A5035006250- Precipitation Measurement and Analysis
- Meteorological Phenomena and Simulations
- Climate variability and models
- Geophysics and Gravity Measurements
- Neural Networks and Applications
- Climate change impacts on agriculture
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Metaheuristic Optimization Algorithms Research
- Flood Risk Assessment and Management
- Advanced Algorithms and Applications
University of California, Irvine
2017-2019
Samueli Institute
2019
Center for Hydrometeorology and Remote Sensing
2017-2018
Irvine University
2017
Abstract Accurate and timely precipitation estimates are critical for monitoring forecasting natural disasters such as floods. Despite having high-resolution satellite information, estimation from remotely sensed data still suffers methodological limitations. State-of-the-art deep learning algorithms, renowned their skill in accurate patterns within large complex datasets, appear well suited to the task of estimation, given ample amount data. In this study, effectiveness applying...
Providing reliable long-term global precipitation records at high spatial and temporal resolutions is crucial for climatological studies. Satellite-based estimations are a promising alternative to rain gauges providing homogeneous information. Most satellite-based products suffer from short-term data records, which make them unsuitable various hydrological applications. However, Precipitation Estimation Remotely Sensed Information using Artificial Neural Networks-Climate Data Record...
ABSTRACT The biases in the Global Circulation Models ( GCMs ) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from assumption that model is stationary. This paper provides a non‐stationary model, termed residual‐based bagging tree RBT to reduce simulation and quantify contributions of single models. Specifically, proposed estimates residuals between individual models observations, takes differences observations ensemble mean into...