Precipitation science: State-of-the-Art in measurement, estimation, and modeling

Precipitation is critical for human society, influencing water resource management, agriculture, and disaster preparedness. However, accurately determining the timing and location of precipitation remains a significant challenge in weather forecasting. Even measuring precipitation is inherently complex due to its high spatial and temporal variability. This paper synthesizes the current state of precipitation science, providing an updated overview of current precipitation products and highlighting recent advancements in measurement techniques (e.g., rain gauges, disdrometers), estimation methods (e.g., radar, satellite-based approaches), and weather and climate modeling. The growing role of machine learning in the field over the past 20 years is also discussed. The review reveals significant uncertainties in precipitation science, leading to three key implications. First, precipitation remains a critical metric for the validation of meteorological and climate models. Second, uncertainties in precipitation measurement have a substantial impact on modern human societies, resulting in loss of life and property. Third, the limitations in observation and modeling underscore the urgent need for continued innovation in developing novel methods to better measure this vital atmospheric parameter. The societal costs of these shortcomings and the need to address scientific challenges are exemplified by two recent episodes: the 2024 Valencia floods in Spain and the July 2025 Texas floods in the United States.