Articles | Volume 18, issue 6
https://doi.org/10.5194/gmd-18-1965-2025
© Author(s) 2025. 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-18-1965-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
26 Mar 2025
Development and technical paper |
| 26 Mar 2025
| 26 Mar 2025
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Jean-François Grailet
CORRESPONDING AUTHOR
MAST-FOCUS, Astrophysics, Geophysics and Oceanography Department, University of Liège, Liège, Belgium
Robin J. Hogan
European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Department of Meteorology, University of Reading, Reading, United Kingdom
Nicolas Ghilain
SPHERES research unit, Department of Geography, University of Liège, Liège, Belgium
Royal Meteorological Institute of Belgium, Uccle, Belgium
David Bolsée
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Uccle, Belgium
Xavier Fettweis
SPHERES research unit, Department of Geography, University of Liège, Liège, Belgium
Marilaure Grégoire
MAST-FOCUS, Astrophysics, Geophysics and Oceanography Department, University of Liège, Liège, Belgium
Related authors
No articles found.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zhengwen Yan, Jiangjun Ran, Pavel Ditmar, C. K. Shum, Roland Klees, Patrick Smith, and Xavier Fettweis
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-512, https://doi.org/10.5194/essd-2024-512, 2025
Preprint under review for ESSD
Short summary
Short summary
The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, frequency-dependent noise processing strategy, and parameterization integrating natural boundaries, which aims to enhance accuracy for monitoring mass transportation on Earth.
Loïc Macé, Luc Vandenbulcke, Jean-Michel Brankart, Pierre Brasseur, and Marilaure Grégoire
EGUsphere, https://doi.org/10.5194/egusphere-2024-3682, https://doi.org/10.5194/egusphere-2024-3682, 2024
Short summary
Short summary
The amount of light found in seawater influences water temperature and primary production and must be finely modelled in systems that aim at representing marine biogeochemical environments. We analyse results from a radiative transfer model accounting for absorption and scattering of light in the ocean and compare them with in situ and remote-sensed data, along with the associated uncertainties. We also highlight the benefits of using advanced representations of light in modelling frameworks.
Lauranne Alaerts, Jonathan Lambrechts, Ny Riana Randresihaja, Luc Vandenbulcke, Olivier Gourgue, Emmanuel Hanert, and Marilaure Grégoire
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-529, https://doi.org/10.5194/essd-2024-529, 2024
Revised manuscript under review for ESSD
Short summary
Short summary
We created the first comprehensive, high-resolution, and easily-accessible bathymetry dataset for the three main branches of the Danube Delta. By combining four data sources, we obtained a detailed representation of the riverbed, with resolutions ranging from 2 to 100 m. This dataset will support future studies on water and nutrient exchanges between the Danube and the Black Sea, and provide insights into the Delta’s buffer role within the understudied Danube-Black Sea continuum.
Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3051, https://doi.org/10.5194/egusphere-2024-3051, 2024
Short summary
Short summary
We investigated how the uncertainty in representing water vapour continuum absorption in the shortwave affects clear-sky shortwave radiative feedback. For current surface temperature, the impact is modest (<2 %). In a warmer world, continuum induced error in estimated shortwave feedback is up to ~5 %. Using the MT_CKD model in radiative transfer calculations may lead to an underestimation of the shortwave feedback. Constraining shortwave continuum will contribute to reducing these discrepancies.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3251, https://doi.org/10.5194/egusphere-2024-3251, 2024
Short summary
Short summary
Due to the melt events in recent decades, the snow condition over Greenland has been changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry, and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event has a long-lasting impact on the volume scattering of Greenland firn. This impact cannot fully recover due to the recent and more frequent melt events.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
Short summary
Short summary
The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
Marie Genevieve Paule Cavitte, Hugues Goosse, Quentin Dalaiden, and Nicolas Ghilain
EGUsphere, https://doi.org/10.5194/egusphere-2024-3140, https://doi.org/10.5194/egusphere-2024-3140, 2024
Short summary
Short summary
Ice cores in East Antarctica show contrasting records of past snowfall. We tested if large-scale weather patterns could explain this by combining ice core data with an atmospheric model and radar-derived errors. However, the reconstruction produced unrealistic wind patterns to fit the ice core records. We suggest that uncertainties are not fully captured and that small-scale local wind effects, not represented in the model, could significantly influence snowfall records in the ice cores.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2750, https://doi.org/10.5194/egusphere-2024-2750, 2024
Short summary
Short summary
Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Howard W. Barker, Jason N. S. Cole, Najda Villefranque, Zhipeng Qu, Almudena Velázquez Blázquez, Carlos Domenech, Shannon L. Mason, and Robin J. Hogan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1651, https://doi.org/10.5194/egusphere-2024-1651, 2024
Short summary
Short summary
Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared and the likelihood of them differing by 10 W/m2 defines the closure.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
Short summary
Short summary
Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
Short summary
Short summary
A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
Short summary
Short summary
Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024, https://doi.org/10.5194/tc-18-475-2024, 2024
Short summary
Short summary
The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
Short summary
Short summary
When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Laura J. Dietrich, Hans Christian Steen-Larsen, Sonja Wahl, Anne-Katrine Faber, and Xavier Fettweis
The Cryosphere, 18, 289–305, https://doi.org/10.5194/tc-18-289-2024, https://doi.org/10.5194/tc-18-289-2024, 2024
Short summary
Short summary
The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone
The Cryosphere, 17, 5061–5074, https://doi.org/10.5194/tc-17-5061-2023, https://doi.org/10.5194/tc-17-5061-2023, 2023
Short summary
Short summary
We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
Short summary
Short summary
The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
Short summary
Short summary
Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
Short summary
Short summary
We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
Short summary
Short summary
We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
Short summary
Short summary
Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
Short summary
Short summary
The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
Short summary
Short summary
We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
Short summary
Short summary
Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
Short summary
Short summary
The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
Short summary
Short summary
Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
Short summary
Short summary
This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
Short summary
Short summary
Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
Short summary
Short summary
The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Estrella Olmedo, Verónica González-Gambau, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Marilaure Gregoire, Aida Álvera-Azcárate, Luminita Buga, and Marie-Hélène Rio
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-364, https://doi.org/10.5194/essd-2021-364, 2021
Revised manuscript not accepted
Short summary
Short summary
We present the first dedicated satellite salinity product in the Black Sea. We use the measurements provided by the European Soil Moisture and Ocean Salinity mission. We introduce enhanced algorithms for dealing with the contamination produced by the Radio Frequency Interferences that strongly affect this basin. We also provide a complete quality assessment of the new product and give an estimated accuracy of it.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
Short summary
Short summary
We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215, https://doi.org/10.5194/gmd-14-5205-2021, https://doi.org/10.5194/gmd-14-5205-2021, 2021
Short summary
Short summary
A major limitation in training machine-learning emulators is often caused by the lack of data. This paper presents a cheap way to increase the size of training datasets using statistical techniques and thereby improve the performance of machine-learning emulators.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
Short summary
Short summary
We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
Short summary
Short summary
Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
Short summary
Short summary
Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Paolo Colosio, Marco Tedesco, Roberto Ranzi, and Xavier Fettweis
The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, https://doi.org/10.5194/tc-15-2623-2021, 2021
Short summary
Short summary
We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
Short summary
Short summary
This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Christoph Kittel, Charles Amory, Cécile Agosta, Nicolas C. Jourdain, Stefan Hofer, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Charlotte Lang, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, https://doi.org/10.5194/tc-15-1215-2021, 2021
Short summary
Short summary
The future surface mass balance (SMB) of the Antarctic ice sheet (AIS) will influence the ice dynamics and the contribution of the ice sheet to the sea level rise. We investigate the AIS sensitivity to different warmings using physical and statistical downscaling of CMIP5 and CMIP6 models. Our results highlight a contrasting effect between the grounded ice sheet (where the SMB is projected to increase) and ice shelves (where the future SMB depends on the emission scenario).
Florian Ricour, Arthur Capet, Fabrizio D'Ortenzio, Bruno Delille, and Marilaure Grégoire
Biogeosciences, 18, 755–774, https://doi.org/10.5194/bg-18-755-2021, https://doi.org/10.5194/bg-18-755-2021, 2021
Short summary
Short summary
This paper addresses the phenology of the deep chlorophyll maximum (DCM) in the Black Sea (BS). We show that the DCM forms in March at a density level set by the winter mixed layer. It maintains this location until June, suggesting an influence of the DCM on light and nutrient profiles rather than mere adaptation to external factors. In summer, the DCM concentrates ~55 % of the chlorophyll in a 10 m layer at ~35 m depth and should be considered a major feature of the BS phytoplankton dynamics.
Arthur Capet, Luc Vandenbulcke, and Marilaure Grégoire
Biogeosciences, 17, 6507–6525, https://doi.org/10.5194/bg-17-6507-2020, https://doi.org/10.5194/bg-17-6507-2020, 2020
Short summary
Short summary
The Black Sea is 2000 m deep, but, due to limited ventilation, only about the upper 100 m contains enough oxygen to support marine life such as fish. This oxygenation depth has been shown to be decreasing (1955–2019). Here, we evidence that atmospheric warming induced a clear shift in an important ventilation mechanism. We highlight the impact of this shift on oxygenation. There are important implications for marine life and carbon and nutrient cycling if this new ventilation regime persists.
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
Short summary
Short summary
A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
Short summary
Short summary
The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
Short summary
Short summary
This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Kang Yang, Aleah Sommers, Lauren C. Andrews, Laurence C. Smith, Xin Lu, Xavier Fettweis, and Manchun Li
The Cryosphere, 14, 3349–3365, https://doi.org/10.5194/tc-14-3349-2020, https://doi.org/10.5194/tc-14-3349-2020, 2020
Short summary
Short summary
This study compares hourly supraglacial moulin discharge simulations from three surface meltwater routing models. Results show that these models are superior to simply using regional climate model runoff without routing, but different routing models, different-spatial-resolution DEMs, and parameterized seasonal evolution of supraglacial stream and river networks induce significant variability in diurnal moulin discharges and corresponding subglacial effective pressures.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
Short summary
Short summary
In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Shujie Wang, Marco Tedesco, Patrick Alexander, Min Xu, and Xavier Fettweis
The Cryosphere, 14, 2687–2713, https://doi.org/10.5194/tc-14-2687-2020, https://doi.org/10.5194/tc-14-2687-2020, 2020
Short summary
Short summary
Glacial algal blooms play a significant role in darkening the Greenland Ice Sheet during summertime. The dark pigments generated by glacial algae could substantially reduce the bare ice albedo and thereby enhance surface melt. We used satellite data to map the spatial distribution of glacial algae and characterized the seasonal growth pattern and interannual trends of glacial algae in southwestern Greenland. Our study is important for bridging microbial activities with ice sheet mass balance.
Sophie Nowicki, Heiko Goelzer, Hélène Seroussi, Anthony J. Payne, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Patrick Alexander, Xylar S. Asay-Davis, Alice Barthel, Thomas J. Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan M. Gregory, Tore Hattermann, Nicolas C. Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher M. Little, Mathieu Morlighem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin S. Smith, Fiammetta Straneo, Luke D. Trusel, Michiel R. van den Broeke, and Roderik van de Wal
The Cryosphere, 14, 2331–2368, https://doi.org/10.5194/tc-14-2331-2020, https://doi.org/10.5194/tc-14-2331-2020, 2020
Short summary
Short summary
This paper describes the experimental protocol for ice sheet models taking part in the Ice Sheet Model Intercomparion Project for CMIP6 (ISMIP6) and presents an overview of the atmospheric and oceanic datasets to be used for the simulations. The ISMIP6 framework allows for exploring the uncertainty in 21st century sea level change from the Greenland and Antarctic ice sheets.
Heiko Goelzer, Brice P. Y. Noël, Tamsin L. Edwards, Xavier Fettweis, Jonathan M. Gregory, William H. Lipscomb, Roderik S. W. van de Wal, and Michiel R. van den Broeke
The Cryosphere, 14, 1747–1762, https://doi.org/10.5194/tc-14-1747-2020, https://doi.org/10.5194/tc-14-1747-2020, 2020
Short summary
Short summary
Future sea-level change projections with process-based ice sheet models are typically driven with surface mass balance forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the one used by the climate model. The proposed remapping method reproduces the original forcing data closely when applied to the original geometry and produces a physically meaningful forcing when applied to different modelled geometries.
Margit Aun, Kaisa Lakkala, Ricardo Sanchez, Eija Asmi, Fernando Nollas, Outi Meinander, Larisa Sogacheva, Veerle De Bock, Antti Arola, Gerrit de Leeuw, Veijo Aaltonen, David Bolsée, Klara Cizkova, Alexander Mangold, Ladislav Metelka, Erko Jakobson, Tove Svendby, Didier Gillotay, and Bert Van Opstal
Atmos. Chem. Phys., 20, 6037–6054, https://doi.org/10.5194/acp-20-6037-2020, https://doi.org/10.5194/acp-20-6037-2020, 2020
Short summary
Short summary
In 2017, new measurements of UV radiation started in Marambio, Antarctica, by the Finnish Meteorological Institute in collaboration with the Argentinian Servicio Meteorológico Nacional. The paper presents the results of UV irradiance measurements from March 2017 to March 2019, and it
compares them with those from 2000–2008 and also with UV measurements at other Antarctic stations. In 2017/2018, below average UV radiation levels were recorded due to favourable ozone and cloud conditions.
Marco Tedesco and Xavier Fettweis
The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, https://doi.org/10.5194/tc-14-1209-2020, 2020
Short summary
Short summary
Unprecedented atmospheric conditions occurring in the summer of 2019 over Greenland promoted new record or close-to-record values of mass loss. Summer of 2019 was characterized by an exceptional persistence of anticyclonic conditions that enhanced melting.
Donald A. Slater, Denis Felikson, Fiamma Straneo, Heiko Goelzer, Christopher M. Little, Mathieu Morlighem, Xavier Fettweis, and Sophie Nowicki
The Cryosphere, 14, 985–1008, https://doi.org/10.5194/tc-14-985-2020, https://doi.org/10.5194/tc-14-985-2020, 2020
Short summary
Short summary
Changes in the ocean around Greenland play an important role in determining how much the ice sheet will contribute to global sea level over the coming century. However, capturing these links in models is very challenging. This paper presents a strategy enabling an ensemble of ice sheet models to feel the effect of the ocean for the first time and should therefore result in a significant improvement in projections of the Greenland ice sheet's contribution to future sea level change.
Alison Delhasse, Christoph Kittel, Charles Amory, Stefan Hofer, Dirk van As, Robert S. Fausto, and Xavier Fettweis
The Cryosphere, 14, 957–965, https://doi.org/10.5194/tc-14-957-2020, https://doi.org/10.5194/tc-14-957-2020, 2020
Short summary
Short summary
The ERA5 reanalysis of the ECMWF replaced the ERA-Interim in August 2019 and has never been evaluated over Greenland. The aim was to evaluate the performance of ERA5 to simulate the near-surface climate of the Greenland Ice sheet (GrIS) against ERA-Interim and regional climate models with the help of in situ observations from the PROMICE dataset. We also highlighted that polar regional climate models are still a useful tool to study the GrIS climate compared to ERA5.
Alison Delhasse, Edward Hanna, Christoph Kittel, and Xavier Fettweis
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-332, https://doi.org/10.5194/tc-2019-332, 2020
Preprint withdrawn
Short summary
Short summary
Significant melting events over Greenland ice sheet related to unusual atmospheric pattern in summer, as observed this summer 2019, are still not considered by the new generation of Earth-system models (CMIP6) and therefore the projected surface melt increase of the ice sheet is likely to be underestimated if such changes persist in the next decades.
Marion Donat-Magnin, Nicolas C. Jourdain, Hubert Gallée, Charles Amory, Christoph Kittel, Xavier Fettweis, Jonathan D. Wille, Vincent Favier, Amine Drira, and Cécile Agosta
The Cryosphere, 14, 229–249, https://doi.org/10.5194/tc-14-229-2020, https://doi.org/10.5194/tc-14-229-2020, 2020
Short summary
Short summary
Modeling the interannual variability of the surface conditions over Antarctic glaciers is important for the identification of climate trends and climate predictions and to assess models. We simulate snow accumulation and surface melting in the Amundsen sector (West Antarctica) over 1979–2017. For all the glaciers, the interannual variability of summer snow accumulation and surface melting is driven by two distinct mechanisms related to variations in the Amundsen Sea Low strength and position.
Donald A. Slater, Fiamma Straneo, Denis Felikson, Christopher M. Little, Heiko Goelzer, Xavier Fettweis, and James Holte
The Cryosphere, 13, 2489–2509, https://doi.org/10.5194/tc-13-2489-2019, https://doi.org/10.5194/tc-13-2489-2019, 2019
Short summary
Short summary
The ocean's influence on the retreat of Greenland's tidewater glaciers is a key factor determining future sea level. By considering observations of ~200 glaciers from 1960, we find a significant relationship between retreat and melting in the ocean. Projected forwards, this relationship estimates the future evolution of Greenland's tidewater glaciers and provides a practical and empirically validated way of representing ice–ocean interaction in large-scale models used to estimate sea level rise.
Shannon L. Mason, Robin J. Hogan, Christopher D. Westbrook, Stefan Kneifel, Dmitri Moisseev, and Leonie von Terzi
Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, https://doi.org/10.5194/amt-12-4993-2019, 2019
Short summary
Short summary
The mass contents of snowflakes are critical to remotely sensed estimates of snowfall. The signatures of snow measured at three radar frequencies can distinguish fluffy, fractal snowflakes from dense and more homogeneous rimed snow. However, we show that the shape of the particle size spectrum also has a significant impact on triple-frequency radar signatures and must be accounted for when making triple-frequency radar estimates of snow that include variations in particle structure and density.
Thomas J. Ballinger, Thomas L. Mote, Kyle Mattingly, Angela C. Bliss, Edward Hanna, Dirk van As, Melissa Prieto, Saeideh Gharehchahi, Xavier Fettweis, Brice Noël, Paul C. J. P. Smeets, Carleen H. Reijmer, Mads H. Ribergaard, and John Cappelen
The Cryosphere, 13, 2241–2257, https://doi.org/10.5194/tc-13-2241-2019, https://doi.org/10.5194/tc-13-2241-2019, 2019
Short summary
Short summary
Arctic sea ice and the Greenland Ice Sheet (GrIS) are melting later in the year due to a warming climate. Through analyses of weather station, climate model, and reanalysis data, physical links are evaluated between Baffin Bay open water duration and western GrIS melt conditions. We show that sub-Arctic air mass movement across this portion of the GrIS strongly influences late summer and autumn melt, while near-surface, off-ice winds inhibit westerly atmospheric heat transfer from Baffin Bay.
Jeronimo Escribano, Alessio Bozzo, Philippe Dubuisson, Johannes Flemming, Robin J. Hogan, Laurent C.-Labonnote, and Olivier Boucher
Geosci. Model Dev., 12, 805–827, https://doi.org/10.5194/gmd-12-805-2019, https://doi.org/10.5194/gmd-12-805-2019, 2019
Short summary
Short summary
Accurate shortwave radiance computations are becoming increasingly important for some applications in atmospheric composition. In this work we propose a benchmark protocol and dataset to asses the accuracy and computing runtime of radiance calculations of radiative transfer models. It is applied to four models, showing the potential of this benchmark to evaluate the model performance under a variety of atmospheric conditions, viewing geometries, aerosol loading, and optical properties.
Sébastien Le clec'h, Sylvie Charbit, Aurélien Quiquet, Xavier Fettweis, Christophe Dumas, Masa Kageyama, Coraline Wyard, and Catherine Ritz
The Cryosphere, 13, 373–395, https://doi.org/10.5194/tc-13-373-2019, https://doi.org/10.5194/tc-13-373-2019, 2019
Short summary
Short summary
Quantifying the future contribution of the Greenland ice sheet (GrIS) to sea-level rise in response to atmospheric changes is important but remains challenging. For the first time a full representation of the feedbacks between a GrIS model and a regional atmospheric model was implemented. The authors highlight the fundamental need for representing the GrIS topography change feedbacks with respect to the atmospheric component face to the strong impact on the projected sea-level rise.
Cécile Agosta, Charles Amory, Christoph Kittel, Anais Orsi, Vincent Favier, Hubert Gallée, Michiel R. van den Broeke, Jan T. M. Lenaerts, Jan Melchior van Wessem, Willem Jan van de Berg, and Xavier Fettweis
The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, https://doi.org/10.5194/tc-13-281-2019, 2019
Short summary
Short summary
Antarctic surface mass balance (ASMB), a component of the sea level budget, is commonly estimated through modelling as observations are scarce. The polar-oriented regional climate model MAR performs well in simulating the observed ASMB. MAR and RACMO2 share common biases we relate to drifting snow transport, with a 3 times larger magnitude than in previous estimates. Sublimation of precipitation in the katabatic layer modelled by MAR is of a magnitude similar to an observation-based estimate.
Nuno Pereira, David Bolsée, Peter Sperfeld, Sven Pape, Dominique Sluse, and Gaël Cessateur
Atmos. Meas. Tech., 11, 6605–6615, https://doi.org/10.5194/amt-11-6605-2018, https://doi.org/10.5194/amt-11-6605-2018, 2018
Short summary
Short summary
The knowledge of the solar spectrum at the top of Earth's atmosphere is of great importance for climatic studies. Satellite instruments allow direct measurements; however, their calibration presents issues. It is possible to determine this spectrum precisely from Earth-based measurements as well, using the Langley plot technique and accurate calibration techniques. We present an infrared spectrum using these techniques for measurements made at the reference Mauna Loa Observatory.
Christoph Kittel, Charles Amory, Cécile Agosta, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Coraline Wyard, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 12, 3827–3839, https://doi.org/10.5194/tc-12-3827-2018, https://doi.org/10.5194/tc-12-3827-2018, 2018
Short summary
Short summary
Regional climate models (RCMs) used to estimate the surface mass balance (SMB) of Antarctica depend on boundary forcing fields including sea surface conditions. Here, we assess the sensitivity of the Antarctic SMB to perturbations in sea surface conditions with the RCM MAR using unchanged atmospheric conditions. Significant SMB anomalies are found for SSC perturbations in the range of CMIP5 global climate model biases.
Alison Delhasse, Xavier Fettweis, Christoph Kittel, Charles Amory, and Cécile Agosta
The Cryosphere, 12, 3409–3418, https://doi.org/10.5194/tc-12-3409-2018, https://doi.org/10.5194/tc-12-3409-2018, 2018
Short summary
Short summary
Since the 2000s, an atmospheric circulation change (CC) gauged by a negative summer shift in the North Atlantic Oscillation has been observed, enhancing surface melt over the Greenland Ice Sheet (GrIS). Future GrIS surface mass balance (SMB) projections are based on global climate models that do not represent this CC. The model MAR has been used to show that previous estimates of these projections could have been significantly overestimated if this current circulation pattern persists.
Edward Hanna, Xavier Fettweis, and Richard J. Hall
The Cryosphere, 12, 3287–3292, https://doi.org/10.5194/tc-12-3287-2018, https://doi.org/10.5194/tc-12-3287-2018, 2018
Short summary
Short summary
The latest/recent generations of global climate models do not simulate the recent (last 30 years) increase in atmospheric high pressure over Greenland in summer but rather projects decreasing pressure.
This difference between climate models and observations raises serious questions about the ability of the models to accurately represent future changes in Greenland climate and ice-sheet mass balance. There are also likely effects on climate predictions downstream, e.g. over Europe.
Jiangjun Ran, Miren Vizcaino, Pavel Ditmar, Michiel R. van den Broeke, Twila Moon, Christian R. Steger, Ellyn M. Enderlin, Bert Wouters, Brice Noël, Catharina H. Reijmer, Roland Klees, Min Zhong, Lin Liu, and Xavier Fettweis
The Cryosphere, 12, 2981–2999, https://doi.org/10.5194/tc-12-2981-2018, https://doi.org/10.5194/tc-12-2981-2018, 2018
Short summary
Short summary
To accurately predict future sea level rise, the mechanisms driving the observed mass loss must be better understood. Here, we combine data from the satellite gravimetry, surface mass balance, and ice discharge to analyze the mass budget of Greenland at various temporal scales. This study, for the first time, suggests the existence of a substantial meltwater storage during summer, with a peak value of 80–120 Gt in July. We highlight its importance for understanding ice sheet mass variability
Rajashree Tri Datta, Marco Tedesco, Cecile Agosta, Xavier Fettweis, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 12, 2901–2922, https://doi.org/10.5194/tc-12-2901-2018, https://doi.org/10.5194/tc-12-2901-2018, 2018
Short summary
Short summary
Surface melting on the East Antarctic Peninsula (East AP) has been linked to ice shelf collapse, including the Larsen A (1995) and Larsen B (2002) ice shelves. Regional climate models (RCMs) are a valuable tool to understand how wind patterns and general warming can impact the stability of ice shelves through surface melt. Here, we evaluate one such RCM (Modèle Atmosphérique Régionale) over the East AP, including the remaining Larsen C ice shelf, by comparing it to satellite and ground data.
Achim Heilig, Olaf Eisen, Michael MacFerrin, Marco Tedesco, and Xavier Fettweis
The Cryosphere, 12, 1851–1866, https://doi.org/10.5194/tc-12-1851-2018, https://doi.org/10.5194/tc-12-1851-2018, 2018
Short summary
Short summary
This paper presents data on temporal changes in snow and firn, which were not available before. We present data on water infiltration in the percolation zone of the Greenland Ice Sheet that improve our understanding of liquid water retention in snow and firn and mass transfer. We compare those findings with model simulations. It appears that simulated accumulation in terms of SWE is fairly accurate, while modeling of the individual parameters density and liquid water content is incorrect.
Amber A. Leeson, Emma Eastoe, and Xavier Fettweis
The Cryosphere, 12, 1091–1102, https://doi.org/10.5194/tc-12-1091-2018, https://doi.org/10.5194/tc-12-1091-2018, 2018
Short summary
Short summary
Future melting of the Greenland Ice Sheet is predicted using regional climate models (RCMs). Here, we assess the ability of the MAR RCM to reproduce observed extreme temperature events and the melt energy produced during these times at 14 locations. We find that MAR underestimates temperatures by >0.5 °C during extreme events, which leads to an underestimate in melt energy by up to 41 %. This is potentially an artefact of the data used to drive the MAR simulation and needs to be corrected for.
Robin J. Hogan, Tristan Quaife, and Renato Braghiere
Geosci. Model Dev., 11, 339–350, https://doi.org/10.5194/gmd-11-339-2018, https://doi.org/10.5194/gmd-11-339-2018, 2018
Short summary
Short summary
This paper describes a fast new method for calculating how much sunlight is absorbed and reflected by forests and other types of vegetation, rigorously taking account of the complex 3-D structure. Careful evaluation shows it to perform well even in difficult scenes with snow on the ground. The method is suitable for use within the computer models used to make weather and climate forecasts, where it has the potential to improve predictions of near-surface temperature and photosynthesis rates.
Andrew J. Tedstone, Jonathan L. Bamber, Joseph M. Cook, Christopher J. Williamson, Xavier Fettweis, Andrew J. Hodson, and Martyn Tranter
The Cryosphere, 11, 2491–2506, https://doi.org/10.5194/tc-11-2491-2017, https://doi.org/10.5194/tc-11-2491-2017, 2017
Short summary
Short summary
The bare ice albedo of the south-west Greenland ice sheet varies dramatically between years. The reasons are unclear but likely involve darkening by inorganic particulates, cryoconite and ice algae. We use satellite imagery to examine dark ice dynamics and climate model outputs to find likely climatological controls. Outcropping particulates can explain the spatial extent of dark ice, but the darkening itself is likely due to ice algae growth controlled by meltwater and light availability.
Shannon L. Mason, J. Christine Chiu, Robin J. Hogan, and Lin Tian
Atmos. Chem. Phys., 17, 11567–11589, https://doi.org/10.5194/acp-17-11567-2017, https://doi.org/10.5194/acp-17-11567-2017, 2017
Short summary
Short summary
Airborne Doppler radar measurements are used to estimate the properties of tropical stratiform rain. Doppler velocity measurements provide sufficient information to estimate the rain rate over land and also to retrieve the raindrop size distribution over ocean, addressing major uncertainties in current satellite measurements of rain. These results suggest that EarthCARE, with the first space-borne Doppler radar, will facilitate improved global measurements of rain.
Johannes Jakob Fürst, Fabien Gillet-Chaulet, Toby J. Benham, Julian A. Dowdeswell, Mariusz Grabiec, Francisco Navarro, Rickard Pettersson, Geir Moholdt, Christopher Nuth, Björn Sass, Kjetil Aas, Xavier Fettweis, Charlotte Lang, Thorsten Seehaus, and Matthias Braun
The Cryosphere, 11, 2003–2032, https://doi.org/10.5194/tc-11-2003-2017, https://doi.org/10.5194/tc-11-2003-2017, 2017
Short summary
Short summary
For the large majority of glaciers and ice caps, there is no information on the thickness of the ice cover. Any attempt to predict glacier demise under climatic warming and to estimate the future contribution to sea-level rise is limited as long as the glacier thickness is not well constrained. Here, we present a two-step mass-conservation approach for mapping ice thickness. Measurements are naturally reproduced. The reliability is readily assessible from a complementary map of error estimates.
Xavier Fettweis, Jason E. Box, Cécile Agosta, Charles Amory, Christoph Kittel, Charlotte Lang, Dirk van As, Horst Machguth, and Hubert Gallée
The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, https://doi.org/10.5194/tc-11-1015-2017, 2017
Short summary
Short summary
This paper shows that the surface melt increase over the Greenland ice sheet since the end of the 1990s has been unprecedented, with respect to the last 120 years, using a regional climate model. These simulations also suggest an increase of the snowfall accumulation through the last century before a surface mass decrease in the 2000s. Such a mass gain could have impacted the ice sheet's dynamic stability and could explain the recent observed increase of the glaciers' velocity.
Brice Noël, Willem Jan van de Berg, Horst Machguth, Stef Lhermitte, Ian Howat, Xavier Fettweis, and Michiel R. van den Broeke
The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, https://doi.org/10.5194/tc-10-2361-2016, 2016
Short summary
Short summary
We present a 1 km resolution data set (1958–2015) of daily Greenland ice sheet surface mass balance (SMB), statistically downscaled from the data of RACMO2.3 at 11 km using elevation dependence, precipitation and bare ice albedo corrections. The data set resolves Greenland narrow ablation zones and local outlet glaciers, and shows more realistic SMB patterns, owing to enhanced runoff at the ice sheet margins. An evaluation of the product against SMB measurements shows improved agreement.
Nicole-Jeanne Schlegel, David N. Wiese, Eric Y. Larour, Michael M. Watkins, Jason E. Box, Xavier Fettweis, and Michiel R. van den Broeke
The Cryosphere, 10, 1965–1989, https://doi.org/10.5194/tc-10-1965-2016, https://doi.org/10.5194/tc-10-1965-2016, 2016
Short summary
Short summary
We investigate Greenland Ice Sheet mass change from 2003–2012 by comparing observations from GRACE with state-of-the-art atmospheric and ice sheet model simulations. We find that the largest discrepancies (in the northwest and southeast) are likely controlled by errors in modeled surface climate as well as ice–ocean interaction and hydrological processes (not included in the models). Models should consider such processes at monthly to seasonal resolutions in order to improve future projections.
Lora S. Koenig, Alvaro Ivanoff, Patrick M. Alexander, Joseph A. MacGregor, Xavier Fettweis, Ben Panzer, John D. Paden, Richard R. Forster, Indrani Das, Joesph R. McConnell, Marco Tedesco, Carl Leuschen, and Prasad Gogineni
The Cryosphere, 10, 1739–1752, https://doi.org/10.5194/tc-10-1739-2016, https://doi.org/10.5194/tc-10-1739-2016, 2016
Short summary
Short summary
Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor surface mass balance in order to improve sea-level rise predictions. Here, we quantify the net annual accumulation over the Greenland Ice Sheet, which comprises the largest component of surface mass balance, at a higher spatial resolution than currently available using high-resolution, airborne-radar data.
Patrick M. Alexander, Marco Tedesco, Nicole-Jeanne Schlegel, Scott B. Luthcke, Xavier Fettweis, and Eric Larour
The Cryosphere, 10, 1259–1277, https://doi.org/10.5194/tc-10-1259-2016, https://doi.org/10.5194/tc-10-1259-2016, 2016
Short summary
Short summary
We compared satellite-derived estimates of spatial and seasonal variations in Greenland Ice Sheet mass with a set of model simulations, revealing an agreement between models and satellite estimates for the ice-sheet-wide seasonal fluctuations in mass, but disagreement at finer spatial scales. The model simulations underestimate low-elevation mass loss. Improving the ability of models to capture variations and trends in Greenland Ice Sheet mass is important for estimating future sea level rise.
Marco Tedesco, Sarah Doherty, Xavier Fettweis, Patrick Alexander, Jeyavinoth Jeyaratnam, and Julienne Stroeve
The Cryosphere, 10, 477–496, https://doi.org/10.5194/tc-10-477-2016, https://doi.org/10.5194/tc-10-477-2016, 2016
Short summary
Short summary
Summer surface albedo over Greenland decreased at a rate of 0.02 per decade between 1996 and 2012. The decrease is due to snow grain growth, the expansion of bare ice areas, and trends in light-absorbing impurities on snow and ice surfaces. Neither aerosol models nor in situ observations indicate increasing trends in impurities in the atmosphere over Greenland. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening.
Arthur Capet, Emil V. Stanev, Jean-Marie Beckers, James W. Murray, and Marilaure Grégoire
Biogeosciences, 13, 1287–1297, https://doi.org/10.5194/bg-13-1287-2016, https://doi.org/10.5194/bg-13-1287-2016, 2016
Short summary
Short summary
We show that the Black Sea oxygen inventory has decreased by 44 % from 1955 to 2015, while oxygen penetration depth decreased from 140 to 90 m. A transient increase of the oxygen inventory during 1985–1995 supported the perception of a stable oxic interface and of a general recovery of the Black Sea after a strong eutrophication phase (1970–1990). Instead, we show that ongoing high oxygen consumption was masked by high ventilation rates, which are now limited by atmospheric warming.
M. Navari, S. A. Margulis, S. M. Bateni, M. Tedesco, P. Alexander, and X. Fettweis
The Cryosphere, 10, 103–120, https://doi.org/10.5194/tc-10-103-2016, https://doi.org/10.5194/tc-10-103-2016, 2016
Short summary
Short summary
An ensemble batch smoother was used to assess the feasibility of generating a reanalysis estimate of the Greenland ice sheet (GrIS) surface mass fluxes (SMF) via integrating measured ice surface temperatures with a regional climate model estimate. The results showed that assimilation of IST were able to overcome uncertainties in meteorological forcings that drive the GrIS surface processes. We showed that the proposed methodology is able to generate posterior reanalysis estimates of the SMF.
C. Agosta, X. Fettweis, and R. Datta
The Cryosphere, 9, 2311–2321, https://doi.org/10.5194/tc-9-2311-2015, https://doi.org/10.5194/tc-9-2311-2015, 2015
Short summary
Short summary
Estimates of the Antarctic surface mass balance with regional climate models (RCMs) require proper fields for forcing; hence we evaluate 41 CMIP5 climate models over Antarctica and include six reanalyses. Most of the models are biased compared to ERA-Interim, ACCESS1-3 being the best choice for forcing RCMs. Climate change is less sensitive to global warming than it is to the present-day simulated sea ice and to the feedback between sea-ice decrease and temperature increase around Antarctica.
V. Masson-Delmotte, H. C. Steen-Larsen, P. Ortega, D. Swingedouw, T. Popp, B. M. Vinther, H. Oerter, A. E. Sveinbjornsdottir, H. Gudlaugsdottir, J. E. Box, S. Falourd, X. Fettweis, H. Gallée, E. Garnier, V. Gkinis, J. Jouzel, A. Landais, B. Minster, N. Paradis, A. Orsi, C. Risi, M. Werner, and J. W. C. White
The Cryosphere, 9, 1481–1504, https://doi.org/10.5194/tc-9-1481-2015, https://doi.org/10.5194/tc-9-1481-2015, 2015
Short summary
Short summary
The deep NEEM ice core provides the oldest Greenland ice core record, enabling improved understanding of the response of ice core records to local climate. Here, we focus on shallow ice cores providing a stack record of accumulation and water-stable isotopes spanning the past centuries. For the first time, we document the ongoing warming in a Greenland ice core. By combining our data with other Greenland ice cores and model results, we characterise the spatio-temporal patterns of variability.
M. D. Fielding, J. C. Chiu, R. J. Hogan, G. Feingold, E. Eloranta, E. J. O'Connor, and M. P. Cadeddu
Atmos. Meas. Tech., 8, 2663–2683, https://doi.org/10.5194/amt-8-2663-2015, https://doi.org/10.5194/amt-8-2663-2015, 2015
C. Lang, X. Fettweis, and M. Erpicum
The Cryosphere, 9, 945–956, https://doi.org/10.5194/tc-9-945-2015, https://doi.org/10.5194/tc-9-945-2015, 2015
Short summary
Short summary
We simulated the 21st century Svalbard SMB with the regional model MAR (RCP8.5 scenario). Melt is projected to increase gently up to 2050 and then dramatically increase, with a larger increase in the south of the archipelago. This difference is due to larger ice albedo decrease in the south causing larger increase of absorbed solar radiation. The ablation area is projected to disappear over the entire Svalbard by 2085. The SMB decrease compared to present is projected to contribute 7mm to SLR.
C. Lang, X. Fettweis, and M. Erpicum
The Cryosphere, 9, 83–101, https://doi.org/10.5194/tc-9-83-2015, https://doi.org/10.5194/tc-9-83-2015, 2015
Short summary
Short summary
We have modelled the surface mass balance (SMB) of Svalbard with the model MAR over 1979--2013. The mean SMB is slightly negative and the Svalbard glaciers are losing mass through surface processes (mainly precipitation and runoff), but there has been no acceleration of the surface melt, contrary to Greenland where melt records have been broken since 2006. We attributed it to a change in atmospheric circulation, resulting in northerly cold flows over Svalbard damping Arctic warming.
A. Belleflamme, X. Fettweis, and M. Erpicum
The Cryosphere, 9, 53–64, https://doi.org/10.5194/tc-9-53-2015, https://doi.org/10.5194/tc-9-53-2015, 2015
Short summary
Short summary
The 2007-2012 summertime circulation anomaly over the Arctic region (i.e. more high pressure systems over the Beaufort Sea, the Canadian Arctic Archipelago, and Greenland) is put in a historical perspective. While the 2007-2012 anomaly seems to be exceptional, similar circulation conditions have occurred since 1871, on the basis of five reanalyses (ERA-Interim, ERA-40, NCEP/NCAR, ERA-20C, 20CRv2). The attribution of this anomaly (natural variability or global warming) remains debatable.
P. M. Alexander, M. Tedesco, X. Fettweis, R. S. W. van de Wal, C. J. P. P. Smeets, and M. R. van den Broeke
The Cryosphere, 8, 2293–2312, https://doi.org/10.5194/tc-8-2293-2014, https://doi.org/10.5194/tc-8-2293-2014, 2014
B. Noël, X. Fettweis, W. J. van de Berg, M. R. van den Broeke, and M. Erpicum
The Cryosphere, 8, 1871–1883, https://doi.org/10.5194/tc-8-1871-2014, https://doi.org/10.5194/tc-8-1871-2014, 2014
J. C. Chiu, J. A. Holmes, R. J. Hogan, and E. J. O'Connor
Atmos. Chem. Phys., 14, 8389–8401, https://doi.org/10.5194/acp-14-8389-2014, https://doi.org/10.5194/acp-14-8389-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 181–194, https://doi.org/10.5194/tc-8-181-2014, https://doi.org/10.5194/tc-8-181-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 195–208, https://doi.org/10.5194/tc-8-195-2014, https://doi.org/10.5194/tc-8-195-2014, 2014
W. Colgan, W. Abdalati, M. Citterio, B. Csatho, X. Fettweis, S. Luthcke, G. Moholdt, and M. Stober
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-537-2014, https://doi.org/10.5194/tcd-8-537-2014, 2014
Revised manuscript not accepted
A. Capet, J.-M. Beckers, and M. Grégoire
Biogeosciences, 10, 3943–3962, https://doi.org/10.5194/bg-10-3943-2013, https://doi.org/10.5194/bg-10-3943-2013, 2013
M. Tedesco, X. Fettweis, T. Mote, J. Wahr, P. Alexander, J. E. Box, and B. Wouters
The Cryosphere, 7, 615–630, https://doi.org/10.5194/tc-7-615-2013, https://doi.org/10.5194/tc-7-615-2013, 2013
C. L. Vernon, J. L. Bamber, J. E. Box, M. R. van den Broeke, X. Fettweis, E. Hanna, and P. Huybrechts
The Cryosphere, 7, 599–614, https://doi.org/10.5194/tc-7-599-2013, https://doi.org/10.5194/tc-7-599-2013, 2013
X. Fettweis, B. Franco, M. Tedesco, J. H. van Angelen, J. T. M. Lenaerts, M. R. van den Broeke, and H. Gallée
The Cryosphere, 7, 469–489, https://doi.org/10.5194/tc-7-469-2013, https://doi.org/10.5194/tc-7-469-2013, 2013
X. Fettweis, E. Hanna, C. Lang, A. Belleflamme, M. Erpicum, and H. Gallée
The Cryosphere, 7, 241–248, https://doi.org/10.5194/tc-7-241-2013, https://doi.org/10.5194/tc-7-241-2013, 2013
B. Franco, X. Fettweis, and M. Erpicum
The Cryosphere, 7, 1–18, https://doi.org/10.5194/tc-7-1-2013, https://doi.org/10.5194/tc-7-1-2013, 2013
Related subject area
Atmospheric sciences
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
A Novel Method for Quantifying the Contribution of Regional Transport to PM2.5 in Beijing (2013–2020): Combining Machine Learning with Concentration-Weighted Trajectory Analysis
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
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
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. 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 in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
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
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
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
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
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
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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
Short summary
Short summary
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.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
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
Short summary
Short summary
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.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
Short summary
Short summary
The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
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
Short summary
Short summary
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.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-157, https://doi.org/10.5194/gmd-2024-157, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study combines Machine Learning with Concentration-Weighted Trajectory Analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
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
Short summary
Short summary
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.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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
Short summary
Short summary
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.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Cited articles
Amory, C., Kittel, C., Le Toumelin, L., Agosta, C., Delhasse, A., Favier, V., and Fettweis, X.: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adélie Land, East Antarctica, Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, 2021. a, b
Benas, N., Solodovnik, I., Stengel, M., Hüser, I., Karlsson, K.-G., Håkansson, N., Johansson, E., Eliasson, S., Schröder, M., Hollmann, R., and Meirink, J. F.: CLAAS-3: the third edition of the CM SAF cloud data record based on SEVIRI observations, Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, 2023. a
Bozzo, A., Rémy, S., Benedetti, A., Flemming, J., Bechtold, P., Rodwell, M., and Morcrette, J.-J.: Implementation of a CAMS-based aerosol climatology in the IFS, Tech. rep., European Centre for Medium-Range Weather Forecasts, ECMWF Technical Report 801, https://doi.org/10.21957/84ya94mls, 2017. a, b
Doutreloup, S.: Évolution actuelle et future des précipitations convectives sur la Belgique et la région du Lac Victoria (Afrique équatoriale de l'Est) à l’aide du modèle climatique régional MAR, PhD thesis, University of Liège, https://doi.org/10.1051/climat/202219001, 2019. a
Fettweis, X.: MARv3 – Modèle Atmosphérique Régional, GitLab [code], https://gitlab.com/Mar-Group/MARv3 (last access: 28 January 2025), 2024. a
Fettweis, X. and Grailet, J.-F.: MAR (Modèle Atmosphérique Régional) version 3.14, Zenodo [code], https://doi.org/10.5281/zenodo.13151275, 2024. a, b
Fettweis, X., Franco, B., Tedesco, M., van Angelen, J. H., Lenaerts, J. T. M., van den Broeke, M. R., and Gallée, H.: Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR, The Cryosphere, 7, 469–489, https://doi.org/10.5194/tc-7-469-2013, 2013a. a, b
Fettweis, X., Hanna, E., Lang, C., Belleflamme, A., Erpicum, M., and Gallée, H.: Brief communication “Important role of the mid-tropospheric atmospheric circulation in the recent surface melt increase over the Greenland ice sheet”, The Cryosphere, 7, 241–248, https://doi.org/10.5194/tc-7-241-2013, 2013b. a
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a, b, c, d, e
Fettweis, X., Ambroise, B., David, P.-M., Ghilain, N., Paul, P., and Wuest, C.: Current evolution (1960–2021) of the snow cover in the French Vosges massif with the help of the regional climate MAR model, Bulletin de la Société Géographique de Liège, 80, 19–41, 2023. a
Flemming, J., Benedetti, A., Inness, A., Engelen, R. J., Jones, L., Huijnen, V., Remy, S., Parrington, M., Suttie, M., Bozzo, A., Peuch, V.-H., Akritidis, D., and Katragkou, E.: The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003–2015, Atmos. Chem. Phys., 17, 1945–1983, https://doi.org/10.5194/acp-17-1945-2017, 2017. a, b, c, d
Fu, Q., Yang, P., and Sun, W. B.: An Accurate Parameterization of the Infrared Radiative Properties of Cirrus Clouds for Climate Models, J. Climate, 11, 2223–2237, 1998. a
Gallée, H.: Simulation of the Mesocyclonic Activity in the Ross Sea, Antarctica, Mon. Weather Rev., 123, 2051–2069, https://doi.org/10.1175/1520-0493(1995)123<2051:SOTMAI>2.0.CO;2, 1995. a
Gallée, H., Moufouma-Okia, W., Bechtold, P., Brasseur, O., Dupays, I., Marbaix, P., Messager, C., Ramel, R., and Lebel, T.: A high-resolution simulation of a West African rainy season using a regional climate model, J. Geophys. Res., 109, D05108, https://doi.org/10.1029/2003JD004020, 2004. a
Gallée, H., Trouvilliez, A., Agosta, C., Genthon, C., Favier, V., and Naaim-Bouvet, F.: Transport of Snow by the Wind: A Comparison Between Observations in Adélie Land, Antarctica, and Simulations Made with the Regional Climate Model MAR, Bound.-Lay. Meteorol., 146, 133–147, 2013. a
Goody, R., West, R., Chen, L., and Crisp, D.: The correlated-k method for radiation calculations in nonhomogeneous atmospheres, J. Quant. Spectrosc. Ra., 42, 539–550, 1989. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 150, 4014–4048, https://doi.org/10.1002/qj.4803, 2020. a
Hourdin, F., Foujols, M.-A., Codron, F., Guemas, V., Dufresne, J.-L., Bony, S., Denvil, S., Guez, L., Lott, F., Ghattas, J., Braconnot, P., Marti, O., Meurdesoif, Y., and Bopp, L.: Climate and sensitivity of the IPSL–CM5A coupled model: Impact of the LMDZ atmospheric grid configuration, Clim. Dynam., 40, 2167–2192, 2013. a
Jacob, D., Elizalde, A., Haensler, A., Hagemann, S., Kumar, P., Podzun, R., Rechid, D., Remedio, A. R., Saeed, F., Sieck, K., Teichmann, C., and Wilhelm, C.: Assessing the Transferability of the Regional Climate Model REMO to Different COordinated Regional Climate Downscaling EXperiment (CORDEX) Regions, Atmosphere, 3, 181–199, 2012. a
Kittel, C.: Present and future sensitivity of the Antarctic surface mass balance to oceanic and atmospheric forcings: insights with the regional climate model MAR, PhD thesis, University of Liège, https://hdl.handle.net/2268/258491 (last access: 28 January 2025), 2021. a
Kittel, C., Amory, C., Hofer, S., Agosta, C., Jourdain, N. C., Gilbert, E., Le Toumelin, L., Vignon, É., Gallée, H., and Fettweis, X.: Clouds drive differences in future surface melt over the Antarctic ice shelves, The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, 2022. a, b, c, d
Lazzari, P., Salon, S., Terzić, E., Gregg, W. W., D'Ortenzio, F., Vellucci, V., Organelli, E., and Antoine, D.: Assessment of the spectral downward irradiance at the surface of the Mediterranean Sea using the radiative Ocean-Atmosphere Spectral Irradiance Model (OASIM), Ocean Sci., 17, 675–697, https://doi.org/10.5194/os-17-675-2021, 2021a. a
Lazzari, P., Álvarez, E., Terzić, E., Cossarini, G., Chernov, I., D’Ortenzio, F., and Organelli, E.: CDOM Spatiotemporal Variability in the Mediterranean Sea: A Modelling Study, Journal of Marine Science and Engineering, 9, 176, https://doi.org/10.3390/jmse9020176, 2021b. a, b
Lefebre, F., Gallée, H., van Ypersele, J., and Greuell, W.: Modeling of snow and ice melt at ETH-camp (West Greenland): a study of surface albedo, J. Geophys. Res.-Atmos., 108, 4231, https://doi.org/10.1029/2001JD001160, 2003. a, b
Manners, J., Edwards, J. M., Hill, P., and Thelen, J.-C.: SOCRATES (Suite Of Community RAdiative Transfer codes based on Edwards and Slingo) Technical Guide, Tech. rep., MET Office, https://homepages.see.leeds.ac.uk/~lecsjed/winscpuse/socrates_userguide.pdf (last access: 28 January 2025), 2015. a
McKenzie, R., Blumthaler, M., Diaz, S., Fioletov, V., Herman, J., Seckmeyer, G., Smedley, A., and Webb, A.: Rationalizing nomenclature for UV doses and effects on humans, CIE 209:2014 and WMO-GAW Report No. 211 Joint Publication, https://files.cie.co.at/cie209_2014.pdf (last access: 28 January 2025), 2014. a, b, c, d
Ménégoz, M., Valla, E., Jourdain, N. C., Blanchet, J., Beaumet, J., Wilhelm, B., Gallée, H., Fettweis, X., Morin, S., and Anquetin, S.: Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010, Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, 2020. a
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016. a
Ramanathan, V., Cess, R., Harrison, E., Minnis, P., Barkstrom, B., Ahmad, E., and Hartmann, D.: Cloud-Radiative Forcing and Climate: Results from The Earth Radiation Budget Experiment, Science, 243, 57–63, 1989. a
Shupe, M. D. and Intrieri, J. M.: Cloud Radiative Forcing of the Arctic Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith Angle, J. Climate, 17, 616–628, https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2, 2004. a
Tegen, I., Hollring, P., Chin, M., Fung, I., Jacob, D., and Penner, J.: Contribution of different aerosol species to the global aerosol extinction optical thickness: Estimates from model results, J. Geophys. Res., 102, 23895–23915, https://doi.org/10.1029/97JD01864, 1997. a, b, c
Trigo, I., Dacamara, C., Viterbo, P., Roujean, J.-L., Olesen, F., Barroso, C., Camacho de Coca, F., Carrer, D., Freitas, S., García-Haro, J., Geiger, B., Gellens-Meulenberghs, F., Ghilain, N., Meliá, J., Pessanha, L., Siljamo, N., and Arboleda, A.: The Satellite Application Facility for Land Surface Analysis, Int. J. Remote Sens., 32, 2725–2744, 2011a. a, b, c
Trigo, I., Monteiro, I., and Freitas, S.: Validation Report Down-welling Longwave Flux (DSLF) – PRODUCTS: LSA-10 (MDSLF), LSA-11 (EDSLF), LSA-12 (DIDSLF), Tech. rep., EUMETSAT Satellite Application Facility on Land Surface Analysis, https://nextcloud.lsasvcs.ipma.pt/s/9BQa6e2CAaJdjRZ?dir=/VR-Validation_Report (last access: 28 January 2025), 2011b. a, b
Uppala, S. M., Kållberg, P., Simmons, A., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J., Haseler, J., Hernandez, A., Kelly, G., Li, X., Onogo, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A., Jenne, R., Mcnally, A. P., Mahfouf, J. F., Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woolen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, 2005. a, b, c
Van Tricht, K., Lhermitte, S., Lenaerts, J., Gorodetskaya, I., L'Ecuyer, T., Noël, B., Van den Broeke, M., Turner, D., and Lipzig, N.: Clouds enhance Greenland ice sheet meltwater runoff, Nat. Commun., 7, 10266, https://doi.org/10.1038/ncomms10266, 2016. a
Van Vuuren, D., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S., and Rose, S.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, 2011. a
Wang, Y., Yang, S., Chen, G., Bao, Q., and Li, J.: Evaluating two diagnostic schemes of cloud-fraction parameterization using the CloudSat data, Atmos. Res., 282, 106510, https://doi.org/10.1016/j.atmosres.2022.106510, 2022. a, b
Weverberg, K., Vogelmann, A., Lin, W., Luke, E., Cialella, A., Minnis, P., Khaiyer, M., Boer, E., and Jensen, M.: The Role of Cloud Microphysics Parameterization in the Simulation of Mesoscale Convective System Clouds and Precipitation in the Tropical Western Pacific, J. Atmos. Sci., 70, 1104–1128, 2013. a
Weverberg, K., Morcrette, C., and Boutle, I.: A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity, Mon. Weather Rev., 149, 859–878, https://doi.org/10.1175/MWR-D-20-0230.1, 2021a. a
Weverberg, K., Morcrette, C., Boutle, I., Furtado, K., and Field, P.: A Bimodal Diagnostic Cloud Fraction Parameterization. Part I: Motivating Analysis and Scheme Description, Mon. Weather Rev., 149, 841–857, https://doi.org/10.1175/MWR-D-20-0224.1, 2021b. a
WHO: Global solar UV index : a practical guide, Geneva: World Health Organization (WHO), World Meteorological Organization (WMO), United Nations Environment Program (UNEP), and International Commission on Non-Ionizing Radiation Protection (ICNRP), https://www.who.int/publications/i/item/9241590076 (last access: 28 January 2025), 2002. a, b
Wyard, C., Scholzen, C., Fettweis, X., Van Campenhout, J., and François, L.: Decrease in climatic conditions favouring floods in the south-east of Belgium over 1959–2010 using the regional climate model MAR, Int. J. Climatol., 37, 2782–2796, 2017. a
Wyard, C., Doutreloup, S., Belleflamme, A., Wild, M., and Fettweis, X.: Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR, Atmosphere, 9, 262, https://doi.org/10.3390/atmos9070262, 2018. a, b, c
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting...
