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CLIMB: Framework for CLIMate data bias-adjustment and downscaling

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Śledziowski,  Jakub
External Organizations;

Terefenko,  Paweł
External Organizations;

Giza,  Andrzej
External Organizations;

Tanwari,  Kamran
External Organizations;

/persons/resource/Dominik.Paprotny

Paprotny,  Dominik       
Potsdam Institute for Climate Impact Research;

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https://zenodo.org/records/17711536
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1-s2.0-S2352711025004455-main.pdf
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Śledziowski, J., Terefenko, P., Giza, A., Tanwari, K., Paprotny, D. (2026): CLIMB: Framework for CLIMate data bias-adjustment and downscaling. - SoftwareX, 33, 102479.
https://doi.org/10.1016/j.softx.2025.102479


???ViewItemOverview_lblCiteAs???: https://publications.pik-potsdam.de/pubman/item/item_33500
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Modern climate impact and attribution science requires timely, high-resolution meteorological and hydrological data. The CLIMB workflow is an open-source framework integrating state-of-the-art datasets and methods for operational generation of high-resolution climate datasets tailored for attribution studies of floods, droughts, heatwaves, and other extremes. We show that global climate reanalysis can be efficiently bias-adjusted and downscaled, and further converted into readily-usable climate indicators. The choice of variables and formatting of the data enables direct application in hydrological models. The workflow implements a fully scripted pipeline that can be automated via cron scheduling, providing daily meteorological outputs. We show an application of the workflow for operational monitoring weather extremes in Poland.