Scale Dependence of the Predictability of Precipitation from Continental Radar Images. Part II: Probability Forecasts
By Urs Germann, I. Zawadzki. 2004
207 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/e06aecc6f88fc1a355a414439c3b72f5cafeb7c2
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
- Elizabeth E. Ebert
- Barbara Casati
- B. Brown
- Neill Bowler
- C. Pierce
- Gyuwon Lee
- Simon Mason
- David B. Stephenson
In Global and Planetary Change
- Barbara Casati
- B. Brown
- Elizabeth E. Ebert
- Neill Bowler
- C. Pierce
- Gyuwon Lee
- David B. Stephenson
- Montserrat Fuentes
Citations in the corpus
- Spatial–temporal mesoscale modeling of rainfall intensity using gage and radar data (2008, background): “The reflectivity–rainfall conversion function is modeled in the natural logarithm scale, because the error component is thought to increase with the precipitation values, and in the original scale too much weight is given to high rainfall rates [Lee and Zawadzki (2005), Germann and Zawadzki (2002)].”
- Intercomparison of Spatial Forecast Verification Methods (2009, unknown): “Scores that evaluate the forecast intensities were proposed by Germann and Zawadzki (2004) and Rezacova et al. (2007).”
- STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP (2006, methodology): “The MAPLE system (Germann and Zawadzki 2004) introduced a method called conditional to Lagragian mean (CLM).”
- Forecast verification: current status and future directions (2008, background): “Germann and Zawadzki (2002, 2004), and Turner et al. (2004) use a similar error-decomposition approach for the MAPLE nowcasting system and study the scale-dependence of precipitation predictability by using wavelets.”
- Fuzzy verification of high‐resolution gridded forecasts: a review and proposed framework (2008, background): “…developed in recent years including those of Brooks et al. (1998); Zepeda-Arce et al. (2000); Atger (2001); Casati et al. (2004); Damrath (2004); Germann and Zawadzki (2004); Weygandt et al. (2004); Theis et al. (2005); Roberts and Lean (2008); Rezacova et al. (2007) and Segawa and Honda (2007).”
- McGill algorithm for precipitation nowcasting by lagrangian extrapolation (MAPLE) applied to the South Korean radar network. Part I: Sensitivity studies of the Variational Echo Tracking (VET) technique (2009, unknown): “A basic description of MAPLE is provided by Germann and Zawadzki (2002), the extension to probabilistic forecasts has then been formulated by Germann and Zawadzki (2004), the implementation of a filtered forecast that removes the perishable scales has been carried out by Seed (2003) and by Turner…”