Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-3055-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-3055-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
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- Estimating the Global Influence of Cover Crops on Ecosystem Service Indicators in Croplands With the LPJ‐GUESS Model J. Ma et al. 10.1029/2022EF003142
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Latest update: 28 Nov 2023
Short summary
Compared to their predecessors, the new Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) methods for bias adjustment and statistical downscaling allow for a more robust adjustment of extreme values and spatial variability, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling.
Compared to their predecessors, the new Inter-Sectoral Impact Model Intercomparison Project...