Articles | Volume 27, issue 6
https://doi.org/10.5194/hess-27-1361-2023
© 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/hess-27-1361-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Mar 2023
Research article |
| 29 Mar 2023
| 29 Mar 2023
Sources of skill in lake temperature, discharge and ice-off seasonal forecasting tools
Norwegian Institute for Water Research (NIVA), Oslo, Norway
Leah Jackson-Blake
Norwegian Institute for Water Research (NIVA), Oslo, Norway
Daniel Mercado-Bettín
Catalan Institute for Water Research (ICRA), Girona, Spain
Universitat de Girona, Girona, Spain
Muhammed Shikhani
Department of Lake Research, Helmholtz Centre for Environmental Research, Magdeburg, Germany
Andrew French
Foras na Mara – Marine Institute, Furnace, Newport, Co. Mayo, Ireland
present address: School of Biological, Earth and Environmental Sciences, University College Cork, Cork, T23 N63K, Ireland
Tadhg Moore
Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
present address: Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA
James Sample
Norwegian Institute for Water Research (NIVA), Oslo, Norway
Magnus Norling
Norwegian Institute for Water Research (NIVA), Oslo, Norway
Maria-Dolores Frias
Dept. Matemática Aplicada y Ciencias de la Computación (MACC). Universidad de Cantabria, Santander, Spain
Grupo de Meteorología y Computación, Universidad de Cantabria, Unidad Asociada al CSIC, Santander, Spain
Sixto Herrera
Dept. Matemática Aplicada y Ciencias de la Computación (MACC). Universidad de Cantabria, Santander, Spain
Elvira de Eyto
Foras na Mara – Marine Institute, Furnace, Newport, Co. Mayo, Ireland
Eleanor Jennings
Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
Karsten Rinke
Department of Lake Research, Helmholtz Centre for Environmental Research, Magdeburg, Germany
Leon van der Linden
SA Water, Adelaide, SA 5000, Australia
Rafael Marcé
Catalan Institute for Water Research (ICRA), Girona, Spain
Universitat de Girona, Girona, Spain
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-585, https://doi.org/10.5194/essd-2025-585, 2025
Preprint under review for ESSD
Short summary
Short summary
This dataset includes monthly measurements of carbon dioxide and methane exchange between land, water, and the atmosphere from over 1,000 sites in Arctic and boreal regions. It combines measurements from a variety of ecosystems, including wetlands, forests, tundra, lakes, and rivers, gathered by over 260 researchers from 1984–2024. This dataset can be used to improve and reduce uncertainty in carbon budgets in order to strengthen our understanding of climate feedbacks in a warming world.
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This preprint is open for discussion and under review for Biogeosciences (BG).
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Jacqueline K. Knutson, François Clayer, Peter Dörsch, Sebastian Westermann, and Heleen A. de Wit
Biogeosciences, 22, 3899–3914, https://doi.org/10.5194/bg-22-3899-2025, https://doi.org/10.5194/bg-22-3899-2025, 2025
Short summary
Short summary
Thawing permafrost at Iškoras in northern Norway is transforming peat plateaus into thermokarst ponds and wetlands. These small ponds show striking oversaturation of dissolved greenhouse gases, such as carbon dioxide (CO2) and methane (CH4), partly owing to organic matter processing. Streams nearby emit CO2, driven by turbulence. As permafrost disappears, carbon dynamics will change, potentially increasing emissions of CH4. This study highlights the need to integrate these changes into climate models.
Ana I. Ayala, José L. Hinostroza, Daniel Mercado-Bettín, Rafael Marcé, Simon N. Gosling, Donald C. Pierson, and Sebastian Sobek
EGUsphere, https://doi.org/10.5194/egusphere-2025-3126, https://doi.org/10.5194/egusphere-2025-3126, 2025
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Climate change affect lakes by including not just the lakes themselves but also the land areas that drain into them. These surrounding areas influence how much water and nutrients flow into lakes which in turn impact water quality. Here, water fluxes from land, derived from a global hydrological model where water fluxes are modelled at the grid scale, were used to estimate streamflow inputs to lakes from their catchments. Using data from 71 Swedish lakes, we showed that our method works well.
Katja Frieler, Stefan Lange, Jacob Schewe, Matthias Mengel, Simon Treu, Christian Otto, Jan Volkholz, Christopher P. O. Reyer, Stefanie Heinicke, Colin Jones, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Ryan Heneghan, Derek P. Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Dánnell Quesada Chacón, Kerry Emanuel, Chia-Ying Lee, Suzana J. Camargo, Jonas Jägermeyr, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Lisa Novak, Inga J. Sauer, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, Michel Bechtold, Robert Reinecke, Inge de Graaf, Jed O. Kaplan, Alexander Koch, and Matthieu Lengaigne
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François Clayer, Jan Erik Thrane, Kuria Ndungu, Andrew King, Peter Dörsch, and Thomas Rohrlack
Biogeosciences, 21, 1903–1921, https://doi.org/10.5194/bg-21-1903-2024, https://doi.org/10.5194/bg-21-1903-2024, 2024
Short summary
Short summary
Determination of dissolved greenhouse gas (GHG) in freshwater allows us to estimate GHG fluxes. Mercuric chloride (HgCl2) is used to preserve water samples prior to GHG analysis despite its environmental and health impacts and interferences with water chemistry in freshwater. Here, we tested the effects of HgCl2, two substitutes and storage time on GHG in water from two boreal lakes. Preservation with HgCl2 caused overestimation of CO2 concentration with consequences for GHG flux estimation.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
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Biogeosciences, 19, 5343–5355, https://doi.org/10.5194/bg-19-5343-2022, https://doi.org/10.5194/bg-19-5343-2022, 2022
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Organic matter (OM) turnover into dissolved inorganic carbon (DIC) was investigated by means of carbon isotope mass balances in Germany's largest water reservoir. This includes a metalimnetic oxygen minimum (MOM). Autochthonous particulate organic carbon (POC) was the main contributor to DIC, with rates that were highest for the MOM. Generally low turnover rates outline the environmental fragility of this water body in the case that OM loads increase due to storm events or land use changes.
Leah A. Jackson-Blake, François Clayer, Sigrid Haande, James E. Sample, and S. Jannicke Moe
Hydrol. Earth Syst. Sci., 26, 3103–3124, https://doi.org/10.5194/hess-26-3103-2022, https://doi.org/10.5194/hess-26-3103-2022, 2022
Short summary
Short summary
We develop a Gaussian Bayesian network (GBN) for seasonal forecasting of lake water quality and algal bloom risk in a nutrient-impacted lake in southern Norway. Bayesian networks are powerful tools for environmental modelling but are almost exclusively discrete. We demonstrate that a continuous GBN is a promising alternative approach. Predictive performance of the GBN was similar or improved compared to a discrete network, and it was substantially less time-consuming and subjective to develop.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Y. Liu, Q. Liu, J. E. Sample, K. Hancke, and A.-B. Salberg
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 439–445, https://doi.org/10.5194/isprs-annals-V-3-2022-439-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-439-2022, 2022
Leah A. Jackson-Blake, François Clayer, Elvira de Eyto, Andrew S. French, María Dolores Frías, Daniel Mercado-Bettín, Tadhg Moore, Laura Puértolas, Russell Poole, Karsten Rinke, Muhammed Shikhani, Leon van der Linden, and Rafael Marcé
Hydrol. Earth Syst. Sci., 26, 1389–1406, https://doi.org/10.5194/hess-26-1389-2022, https://doi.org/10.5194/hess-26-1389-2022, 2022
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We explore, together with stakeholders, whether seasonal forecasting of water quantity, quality, and ecology can help support water management at five case study sites, primarily in Europe. Reliable forecasting, a season in advance, has huge potential to improve decision-making. However, managers were reluctant to use the forecasts operationally. Key barriers were uncertainty and often poor historic performance. The importance of practical hands-on experience was also highlighted.
Magnus Dahler Norling, Leah Amber Jackson-Blake, José-Luis Guerrero Calidonio, and James Edward Sample
Geosci. Model Dev., 14, 1885–1897, https://doi.org/10.5194/gmd-14-1885-2021, https://doi.org/10.5194/gmd-14-1885-2021, 2021
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In order to allow researchers to quickly prototype and build models of natural systems, we have created the Mobius framework. Such models can, for instance, be used to ask questions about what the impacts of land-use changes are to water quality in a river or lake, or the response of biogeochemical systems to climate change. The Mobius framework makes it quick to build models that run fast, which enables the user to explore many different scenarios and model formulations.
Matthias Koschorreck, Yves T. Prairie, Jihyeon Kim, and Rafael Marcé
Biogeosciences, 18, 1619–1627, https://doi.org/10.5194/bg-18-1619-2021, https://doi.org/10.5194/bg-18-1619-2021, 2021
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The concentration of carbon dioxide (CO2) in water samples is often measured using a gas chromatograph. Depending on the chemical composition of the water, this method can produce wrong results. We quantified the possible error and how it depends on water composition and the analytical procedure. We propose a method to correct wrong results by additionally analysing alkalinity in the samples. We provide an easily usable computer code to perform the correction calculations.
Harriet L. Wilson, Ana I. Ayala, Ian D. Jones, Alec Rolston, Don Pierson, Elvira de Eyto, Hans-Peter Grossart, Marie-Elodie Perga, R. Iestyn Woolway, and Eleanor Jennings
Hydrol. Earth Syst. Sci., 24, 5559–5577, https://doi.org/10.5194/hess-24-5559-2020, https://doi.org/10.5194/hess-24-5559-2020, 2020
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Lakes are often described in terms of vertical layers. The
epilimnionrefers to the warm surface layer that is homogeneous due to mixing. The depth of the epilimnion can influence air–water exchanges and the vertical distribution of biological variables. We compared various methods for defining the epilimnion layer and found large variability between methods. Certain methods may be better suited for applications such as multi-lake comparison and assessing the impact of climate change.
Cited articles
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Short summary
We assessed the predictive skill of forecasting tools over the next season for water discharge and lake temperature. Tools were forced with seasonal weather predictions; however, most of the prediction skill originates from legacy effects and not from seasonal weather predictions. Yet, when skills from seasonal weather predictions are present, additional skill comes from interaction effects. Skilful lake seasonal predictions require better weather predictions and realistic antecedent conditions.
We assessed the predictive skill of forecasting tools over the next season for water discharge...
