Satellite Rainfall Applications for Surface Hydrology /
| Autor Corporativo: | |
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| Otros Autores: | , |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Dordrecht :
Springer Netherlands : Imprint: Springer,
2010.
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| Edición: | 1st ed. 2010. |
| Materias: |
Tabla de Contenidos:
- Evolution of High Resolution Precipitation Products
- The TRMM Multi-Satellite Precipitation Analysis (TMPA)
- CMORPH: A “Morphing” Approach for High Resolution Precipitation Product Generation
- The Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) for High-Resolution, Low-Latency Satellite-Based Rainfall Estimates
- Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm
- The Combined Passive Microwave-Infrared (PMIR) Algorithm
- The NRL-Blend High Resolution Precipitation Product and its Application to Land Surface Hydrology
- Kalman Filtering Applications for Global Satellite Mapping of Precipitation (GSMaP)
- Evaluation of High Resolution Precipitation Products
- Neighborhood Verification of High Resolution Precipitation Products
- A Practical Guide to a Space-Time Stochastic Error Model for Simulation of High Resolution Satellite Rainfall Data
- Regional Evaluation Through Independent Precipitation Measurements: USA
- Comparison of CMORPH and TRMM-3B42 over Mountainous Regions of Africa and South America
- Evaluation Through Independent Measurements: Complex Terrain and Humid Tropical Region in Ethiopia
- Error Propagation of Satellite-Rainfall in Flood Prediction Applications over Complex Terrain: A Case Study in Northeastern Italy
- Probabilistic Assessment of the Satellite Rainfall Retrieval Error Translation to Hydrologic Response
- Real Time Operations for Decision Support Systems
- Applications of TRMM-Based Multi-Satellite Precipitation Estimation for Global Runoff Prediction: Prototyping a Global Flood Modeling System
- Real-Time Hydrology Operations at USDA for Monitoring Global Soil Moisture and Auditing National Crop Yield Estimates
- Real-Time Decision Support Systems: The Famine Early Warning System Network.