Preprints
https://doi.org/10.5194/egusphere-2025-5331
https://doi.org/10.5194/egusphere-2025-5331
07 Nov 2025
 | 07 Nov 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

An improved modelling chain for bias-adjusted high-resolution climate and hydrological projections for Norway

Shaochun Huang, Wai Kwok Wong, Andreas Dobler, Sigrid Jørgensen Bakke, Stein Beldring, Ingjerd Haddeland, Hans Olav Hygen, Tyge Løvset, Stephanie Mayer, Kjetil Melvold, Irene Brox Nilsen, Gusong Ruan, Silje Lund Sørland, and Anita Verpe Dyrrdal

Abstract. About every 10 years, the Norwegian Centre for Climate Services publishes a national climate assessment report, presenting the updated historical climate change and climate projections towards the end of this century. This paper documents the model experiment used to generate high-resolution climate and hydrological projections for the new climate assessment report published in October 2025. The model experiment follows the standard modelling chain for hydrological impact assessment, i.e., climate model selection – downscaling and bias adjustment – hydrological modelling. However, compared with the model experiment for the climate assessment report published in 2015, all modelling components have been improved in terms of data availability, data quality and methodology. Specifically, a large climate model ensemble was available and new criteria were developed to select tailored climate projections for Norway. Two bias-adjustment methods (one univariate and one multivariate) were applied to account for the uncertainty of method choice. The hydrological modelling was improved by implementing a physically-based Penman-Monteith method for evaporation and a glacier model accounting for glacier retreat under climate change scenarios. Besides model description, this paper elaborates the effects of different bias-adjustment methods and the contribution of climate models and bias-adjustment methods to the uncertainty of climate and hydrological projections under the RCP4.5 scenario as examples. The results show that the two bias-adjustment methods can contribute larger uncertainty to seasonal projections than climate models. The multivariate bias-adjustment method improves hydrological simulations, especially in the reference period, but cannot conserve climate change signals of the original climate projections. The dataset generated by the presented modelling chain provides the most updated, comprehensive and detailed hydrometeorological projections for mainland Norway, serving as a knowledge base for climate change adaptation to decision makers at various administrative levels in Norway.

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Shaochun Huang, Wai Kwok Wong, Andreas Dobler, Sigrid Jørgensen Bakke, Stein Beldring, Ingjerd Haddeland, Hans Olav Hygen, Tyge Løvset, Stephanie Mayer, Kjetil Melvold, Irene Brox Nilsen, Gusong Ruan, Silje Lund Sørland, and Anita Verpe Dyrrdal

Status: open (until 02 Jan 2026)

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Shaochun Huang, Wai Kwok Wong, Andreas Dobler, Sigrid Jørgensen Bakke, Stein Beldring, Ingjerd Haddeland, Hans Olav Hygen, Tyge Løvset, Stephanie Mayer, Kjetil Melvold, Irene Brox Nilsen, Gusong Ruan, Silje Lund Sørland, and Anita Verpe Dyrrdal

Data sets

Daily bias-adjusted climate (COR-BA-2025) and hydrological (distHBV-COR-BA-2025) projections for Norway W. K. Wong et al. https://doi.org/10.21343/0k90-6w67

seNorge_2018 daily mean temperature 1957-2019 Cristian Lussana https://zenodo.org/records/3923706

seNorge_2018 daily maximum temperature 1957-2019 Cristian Lussana https://zenodo.org/records/3923700

seNorge_2018 daily minimum temperature 1957-2019 Cristian Lussana https://zenodo.org/records/3923697

seNorge_2018 daily total precipitation amount 1957-2019 Cristian Lussana https://zenodo.org/records/3923703

HySN2018v2005ERA5 Ingjerd Haddeland https://zenodo.org/records/5947547

KliNoGrid_16.12 wind dataset MET Norway https://thredds.met.no/thredds/catalog/metusers/klinogrid/KliNoGrid_16.12/FFMRR-Nor/catalog.html

Model code and software

DistributedHbv Stein Beldring https://github.com/nve-sbe/DistributedHbv/tree/master/SourcePenmanMonteith

DistributedElementWaterModel Stein Beldring https://github.com/DistributedElementWaterModel/Version_3.03

3DBC: Version 2023 Andreas Dobler https://zenodo.org/records/15260335

qmap: Statistical Transformations for Post-Processing Climate Model Output Lukas Gudmundsson https://cran.r-project.org/web/packages/qmap/index.html

Shaochun Huang, Wai Kwok Wong, Andreas Dobler, Sigrid Jørgensen Bakke, Stein Beldring, Ingjerd Haddeland, Hans Olav Hygen, Tyge Løvset, Stephanie Mayer, Kjetil Melvold, Irene Brox Nilsen, Gusong Ruan, Silje Lund Sørland, and Anita Verpe Dyrrdal
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Latest update: 07 Nov 2025
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Short summary
This paper documents the model experiment used to generate the most updated, comprehensive and detailed climate and hydrological projections for the national climate assessment report for Norway published in October 2025. The new datasets (COR-BA-2025 and distHBV-COR-BA-2025) of these projections are openly accessible and will serve as a knowledge base for climate change adaptation to decision makers at various administrative levels in Norway.
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