Articles | Volume 8, issue 3
https://doi.org/10.5194/gmd-8-579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
12 Mar 2015
Model evaluation paper |
| 12 Mar 2015
A statistical downscaling method for daily air temperature in data-sparse, glaciated mountain environments
Institute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
B. Marzeion
Institute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
Climate System Research Group, Institute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Nuremberg, Germany
Related authors
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
Short summary
Short summary
This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Johannes Horak, Marlis Hofer, Fabien Maussion, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Hydrol. Earth Syst. Sci., 23, 2715–2734, https://doi.org/10.5194/hess-23-2715-2019, https://doi.org/10.5194/hess-23-2715-2019, 2019
Short summary
Short summary
This study presents an in-depth evaluation of the Intermediate Complexity Atmospheric Research (ICAR) model for high-resolution precipitation fields in complex topography. ICAR is evaluated with data from weather stations located in the Southern Alps of New Zealand. While ICAR underestimates rainfall amounts, it clearly improves over a coarser global model and shows potential to generate precipitation fields for long-term impact studies focused on the local impact of a changing global climate.
Wolfgang Gurgiser, Irmgard Juen, Katrin Singer, Martina Neuburger, Simone Schauwecker, Marlis Hofer, and Georg Kaser
Earth Syst. Dynam., 7, 499–515, https://doi.org/10.5194/esd-7-499-2016, https://doi.org/10.5194/esd-7-499-2016, 2016
Short summary
Short summary
Working on the interface of water availability and water demand in a small Andean catchment, peasants’ reports on detrimental precipitation changes during the last decades have attracted our scientific interest. We could not confirm any precipitation trends in this period with nearby precipitation records, but we found precipitation patterns that very likely pose challenges for rain-fed farming – in addition to potential other stresses by environmental and sociopolitical changes.
Florentin Hofmeister, Xinyang Fan, Madlene Pfeiffer, Ben Marzeion, Bettina Schaefli, and Gabriele Chiogna
EGUsphere, https://doi.org/10.5194/egusphere-2025-3256, https://doi.org/10.5194/egusphere-2025-3256, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We use the WRF model for dynamically downscaling a global reanalysis product for the period 1850 to 2015 for the central European Alps. We demonstrate a workflow for transferring coarse-resolution (2 km) WRF temperature and precipitation to a much finer spatial resolution (25 m) of a physics-based hydrological model (WaSiM) and evaluate the results in a multi-data approach covering different simulation periods. Our results highlight the need for plausible and consistent elevation gradients.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Maria Kappelsberger, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
The Cryosphere, 19, 1789–1824, https://doi.org/10.5194/tc-19-1789-2025, https://doi.org/10.5194/tc-19-1789-2025, 2025
Short summary
Short summary
The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean processes related to the mass balance of glaciers in northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79° N Glacier. We find that together, the different in situ and remote sensing observations and model simulations reveal a consistent picture of a coupled atmosphere–ice sheet–ocean system that has entered a phase of major change.
David Ibel, Thomas Mölg, and Christian Sommer
EGUsphere, https://doi.org/10.5194/egusphere-2025-415, https://doi.org/10.5194/egusphere-2025-415, 2025
Short summary
Short summary
As (tropical) glaciers retreat on a global scale, we analysed area changes of the Puncak Jaya glaciers in South-East Asia on West Papua, Indonesia using high resolution optical satellite imagery and historical glacier accounts from analogue maps. The results show a decrease of total glacier surface area by more than 99 % since 1850 and by 64 % since the last survey in 2018, with current glacier area (in 2024) amounting to 0.165 km2. Puncak Jaya glaciers will likely disappear around 2030.
Jan-Hendrik Malles, Ben Marzeion, and Paul G. Myers
Earth Syst. Dynam., 16, 347–377, https://doi.org/10.5194/esd-16-347-2025, https://doi.org/10.5194/esd-16-347-2025, 2025
Short summary
Short summary
Glaciers in the high-latitude Northern Hemisphere (outside Greenland) are losing mass at roughly half the Greenland ice sheet's rate. Still, this is usually not included in the freshwater input data for ocean circulation models. Also, the submarine melt of glaciers (outside the ice sheets) has not been quantified yet. We tackle both issues by using a glacier model's output as additional fresh water for the ocean model and by using the ocean model's output to model submarine melt.
Harry Zekollari, Matthias Huss, Lilian Schuster, Fabien Maussion, David R. Rounce, Rodrigo Aguayo, Nicolas Champollion, Loris Compagno, Romain Hugonnet, Ben Marzeion, Seyedhamidreza Mojtabavi, and Daniel Farinotti
The Cryosphere, 18, 5045–5066, https://doi.org/10.5194/tc-18-5045-2024, https://doi.org/10.5194/tc-18-5045-2024, 2024
Short summary
Short summary
Glaciers are major contributors to sea-level rise and act as key water resources. Here, we model the global evolution of glaciers under the latest generation of climate scenarios. We show that the type of observations used for model calibration can strongly affect the projections at the local scale. Our newly projected 21st century global mass loss is higher than the current community estimate as reported in the latest Intergovernmental Panel on Climate Change (IPCC) report.
Thomas Mölg, Jan C. Schubert, Annette Debel, Steffen Höhnle, Kathy Steppe, Sibille Wehrmann, and Achim Bräuning
Geosci. Commun., 7, 215–225, https://doi.org/10.5194/gc-7-215-2024, https://doi.org/10.5194/gc-7-215-2024, 2024
Short summary
Short summary
We examine the understanding of weather and climate impacts on forest health in high school students. Climate physics, tree ring science, and educational research collaborate to provide an online platform that captures the students’ observations, showing they translate the measured weather and basic tree responses well. However, students hardly ever detect the causal connections. This result will help refine future classroom concepts and public climate change communication on changing forests.
Muhammad Shafeeque, Jan-Hendrik Malles, Anouk Vlug, Marco Möller, and Ben Marzeion
EGUsphere, https://doi.org/10.5194/egusphere-2024-2184, https://doi.org/10.5194/egusphere-2024-2184, 2024
Short summary
Short summary
The study explores how Greenland's peripheral glaciers will change due to future climate change using OGGM. They might lose 52 % of ice mass. We predict changes in ice discharge versus melting, affecting fjords, sea levels, and ocean currents. Freshwater runoff composition, seasonality, and peak water timing vary by regions and scenarios. Our findings stress the importance of reducing greenhouse gases to minimize impacts on these glaciers, which influence local ecosystems and global sea level.
Annelies Voordendag, Brigitta Goger, Rainer Prinz, Tobias Sauter, Thomas Mölg, Manuel Saigger, and Georg Kaser
The Cryosphere, 18, 849–868, https://doi.org/10.5194/tc-18-849-2024, https://doi.org/10.5194/tc-18-849-2024, 2024
Short summary
Short summary
Wind-driven snow redistribution affects glacier mass balance. A case study of Hintereisferner glacier in Austria used high-resolution observations and simulations to model snow redistribution. Simulations matched observations, showing the potential of the model for studying snow redistribution on other mountain glaciers.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
Short summary
Short summary
We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
Short summary
Short summary
We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
Short summary
Short summary
Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Ben Marzeion
Earth Syst. Dynam., 12, 1057–1060, https://doi.org/10.5194/esd-12-1057-2021, https://doi.org/10.5194/esd-12-1057-2021, 2021
Short summary
Short summary
The oceans are typically darker than land surfaces. Expanding oceans through sea-level rise may thus lead to a darker planet Earth, reflecting less sunlight. The additionally absorbed sunlight may heat planet Earth, leading to further sea-level rise. Here, we provide a rough estimate of the strength of this feedback: it turns out to be very weak, but clearly positive, thereby destabilizing the Earth system.
Jan-Hendrik Malles and Ben Marzeion
The Cryosphere, 15, 3135–3157, https://doi.org/10.5194/tc-15-3135-2021, https://doi.org/10.5194/tc-15-3135-2021, 2021
Short summary
Short summary
To better estimate the uncertainty in glacier mass change modeling during the 20th century we ran an established model with an ensemble of meteorological data sets. We find that the total ensemble uncertainty, especially in the early 20th century, when glaciological and meteorological observations at glacier locations were sparse, increases considerably compared to individual ensemble runs. This stems from regions with a lot of ice mass but few observations (e.g., Greenland periphery).
Gerard H. Roe, John Erich Christian, and Ben Marzeion
The Cryosphere, 15, 1889–1905, https://doi.org/10.5194/tc-15-1889-2021, https://doi.org/10.5194/tc-15-1889-2021, 2021
Short summary
Short summary
The worldwide retreat of mountain glaciers and consequent loss of ice mass is one of the most obvious signs of a changing climate and has significant implications for the hydrology and natural hazards in mountain landscapes. Consistent with our understanding of the human role in temperature change, we demonstrate that the central estimate of the size of the human-caused mass loss is essentially 100 % of the observed loss. This assessment resolves some important inconsistencies in the literature.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
Short summary
Short summary
This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Emily Collier and Thomas Mölg
Earth Syst. Sci. Data, 12, 3097–3112, https://doi.org/10.5194/essd-12-3097-2020, https://doi.org/10.5194/essd-12-3097-2020, 2020
Short summary
Short summary
As part of a recent project that aims to investigate the impact of climate change on forest ecosystems in Bavaria, we developed a high-resolution atmospheric dataset, BAYWRF, for this region that covers the period of September 1987 to August 2018. The data reproduce observed variability in recent meteorological conditions well and provide a useful tool for linking large-scale climate change to local impacts on economic, societal, ecological, and agricultural processes.
Catrin Stadelmann, Johannes Jakob Fürst, Thomas Mölg, and Matthias Braun
The Cryosphere, 14, 3399–3406, https://doi.org/10.5194/tc-14-3399-2020, https://doi.org/10.5194/tc-14-3399-2020, 2020
Short summary
Short summary
The glaciers on Kilimanjaro are unique indicators for climatic changes in the tropical midtroposphere of Africa. A history of severe glacier area loss raises concerns about an imminent future disappearance. Yet the remaining ice volume is not well known. Here, we reconstruct ice thickness maps for the two largest remaining ice bodies to assess the current glacier state. We believe that our approach could provide a means for a glacier-specific calibration of reconstructions on different scales.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851, https://doi.org/10.5194/hess-24-4831-2020, https://doi.org/10.5194/hess-24-4831-2020, 2020
Short summary
Short summary
We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Thomas Mölg, Douglas R. Hardy, Emily Collier, Elena Kropač, Christina Schmid, Nicolas J. Cullen, Georg Kaser, Rainer Prinz, and Michael Winkler
Earth Syst. Dynam., 11, 653–672, https://doi.org/10.5194/esd-11-653-2020, https://doi.org/10.5194/esd-11-653-2020, 2020
Short summary
Short summary
The glaciers on Kilimanjaro summit are like sample spots of the climate in the tropical mid-troposphere. Measurements of air temperature, air humidity, and precipitation with automated weather stations show that the differences in these meteorological elements between two altitudes (~ 5600 and ~ 5900 m) vary significantly over the day and the seasons, in concert with airflow dynamics around the mountain. Knowledge of these variations will improve atmosphere and cryosphere models.
Jenny V. Turton, Thomas Mölg, and Emily Collier
Earth Syst. Sci. Data, 12, 1191–1202, https://doi.org/10.5194/essd-12-1191-2020, https://doi.org/10.5194/essd-12-1191-2020, 2020
Short summary
Short summary
The Northeast Greenland Ice Stream drains approximately 12 % of the entire Greenland ice sheet and could contribute over 1 m of sea level rise if it were to completely disappear. However, this region is a relatively new research area. Here we provide an atmospheric modelling dataset from 2014 to 2018, which includes many meteorological and radiation variables. The model data have been compared to weather stations and show good agreement. This dataset has many future applications.
Julia Eis, Fabien Maussion, and Ben Marzeion
The Cryosphere, 13, 3317–3335, https://doi.org/10.5194/tc-13-3317-2019, https://doi.org/10.5194/tc-13-3317-2019, 2019
Short summary
Short summary
To provide estimates of past glacier mass changes, an adequate initial state is required. However, information about past glacier states at regional or global scales is largely incomplete. Our study presents a new way to initialize the Open Global Glacier Model from past climate information and present-day geometries. We show that even with perfectly known but incomplete boundary conditions, the problem of model initialization leads to nonunique solutions, and we propose an ensemble approach.
Beatriz Recinos, Fabien Maussion, Timo Rothenpieler, and Ben Marzeion
The Cryosphere, 13, 2657–2672, https://doi.org/10.5194/tc-13-2657-2019, https://doi.org/10.5194/tc-13-2657-2019, 2019
Short summary
Short summary
We have implemented a frontal ablation parameterization into the Open Global Glacier Model and have shown that inversion methods based on mass conservation systematically underestimate the mass turnover (and therefore the thickness) of tidewater glaciers when neglecting frontal ablation. This underestimation can rise up to 19 % on a regional scale. Not accounting for frontal ablation will have an impact on the estimate of the glaciers’ potential contribution to sea level rise.
Johannes Horak, Marlis Hofer, Fabien Maussion, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Hydrol. Earth Syst. Sci., 23, 2715–2734, https://doi.org/10.5194/hess-23-2715-2019, https://doi.org/10.5194/hess-23-2715-2019, 2019
Short summary
Short summary
This study presents an in-depth evaluation of the Intermediate Complexity Atmospheric Research (ICAR) model for high-resolution precipitation fields in complex topography. ICAR is evaluated with data from weather stations located in the Southern Alps of New Zealand. While ICAR underestimates rainfall amounts, it clearly improves over a coarser global model and shows potential to generate precipitation fields for long-term impact studies focused on the local impact of a changing global climate.
Fabien Maussion, Anton Butenko, Nicolas Champollion, Matthias Dusch, Julia Eis, Kévin Fourteau, Philipp Gregor, Alexander H. Jarosch, Johannes Landmann, Felix Oesterle, Beatriz Recinos, Timo Rothenpieler, Anouk Vlug, Christian T. Wild, and Ben Marzeion
Geosci. Model Dev., 12, 909–931, https://doi.org/10.5194/gmd-12-909-2019, https://doi.org/10.5194/gmd-12-909-2019, 2019
Short summary
Short summary
Mountain glaciers are one of the few remaining subsystems of the global climate system for which no globally applicable community-driven model exists. Here we present the Open Global Glacier Model (OGGM; www.oggm.org), developed to provide a modular and open-source numerical model framework for simulating past and future change of any glacier in the world.
Hugues Goosse, Pierre-Yves Barriat, Quentin Dalaiden, François Klein, Ben Marzeion, Fabien Maussion, Paolo Pelucchi, and Anouk Vlug
Clim. Past, 14, 1119–1133, https://doi.org/10.5194/cp-14-1119-2018, https://doi.org/10.5194/cp-14-1119-2018, 2018
Short summary
Short summary
Glaciers provide iconic illustrations of past climate change, but records of glacier length fluctuations have not been used systematically to test the ability of models to reproduce past changes. One reason is that glacier length depends on several complex factors and so cannot be simply linked to the climate simulated by models. This is done here, and it is shown that the observed glacier length fluctuations are generally well within the range of the simulations.
Stephan Peter Galos, Christoph Klug, Fabien Maussion, Federico Covi, Lindsey Nicholson, Lorenzo Rieg, Wolfgang Gurgiser, Thomas Mölg, and Georg Kaser
The Cryosphere, 11, 1417–1439, https://doi.org/10.5194/tc-11-1417-2017, https://doi.org/10.5194/tc-11-1417-2017, 2017
Kai-Uwe Eiselt, Frank Kaspar, Thomas Mölg, Stefan Krähenmann, Rafael Posada, and Jens O. Riede
Adv. Sci. Res., 14, 163–173, https://doi.org/10.5194/asr-14-163-2017, https://doi.org/10.5194/asr-14-163-2017, 2017
Short summary
Short summary
As one element of the SASSCAL initiative (a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany) networks of automatic weather stations have been installed or improved in Southern Africa. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. The best interpolation results have been achieved combining multiple linear regression with three dimensional inverse distance weighted interpolation.
Riccardo E. M. Riva, Thomas Frederikse, Matt A. King, Ben Marzeion, and Michiel R. van den Broeke
The Cryosphere, 11, 1327–1332, https://doi.org/10.5194/tc-11-1327-2017, https://doi.org/10.5194/tc-11-1327-2017, 2017
Short summary
Short summary
The reduction of ice masses stored on land has made an important contribution to sea-level rise over the last century, as well as changed the Earth's shape. We model the solid-earth response to ice mass changes and find significant vertical deformation signals over large continental areas. We show how deformation rates have varied strongly throughout the last century, which affects the interpretation and extrapolation of recent observations of vertical land motion and sea-level change.
Wolfgang Gurgiser, Irmgard Juen, Katrin Singer, Martina Neuburger, Simone Schauwecker, Marlis Hofer, and Georg Kaser
Earth Syst. Dynam., 7, 499–515, https://doi.org/10.5194/esd-7-499-2016, https://doi.org/10.5194/esd-7-499-2016, 2016
Short summary
Short summary
Working on the interface of water availability and water demand in a small Andean catchment, peasants’ reports on detrimental precipitation changes during the last decades have attracted our scientific interest. We could not confirm any precipitation trends in this period with nearby precipitation records, but we found precipitation patterns that very likely pose challenges for rain-fed farming – in addition to potential other stresses by environmental and sociopolitical changes.
R. Prinz, L. I. Nicholson, T. Mölg, W. Gurgiser, and G. Kaser
The Cryosphere, 10, 133–148, https://doi.org/10.5194/tc-10-133-2016, https://doi.org/10.5194/tc-10-133-2016, 2016
Short summary
Short summary
Lewis Glacier has lost > 80 % of its extent since the late 19th century. A sensitivity study using a process-based model assigns this shrinking to decreased atmospheric moisture without increasing air temperatures required. The glacier retreat implies a distinctly different coupling between the glacier's surface-air layer and its surrounding boundary layer, underlining the difficulty of deriving palaeoclimates for larger glacier extents on the basis of modern measurements of small glaciers.
B. Marzeion, P. W. Leclercq, J. G. Cogley, and A. H. Jarosch
The Cryosphere, 9, 2399–2404, https://doi.org/10.5194/tc-9-2399-2015, https://doi.org/10.5194/tc-9-2399-2015, 2015
Short summary
Short summary
We show that estimates of global glacier mass change during the 20th century, obtained from glacier-length-based reconstructions and from a glacier model driven by gridded climate observations are now consistent with each other and also with an estimate for the years 2003-2009 that is mostly based on remotely sensed data. This consistency is found throughout the entire common periods of the respective data sets. Inconsistencies of reconstructions and observations persist on regional scales.
F. Maussion, W. Gurgiser, M. Großhauser, G. Kaser, and B. Marzeion
The Cryosphere, 9, 1663–1683, https://doi.org/10.5194/tc-9-1663-2015, https://doi.org/10.5194/tc-9-1663-2015, 2015
Short summary
Short summary
Using a newly developed open-source tool, we downscale the glacier surface energy and mass balance fluxes at Shallap Glacier. This allows an unprecedented quantification of the ENSO influence on a tropical glacier at climatological time scales (1980-2013). We find a stronger and steadier anti-correlation between Pacific sea-surface temperature (SST) and glacier mass balance than previously reported and provide keys to understand its mechanism.
E. Collier, F. Maussion, L. I. Nicholson, T. Mölg, W. W. Immerzeel, and A. B. G. Bush
The Cryosphere, 9, 1617–1632, https://doi.org/10.5194/tc-9-1617-2015, https://doi.org/10.5194/tc-9-1617-2015, 2015
Short summary
Short summary
We investigate the impact of surface debris on glacier energy and mass fluxes and on atmosphere-glacier feedbacks in the Karakoram range, by including debris in an interactively coupled atmosphere-glacier model. The model is run from 1 May to 1 October 2004, with a simple specification of debris thickness. We find an appreciable reduction in ablation that exceeds 5m w.e. on glacier tongues, as well as significant alterations to near-surface air temperatures and boundary layer dynamics.
B. Marzeion, A. H. Jarosch, and J. M. Gregory
The Cryosphere, 8, 59–71, https://doi.org/10.5194/tc-8-59-2014, https://doi.org/10.5194/tc-8-59-2014, 2014
W. Gurgiser, B. Marzeion, L. Nicholson, M. Ortner, and G. Kaser
The Cryosphere, 7, 1787–1802, https://doi.org/10.5194/tc-7-1787-2013, https://doi.org/10.5194/tc-7-1787-2013, 2013
S. MacDonell, C. Kinnard, T. Mölg, L. Nicholson, and J. Abermann
The Cryosphere, 7, 1513–1526, https://doi.org/10.5194/tc-7-1513-2013, https://doi.org/10.5194/tc-7-1513-2013, 2013
T. Mölg, F. Maussion, W. Yang, and D. Scherer
The Cryosphere, 6, 1445–1461, https://doi.org/10.5194/tc-6-1445-2012, https://doi.org/10.5194/tc-6-1445-2012, 2012
Related subject area
Atmospheric sciences
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results
Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
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
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
CoCoMET v1.0: A Unified Open-Source Toolkit for Atmospheric Object Tracking and Analysis
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
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
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
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
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
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev., 18, 4855–4876, https://doi.org/10.5194/gmd-18-4855-2025, https://doi.org/10.5194/gmd-18-4855-2025, 2025
Short summary
Short summary
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS) operational global numerical weather model. The results show that assimilating BC (black carbon) observations can generate analysis increments not only for BC but also for atmospheric variables.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
Short summary
Short summary
We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced-order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity, and produces uncertainty quantification metrics. It is ideal for the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
Short summary
Short summary
This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere that are 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.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
Short summary
Short summary
A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
Short summary
Short summary
Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
Short summary
Short summary
We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
Short summary
Short summary
We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
Short summary
Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
Short summary
Short summary
SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
Short summary
Short summary
It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
Short summary
Short summary
Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
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., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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-kilometre-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 an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
Short summary
Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at the 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 between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
Short summary
Short summary
Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
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., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
Short summary
Short summary
We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
Short summary
Short summary
Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently 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 has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
Short summary
Short summary
In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
Short summary
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Short summary
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
Short summary
Short summary
This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
Short summary
Short summary
This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary
Short summary
We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Short summary
Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Short summary
Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
Short summary
Short summary
We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Short summary
The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
Short summary
Short summary
We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Travis Hahn, Hershel Weiner, Calvin Brooks, Jie Xi Li, Siddhant Gupta, and Dié Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1328, https://doi.org/10.5194/egusphere-2025-1328, 2025
Short summary
Short summary
Understanding how clouds evolve is important for improving weather predictions, but existing tools for tracking cloud changes are complex and difficult to compare. To address this, we developed the Community Cloud Model Evaluation Toolkit (CoCoMET) that makes it easier to analyze clouds in both models and observations. By simplifying data processing, standardizing results, and introducing new analysis features, CoCoMET helps researchers better evaluate cloud behavior and improve models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
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.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
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.
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.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
Short summary
Short summary
Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
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.
Cited articles
Ames, A.: A documentation of glacier tongue variations and lake developement in the Cordillera Blanca, Peru, Zeitung für Gletscherkunde und Glazialgeologie, 34, 1–36, 1998.
Bair, E., Hastie, T., and Tibshirani, R.: Prediction by Supervised Principal Components, J. Am. Stat. Assoc., 101, 119–137, https://doi.org/10.1198/016214505000000628, 2006.
Benestad, R., Førland, E. J., and Hanssen-Bauer, I.: Empirically downscaling temperature scenarios for Svalbard, Atmos. Sci. Lett., 3, 71–93, https://doi.org/10.1006/asle.2002.0050, 2002.
Benestad, R. E., Hanssen-Bauer, I., and Deliang, C.: Empirical-statistical downscaling, World Scientific, Singapore, 2008.
Carey, M.: Living and dying with glaciers: people's historical vulnerability to avalanches and outburst floods in Peru, Global Planet. Change, 47, 122–134, 2005.
Carey, M.: In the Shadow of Melting Glaciers. Climate Change and Andean Society, Oxford University Press, 2010.
Cavazos, T. and Hewitson, B. C.: Performance of NCEP-NCAR reanalysis variables in statistical downscaling of daily precipitation, Climate Res., 28, 95–107, 2005.
Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R. K., Kwon, W.-T., Laprise, R., Magaña Rueda, V., Mearns, L., Menéndez, C. G., Räisänen, J., Rinke, A., Sarr, A., and Whetton, P.: Regional Climate Projections, in: Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007.
Frías, M. D., Zorita, E., Fernández, J., and Rodr\'iguez-Puebla, C.: Testing statistical downscaling methods in simulated climates, Geophys. Res. Lett., 33, L19807, https://doi.org/10.1029/2006GL027453, 2006.
Garreaud, R., Vuille, M., and Clement, A.: The climate of the Altiplano: observed current conditions and mechanisms of past changes, Palaeogeography, Palaeoclimatology, Palaeoecology, 194, 5–22, https://doi.org/10.1016/S0031-0182(03)00269-4, 2003.
Georges, C.: Ventilated and unventilated air temperature measurements for glacier-climate studies on a tropical high mountain site, J. Geophys. Res., 107, 2156–2202, https://doi.org/10.1029/2002JD002503, 2002.
Georges, C.: 20th-century glacier fluctuations in the tropical Cordillera Blanca, Peru, Arctic, Antarctic, Alpine Res., 36, 100–107, 2004.
Georges, C.: Recent Glacier Fluctuations in the Tropical Cordillera Blanca and Aspects of the Climate Forcing, Ph.D. thesis, Leopold-Franzens University Innsbruck, Innsbruck, Austria, 2005.
Giesen, R. H. and Oerlemans, J.: Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise, Clim. Dynam., 1–18, https://doi.org/10.1007/s00382-013-1743-7, 2013.
Giorgi, F. and Bates, G. T.: The climatological skill of a regional model over complex terrain, Mon. Weather Rev., 117, 2325–2347, https://doi.org/10.1175/1520-0493(1989)117<2325:TCSOAR>2.0.CO;2, 1989.
Grotch, S. L. and MacCracken, M. C.: The use of global climate models to predict regional climatic change, J. Climate, 4, 286–303, 1991.
Hastie, T., Tibshirani, R., and Friedman, J.: The elements of statistical learning: data mining, inference, and prediction, Springer series in statistics, Springer, New York, 1 edn., 2001.
Hessami, M., P. G., Ouarda, T. B. M. J., and St-Hilaire, A.: Automated regression-based statistical downscaling tool, J. Environ. Model. Softw., 23, 813–834, https://doi.org/10.1016/j.envsoft.2007.10.004, 2008.
Hill, G. E.: Grid Telescoping in Numerical Weather Prediction, J. Appl. Meteorol., 7, 29–38, https://doi.org/10.1175/1520-0450(1968)007<0029:GTINWP>2.0.CO;2, 1968.
Hofer, M., Mölg, T., Marzeion, B., and Kaser, G.: Empirical-statistical downscaling of reanalysis data to high-resolution air temperature and specific humidity above a glacier surface (Cordillera Blanca, Peru), J. Geophys. Res.-Atmos., 115, 2156–2202, https://doi.org/10.1029/2009JD012556, 2010.
Hofer, M., Marzeion, B., and Mölg, T.: Comparing the skill of different reanalyses and their ensembles as predictors for daily air temperature on a glaciated mountain (Peru), Clim. Dynam., 39, 1969–1980, https://doi.org/10.1007/s00382-012-1501-2, 2012.
Huth, R.: Sensitivity of local daily temperature change estimates to the selection of downscaling models and predictors, J. Climate, 17, https://doi.org/10.1175/1520-0442(2004)017<0640:SOLDTC>2.0.CO;2, 2004.
Juen, I.: Glacier mass balance and runoff in the Cordillera Blanca, Peru, PhD thesis, University of Innsbruck, 2006.
Juen, I., Georges, C., and Kaser, G.: Modelling observed and future runoff from a glacierized tropical catchment (Cordillera Blanca, Peru), Global Planet. Change, 59, 37–48, 2007.
Kaser, G. and Osmaston, H.: Tropical Glaciers, International Hydrology Series, Cambridge University Press, Cambridge, UK, 2002.
Kaser, G., Juen, I., Georges, C., Gomez, J., and Tamayo, W.: The impact of glaciers on the runoff and the reconstruction of mass balance history from hydrological data in the tropical Cordillera Blanca, Peru, J. Hydrol., 282, 130–144, 2003.
Kaser, G., Grosshauser, M., and Marzeion, B.: The contribution potential of glaciers to water availability in different climate regimes, Proc. Natl. Acad. Sci. USA, 107, 20223–20227, 2010.
Kidson, J. W. and Thompson, C. S.: A comparison of statistical and model-based downscaling techniques for estimating local climate variations, J. Climate, 11, 735–753, https://doi.org/10.1175/1520-0442(1998)011<0735:ACOSAM>2.0.CO;2, 1998.
Klein, W. H. and Glahn, H. R.: Forecasting local weather by means of model output statistics, B. Am. Meteorol. Soc., 55, 1217–1227, 1974.
Klein, W. H., Lewis, B. M., and Enger, I.: Objective prediction of five-day mean temperature during winter, J. Meteorol., 16, 672–682, https://doi.org/10.1175/1520-0469(1959)016<0672:OPOFDM>2.0.CO;2, 1959.
Kotlarski, S., Paul, F., and Jacob, D.: Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part I: Climate Model Evaluation, J. Climate, 23, 1589–1606, https://doi.org/10.1175/2009JCLI2711.1, 2010.
Madden, R. A.: Estimates of the Natural Variability of Time-Averaged Sea-Level Pressure, Mon. Weather Rev., 104, 942–952, https://doi.org/10.1175/1520-0493(1976)104<0942:EOTNVO>2.0.CO;2, 1976.
Madden, R. A. and Julian, P. R.: Observations of the 40 to 50-Day Tropical Oscillation: A Review, Mon. Weather Rev., 122, 814–837, https://doi.org/10.1175/1520-0493(1994)122<0814:OOTDTO>2.0.CO;2, 1994.
Mark, B. G. and Seltzer, G. O.: Tropical glacier meltwater contribution to stream discharge: a case study in the Cordillera Blanca, Peru, J. Glaciol., 49, 271–281, 2003.
Marzeion, B., Jarosch, A. H., and Hofer, M.: Past and future sea-level change from the surface mass balance of glaciers, The Cryosphere, 6, 1295–1322, https://doi.org/10.5194/tc-6-1295-2012, 2012.
Mason, S. J.: Understanding forecast verification statistics, Meteorol. Applications, 15, 31–40, https://doi.org/10.1002/met.51, 2008.
Mearns, L. O., Giorgi, F., Whetton, P., Pabon, D., Hulme, M., and Lal, M.: Guidelines for Use of Climate Scenarios Developed from Regional Climate Model Experiments, IPCC Supporting Material, http://ipcc-data.org/guidelines/dgm_no1_v1_10-2003.pdf (last access: 7 May 2013), 2003.
Michaelsen, J.: Cross-validation in statistical climate forecast models, J. Clim. Appl. Meteorol., 26, 1589–1600, 1987.
Mölg, T., Grosshauser, M., Hemp, A., Hofer, M., and Marzeion, B.: Limited forcing of glacier loss through land-cover change on Kilimanjaro, Nature Clim. Change, 2, 254–258, 2012.
Murphy, A. H.: Skill Scores Based on the Mean Square Error and Their Relationships to the Correlation Coefficient, Mon. Weather Rev., 116, 2417–2424, https://doi.org/10.1175/1520-0493(1988)116<2417:SSBOTM>2.0.CO;2, 1988.
Murphy, J.: An evaluation of statistical and dynamical techniques for downscaling local climate, J. Climate, 12, 2256–2284, https://doi.org/10.1175/1520-0442(1999)012<2256:AEOSAD>2.0.CO;2, 1999.
Niedertscheider, J.: Untersuchungen zur Hydrographie der Cordillera Blanca (Peru), Master's thesis, Leopold Franzens University, Innsbruck, 1990.
Paul, F. and Kotlarski, S.: Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part II: Downscaling Strategy and Results for two Swiss Glaciers, J. Climate, 23, 1607–1620, 2010.
Räisänen, J. and Ylhäisi, J. S.: How Much Should Climate Model Output Be Smoothed in Space?, J. Climate, 24, 867–880, https://doi.org/10.1175/2010JCLI3872.1, 2011.
Rummukainen, M.: Methods for statistical downscaling of GCM simulations, no. 80 in SMHI reports meteorology and climatology, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden, 1997.
Sauter, T. and Venema, V.: Natural three-dimensional predictor domains for statistical precipitation downscaling, J. Climate, 24, 6132–6145, https://doi.org/10.1175/2011JCLI4155.1, 2011.
Schauwecker, S., Rohrer, M., Acuña, D., Cochachin, A., Dávila, L., Frey, H., Giráldez, C., Gómez, J., Huggel, C., Jacques-Coper, M., Loarte, E., Salzmann, N., and Vuille, M.: Climate trends and glacier retreat in the Cordillera Blanca, Peru, revisited, Global Planet. Change, 119, 85–97, https://doi.org/10.1016/j.gloplacha.2014.05.005, 2014.
Schmidli, J., Goodess, C. M., Frei, C., Haylock, M. R., Hundecha, Y., Ribalaygua, J., and Schmith, T.: Statistical and dynamical downscaling of precipitation: An evaluation and comparison of scenarios for the European Alps, J. Geophys. Res.-Atmos., 112, 679–689, https://doi.org/10.1029/2005JD007026, 2007.
Silverio, W. and Jaquet, J.-M.: Glacial cover mapping (1987–1996) of the Cordillera Blanca (Peru) using satellite imagery, Remote Sens. Environ., 95, 342–350, 2005.
Stahl, K., Moore, R., Shea, J., Hutchinson, D., and Cannon, A.: Coupled modelling of glacier and streamflow response to future climate scenarios, Water Resour. Res., 44, 2, https://doi.org/10.1029/2007WR005956, 2008.
Themeßl, J. M., Gobiet, A., and Leuprecht, A.: Empirical-statistical downscaling and error correction of daily precipitation from regional climate models, Int. J. Climatol., 31, 1530–1544, https://doi.org/10.1002/joc.2168, 2011.
Trenberth, K. E., Stepaniak, D. P., Hurrell, J. W., and Fiorino, M.: Quality of reanalyses in the tropics, J. Climate, 14, 1499–1510, https://doi.org/10.1175/1520-0442(2001)014<1499:QORITT>2.0.CO;2, 2001.
van Pelt, W. J. J., Oerlemans, J., Reijmer, C. H., Pohjola, V. A., Pettersson, R., and van Angelen, J. H.: Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model, The Cryosphere, 6, 641–659, https://doi.org/10.5194/tc-6-641-2012, 2012.
Von Storch, H.: On the Use of Inflation in Statistical Downscaling, J. Climate, 12, 3505–3506, 1999.
Von Storch, H. and Zwiers, F.: Statistical analysis in climate research, Cambridge University Press, Cambridge, UK, 2001.
Vuille, M., Francou, B., Wagnon, P., Juen, I., Kaser, G., Mark, B. G., and Bradley, R. S.: Climate change and tropical Andean glaciers: Past, present and future, Earth-Sci. Rev., 89, 79–96, https://doi.org/10.1016/j.earscirev.2008.04.002, 2008a.
Vuille, M., Kaser, G., and Juen, I.: Glacier mass balance variability in the Cordillera Blanca, Peru and its relationship to climate and large scale circulation, Global Planet. Change, 62, 14–28, 2008b.
Widmann, M., Bretherton, C. S., and Salathé, E.: Statistical Precipitation Downscaling over the Northwestern United States Using Numerically Simulated Precipitation as a Predictor, J. Climate, 16, 799–816, 2003.
Wilby, R. and Dawson, C.: SDSM 4.2 – A decision support tool for the assessment of regional climate change impacts, Loughborough University, Leicestershire, UK, 2007.
Wilby, R., Dawson, C., and Barrow, E.: SDSM – a decision support tool for the assessment of regional climate change impacts, Environ. Model. Softw., 17, 145–157, 2002.
Wilby, R., Charles, S., Zorita, E., Timbal, B., Whetton, P., and Mearns, L.: Guidelines for Use of Climate Scenarios Developed from Statistical Downscaling Methods, Tech. rep., available at: http://www.narccap.ucar.edu/doc/tgica-guidance-2004.pdf (11 March 2015), 2004.
Wilks, D. S.: Resampling hypothesis tests for autocorrelated fields, J. Climate, 10, 65–82, 1997.
Wilks, D. S.: Statistical methods in the atmospheric sciences, vol. 91 of International Geophysics Series, Academic Press, 2 edn., 2006.
Williamson, D. L. and Laprise, R.: Numerical modeling of the global atmosphere in the climate system, chap. Numerical approximations for global atmospheric GCMs, pp. 147–219, Kluwer Academic, Castelvecchio Pascoli, Italy, 2000.
Winkler, J. A., Palutikof, J. P., Andresen, J. A., and Goodess, C. M.: The Simulation of Daily Temperature Time Series from GCM Output. Part two: Sensitivity Analysis of an Empirical Transfer Function Methodology, J. Climate, 10, 2514–2532, https://doi.org/10.1175/1520-0442(1997)010<2514:TSODTT>2.0.CO;2, 1997.
Zucchini, W.: An Introduction to Model Selection, J. Math. Psych., 44, 41–61, https://doi.org/10.1006/jmps.1999.1276, 2000.
