Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)

By S. Lange. Geoscientific Model Development, 2019

553 citations recorded by the source corpus.

Abstract. In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In comparison to their predecessors, the new methods allow for a more robust bias adjustment of extreme values, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling. The new statistical downscaling method is stochastic and better at adjusting spatial variability than the old interpolation method. Improvements in bias adjustment and trend preservation are demonstrated in a cross-validation framework.

Subfields: Economics and Econometrics, Global and Planetary Change, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/37c2eda05ba5960a48ef946e5ed94bafd51861aa