Here for Full Article Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in downscaling

[1] Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However, studies have shown that climate changemay manifest in terms of changes in frequencies of occurrence of the leadingmodes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster‐Shafer (D‐S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (“cluster linking”) and scale