Precipitation Data

Accurate precipitation data acquisition and forecasting are crucial for numerous applications, from hydrological modeling and disaster mitigation to water resource management and agricultural planning. Current research emphasizes improving the accuracy and resolution of precipitation estimates by merging data from diverse sources (rain gauges, radar, satellites) using advanced machine learning techniques, including deep learning architectures like LSTMs and transformers, and ensemble methods. These advancements aim to enhance prediction accuracy, particularly for short-term forecasts and extreme precipitation events, ultimately leading to more effective decision-making and improved societal resilience to weather-related hazards.