A precipitation downscaling method is presented using precipitation from a general circulation model (GCM) as predictor. The method extends a previous method from monthly to daily temporal resolution. The simplest form of the method corrects for biases in wet-day frequency and intensity. A more soph
Coupling statistical and dynamical methods for spatial downscaling of precipitation
✍ Scribed by Chen, Jie; Brissette, François P.; Leconte, Robert
- Book ID
- 118797700
- Publisher
- Springer
- Year
- 2012
- Tongue
- English
- Weight
- 248 KB
- Volume
- 114
- Category
- Article
- ISSN
- 0165-0009
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
## Abstract Six statistical and two dynamical downscaling models were compared with regard to their ability to downscale seven seasonal indices of heavy precipitation for two station networks in northwest and southeast England. The skill among the eight downscaling models was high for those indices
## Abstract We present results from a 15‐year 10‐member warm season (March–September) hindcast ensemble of maximum and minimum surface air temperatures and precipitation in southeast USA. The hindcasts are derived from the Florida State University/Center for Ocean‐Atmospheric Prediction Studies Glo
## Abstract Place‐based data is required in wildfire analyses, particularly in regions of diverse terrain that foster not only strong gradients in meteorological variables, but also complex fire behaviour. However, a majority of downscaling methods are inappropriate for wildfire application due to