 15, 3691–3719, https://doi.org/10.5194/gmd-15-3691-2022, https://doi.org/10.5194/gmd-15-3691-2022, 2022
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Paleoclimate research requires better numerical model tools to explore interactions among the cryosphere, atmosphere, ocean and land surface. To explore those interactions, this study offers a tool, the GREB-ISM, which can be run for 2 million model years within 1 month on a personal computer. A series of experiments show that the GREB-ISM is able to reproduce the modern ice sheet distribution as well as classic climate oscillation features under paleoclimate conditions.
Yannic Fischler, Martin Rückamp, Christian Bischof, Vadym Aizinger, Mathieu Morlighem, and Angelika Humbert
Geosci. Model Dev., 15, 3753–3771, https://doi.org/10.5194/gmd-15-3753-2022, https://doi.org/10.5194/gmd-15-3753-2022, 2022
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Ice sheet models are used to simulate the changes of ice sheets in future but are currently often run in coarse resolution and/or with neglecting important physics to make them affordable in terms of computational costs. We conducted a study simulating the Greenland Ice Sheet in high resolution and adequate physics to test where the ISSM ice sheet code is using most time and what could be done to improve its performance for future computer architectures that allow massive parallel computing.
Sophy Oliver, Coralia Cartis, Iris Kriest, Simon F. B Tett, and Samar Khatiwala
Geosci. Model Dev., 15, 3537–3554, https://doi.org/10.5194/gmd-15-3537-2022, https://doi.org/10.5194/gmd-15-3537-2022, 2022
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Global ocean biogeochemical models are used within Earth system models which are used to predict future climate change. However, these are very computationally expensive to run and therefore are rarely routinely improved or calibrated to real oceanic observations. Here we apply a new, fast optimisation algorithm to one such model and show that it can calibrate the model much faster than previously managed, therefore encouraging further ocean biogeochemical model improvements.
Anahí Villalba-Pradas and Francisco J. Tapiador
Geosci. Model Dev., 15, 3447–3518, https://doi.org/10.5194/gmd-15-3447-2022, https://doi.org/10.5194/gmd-15-3447-2022, 2022
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The paper provides a comprehensive review of the empirical values and assumptions used in the convection schemes of numerical models. The focus is on the values and assumptions used in the activation of convection (trigger), the transport and microphysics (commonly referred to as the cloud model), and the intensity of convection (closure). Such information can assist satellite missions focused on elucidating convective processes and the evaluation of model output uncertainties.
Maria Chara Karypidou, Eleni Katragkou, and Stefan Pieter Sobolowski
Geosci. Model Dev., 15, 3387–3404, https://doi.org/10.5194/gmd-15-3387-2022, https://doi.org/10.5194/gmd-15-3387-2022, 2022
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The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Reliable climatic information is therefore necessary for the optimal adaptation of local communities. In this work we show that regional climate models are reliable tools for the simulation of precipitation over southern Africa. However, there is still a great need for the expansion and maintenance of observational data.
Stipo Sentić, Peter Bechtold, Željka Fuchs-Stone, Mark Rodwell, and David J. Raymond
Geosci. Model Dev., 15, 3371–3385, https://doi.org/10.5194/gmd-15-3371-2022, https://doi.org/10.5194/gmd-15-3371-2022, 2022
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The Organization of Tropical East Pacific Convection (OTREC) field campaign focuses on studying convection in the eastern Pacific and Caribbean. Observations obtained from dropsondes have been assimilated into the ECMWF model and compared to a model run in which sondes have not been assimilated. The model performs well in both simulations, but the assimilation of sondes helps to reduce the departure for pre-tropical-storm conditions. Variables important to studying convection are also studied.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon
Geosci. Model Dev., 15, 3205–3231, https://doi.org/10.5194/gmd-15-3205-2022, https://doi.org/10.5194/gmd-15-3205-2022, 2022
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This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.
Milena Veneziani, Wieslaw Maslowski, Younjoo J. Lee, Gennaro D'Angelo, Robert Osinski, Mark R. Petersen, Wilbert Weijer, Anthony P. Craig, John D. Wolfe, Darin Comeau, and Adrian K. Turner
Geosci. Model Dev., 15, 3133–3160, https://doi.org/10.5194/gmd-15-3133-2022, https://doi.org/10.5194/gmd-15-3133-2022, 2022
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We present an Earth system model (ESM) simulation, E3SM-Arctic-OSI, with a refined grid to better resolve the Arctic ocean and sea-ice system and low spatial resolution elsewhere. The configuration satisfactorily represents many aspects of the Arctic system and its interactions with the sub-Arctic, while keeping computational costs at a fraction of those necessary for global high-resolution ESMs. E3SM-Arctic can thus be an efficient tool to study Arctic processes on climate-relevant timescales.
Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, https://doi.org/10.5194/gmd-15-3041-2022, 2022
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This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Hengqi Wang, Yiran Peng, Knut von Salzen, Yan Yang, Wei Zhou, and Delong Zhao
Geosci. Model Dev., 15, 2949–2971, https://doi.org/10.5194/gmd-15-2949-2022, https://doi.org/10.5194/gmd-15-2949-2022, 2022
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The aerosol activation scheme is an important part of the general circulation model, but evaluations using observed data are mostly regional. This research introduced a numerically efficient aerosol activation scheme and evaluated it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The decent performance indicates that the scheme is suitable for simulations of cloud droplet number concentrations over wide conditions.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Jewgenij Torizin, Nick Schüßler, and Michael Fuchs
Geosci. Model Dev., 15, 2791–2812, https://doi.org/10.5194/gmd-15-2791-2022, https://doi.org/10.5194/gmd-15-2791-2022, 2022
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With LSAT PM we introduce an open-source, stand-alone, easy-to-use application that supports scientific principles of openness, knowledge integrity, and replicability. Doing so, we want to share our experience in the implementation of heuristic and data-driven landslide susceptibility assessment methods such as analytic hierarchy process, weights of evidence, logistic regression, and artificial neural networks. A test dataset is available.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, https://doi.org/10.5194/gmd-15-2635-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with a recent observational gridded dataset as a reference, covering the entire Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional climate models encouraged this study. For precipitation, most models reveal added value. The gains are even more evident for precipitation extremes, particularly at a more local scale.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2653–2671, https://doi.org/10.5194/gmd-15-2653-2022, https://doi.org/10.5194/gmd-15-2653-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with an observational gridded dataset as a reference covering the Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional models encouraged this study. For the max and min temperature, although most models reveal added value, some display losses. At more local scales, coastal sites display important gains, contrasting with the interior.
Guillaume Marie, B. Sebastiaan Luyssaert, Cecile Dardel, Thuy Le Toan, Alexandre Bouvet, Stéphane Mermoz, Ludovic Villard, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 15, 2599–2617, https://doi.org/10.5194/gmd-15-2599-2022, https://doi.org/10.5194/gmd-15-2599-2022, 2022
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Most Earth system models make use of vegetation maps to initialize a simulation at global scale. Satellite-based biomass map estimates for Africa were used to estimate cover fractions for the 15 land cover classes. This study successfully demonstrates that satellite-based biomass maps can be used to better constrain vegetation maps. Applying this approach at the global scale would increase confidence in assessments of present-day biomass stocks.
Anni Zhao, Chris M. Brierley, Zhiyi Jiang, Rachel Eyles, Damián Oyarzún, and Jose Gomez-Dans
Geosci. Model Dev., 15, 2475–2488, https://doi.org/10.5194/gmd-15-2475-2022, https://doi.org/10.5194/gmd-15-2475-2022, 2022
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We describe the way that our group have chosen to perform our recent analyses of the Palaeoclimate Modelling Intercomparison Project ensemble simulations. We document the approach used to obtain and curate the simulations, process those outputs via the Climate Variability Diagnostics Package, and then continue through to compute ensemble-wide statistics and create figures. We also provide interim data from all steps, the codes used and the ability for users to perform their own analyses.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Stefan Kruse, Simone M. Stuenzi, Julia Boike, Moritz Langer, Josias Gloy, and Ulrike Herzschuh
Geosci. Model Dev., 15, 2395–2422, https://doi.org/10.5194/gmd-15-2395-2022, https://doi.org/10.5194/gmd-15-2395-2022, 2022
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We coupled established models for boreal forest (LAVESI) and permafrost dynamics (CryoGrid) in Siberia to investigate interactions of the diverse vegetation layer with permafrost soils. Our tests showed improved active layer depth estimations and newly included species growth according to their species-specific limits. We conclude that the new model system can be applied to simulate boreal forest dynamics and transitions under global warming and disturbances, expanding our knowledge.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Hong Li, Xiang Li, and Yunfei Zhang
Geosci. Model Dev., 15, 2345–2363, https://doi.org/10.5194/gmd-15-2345-2022, https://doi.org/10.5194/gmd-15-2345-2022, 2022
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To better understand the effects of surface waves on global intraseasonal prediction, we incorporated the WW3 model into CFSv2.0. Processes of Langmuir mixing, Stokes–Coriolis force with entrainment, air–sea fluxes modified by Stokes drift, and momentum roughness length were considered. Results from two groups of 56 d experiments show that overestimated sea surface temperature, 2 m air temperature, 10 m wind, wave height, and underestimated mixed layer from the original CFSv2.0 are improved.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
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We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Yusuke Sasaki, Hidetaka Kobayashi, and Akira Oka
Geosci. Model Dev., 15, 2013–2033, https://doi.org/10.5194/gmd-15-2013-2022, https://doi.org/10.5194/gmd-15-2013-2022, 2022
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For realistically simulating the recently observed distributions of dissolved 230Th and 231Pa in the ocean, we highlight the importance of the removal process of 231Pa and 230Th at the seafloor (bottom scavenging) and the dependence of scavenging efficiency on particle concentration. We show that consideration of these two processes can well reproduce not only the oceanic distribution of 231Pa and 230Th but also the sedimentary 231Pa/230Th ratios.
Stefan Hergarten and Jörg Robl
Geosci. Model Dev., 15, 2063–2084, https://doi.org/10.5194/gmd-15-2063-2022, https://doi.org/10.5194/gmd-15-2063-2022, 2022
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The influence of climate on landform evolution has attracted great interest over the past decades. This paper presents a simple model for simulating the influence of topography on precipitation and the decrease in precipitation over large continental areas. The approach can be included in numerical models of large-scale landform evolution and causes only a moderate increase in the numerical complexity. It opens a door to investigating feedbacks between climate and landform evolution.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Justus Contzen, Thorsten Dickhaus, and Gerrit Lohmann
Geosci. Model Dev., 15, 1803–1820, https://doi.org/10.5194/gmd-15-1803-2022, https://doi.org/10.5194/gmd-15-1803-2022, 2022
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Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Enrico Scoccimarro, Daniele Peano, Silvio Gualdi, Alessio Bellucci, Tomas Lovato, Pier Giuseppe Fogli, and Antonio Navarra
Geosci. Model Dev., 15, 1841–1854, https://doi.org/10.5194/gmd-15-1841-2022, https://doi.org/10.5194/gmd-15-1841-2022, 2022
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This study evaluated the ability of the CMCC-CM2 climate model participating to the last CMIP6 effort, in representing extreme events of precipitation and temperature at the daily and 6-hourly frequencies. The 1/4° resolution version of the atmospheric model provides better results than the version at 1° resolution for temperature extremes, at both time frequencies. For precipitation extremes, especially at the daily time frequency, the higher resolution does not improve model results.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
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This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
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Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Zhiping Tian, Dabang Jiang, Ran Zhang, and Baohuang Su
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-49, https://doi.org/10.5194/gmd-2022-49, 2022
Revised manuscript accepted for GMD
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This manuscript presents the experimental design for a new set of transient experiments for the Holocene from 11.5 ka to the preindustrial period (1850 CE) with a relatively high-resolution Earth system model. Model boundary conditions include time-varying full and single forcing of orbital parameters, greenhouse gases, and ice sheets. The simulations will help to study the mean climate trend and abrupt climate changes through the Holocene in response to both full and single external forcings.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Christopher Holder, Anand Gnanadesikan, and Marie Aude-Pradal
Geosci. Model Dev., 15, 1595–1617, https://doi.org/10.5194/gmd-15-1595-2022, https://doi.org/10.5194/gmd-15-1595-2022, 2022
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It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.
Kun Zheng, Yan Liu, Jinbiao Zhang, Cong Luo, Siyu Tang, Huihua Ruan, Qiya Tan, Yunlei Yi, and Xiutao Ran
Geosci. Model Dev., 15, 1467–1475, https://doi.org/10.5194/gmd-15-1467-2022, https://doi.org/10.5194/gmd-15-1467-2022, 2022
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In extrapolation methods, there is a phenomenon that causes the extrapolated image to be blurred and unrealistic. The paper proposes the GAN–argcPredNet v1.0 network model, which aims to solve this problem through GAN's ability to strengthen the characteristics of multi-modal data modeling. GAN–argcPredNet v1.0 has achieved excellent results. Our model can reduce the prediction loss in a small-scale space so that the prediction results have more detailed features.
Swen Brands
Geosci. Model Dev., 15, 1375–1411, https://doi.org/10.5194/gmd-15-1375-2022, https://doi.org/10.5194/gmd-15-1375-2022, 2022
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The present study evaluates the last two global climate model generations in terms of their capability to reproduce recurrent regional atmospheric circulation patterns in the Northern Hemisphere mid-to-high latitudes under present climate conditions. These patterns are linked with many environmental variables on the local scale and thus provide an overarching concept for model verification. The results are expected to be of interest for model developers and regional climate scientists.
Shuqi Lin, Leon Boegman, Shiliang Shan, and Ryan Mulligan
Geosci. Model Dev., 15, 1331–1353, https://doi.org/10.5194/gmd-15-1331-2022, https://doi.org/10.5194/gmd-15-1331-2022, 2022
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An operational hydrodynamics forecast system, COASTLINES, using the Windows Task Scheduler, Python, and MATLAB scripts, to automate application of a 3-D model (AEM3D) in Lake Erie was developed. The system predicted storm-surge and up-/downwelling events that are important for flood water and drinking water/fishery management. This example of the successful development of an operational forecast system can be adapted to simulate aquatic systems as required for management and public safety.
Niels J. de Winter
Geosci. Model Dev., 15, 1247–1267, https://doi.org/10.5194/gmd-15-1247-2022, https://doi.org/10.5194/gmd-15-1247-2022, 2022
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ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives based on the seasonal variability in temperature and salinity or precipitation recorded in stable oxygen isotope measurements. The model allows dating of fossil archives within a year, which is important for climate reconstructions on the sub-seasonal to decadal scale. In this paper, I introduce ShellChron and test it on a range of real and virtual datasets to demonstrate its use.
Fanglou Liao, Xiao Hua Wang, and Zhiqiang Liu
Geosci. Model Dev., 15, 1129–1153, https://doi.org/10.5194/gmd-15-1129-2022, https://doi.org/10.5194/gmd-15-1129-2022, 2022
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The ocean heat content (OHC) estimated using two eddying hindcast simulations, OFES1 and OFES2, was compared from 1960 to 2016, with observation-based results as a reference. Marked differences were found, especially in the Atlantic Ocean. These were related to the differences in the net surface heating, heat advection, and vertical heat diffusion. These documented differences may help the community better understand and use these quasi-global high-resolution datasets for their own purposes.
Kai-Yuan Cheng, Lucas M. Harris, and Yong Qiang Sun
Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, https://doi.org/10.5194/gmd-15-1097-2022, 2022
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This paper presents the implementation of container technology for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model that can be used as a global, a global–nest, and a regional model for weather-to-seasonal prediction. Container technology makes SHiELD cross-platform and easy to use, which opens opportunities for collaborative research and development. The performance and scalability of the containerized SHiELD are evaluated and discussed.
Junichi Tsutsui
Geosci. Model Dev., 15, 951–970, https://doi.org/10.5194/gmd-15-951-2022, https://doi.org/10.5194/gmd-15-951-2022, 2022
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A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
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The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
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C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
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The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
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The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev., 15, 683–713, https://doi.org/10.5194/gmd-15-683-2022, https://doi.org/10.5194/gmd-15-683-2022, 2022
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We describe in this paper the implementation of a process-based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.2. The performance of the model simulations for the year 2010 is evaluated against in situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved, although in some areas the model shows a decline in performance.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
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Short summary
The Adriatic Sea and Coast model was developed due to the need for higher-resolution climate models and longer-term simulations to capture coastal atmospheric and ocean processes at climate scales in the Adriatic Sea. The ocean results of a 31-year-long simulation were compared to the observational data. The evaluation revealed that the model is capable of reproducing the observed physical properties with good accuracy and can be further used to study the dynamics of the Adriatic–Ionian basin.
The Adriatic Sea and Coast model was developed due to the need for higher-resolution climate...
