Precipitation drives the atmospheric storage, movement, and quality of water. It is both the primary source of freshwater and a major driver of natural hazards. While a fundamental hydrologic flux, precipitation comprises the most challenging processes to estimate, model, and predict, because of its variability at all scales and its evolving interactions with the water, energy, and carbon cycles under a changing climate. It is therefore a major component of uncertainty in weather predictions and cliamte projections, with significant implications for our ability to quantify water cycle dynamics, inform decision making, and predict hydro-geomorphic hazards in response to extremes. A key to these efforts is model-observations synergy to advance precipitation science by jointly enhancing the accuracy of modeled processes and our insight into observations across space and time scales.
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