Articles | Volume 11, issue 3
https://doi.org/10.5194/gmd-11-843-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-843-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
06 Mar 2018
Model description paper |
| 06 Mar 2018
| 06 Mar 2018
Isca, v1.0: a framework for the global modelling of the atmospheres of Earth and other planets at varying levels of complexity
University of Exeter, Department of Mathematics, Exeter, UK
Greg Colyer
University of Exeter, Department of Mathematics, Exeter, UK
Ruth Geen
University of Exeter, Department of Mathematics, Exeter, UK
Edwin Gerber
New York University, Courant Institute, New York, USA
Martin Jucker
University of Melbourne, School of Earth Sciences, Melbourne, Australia
Penelope Maher
University of Exeter, Department of Mathematics, Exeter, UK
Alexander Paterson
University of Exeter, Department of Mathematics, Exeter, UK
Marianne Pietschnig
University of Exeter, Department of Mathematics, Exeter, UK
James Penn
University of Exeter, Department of Mathematics, Exeter, UK
Stephen I. Thomson
University of Exeter, Department of Mathematics, Exeter, UK
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Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev., 14, 2801–2826, https://doi.org/10.5194/gmd-14-2801-2021, https://doi.org/10.5194/gmd-14-2801-2021, 2021
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Clouds play an vital role in Earth's energy budget, and even a small change in cloud fields can have a large impact on the climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties and thus provide a useful tool to explore unsolved problems relating to clouds.
Aaron Match, Edwin P. Gerber, and Stephan Fueglistaler
Atmos. Chem. Phys., 24, 10305–10322, https://doi.org/10.5194/acp-24-10305-2024, https://doi.org/10.5194/acp-24-10305-2024, 2024
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Earth's ozone layer absorbs incoming UV light, protecting life. Removing ozone aloft allows UV light to penetrate deeper, where it is known to produce new ozone, leading to "self-healing" that partially stabilizes total ozone. However, a photochemistry model shows that, above 40 km in the tropics, deeper-penetrating UV destroys ozone, destabilizing the total ozone. Photochemical theory reveals that this destabilizing regime occurs where overhead ozone is below a key threshold.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Chaim I. Garfinkel, Zachary D. Lawrence, Amy H. Butler, Etienne Dunn-Sigouin, Irene Erner, Alexey Yu. Karpechko, Gerbrand Koren, Marta Abalos, Blanca Ayarzaguena, David Barriopedro, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Judah Cohen, Daniela I. V. Domeisen, Javier García-Serrano, Neil P. Hindley, Martin Jucker, Hera Kim, Robert W. Lee, Simon H. Lee, Marisol Osman, Froila M. Palmeiro, Inna Polichtchouk, Jian Rao, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1762, https://doi.org/10.5194/egusphere-2024-1762, 2024
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Variability in the extratropical stratosphere and troposphere are coupled, and because of the longer timescales characteristic of the stratosphere, this allows for a window of opportunity for surface prediction. This paper assesses whether models used for operational prediction capture these coupling processes accurately. We find that most processes are too-weak, however downward coupling from the lower stratosphere to the near surface is too strong.
Aaron Match, Edwin P. Gerber, and Stephan Fueglistaler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1552, https://doi.org/10.5194/egusphere-2024-1552, 2024
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Explanations for the tropical ozone maximum at 26 km have fragmented into two paradigms, shown to represent limiting regimes of ozone photochemistry with production by UV and generalized destruction by catalytic cycles and transport. Paradoxically, neither paradigm explains the observed ozone peak, motivating a new theory: peak ozone occurs precisely at the transition between these regimes. An idealized analytical ozone profile is derived, helping to interpret sensitivities to UV perturbations.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Zachary D. Lawrence, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Amy H. Butler, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Daniela I. V. Domeisen, Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel, Neil P. Hindley, Liwei Jia, Martin Jucker, Alexey Y. Karpechko, Hera Kim, Andrea L. Lang, Simon H. Lee, Pu Lin, Marisol Osman, Froila M. Palmeiro, Judith Perlwitz, Inna Polichtchouk, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Irene Erner, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
Weather Clim. Dynam., 3, 977–1001, https://doi.org/10.5194/wcd-3-977-2022, https://doi.org/10.5194/wcd-3-977-2022, 2022
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Forecast models that are used to predict weather often struggle to represent the Earth’s stratosphere. This may impact their ability to predict surface weather weeks in advance, on subseasonal-to-seasonal (S2S) timescales. We use data from many S2S forecast systems to characterize and compare the stratospheric biases present in such forecast models. These models have many similar stratospheric biases, but they tend to be worse in systems with low model tops located within the stratosphere.
Thomas Reichler and Martin Jucker
Weather Clim. Dynam., 3, 659–677, https://doi.org/10.5194/wcd-3-659-2022, https://doi.org/10.5194/wcd-3-659-2022, 2022
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Variations in the stratospheric polar vortex, so-called vortex events, can improve predictions of surface weather and climate. There are various ways to detect such events, and here we use the amount of wave energy that propagates into the stratosphere. The new definition is tested against so-called stratospheric sudden warmings (SSWs). We find that the wave definition has advantages over SSWs, for example in terms of a stronger surface response that follows the events.
Penelope Maher and Paul Earnshaw
Geosci. Model Dev., 15, 1177–1194, https://doi.org/10.5194/gmd-15-1177-2022, https://doi.org/10.5194/gmd-15-1177-2022, 2022
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Climate models do a pretty good job. But they are far from perfect. Fixing these imperfections is really hard because the models are complicated. One way to make progress is to create simpler models: think impressionism rather than realism in the art world. We changed the Met Office model to be intentionally simple and it still does a pretty good job. This will help to identify sources of model imperfections, develop new methods and improve our understanding of how the climate works.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev., 14, 2801–2826, https://doi.org/10.5194/gmd-14-2801-2021, https://doi.org/10.5194/gmd-14-2801-2021, 2021
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Clouds play an vital role in Earth's energy budget, and even a small change in cloud fields can have a large impact on the climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties and thus provide a useful tool to explore unsolved problems relating to clouds.
Andrew Orr, Hua Lu, Patrick Martineau, Edwin P. Gerber, Gareth J. Marshall, and Thomas J. Bracegirdle
Atmos. Chem. Phys., 21, 7451–7472, https://doi.org/10.5194/acp-21-7451-2021, https://doi.org/10.5194/acp-21-7451-2021, 2021
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Reanalysis datasets combine observations and weather forecast simulations to create our best estimate of the state of the atmosphere and are important for climate monitoring. Differences in the technical details of these products mean that they may give different results. This study therefore examined how changes associated with the so-called Antarctic ozone hole are represented, which is one of the most important climate changes in recent decades, and showed that they were broadly consistent.
Edwin P. Gerber and Patrick Martineau
Atmos. Chem. Phys., 18, 17099–17117, https://doi.org/10.5194/acp-18-17099-2018, https://doi.org/10.5194/acp-18-17099-2018, 2018
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The annular modes characterize the variability of the extratropical circulation. We show that they are extremely consistent across all reanalyses during the satellite era (1979 onward). Consequently, uncertainty in the annual cycle of variability of the tropospheric jet streams and their coupling with the stratospheric polar vortices is dominated by sampling uncertainty. Pre-satellite reanalysis of the Northern Hemisphere appears to be of high quality and can help reduce this uncertainty.
Marianne Pietschnig, Michael Mayer, Takamasa Tsubouchi, Andrea Storto, Sebastian Stichelberger, and Leopold Haimberger
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-98, https://doi.org/10.5194/os-2017-98, 2017
Revised manuscript not accepted
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New estimates of volume and temperature transports into the Arctic Ocean through the four major gateways (Davis, Fram and Bering Strait and the Barents Sea Opening) have recently become available. These estimates are derived from moored observations. In this study, the same transports derived from a recent ocean reanalysis are compared to the observation-based estimates in the straits. In addition, cross-section plots of velocity, temperature and temperature flux density are investigated.
Masatomo Fujiwara, Jonathon S. Wright, Gloria L. Manney, Lesley J. Gray, James Anstey, Thomas Birner, Sean Davis, Edwin P. Gerber, V. Lynn Harvey, Michaela I. Hegglin, Cameron R. Homeyer, John A. Knox, Kirstin Krüger, Alyn Lambert, Craig S. Long, Patrick Martineau, Andrea Molod, Beatriz M. Monge-Sanz, Michelle L. Santee, Susann Tegtmeier, Simon Chabrillat, David G. H. Tan, David R. Jackson, Saroja Polavarapu, Gilbert P. Compo, Rossana Dragani, Wesley Ebisuzaki, Yayoi Harada, Chiaki Kobayashi, Will McCarty, Kazutoshi Onogi, Steven Pawson, Adrian Simmons, Krzysztof Wargan, Jeffrey S. Whitaker, and Cheng-Zhi Zou
Atmos. Chem. Phys., 17, 1417–1452, https://doi.org/10.5194/acp-17-1417-2017, https://doi.org/10.5194/acp-17-1417-2017, 2017
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We introduce the SPARC Reanalysis Intercomparison Project (S-RIP), review key concepts and elements of atmospheric reanalysis systems, and summarize the technical details of and differences among 11 of these systems. This work supports scientific studies and intercomparisons of reanalysis products by collecting these background materials and technical details into a single reference. We also address several common misunderstandings and points of confusion regarding reanalyses.
Leon S. Friedrich, Adrian J. McDonald, Gregory E. Bodeker, Kathy E. Cooper, Jared Lewis, and Alexander J. Paterson
Atmos. Chem. Phys., 17, 855–866, https://doi.org/10.5194/acp-17-855-2017, https://doi.org/10.5194/acp-17-855-2017, 2017
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Information from long-duration balloons flying in the Southern Hemisphere stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses. This work assesses the potential of the X Project Loon observations to validate outputs from the reanalysis models. In particular, we examined how the model winds compared with those derived from the balloon GPS information. We also examined simulated trajectories compared with the true trajectories.
Edwin P. Gerber and Elisa Manzini
Geosci. Model Dev., 9, 3413–3425, https://doi.org/10.5194/gmd-9-3413-2016, https://doi.org/10.5194/gmd-9-3413-2016, 2016
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Diagnostics of atmospheric momentum and energy transport are needed to investigate and understand circulation biases in climate models and the atmospheric response to natural and anthropogenic forcing. To reduce such biases is of importance because they add uncertainty in regional climate projections. We define requirements for diagnosing resolved and parameterized dynamical processes relevant to atmospheric variability and the transport of mass, momentum and energy within CMIP.
Davide Zanchettin, Myriam Khodri, Claudia Timmreck, Matthew Toohey, Anja Schmidt, Edwin P. Gerber, Gabriele Hegerl, Alan Robock, Francesco S. R. Pausata, William T. Ball, Susanne E. Bauer, Slimane Bekki, Sandip S. Dhomse, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Michael Mills, Marion Marchand, Ulrike Niemeier, Virginie Poulain, Eugene Rozanov, Angelo Rubino, Andrea Stenke, Kostas Tsigaridis, and Fiona Tummon
Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, https://doi.org/10.5194/gmd-9-2701-2016, 2016
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Simulating volcanically-forced climate variability is a challenging task for climate models. The Model Intercomparison Project on the climatic response to volcanic forcing (VolMIP) – an endorsed contribution to CMIP6 – defines a protocol for idealized volcanic-perturbation experiments to improve comparability of results across different climate models. This paper illustrates the design of VolMIP's experiments and describes the aerosol forcing input datasets to be used.
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Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
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., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the 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 at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
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, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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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.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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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.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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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.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1437, https://doi.org/10.5194/egusphere-2024-1437, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can well reproduce the distribution of PAHs. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change of BaP is less than PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although "the Action Plan" has been implemented.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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Short summary
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 perform salting and plowing operations at the right time and keep roads safe for drivers.
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Short summary
The models that are used to describe the atmospheres of Earth and other planets are often very complicated. Although this is necessary for such things as weather prediction, it does not help in understanding. Furthermore, when studying other planets, there are insufficient data to warrant the use of complicated models. We have developed a framework that allows the construction of models of appropriate complexity for the problem at hand, and thus helps to actually model these atmospheres.
The models that are used to describe the atmospheres of Earth and other planets are often very...
