An asynchronous regional regression model for statistical downscaling of daily climate variables

By A. Stoner, Katharine Hayhoe, Xiaohui Yang, D. Wuebbles. 2013

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DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution (2017, methodology): “uding kernel regression [42], random forests[31], and anchored neighborhood regression [35], have been proposed for SR to improve accuracy and speed, all related to methods presented in SD literature [5, 13, 32]. Sparse-coding techniques, a form of dictionary learning, have recently shown state-of-t”
Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? (2015, unknown): “It is possible that more parsimonious methods, such as asynchronous regression (Stoner et al. 2013), may be more robust.”