UH Researchers Discover Approach To Improve Rain Forecast Accuracy

July 31, 2019, 2:09 PM HST (Updated July 31, 2019, 2:09 PM)
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Kohala mountains. File image by James Grenz.

The presence of mountains is a key factor in the distribution of precipitation over land, and the need to accurately model the influence of mountains on the atmosphere is imperative for providing reliable weather forecasts, a press release from the University of Hawaiʻi at Mānoa said.

Now atmospheric science researchers at UH have discovered a new approach that more efficiently represents the slopes of terrain in numerical weather prediction models, the release continued.

When the new approach was tested in a regional weather forecast model over Oʻahu, and compared to the current method of handling terrain, the estimated precipitation amount and forecast accuracy was improved.

“The windward side has extremely steep mountains (or pali), which are poorly resolved by the National Weather Service operational forecast model because the model grid spacing is not fine enough,” said study co-author Steven Businger, a professor at the School of Ocean and Earth Science and Technology (SOEST). “When the resolution or grid spacing in a weather model is increased by a factor of two, the computational expense increases by a factor of eight, making it too expensive to capture the details of the windward cliffs. By including the enhanced terrain slope in the forecast model, estimates of uplift at low levels all along the windward cliffs and cirques are significantly improved.”

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Businger and lead author Thomas Robinson, who was a SOEST doctoral student at the time of this work, tested the new method. Results showed a decrease in the number of false alarms of threatening rain events, the release stated. After running the model for an entire month, the new method was shown to be useful for predicting the amount and location of rain during precipitation events.

The new method can be incorporated in future versions of regional and global weather and climate models. This provides gains in the virtual increase of terrain resolution in a computationally efficient way, said Busiger. In the future, this method can be applied to other models over a larger area to similarly improve precipitation forecasts.

Future work can also explore how the method performs with different conditions and how predictions of phenomenon other than precipitation may be impacted by the terrain enhancement, the release stated.

The study was published online in the American Meteorological Society journal.

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