Articles | Volume 26, issue 2
https://doi.org/10.5194/hess-26-279-2022
© Author(s) 2022. 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-26-279-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2022
Research article |
| 24 Jan 2022
| 24 Jan 2022
Diagnostic evaluation of river discharge into the Arctic Ocean and its impact on oceanic volume transports
Susanna Winkelbauer
CORRESPONDING AUTHOR
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Michael Mayer
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Vanessa Seitner
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Ervin Zsoter
European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Leopold Haimberger
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
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Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2883, https://doi.org/10.5194/egusphere-2023-2883, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data is complicated by the distortion of the used modelling grids and the large number of different grid-types. We present two new methods that allow to calculate oceanic fluxes of volume, heat, salinity and ice through almost arbitrary sections for various models and reanalyses, independent of the used modelling grids.
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This paper compares oceanic fluxes across the Greenland–Scotland Ridge (GSR) from ocean reanalyses to largely independent observational data. Reanalyses tend to underestimate the inflow of warm waters of subtropical Atlantic origin and hence oceanic heat transport across the GSR. Investigation of a strong negative heat transport anomaly around 2018 highlights the interplay of variability on different timescales and the need for long-term monitoring of the GSR to detect forced climate signals.
Magdalena Fritz, Michael Mayer, Leopold Haimberger, and Susanna Winkelbauer
Ocean Sci., 19, 1203–1223, https://doi.org/10.5194/os-19-1203-2023, https://doi.org/10.5194/os-19-1203-2023, 2023
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The interaction between the Indonesian Throughflow (ITF) and regional climate phenomena indicates the high relevance for monitoring the ITF. Observations remain temporally and spatially limited; hence near-real-time monitoring is only possible with reanalyses. We assess how well ocean reanalyses depict the intensity of the ITF via comparison to observations. The results show that reanalyses agree reasonably well with in situ observations; however, some aspects require higher-resolution products.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2883, https://doi.org/10.5194/egusphere-2023-2883, 2024
Short summary
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data is complicated by the distortion of the used modelling grids and the large number of different grid-types. We present two new methods that allow to calculate oceanic fluxes of volume, heat, salinity and ice through almost arbitrary sections for various models and reanalyses, independent of the used modelling grids.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-215, https://doi.org/10.5194/gmd-2023-215, 2023
Revised manuscript accepted for GMD
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Ocean Sci., 19, 1203–1223, https://doi.org/10.5194/os-19-1203-2023, https://doi.org/10.5194/os-19-1203-2023, 2023
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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
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Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina I. Kristiansen, Massimo Cassiani, Sabine Eckhardt, Delia Arnold, Don Morton, Rona L. Thompson, Christine D. Groot Zwaaftink, Nikolaos Evangeliou, Harald Sodemann, Leopold Haimberger, Stephan Henne, Dominik Brunner, John F. Burkhart, Anne Fouilloux, Jerome Brioude, Anne Philipp, Petra Seibert, and Andreas Stohl
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Jamie Towner, Hannah L. Cloke, Ervin Zsoter, Zachary Flamig, Jannis M. Hoch, Juan Bazo, Erin Coughlan de Perez, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci., 23, 3057–3080, https://doi.org/10.5194/hess-23-3057-2019, https://doi.org/10.5194/hess-23-3057-2019, 2019
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This study presents an intercomparison analysis of eight global hydrological models (GHMs), assessing their ability to simulate peak river flows in the Amazon basin. Results indicate that the meteorological input is the most influential component of the hydrological modelling chain, with the recent ERA-5 reanalysis dataset significantly improving the ability to simulate flood peaks in the Peruvian Amazon. In contrast, calibration of the Lisflood routing model was found to have no impact.
Hao Zuo, Magdalena Alonso Balmaseda, Steffen Tietsche, Kristian Mogensen, and Michael Mayer
Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, https://doi.org/10.5194/os-15-779-2019, 2019
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OCEAN5 is the fifth generation of the ocean and sea-ice analysis system at ECMWF. It was used for production of historical ocean and sea-ice states from 1979 onwards and is also used for generating real-time ocean and sea-ice states responsible for initializing the operational ECMWF weather forecasting system. This is a valuable data set with broad applications. A description of the OCEAN5 system and an assessment of the historical data set have been documented in this reference paper.
Christopher D. Roberts, Retish Senan, Franco Molteni, Souhail Boussetta, Michael Mayer, and Sarah P. E. Keeley
Geosci. Model Dev., 11, 3681–3712, https://doi.org/10.5194/gmd-11-3681-2018, https://doi.org/10.5194/gmd-11-3681-2018, 2018
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This paper presents climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6).
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346, https://doi.org/10.5194/gmd-11-3327-2018, https://doi.org/10.5194/gmd-11-3327-2018, 2018
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Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Jean-François Legeais, Michaël Ablain, Lionel Zawadzki, Hao Zuo, Johnny A. Johannessen, Martin G. Scharffenberg, Luciana Fenoglio-Marc, M. Joana Fernandes, Ole Baltazar Andersen, Sergei Rudenko, Paolo Cipollini, Graham D. Quartly, Marcello Passaro, Anny Cazenave, and Jérôme Benveniste
Earth Syst. Sci. Data, 10, 281–301, https://doi.org/10.5194/essd-10-281-2018, https://doi.org/10.5194/essd-10-281-2018, 2018
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Sea level is one of the best indicators of climate change and has been listed as one of the essential climate variables. Sea level measurements have been provided by satellite altimetry for 25 years, and the Climate Change Initiative (CCI) program of the European Space Agency has given the opportunity to provide a long-term, homogeneous and accurate sea level record. It will help scientists to better understand climate change and its variability.
Marianne Pietschnig, Michael Mayer, Takamasa Tsubouchi, Andrea Storto, Sebastian Stichelberger, and Leopold Haimberger
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-98, https://doi.org/10.5194/os-2017-98, 2017
Revised manuscript not accepted
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New estimates of volume and temperature transports into the Arctic Ocean through the four major gateways (Davis, Fram and Bering Strait and the Barents Sea Opening) have recently become available. These estimates are derived from moored observations. In this study, the same transports derived from a recent ocean reanalysis are compared to the observation-based estimates in the straits. In addition, cross-section plots of velocity, temperature and temperature flux density are investigated.
Erin Coughlan de Perez, Bart van den Hurk, Maarten K. van Aalst, Irene Amuron, Deus Bamanya, Tristan Hauser, Brenden Jongma, Ana Lopez, Simon Mason, Janot Mendler de Suarez, Florian Pappenberger, Alexandra Rueth, Elisabeth Stephens, Pablo Suarez, Jurjen Wagemaker, and Ervin Zsoter
Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, https://doi.org/10.5194/hess-20-3549-2016, 2016
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Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.
L. Ramella Pralungo and L. Haimberger
Earth Syst. Sci. Data, 6, 297–316, https://doi.org/10.5194/essd-6-297-2014, https://doi.org/10.5194/essd-6-297-2014, 2014
L. Ramella Pralungo, L. Haimberger, A. Stickler, and S. Brönnimann
Earth Syst. Sci. Data, 6, 185–200, https://doi.org/10.5194/essd-6-185-2014, https://doi.org/10.5194/essd-6-185-2014, 2014
Related subject area
Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
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Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model
Global change in streamflow extremes under climate change over the 21st century
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Sensitivity of future continental United States water deficit projections to general circulation models, the evapotranspiration estimation method, and the greenhouse gas emission scenario
Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use
Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach
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The impact of climate mitigation on projections of future drought
Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data
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Improving runoff estimates from regional climate models: a performance analysis in Spain
A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models
Error characterisation of global active and passive microwave soil moisture datasets
Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations
Petra Döll, H. M. Mehedi Hasan, Kerstin Schulze, Helena Gerdener, Lara Börger, Somayeh Shadkam, Sebastian Ackermann, Seyed-Mohammad Hosseini-Moghari, Hannes Müller Schmied, Andreas Güntner, and Jürgen Kusche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-18, https://doi.org/10.5194/hess-2023-18, 2023
Revised manuscript accepted for HESS
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For the pilot region Mississippi River basin, we explored three model calibration approaches for using both streamflow and total water storage anomaly (TWSA) observations to adjust parameter sets of a global hydrological model. We developed a method for considering the observation uncertainties to determine not only optimal but also behavioral parameter sets and model output uncertainty. Model performance was improved but trade-offs between optimal fits to streamflow and TWSA may be large.
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423, https://doi.org/10.5194/hess-26-1407-2022, https://doi.org/10.5194/hess-26-1407-2022, 2022
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The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
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Hiroki Mizuochi, Agnès Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Vladislav Bastrikov, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci., 25, 2199–2221, https://doi.org/10.5194/hess-25-2199-2021, https://doi.org/10.5194/hess-25-2199-2021, 2021
Samuel Saxe, William Farmer, Jessica Driscoll, and Terri S. Hogue
Hydrol. Earth Syst. Sci., 25, 1529–1568, https://doi.org/10.5194/hess-25-1529-2021, https://doi.org/10.5194/hess-25-1529-2021, 2021
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We compare simulated values from 47 models estimating surface water over the USA. Results show that model uncertainty is substantial over much of the conterminous USA and especially high in the west. Applying the studied models to a simple water accounting equation shows that model selection can significantly affect research results. This paper concludes that multimodel ensembles help to best represent uncertainty in conclusions and suggest targeted research efforts in arid regions.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
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We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Toby R. Marthews, Eleanor M. Blyth, Alberto Martínez-de la Torre, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 24, 75–92, https://doi.org/10.5194/hess-24-75-2020, https://doi.org/10.5194/hess-24-75-2020, 2020
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Climate change impact modellers can only act on predictions of the occurrence of an extreme event in the Earth system if they know the uncertainty in that prediction and how uncertainty is attributable to different model components. Using eartH2Observe data, we quantify the balance between different sources of uncertainty in global evapotranspiration and runoff, making a crucial contribution to understanding the spatial distribution of water resources allocation deficiencies.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, https://doi.org/10.5194/hess-22-4667-2018, 2018
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Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
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We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Behzad Asadieh and Nir Y. Krakauer
Hydrol. Earth Syst. Sci., 21, 5863–5874, https://doi.org/10.5194/hess-21-5863-2017, https://doi.org/10.5194/hess-21-5863-2017, 2017
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Multi-model analysis of global streamflow extremes for the 20th and 21st centuries under two warming scenarios is performed. About 37 and 43 % of global land areas show potential for increases in flood and drought events. Nearly 10 % of global land areas, holding around 30 % of world’s population, reflect a potentially worsening hazard of flood and drought. A significant increase in streamflow of the regions near and above the Arctic Circle, and decrease in subtropical arid areas, is projected.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Seungwoo Chang, Wendy D. Graham, Syewoon Hwang, and Rafael Muñoz-Carpena
Hydrol. Earth Syst. Sci., 20, 3245–3261, https://doi.org/10.5194/hess-20-3245-2016, https://doi.org/10.5194/hess-20-3245-2016, 2016
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Projecting water deficit depends on how researchers combine possible future climate scenarios such as general circulation models (GCMs), evapotranspiration estimation method (ET), and greenhouse gas emission scenarios. Using global sensitivity analysis, we found the relative contribution of each of these factors to projecting future water deficit and the choice of ET estimation method are as important as the choice of GCM, and greenhouse gas emission scenario is less influential than the others.
Hannes Müller Schmied, Linda Adam, Stephanie Eisner, Gabriel Fink, Martina Flörke, Hyungjun Kim, Taikan Oki, Felix Theodor Portmann, Robert Reinecke, Claudia Riedel, Qi Song, Jing Zhang, and Petra Döll
Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, https://doi.org/10.5194/hess-20-2877-2016, 2016
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The assessment of water balance components of the global land surface by means of hydrological models is affected by large uncertainties, in particular related to meteorological forcing. We analyze the effect of five state-of-the-art forcings on water balance components at different spatial and temporal scales modeled with WaterGAP. Furthermore, the dominant effect (precipitation/human alteration) for long-term changes in river discharge is assessed.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
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Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
H. Müller Schmied, S. Eisner, D. Franz, M. Wattenbach, F. T. Portmann, M. Flörke, and P. Döll
Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, https://doi.org/10.5194/hess-18-3511-2014, 2014
P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
H. Xie, L. Longuevergne, C. Ringler, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 16, 3083–3099, https://doi.org/10.5194/hess-16-3083-2012, https://doi.org/10.5194/hess-16-3083-2012, 2012
F. Sienz, O. Bothe, and K. Fraedrich
Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, https://doi.org/10.5194/hess-16-2143-2012, 2012
D. González-Zeas, L. Garrote, A. Iglesias, and A. Sordo-Ward
Hydrol. Earth Syst. Sci., 16, 1709–1723, https://doi.org/10.5194/hess-16-1709-2012, https://doi.org/10.5194/hess-16-1709-2012, 2012
S. N. Gosling, R. G. Taylor, N. W. Arnell, and M. C. Todd
Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, https://doi.org/10.5194/hess-15-279-2011, 2011
W. A. Dorigo, K. Scipal, R. M. Parinussa, Y. Y. Liu, W. Wagner, R. A. M. de Jeu, and V. Naeimi
Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, https://doi.org/10.5194/hess-14-2605-2010, 2010
G. Schumann, D. J. Lunt, P. J. Valdes, R. A. M. de Jeu, K. Scipal, and P. D. Bates
Hydrol. Earth Syst. Sci., 13, 1545–1553, https://doi.org/10.5194/hess-13-1545-2009, https://doi.org/10.5194/hess-13-1545-2009, 2009
Cited articles
Aagaard, K. and Carmack, E. C.: The role of sea ice and other fresh water in
the Arctic circulation, J. Geophys. Res.-Oceans, 94, 14485–14498, https://doi.org/10.1029/JC094iC10p14485, 1989. a
Bacon, S., Aksenov, Y., Fawcett, S., and Madec, G.: Arctic mass, freshwater and heat fluxes: methods and modelled seasonal variability, Philos. T. Roy. Soc. A, 373, 20140169, https://doi.org/10.1098/rsta.2014.0169, 2015. a, b, c, d
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643,
https://doi.org/10.1175/2008JHM1068.1, 2009. a
Blockley, E. W., Martin, M. J., McLaren, A. J., Ryan, A. G., Waters, J., Lea,
D. J., Mirouze, I., Peterson, K. A., Sellar, A., and Storkey, D.: Recent
development of the Met Office operational ocean forecasting system: an
overview and assessment of the new Global FOAM forecasts, Geosci. Model Dev., 7, 2613–2638, https://doi.org/10.5194/gmd-7-2613-2014, 2014. a
Box, J. E., Colgan, W. T., Wouters, B., Burgess, D. O., O'Neel, S., Thomson,
L. I., and Mernild, S. H.: Global sea-level contribution from Arctic land
ice: 1971–2017, Environ. Res. Lett., 13, 125012,
https://doi.org/10.1088/1748-9326/aaf2ed, 2018. a
Burek, P., Van der Knijff, J., and De Roo, A.: LISFLOOD – Distributed Water
Balance and Flood Simulation Model – Revised User Manual 2013,
https://doi.org/10.2788/24982, 2013. a
Cao, B., Gruber, S., Zheng, D., and Li, X.: The ERA5-Land soil temperature bias in permafrost regions, The Cryosphere, 14, 2581–2595,
https://doi.org/10.5194/tc-14-2581-2020, 2020. a
Church, J., Clark, P., Cazenave, A., Gregory, J., Jevrejeva, S., Levermann, A., Merrifield, M., Milne, G., Nerem, R., Nunn, P., Payne, A., Pfeffer, W.,
Stammer, D., and Unnikrishnan, A.: Sea Level Change, in: Climate Change 2013:
The Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1535 pp.,
ISBN 978-1-107-05799-1, 2013. a
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, ISBN 978-1-107-05799-1, 2013. a
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S.,
Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted
ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020. a
Curry, B., Lee, C. M., and Petrie, B.: Volume, Freshwater, and Heat Fluxes
through Davis Strait, 2004–05, J. Phys. Oceanogr., 41, 429–436, https://doi.org/10.1175/2010JPO4536.1, 2011. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Desportes, C., Garric, G., Régnier, C., Drévillon, M., Parent, L., Drillet, Y., Masina, S., Storto, A., Mirouze, I., Cipollone, A., Zuo, H., Balmaseda, M., Peterson, D., Wood, R., Jackson, L., Mulet, S., and Greiner, E.: CMEMS-GLO-QUID-001-026, EU Copernicus Marine Service Information, available at: https://oceanrep.geomar.de/46419/1/CMEMS-GLO-QUID-001-024.pdf (last access: 2 August 2021), 2017. a
Dickson, R., Rudels, B., Dye, S., Karcher, M., Meincke, J., and Yashayaev, I.: Current estimates of freshwater flux through Arctic and subarctic seas,
Prog. Oceanogr., 73, 210–230, https://doi.org/10.1016/j.pocean.2006.12.003, 2007. a, b, c
Fukumori, I., Wang, O., Llovel, W., Fenty, I., and Forget, G.: A near-uniform
fluctuation of ocean bottom pressure and sea level across the deep ocean basins of the Arctic Ocean and the Nordic Seas, Prog. Oceanogr., 134, 152–172, https://doi.org/10.1016/j.pocean.2015.01.013, 2015. a
Garric, G., Parent, L., Greiner, E., Drévillon, M., Hamon, M., Lellouche, J.-M., Régnier, C., Desportes, C., Le Galloudec, O., Bricaud, C., Drillet, Y., Hernandez, F., and Le Traon, P.-Y.: Performance and quality assessment of the global ocean eddy-permitting physical reanalysis GLORYS2V4, in: EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, 23–28 April 2017, Vienna, Austria, p. 18776, available at: https://presentations.copernicus.org/EGU2017/EGU2017-18776_presentation.pdf
(last access: 15 April 2021), 2017. a
GRDC: WMO Basins and Sub-Basins/Global Runoff Data Centre, GRDC, 3rd. rev.
ext. Edn., Federal Institute of Hydrology (BfG), Koblenz, Germany, available at: https://www.bafg.de/GRDC/EN/02_srvcs/22_gslrs/223_WMO/wmo_regions_node.html
(last access: 4 June 2021), 2020. a
Haine, T. W., Curry, B., Gerdes, R., Hansen, E., Karcher, M., Lee, C., Rudels, B., Spreen, G., de Steur, L., Stewart, K. D., and Woodgate, R.: Arctic freshwater export: Status, mechanisms, and prospects, Global Planet. Change, 125, 13–35, https://doi.org/10.1016/j.gloplacha.2014.11.013, 2015. a, b, c, d, e, f
Haine, T. W. N.: Arctic Ocean Freshening Linked to Anthropogenic Climate
Change: All Hands on Deck, Geophys. Res. Lett., 47, e2020GL090678, https://doi.org/10.1029/2020GL090678, 2020. a
Harrigan, S., Zsoter, E., Barnard, C. F. W., Salamon, P., and Prudhomme, C.:
River discharge and related historical data from the Global Flood Awareness
System, v2.1, CDS [data set], https://doi.org/10.24381/cds.a4fdd6b9, 2019. a, b
Harrigan, S., Zsoter, E., Alfieri, L., Prudhomme, C., Salamon, P., Wetterhall, F., Barnard, C., Cloke, H., and Pappenberger, F.: GloFAS-ERA5 operational global river discharge reanalysis 1979–present, Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, 2020. a, b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1979 to present, CDS [data set],
https://doi.org/10.24381/cds.f17050d7, 2019. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global
reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b, c
Holmes, R., Shiklomanov, A., Suslova, A., Tretiakov, M., McClelland, J.,
Spencer, R., and Tank, S.: River Discharge, Arctic Report Card: Update for 2018, available at:
https://arctic.noaa.gov/Report-Card/Report-Card-2018/ArtMID/7878/ArticleID/786/River-Discharge (last access: 1 June 2021), 2018. a, b, c
Jeon, T., Seo, K.-W., Kim, B.-H., Kim, J.-S., Chen, J., and Wilson, C. R.: Sea level fingerprints and regional sea level change, Earth Planet. Sc. Lett., 567, 116985, https://doi.org/10.1016/j.epsl.2021.116985, 2021. a
Knijff, J. M. V. D., Younis, J., and Roo, A. P. J. D.: LISFLOOD: a GIS‐based
distributed model for river basin scale water balance and flood simulation,
Int. J. Geogr. Inform. Sci., 24, 189–212, https://doi.org/10.1080/13658810802549154, 2010. a
Kobayashi, C., Endo, H., Ota, Y., Kobayashi, S., Onoda, H., Harada, Y., Onogi, K., and Kamahori, H.: Preliminary Results of the JRA-55C, an Atmospheric Reanalysis Assimilating Conventional Observations Only, Scient. Online Lett. Atmos., 10, 78–82, https://doi.org/10.2151/sola.2014-016, 2014. a
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.:
The JRA-55 Reanalysis: General Specifications and Basic Characteristics, J. Meteorol. Soc. Jpn. Ser. II, 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015. a
Lammers, R. B., Shiklomanov, A. I., Vörösmarty, C. J., Fekete, B. M., and Peterson, B. J.: Assessment of contemporary Arctic river runoff based on
observational discharge records, J. Geophys. Res.-Atmos., 106, 3321–3334, https://doi.org/10.1029/2000JD900444, 2001. a, b, c
Landerer, F.: CSR TELLUS GRACE Level-3 Monthly Ocean Bottom Pressure Anomaly
RL06 v03, NASA [data set], https://doi.org/10.5067/TEOCN-3AC63, 2020a. a
Landerer, F.: CSR TELLUS GRACE Level-3 Monthly Land Water-Equivalent-Thickness Surface Mass Anomaly RL06 v03, NASA [data set], https://doi.org/10.5067/TELND-3AC63, 2020b. a
Landerer, F. W., Flechtner, F. M., Save, H., Webb, F. H., Bandikova, T.,
Bertiger, W. I., Bettadpur, S. V., Byun, S. H., Dahle, C., Dobslaw, H.,
Fahnestock, E., Harvey, N., Kang, Z., Kruizinga, G. L. H., Loomis, B. D.,
McCullough, C., Murböck, M., Nagel, P., Paik, M., Pie, N., Poole, S.,
Strekalov, D., Tamisiea, M. E., Wang, F., Watkins, M. M., Wen, H.-Y., Wiese,
D. N., and Yuan, D.-N.: Extending the Global Mass Change Data Record: GRACE
Follow-On Instrument and Science Data Performance, Geophys. Res. Lett., 47, e2020GL088306, https://doi.org/10.1029/2020GL088306, 2020. a
L'Ecuyer, T. S., Beaudoing, H. K., Rodell, M., Olson, W., Lin, B., Kato, S.,
Clayson, C. A., Wood, E., Sheffield, J., Adler, R., Huffman, G., Bosilovich,
M., Gu, G., Robertson, F., Houser, P. R., Chambers, D., Famiglietti, J. S.,
Fetzer, E., Liu, W. T., Gao, X., Schlosser, C. A., Clark, E., Lettenmaier, D. P., and Hilburn, K.: The Observed State of the Energy Budget in the Early
Twenty-First Century, J. Climate, 28, 8319–8346, https://doi.org/10.1175/JCLI-D-14-00556.1, 2015. a, b
Lin, X., Massonnet, F., Yang, C., Artale, V., de Toma, V., and Rana, A.: Arctic freshwater cycle and the interaction with the North Atlantic, in: eGU General Assembly 2021, online, 19–30 April 2021, EGU21-436, https://doi.org/10.5194/egusphere-egu21-436, 2021. a
Loomis, B. D., Luthcke, S., and Sabaka, T. J.: Regularization and error
characterization of GRACE mascons, J. Geod., 93, 1381–1398,
https://doi.org/10.1007/s00190-019-01252-y, 2019. a
Ludwigsen, C. A., Andersen, O. B., and Rose, S. K.: Assessment of 21 years of Arctic Ocean Absolute Sea Level Trends (1995–2015), Ocean Sci. Discuss. [preprint], https://doi.org/10.5194/os-2020-87, in review, 2020. a
Madec, G., Team, N. S., and Team, N. S.: NEMO ocean engine, Zenodo,
https://doi.org/10.5281/zenodo.1464816, 2019. a, b, c
Mankoff, K. D., Noël, B., Fettweis, X., Ahlstrøm, A. P., Colgan, W.,
Kondo, K., Langley, K., Sugiyama, S., van As, D., and Fausto, R. S.:
Greenland liquid water discharge from 1958 through 2019, Earth Syst. Sci.
Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, 2020a. a, b, c
Mankoff, K. D., Solgaard, A., Colgan, W., Ahlstrøm, A. P., Khan, S. A., and Fausto, R. S.: Greenland Ice Sheet solid ice discharge from 1986 through
March 2020, Earth Syst. Sci. Data, 12, 1367–1383, https://doi.org/10.5194/essd-12-1367-2020, 2020b. a, b, c, d
Mayer, M., Alonso Balmaseda, M., and Haimberger, L.: Unprecedented 2015/2016 Indo-Pacific Heat Transfer Speeds Up Tropical Pacific Heat Recharge, Geophys. Res. Lett., 45, 3274–3284, https://doi.org/10.1002/2018GL077106,
2018. a
Mayer, M., Tietsche, S., Haimberger, L., Tsubouchi, T., Mayer, J., and Zuo, H.: An Improved Estimate of the Coupled Arctic Energy Budget, J. Climate, 32, 7915–7934, https://doi.org/10.1175/JCLI-D-19-0233.1, 2019. a, b
Moon, T., Ahlstrom, A., Goelzer, H., Lipscomb, W., and Nowicki, S.: Rising
Oceans Guaranteed: Arctic Land Ice Loss and Sea Level Rise, Curr. Clim. Change Rep., 4, 211–222, https://doi.org/10.1007/s40641-018-0107-0, 2018. a
Morison, J., Kwok, R., Peralta Ferriz, C., Alkire, M., Rigor, I., Andersen, R., and Steele, M.: Changing Arctic Ocean freshwater pathways, Nature, 481,
66–70, https://doi.org/10.1038/nature10705, 2012. a, b
Muñoz Sabater, J.: ERA5-Land monthly averaged data from 1981 to present,
CDS [data set], https://doi.org/10.24381/cds.68d2bb30, 2019. a, b
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021. a, b
Muntjewerf, L., Petrini, M., Vizcaino, M., Ernani da Silva, C., Sellevold, R., Scherrenberg, M. D. W., Thayer-Calder, K., Bradley, S. L., Lenaerts, J.
T. M., Lipscomb, W. H., and Lofverstrom, M.: Greenland Ice Sheet Contribution
to 21st Century Sea Level Rise as Simulated by the Coupled CESM2.1-CISM2.1,
Geophys. Res. Lett., 47, e2019GL086836, https://doi.org/10.1029/2019GL086836, 2020. a
Proshutinsky, A., Pavlov, V., and Bourke, R. H.: Sea level rise in the Arctic
Ocean, Geophys. Res. Lett., 28, 2237–2240, https://doi.org/10.1029/2000GL012760, 2001. a
Proshutinsky, A., Krishfield, R., Toole, J. M., Timmermans, M.-L., Williams,
W., Zimmermann, S., Yamamoto-Kawai, M., Armitage, T. W. K., Dukhovskoy, D.,
Golubeva, E., Manucharyan, G. E., Platov, G., Watanabe, E., Kikuchi, T.,
Nishino, S., Itoh, M., Kang, S.-H., Cho, K.-H., Tateyama, K., and Zhao, J.:
Analysis of the Beaufort Gyre Freshwater Content in 2003–2018, J. Geophys. Res.-Oceans, 124, 9658–9689, https://doi.org/10.1029/2019JC015281, 2019. a
Prowse, T. D. and Flegg, P. O.: The magnitude of river flow to the Arctic
Ocean: dependence on contributing area, Hydrol. Process., 14, 3185–3188,
https://doi.org/10.1002/1099-1085(200011/12)14:16/17<3185::AID-HYP170>3.0.CO;2-S, 2000. a
Rawlins, M. A., Steele, M., Holland, M. M., Adam, J. C., Cherry, J. E.,
Francis, J. A., Groisman, P. Y., Hinzman, L. D., Huntington, T. G., Kane, D. L., Kimball, J. S., Kwok, R., Lammers, R. B., Lee, C. M., Lettenmaier, D. P., McDonald, K. C., Podest, E., Pundsack, J. W., Rudels, B., Serreze, M. C., Shiklomanov, A., Øystein, S., Troy, T. J., Vörösmarty, C. J.,
Wensnahan, M., Wood, E. F., Woodgate, R., Yang, D., Zhang, K., and Zhang, T.:
Analysis of the Arctic System for Freshwater Cycle Intensification:
Observations and Expectations, J. Climate, 23, 5715–5737, https://doi.org/10.1175/2010JCLI3421.1, 2010. a
Rodell, M., Beaudoing, H. K., L'Ecuyer, T. S., Olson, W. S., Famiglietti, J. S., Houser, P. R., Adler, R., Bosilovich, M. G., Clayson, C. A., Chambers, D., Clark, E., Fetzer, E. J., Gao, X., Gu, G., Hilburn, K., Huffman, G. J.,
Lettenmaier, D. P., Liu, W. T., Robertson, F. R., Schlosser, C. A., Sheffield, J., and Wood, E. F.: The Observed State of the Water Cycle in the
Early Twenty-First Century, J. Climate, 28, 8289–8318,
https://doi.org/10.1175/JCLI-D-14-00555.1, 2015. a, b
Save, H.: CSR GRACE and GRACE-FO RL06 Mascon Solutions v02, GRACE,
https://doi.org/10.15781/cgq9-nh24, 2020. a
Save, H., Bettadpur, S., and Tapley, B. D.: High-resolution CSR GRACE RL05
mascons, J. Geophys. Res.-Solid, 121, 7547–7569, https://doi.org/10.1002/2016JB013007, 2016. a
Schauer, U. and Losch, M.: “Freshwater” in the Ocean is Not a Useful
Parameter in Climate Research, J. Phys. Oceanogr., 49, 2309–2321, https://doi.org/10.1175/JPO-D-19-0102.1, 2019. a
Serreze, M. C. and Barry, R. G.: The Arctic Climate System, Cambridge
Atmospheric and Space Science Series, 2nd Edn., Cambridge University Press,
https://doi.org/10.1017/CBO9781139583817, 2014. a
Shiklomanov, A. and Lammers, R.: 5.11 – Changing Discharge Patterns of
High-Latitude Rivers, in: Climate Vulnerability, edited by: Pielke, R. A.,
Academic Press, Oxford, 161–175, https://doi.org/10.1016/B978-0-12-384703-4.00526-8,
2013. a, b, c
Shiklomanov, A. I. and Vuglinsky, V. S.: Hydrological networks, available at:
https://www.arcticobserving.org/images/pdf/Workshops/4th_stpetersburg/slideshow/shiklomanov_ppt.pdf
(last access: 9 June 2021), 2008. a
Shiklomanov, A. I., Lammers, R. B., and Vörösmarty, C. J.: Widespread decline in hydrological monitoring threatens Pan-Arctic Research, Eos Trans. Am. Geophys. Union, 83, 13–17, https://doi.org/10.1029/2002EO000007, 2002. a, b, c
Shiklomanov, I. and Shiklomanov, A.: Climatic Change and the Dynamics of River Runoff into the Arctic Ocean, Water Resour., 30, 593–601,
https://doi.org/10.1023/B:WARE.0000007584.73692.ca, 2003. a, b, c
Stahl, K., Tallaksen, L. M., Hannaford, J., and van Lanen, H. A. J.: Filling
the white space on maps of European runoff trends: estimates from a multi-model ensemble, Hydrol. Earth Syst. Sci., 16, 2035–2047,
https://doi.org/10.5194/hess-16-2035-2012, 2012. a
Storto, A. and Masina, S.: C-GLORSv5: an improved multipurpose global ocean
eddy-permitting physical reanalysis, Earth Syst. Sci. Data, 8, 679–696,
https://doi.org/10.5194/essd-8-679-2016, 2016. a
Storto, A., Masina, S., Simoncelli, S., Iovino, D., Cipollone, A., Drevillon,
M., Drillet, Y., Schuckmann, K., Parent, L., Garric, G., Greiner, E.,
Desportes, C., Zuo, H., Balmaseda, M., and Peterson, K.: The added value of
the multi-system spread information for ocean heat content and steric sea
level investigations in the CMEMS GREP ensemble reanalysis product, Clim.
Dynam., 53, 287–312, https://doi.org/10.1007/s00382-018-4585-5, 2019. a, b, c
Syed, T. H., Famiglietti, J. S., Zlotnicki, V., and Rodell, M.: Contemporary
estimates of Pan-Arctic freshwater discharge from GRACE and reanalysis,
Geophys. Res. Lett., 34, L19404, https://doi.org/10.1029/2007GL031254, 2007. a
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity
recovery and climate experiment: Mission overview and early results,
Geophys. Res. Lett., 31, L09607, https://doi.org/10.1029/2004GL019920, 2004. a
Tsubouchi, T., Bacon, S., Naveira Garabato, A. C., Aksenov, Y., Laxon, S. W.,
Fahrbach, E., Beszczynska-Möller, A., Hansen, E., Lee, C. M., and
Ingvaldsen, R. B.: The Arctic Ocean in summer: A quasi-synoptic inverse
estimate of boundary fluxes and water mass transformation, J. Geophys. Res.-Oceans, 117, C01024, https://doi.org/10.1029/2011JC007174, 2012. a, b, c, d, e
Tsubouchi, T., Bacon, S., Aksenov, Y., Garabato, A. C. N., Beszczynska-Möller, A., Hansen, E., de Steur, L., Curry, B., and Lee, C. M.: The Arctic Ocean Seasonal Cycles of Heat and Freshwater Fluxes: Observation-Based Inverse Estimates, J. Phys. Oceanogr., 48, 2029–2055,
https://doi.org/10.1175/JPO-D-17-0239.1, 2018. a, b, c, d
Tsubouchi, T., von Appen, W.-J., Schauer, U., Kanzow, T., Lee, C., Curry, B., de Steur, L., Ingvaldsen, R., and Woodgate, R. A.: The Arctic Ocean volume, heat and fresh water transports time series from October 2004 to May 2010, PANGEA, https://doi.org/10.1594/PANGAEA.909966, 2019. a, b
Uotila, P., Goosse, H., Haines, K., Chevallier, M., Barthelemy, A., Bricaud,
C., Carton, J., Fuckar, N., Garric, G., Iovino, D., Kauker, F., Korhonen, M.,
Lien, V., Marnela, M., Massonnet, F., Mignac, D., Peterson, K. A., Sadikini,
R., Shi, L., Tietsche, S., Toyoda, T., Xie, J., and Zhang, Z.: An assessment of ten ocean reanalyses in the polar regions, Clim. Dynam., 52, 1613–1650, https://doi.org/10.1007/s00382-018-4242-z, 2019. a
Vaughan, D., Comiso, J., Allison, I., Carrasco, J., Kaser, G., Kwok, R., Mote, P., Murray, T., Paul, F., Ren, J., Rignot, E., Solomina, O., Steffen, K., and Zhang, T.: Observations: Cryosphere, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, https://doi.org/10.1017/CBO9781107415324.012, 2013. a
Volkov, D. L. and Landerer, F. W.: Nonseasonal fluctuations of the Arctic Ocean mass observed by the GRACE satellites, J. Geophys. Res.-Oceans, 118, 6451–6460, https://doi.org/10.1002/2013JC009341, 2013. a, b
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., and Landerer, F. W.:
Improved methods for observing Earth's time variable mass distribution with
GRACE using spherical cap mascons, J. Geophys. Res.-Solid, 120, 2648–2671, https://doi.org/10.1002/2014JB011547, 2015. a, b
Wiese, D. N., Yuan, D.-N., Boening, C., Landerer, F. W., and Watkins, M. M.:
JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height Release 06
Coastal Resolution Improvement (CRI) Filtered Version 1.0, NASA,
https://doi.org/10.5067/TEMSC-3MJC6, 2018. a
Wouters, B., Gardner, A., and Moholdt, G.: Global Glacier Mass Loss During the GRACE Satellite Mission (2002–2016), Front. Earth Sci., 7, 96,
https://doi.org/10.3389/feart.2019.00096, 2019. a, b
Yang, D., Ye, B., and Kane, L. D.: Streamflow changes over Siberian Yenisei
River Basin, J. Hydrol., 296, 59–80, https://doi.org/10.1016/j.jhydrol.2004.03.017, 2004a. a
Yang, D., Ye, B., and Shiklomanov, A.: Discharge Characteristics and Changes
over the Ob River Watershed in Siberia, J. Hydrometeorol., 5, 595–610, https://doi.org/10.1175/1525-7541(2004)005<0595:DCACOT>2.0.CO;2, 2004b. a, b
Yang, D., Zhao, Y., Armstrong, R., Robinson, D., and Brodzik, M.-J.: Streamflow response to seasonal snow cover mass changes over large Siberian watersheds, J. Geophys. Res.-Earth, 112, F02S22, https://doi.org/10.1029/2006JF000518, 2007. a
Ye, B., Yang, D., and Kane, D. L.: Changes in Lena River streamflow hydrology: Human impacts versus natural variations, Water Resour. Res., 39,
1200, https://doi.org/10.1029/2003WR001991, 2003. a
Zuo, H., Alonso-Balmaseda, M., Mogensen, K., and Tietsche, S.: OCEAN5: The
ECMWF Ocean Reanalysis System and its Real-Time analysis component, ECMWF,
https://doi.org/10.21957/la2v0442, 2018. a
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M.: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment, Ocean Sci., 15, 779–808,
https://doi.org/10.5194/os-15-779-2019, 2019. a
Zuo, H., de Boisseson, E., Zsoter, E., Harrigan, S., de Rosnay, P., Wetterhall, F., and Prudhomme, C.: Benefits of dynamically modelled river discharge input for ocean and coupled atmosphere-land-ocean systems, J. Adv. Model. Earth Syst., in preperation, 2022. a
Short summary
We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses, inter alia the most recent Global Flood Awareness System (GloFAS) river discharge reanalysis version 3.1. Furthermore, we combine reanalysis data, in situ observations, ocean reanalyses, and satellite data and use a Lagrangian optimization scheme to close the Arctic's volume budget on annual and seasonal scales, resulting in one reliable and up-to-date estimate of every volume budget term.
We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses,...
