Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?
Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC)...
Main Authors: | Manzanas, R, Lucero, A, Weisheimer, A, Gutiérrez, J |
---|---|
格式: | Journal article |
出版: |
Springer Verlag
2017
|
相似书籍
-
Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts
由: L. Crochemore, et al.
出版: (2016-09-01) -
Assessment of Model Drifts in Seasonal Forecasting: Sensitivity to Ensemble Size and Implications for Bias Correction
由: Rodrigo Manzanas
出版: (2020-03-01) -
Statistical Bias Correction of Precipitation Forecasts Based on Quantile Mapping on the Sub-Seasonal to Seasonal Scale
由: Xiaomeng Li, et al.
出版: (2023-03-01) -
Customized deep learning for precipitation bias correction and downscaling
由: F. Wang, et al.
出版: (2023-01-01) -
Assessing Three Perfect Prognosis Methods for Statistical Downscaling of Climate Change Precipitation Scenarios
由: M. N. Legasa, et al.
出版: (2023-05-01)