Anyone who's been caught in an unexpected downpour knows that weather forecasting is an imperfect science. Now, researchers are taking aim at one of meteorologists' biggest blind spots: extremely short-term forecasts, or nowcasts, that predict what will happen in a given location over the next few minutes.
Anyone who's been caught in an unexpected downpour knows that weather forecasting is an imperfect science. Now, researchers at Stevens Institute of Technology are taking aim at one of meteorologists' biggest blind spots: extremely short-term forecasts, or nowcasts, that predict what will happen in a given location over the next few minutes.
The National Oceanic and Atmospheric Administration publishes round-the-clock rainfall predictions, but its shortest-term forecasts begin a few hours into the future. The lack of more immediate nowcasting hinders community responses to sudden catastrophes such as Hurricane Ida, for example, in which rapid flooding killed multiple people in New York City, explained Marouane Temimi, a hydrometeorologist at Stevens whose work appears in the Aug.
If probabilistic models are highly accurate in predicting both long- and short-term rainfall events, why have deterministic models? Validating deterministic models is useful because probabilistic models are far more computationally demanding. For instance, LINDA-P, a probabilistic model, proved to be the most accurate model tested, but it takes 15 minutes to generate a nowcast based on current conditions. Therefore, it can't be used for extremely short-term projections.
"The key takeaway is that we need to select nowcasting models based on their intended use-case," said Achraf Tounsi, the paper's lead author who recently completed his doctorate in Temimi's lab."If you want to know if it will rain in the next five minutes, you need a deterministic model. If you're running an airport or seaport and want data for the next 20 minutes, or hour, you'll be better served with a probabilistic model.
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