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

被引：364

作者：

Lange, Stefan ^{[1
]}

机构：

[1] Potsdam Inst Climate Impact Res PIK, Leibniz Assoc, POB 60 12 03, D-14412 Potsdam, Germany

来源：

GEOSCIENTIFIC MODEL DEVELOPMENT | 2019年 / 12卷 / 07期

基金：

欧盟地平线“2020”;

关键词：

D O I：

10.5194/gmd-12-3055-2019

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

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.

引用

页码：3055 / 3070

页数：16

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