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Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China

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Outgoing claims: the papers this work cites, builds on, or argues with.

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The Nature of Statistical Learning Theory
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Stochastic modeling of daily precipitation in China
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Downscaling GCMs using the Smooth Support Vector Machine method to predict daily precipitation in the Hanjiang Basin
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Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing
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Maximum likelihood Bayesian averaging of uncertain model predictions
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A statistical downscaling scheme to improve global precipitation forecasting
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Seasonality properties of four statistical-downscaling methods in central Sweden
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Multi-model ensemble hydrologic prediction using Bayesian model averaging
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Towards the characterization of streamflow simulation uncertainty through multimodel ensembles
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Uncertainty analysis of statistical downscaling methods
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Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze River) catchment
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Downscaling of precipitation for climate change scenarios: A support vector machine approach
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A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River basin, Colorado
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Benchmark priors for Bayesian model averaging
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sdsm — a decision support tool for the assessment of regional climate change impacts
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Climate Change and Hydrologic Models: A Review of Existing Gaps and Recent Research Developments
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Least Squares Support Vector Machine Classifiers
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An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
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Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
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Bayesian model averaging: development of an improved multi-class, gene selection and classification tool for microarray data
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The Use of Bayesian Model Averaging to Better Represent Uncertainty in Ecological Models
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Assessment and Propagation of Model Uncertainty
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The Use of General Circulation Models to Predict Regional Climatic Change
inferredcites →https://doi.org/10.1175/1520-0442(1999)012<2474:tamaas>2.0.co;2openalex-snapshot
The Analog Method as a Simple Statistical Downscaling Technique: Comparison with More Complicated Methods
inferredcites →https://doi.org/10.1175/jhm519.1openalex-snapshot
Multimodel Combination Techniques for Analysis of Hydrological Simulations: Application to Distributed Model Intercomparison Project Results
inferredcites →https://doi.org/10.1175/mwr2906.1openalex-snapshot
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Downscaling general circulation model output: a review of methods and limitations
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Discussion
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Bayesian Model Averaging With Applications to Benchmark Dose Estimation for Arsenic in Drinking Water
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Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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