Statistical Precipitation Downscaling over the Northwestern United States Using Numerically Simulated Precipitation as a Predictor
By M. Widmann, Chris Bretherton, E. Salathe. 2003
319 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/cd480e97224b9b3df47cdfacdcac83d4d98baf8e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Mathieu Vrac
- Douglas Maraun
- M. Widmann
- Hayley J. Fowler
- Renate A. I. Wilcke
- A. Gobiet
- T. Mendlik
- G. Wong
In Global and Planetary Change
- Mathieu Vrac
- Douglas Maraun
- M. Widmann
- Hayley J. Fowler
- Renate A. I. Wilcke
- A. Gobiet
- T. Mendlik
- G. Wong
Citations in the corpus
- Multi-variable error correction of regional climate models (2013, background): “S27), one should re-consider or at least be aware of it when applying QM to this RCM (Widmann et al. 2003; Eden et al. 2012).”
- Climate model bias correction and the role of timescales (2010, background): “More advanced bias correction methodologies correct for more than one explicitly chosen statistical aspect (Leander and Buishand, 2007and applied byHurkmans et al., 2010; Widmann et al., 2003; Schmidli et al., 2006).”
- A method for statistical downscaling of seasonal ensemble predictions (2005, result): “Similar results using related statistical correction methods applied to a number of different atmospheric model simulations have been reported for a number of later studies (Gershunov et al., 2000; Kharin and Zwiers, 2001; Tippett et al., 2003; Widmann et al., 2003; Kang et al., 2004).”
- Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling (2007, methodology): “Similarly, Widmann et al. (2003) found that using GCM precipitation as a predictor in downscaling improved results considerably, without the use of complex statistical methods.”
- Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes (2014, background): “Therefore, one is able to formulate regressionmodels between simulated predictors and observed predictands (e.g., Widmann et al. 2003; Themeßl et al. 2011).”
- Statistical downscaling model based on canonical correlation analysis for winter extreme precipitation events in the Emilia‐Romagna region (2008, methodology): “, 2004) or singular-value decompositions (e.g. Huth, 2002; Widmann et al., 2003).”