2017
DOI: 10.1002/qj.3126
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Recursive multivariate principal‐monotonicity inferential climate downscaling

Abstract: A recursive multivariate principal‐monotonicity inferential downscaling approach (ReMPMID) is proposed for climate downscaling under complexities of data uncertainties, nonlinear predictor–predictand correspondences, predictand dependencies, non‐normal distributions, spatial homogeneities, and temporal non‐stationarities. This approach is applied to the Athabasca River Basin (ARB) to verify methodological effectiveness. Many findings are revealed. For instance, ReMPMID may enable improvement of statistical dow… Show more

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Cited by 7 publications
(4 citation statements)
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“…There is an overestimation of annual maximum temperature and an underestimation of annual minimum temperature over the whole China except South China. The nonuniform between simulated temperature and observation is a common occurrence in many other GCMs with a coarse resolution (Cheng et al, ; Flato et al, ; Zhou et al, ). PRECIS significantly eliminates its occurrences and reproduces better spatial patterns for annual mean, maximum, and minimum temperatures.…”
Section: Simulations Of Historical Temperature and Humiditymentioning
confidence: 99%
“…There is an overestimation of annual maximum temperature and an underestimation of annual minimum temperature over the whole China except South China. The nonuniform between simulated temperature and observation is a common occurrence in many other GCMs with a coarse resolution (Cheng et al, ; Flato et al, ; Zhou et al, ). PRECIS significantly eliminates its occurrences and reproduces better spatial patterns for annual mean, maximum, and minimum temperatures.…”
Section: Simulations Of Historical Temperature and Humiditymentioning
confidence: 99%
“…The commonly used statistical downscaling methods consider climate variables independently. However, there are more and more methods focusing on the intervariable relationships, which are based on either MOS (C. Vrac and Friederichs 2015;Cannon 2016;Guo et al 2019) or PP strategy (Abatzoglou and Brown 2012;Cheng et al 2017). In this study, when the statistical downscaling was conducted, the relationships between different variables have not been considered and the interannual variation has not been well corrected as we mentioned in the evaluation section.…”
Section: Bth Daqinghe Mountain Western Plain Eastern Plainmentioning
confidence: 99%
“…GR model, Perrin et al, 2003) deal with the system as a whole and do not consider the spatial heterogeneity of the problem domain (Khakbaz et al, 2012). However, flooding may present clear spatial variations as influenced by localized weather and topographic conditions (Chen et al, 2017a;Cheng et al, 2017c;Cheng et al, 2017d). Distributed hydrological models (e.g.…”
Section: Introductionmentioning
confidence: 99%