Verification and Calibration of Neighborhood and Object-Based Probabilistic Precipitation Forecasts from a Multimodel Convection-Allowing Ensemble
By Aaron Johnson, Xuguang Wang. 2012
66 citations recorded by the source corpus.
Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/0f608e9ffdf54516261f575565469db6955afc6b
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
- Yongming Wang
- Michael Scheuerer
- Xuguang Wang
- R. Bullock
- M. Clark
- G. Holland
- Changhai Liu
- Kyoko Ikeda
In Environmental Engineering
In Global and Planetary Change
- Yongming Wang
- Michael Scheuerer
- Xuguang Wang
- R. Bullock
- M. Clark
- Changhai Liu
- Kyoko Ikeda
- Andreas F. Prein
Citations in the corpus
- Simulating North American mesoscale convective systems with a convection-permitting climate model (2017, background): “Similar overestimations are found in convectionpermitting weather forecasting models in all US regions (Johnson and Wang 2012; Clark et al.”
- Probabilistic quantitative precipitation forecasting using Ensemble Model Output Statistics (2013, background): “This is in agreement with Johnson and Wang (2012), who study neighbourhood-based probabilistic forecasts using a 48 km radius, and Mittermaier et al.”
- Direct Assimilation of Radar Reflectivity without Tangent Linear and Adjoint of the Nonlinear Observation Operator in the GSI-Based EnVar System: Methodology and Experiment with the 8 May 2003 Oklahoma City Tornadic Supercell (2017, methodology): “The neighborhood method is used to account for the small displacement errors across the ensemble members (Theis et al. 2005; Mittermaier 2007; Ebert 2009; Schwartz et al. 2010; Bouallegue et al. 2011; Johnson and Wang 2012; Yussouf et al. 2013).”