A Comparison between Raw Ensemble Output, (Modified) Bayesian Model Averaging, and Extended Logistic Regression Using ECMWF Ensemble Precipitation Reforecasts

By Maurice Schmeits, Kees Kok. 2010

86 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5f0b7b1119ae74e4ecc16c6c25bab205e994344f

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

1. Achim Zeileis
2. Jakob W. Messner
3. Georg J. Mayr
4. D. Wilks
5. Tilmann Gneiting
6. Thordis Linda Thorarinsdottir
7. Michael Scheuerer
8. Kees Kok

In Global and Planetary Change

1. Achim Zeileis
2. Jakob W. Messner
3. Georg J. Mayr
4. D. Wilks
5. Tilmann Gneiting
6. Thordis Linda Thorarinsdottir
7. Khaled H. Hamed
8. Michael Scheuerer

Citations in the corpus

• Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau (2017, methodology): “The BMA scheme was recently extended to ensemble precipitation research (Fu et al., 2014; Schmeits & Kok, 2010; Sloughter et al., 2007; Wang et al., 2012; Zhu et al., 2015).”
• Heteroscedastic Extended Logistic Regression for Postprocessing of Ensemble Guidance (2014, methodology): “The extended logistic regression method has been used in several studies for probabilistic precipitation forecasts (Schmeits and Kok 2010; Ruiz and Saulo 2012; Roulin and Vannitsem 2012; Hamill 2012; Ben Bouall egue 2013; Scheuerer 2013) and was shown to perform very well compared to standard logist”
• Extending Extended Logistic Regression: Extended versus Separate versus Ordered versus Censored (2014, methodology): “Extended logistic regression has been used frequently (Schmeits and Kok 2010; Ruiz and Saulo 2012; Roulin andVannitsem 2012; Hamill 2012; Ben Bouallègue 2013; Scheuerer 2014; Messner et al. 2014) and has been further extended to additionally account for conditional heteroscedasticy (Messner et al.…”
• Statistical Postprocessing of Ensemble Precipitation Forecasts by Fitting Censored, Shifted Gamma Distributions* (2015, unknown): “…of the parametric postprocessing approaches mentioned in section 1 (ExLR, BMA, EMOS) suggest that their predictive performance is quite similar (Schmeits and Kok 2010; Scheuerer 2014), so how much extra skill can be gained by adding additional predictors or permitting certain forms of…”