Abstract
One of the most important applications of satellite rainfall estimates is the hydrological modeling in basins where the conventional and real time rain gauges networks are inadequate in term of the spatial and temporal resolution. This study discuss the performance of the multidimensional stochastic error model (SREM2D), which simulates an ensemble of daily precipitation fields with the same statistical patterns (spread) as the differences of satellite precipitation fields and rain gauges of a longer data series. Most models treat errors only in one dimension, without recognizing that rainfall is a time and space intermittent process. The SREMD2 model characterize the spatial and temporal structure, and the stail variability of errors, of rainfall estimates. This study assess SREM2D simulations results for several rainfall estimates algorithms in the Tocantins-Araguaia river basin.
| Translated title of the contribution | Evaluation of a multidimensional stochastic error model applied to satellite rainfall estimates |
|---|---|
| Original language | Portuguese |
| Pages (from-to) | 52-63 |
| Number of pages | 12 |
| Journal | Revista Brasileira de Meteorologia |
| Volume | 31 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2016 |
Keywords
- Hydrological modeling
- Metrics calibration
- Satellite rainfall estimate
- Stochastic model