Articles | Volume 4, issue 2
https://doi.org/10.5194/wcd-4-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-4-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 May 2023
Research article |
| 15 May 2023
| 15 May 2023
Model-simulated hydroclimate in the East Asian summer monsoon region during past and future climate: a pilot study with a moisture source perspective
Astrid Fremme
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
now at: Statkraft, Oslo, Norway
Paul J. Hezel
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Øyvind Seland
Norwegian Meteorological Institute, Oslo, Norway
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
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Fiona Paulus, Joshua J. Müller, Benjamin Kirbus, Harald Sodemann, Lars van Gelder, Andreas Walbröl, Manfred Wendisch, and Roel A. J. Neggers
Atmos. Chem. Phys., 26, 13983–14014, https://doi.org/10.5194/acp-26-13983-2026, https://doi.org/10.5194/acp-26-13983-2026, 2026
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Cold Arctic air flowing from sea ice onto the warmer ocean waters rapidly warms, moistens, and forms clouds and precipitation. These events shape the Arctic climate but are difficult to observe and model. Particularly the role of large-scale sinking motion during these events is not fully understood. Using rare aircraft data and simulations to track an air mass for two days, we show that strong downward motion suppresses cloud growth, limits and delays precipitation, and reduces cloud lifetimes.
Janne Liburd, Kristof Tomej, Ann Eileen Lennert, Benjamin Fischer, Andrea L. Popp, Mahaut de Vareilles, Costijn Zwart, and Harald Sodemann
EGUsphere, https://doi.org/10.5194/egusphere-2026-5504, https://doi.org/10.5194/egusphere-2026-5504, 2026
This preprint is open for discussion and under review for Geoscience Communication (GC).
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As scientists increasingly work with citizens and other stakeholders, collaboration becomes more valuable, but also more challenging. The example of the ISOSCAN research project on water forecasting shows how co-designing research activities can foster learning, trust, and new ways of thinking about scientific work, thereby benefiting research outcomes and the scientists involved. Tensions between different perspectives can become opportunities for reflection, learning and innovation.
Jianyu Zheng, Hongbin Yu, Chamara Rajapakse, Mian Chin, Michael Schulz, Yves Balkanski, Susanne E. Bauer, Huisheng Bian, Peter Colarco, Dongchul Kim, Ramiro Checa-Garcia, Yevgeny Derimian, Oleg Dubovik, Paul Ginoux, Zak Kipling, Jasper F. Kok, Harri Kokkola, Philippe Le Sager, Lei Li, Marianne Tronstad Lund, Gunnar Myhre, Hitoshi Matsui, Dirk J. L. Olivie, Samuel Remy, Oyvind Seland, Qianqian Song, Toshihiko Takemura, Qian Tan, Kostas Tsigaridis, Twan van Noije, David Winker, Bin Xie, Hua Zhang, Xindan Zhang, and Zhibo Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2026-4322, https://doi.org/10.5194/egusphere-2026-4322, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Winds carry vast amounts of Saharan dust across the Atlantic Ocean, influencing climate, air quality, and ocean ecosystems. Within the Aerosol Comparisons between Observations and Models (AeroCom) project, we evaluated 17 numerical models against observations. Models deposit dust too quickly, so too little reaches the Caribbean. Better simulations require emitting larger particles, treating their non-spherical shapes, and capturing processes that keep dust aloft during transport.
Sara M. Blichner, Theodore Khadir, Sini Talvinen, Paulo Artaxo, Liine Heikkinen, Harri Kokkola, Radovan Krejci, Muhammed Irfan, Twan van Noije, Tuukka Petäjä, Christopher Pöhlker, Øyvind Seland, Carl Svenhag, Antti Vartiainen, and Ilona Riipinen
Atmos. Chem. Phys., 26, 11281–11307, https://doi.org/10.5194/acp-26-11281-2026, https://doi.org/10.5194/acp-26-11281-2026, 2026
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This study looks at how well climate models capture the impact of rain on particles that help form cloud droplets. Using data from three measurement stations and applying both a correlation analysis and a machine learning approach, we found that models often miss how new particles form after rain and struggle in cold environments. This matters because these particles influence cloud formation and climate.
Nina Elisabeth Larsgård, Tim Carlsen, Robert Oscar David, Filip Severin von der Lippe, Alfons Schwarzenboek, Harald Sodemann, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2026-1650, https://doi.org/10.5194/egusphere-2026-1650, 2026
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In-situ data from multiple research flights are combined to investigate the cloud evolution of Arctic marine cold air outbreaks during the ISLAS2022 campaign. We observe a cloud development similar to what other studies have shown: More liquid at cloud top close to the sea ice, and increased glaciation as clouds mature and deepen. This composite approach can be used by the community to further understand mCAO cloud evolution with increased confidence compared to single-flight analysis.
Alena Dekhtyareva, Harald Sodemann, Tim Carlsen, Iris Thurnherr, Aina Johannessen, Andrew Seidl, David M. Chandler, Daniele Zannoni, Alexandra Touzeau, Marvin Kähnert, Astrid B. Gjelsvik, Franziska Hellmuth, Britta Schäfer, and Robert O. David
Earth Syst. Sci. Data, 18, 2573–2607, https://doi.org/10.5194/essd-18-2573-2026, https://doi.org/10.5194/essd-18-2573-2026, 2026
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During a recent field campaign from 15 to 30 March 2021 at Andenes, Norway, we collected a set of observations that allows to better constrain how clouds and precipitation processes work. Frequent alternations between mid-latitude and arctic weather systems were encountered during the campaign. Our dataset is unique in combining measurements in both vapour and precipitation, aerosols, ice nucleating particles, and was made simultaneously at different elevations at a high latitude location.
Andrew W. Seidl, Aina Johannessen, Alena Dekhtyareva, Jannis M. Huss, Marius O. Jonassen, Alexander Schulz, Ove Hermansen, Christoph K. Thomas, and Harald Sodemann
Earth Syst. Sci. Data, 18, 1969–1993, https://doi.org/10.5194/essd-18-1969-2026, https://doi.org/10.5194/essd-18-1969-2026, 2026
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ISLAS2020 set out to measure the stable water isotopic composition of Arctic moisture. By not only measuring at different sites around Ny-Ålesund, Svalbard, but also measuring at variable heights above surface level, we aim to characterize processes that produce or modify the isotopic composition. We also collect precipitation samples from sites that were typically downstream of Ny-Ålesund, so as to capture the isotopic composition during removal from the atmospheric water cycle.
Harald Sodemann
Geosci. Model Dev., 18, 8887–8926, https://doi.org/10.5194/gmd-18-8887-2025, https://doi.org/10.5194/gmd-18-8887-2025, 2025
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The WaterSip software locates regions where precipitation comes from. WaterSip evaluates of the water budget of the air masses, providing information on the conditions during evaporation, transport, and arrival at the target area. WaterSip can be easily configured and writes gridded output files. Guidance is given on where uncertainties arise using a case study, and best practices are recommended. This manuscript supports the comparison of different methods to find precipitation sources.
Manfred Wendisch, Benjamin Kirbus, Davide Ori, Matthew D. Shupe, Susanne Crewell, Harald Sodemann, and Vera Schemann
Atmos. Chem. Phys., 25, 15047–15076, https://doi.org/10.5194/acp-25-15047-2025, https://doi.org/10.5194/acp-25-15047-2025, 2025
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Aircraft observations of air parcels moving into and out of the Arctic are reported. From the data, heating and cooling as well as drying and moistening of the air masses along their way into and out of the Arctic could be measured for the first time. These data are used to evaluate if weather prediction models are able to accurately represent these air mass transformations. This work helps to model the future Arctic climate changes, which may have an impact for mid-latitude weather as well.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
Earth Syst. Dynam., 16, 1671–1698, https://doi.org/10.5194/esd-16-1671-2025, https://doi.org/10.5194/esd-16-1671-2025, 2025
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The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth System Model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea ice retreat regions and the largest uncertainty found on the Atlantic side.
Daniele Zannoni, Hans Christian Steen-Larsen, Harald Sodemann, Iris Thurnherr, Cyrille Flamant, Patrick Chazette, Julien Totems, Martin Werner, and Myriam Raybaut
Atmos. Chem. Phys., 25, 9471–9495, https://doi.org/10.5194/acp-25-9471-2025, https://doi.org/10.5194/acp-25-9471-2025, 2025
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High-resolution airborne observations reveal that mixing between the free troposphere and surface evapotranspiration flux primarily modulates the water vapor isotopic composition in the lower troposphere. Water vapor isotope structure variations occur on the scale of hundreds of meters, underlining the utility of stable isotopes for studying microscale atmospheric dynamics. This study also provides the basis for better validation of water vapor isotope remote sensing retrievals with surface observations.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Astrid B. Gjelsvik, Robert O. David, Tim Carlsen, Franziska Hellmuth, Stefan Hofer, Zachary McGraw, Harald Sodemann, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1617–1637, https://doi.org/10.5194/acp-25-1617-2025, https://doi.org/10.5194/acp-25-1617-2025, 2025
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Ice formation in clouds has a substantial impact on radiation and precipitation and must be realistically simulated in order to understand present and future Arctic climate. Rare aerosols known as ice-nucleating particles can play an important role in cloud ice formation, but their representation in global climate models is not well suited for the Arctic. In this study, the simulation of cloud phase is improved when the representation of these particles is constrained by Arctic observations.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Harald Sodemann, Alena Dekhtyareva, Alvaro Fernandez, Andrew Seidl, and Jenny Maccali
Atmos. Meas. Tech., 16, 5181–5203, https://doi.org/10.5194/amt-16-5181-2023, https://doi.org/10.5194/amt-16-5181-2023, 2023
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We describe a device that allows one to produce a continuous stream of water vapour with a specified level of humidity. As a main innovation, we can mix waters with different water isotope composition. Through a series of tests we show that the performance characteristics of the device are in line with specifications. We present two laboratory applications where the device proves useful, first in characterizing instruments, and second for the analysis of water contained in stalagmites.
Andrew W. Seidl, Harald Sodemann, and Hans Christian Steen-Larsen
Atmos. Meas. Tech., 16, 769–790, https://doi.org/10.5194/amt-16-769-2023, https://doi.org/10.5194/amt-16-769-2023, 2023
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It is challenging to make field measurements of stable water isotopes in the Arctic. To this end, we present a modular stable-water-isotope analyzer profiling system. The system operated for a 2-week field campaign on Svalbard during the Arctic winter. We evaluate the system’s performance and analyze any potential impact that the field conditions might have had on the isotopic measurements and the system's ability to resolve isotope gradients in the lowermost layer of the atmosphere.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
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We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
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A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
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Short summary
We study the atmospheric moisture transport into eastern China for past, present, and future climate. Hence, we use different climate and weather prediction model data with a moisture source identification method. We find that while the moisture to first order originates mostly from similar regions, smaller changes consistently point to differences in the recycling of precipitation over land between different climates. Some differences are larger between models than between different climates.
We study the atmospheric moisture transport into eastern China for past, present, and future...
