Using a network of a newly introduced type of rain gauge that can measure rainfall with drop-by-drop precision, KAUST researchers have developed a high-frequency rainfall model to improve understanding of rainfall/runoff dynamics, such as flash flooding and hydrodynamics in small watersheds.
Rainfall modeling is one of the core aspects of weather forecasting and is often used to predict other weather parameters, such as wind and solar irradiance. Yet the power and insight of such models are limited by the data used to construct them. When it comes to precipitation, this means that modelers have to rely on sparse recordings of rainfall at 6-15-minute intervals at best, but more often hourly intervals. This leads to a "smoothing" of rainfall over time and a loss of information about how much rain falls during each rainfall event, which is a problem, according to Ph.D. student Yuxiao Li.
“This assumption is not appropriate for modeling precipitation at high frequency because large quantities of rainfall in the past can result in an unrealistically high probability of rainfall occurrence in such models,” explains Li. “In this study, we used the high-frequency rainfall data collected by new instruments called Pluvimate rain gauges to better reproduce the statistical properties of precipitation occurrence, intensity, and dry-spell duration.”
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