368722 Assessing the Predictability of WRF Precipitaiton Forecasts for the Bay Area

Tuesday, 14 January 2020
Hall B1 (Boston Convention and Exhibition Center)
Paul Zechiel, San Jose State Univ., San Jose, CA; and S. Chiao

The evaluation of the precipitation forecasts for the 2018-2019 rain season over the Santa Clara valley is performed. We conduct a real-time high-resolution Weather Research and Forecasting (WRF) model 4-times per day for the San Francisco Bay Area. The coastal mountainous topography in the San Francisco Bay Area plays a significant role in modulating precipitation distribution/intensity during winter storm events. Rainfall amounts in the Santa Clara Valley are largely controlled by the orographic lifting and/or blocking as well as rain shadow effects of the airflow over the surrounding mountains as well the direction of the incoming storm system. It is essential to create localized hourly rainfall forecasts to help support the hydrological streamflow forecasting efforts and decision-making process during periods of heavy rainfall and atmospheric river (AR) events. Observations are used from 47 water district rain gauges to evaluate the effectiveness of our WRF model. Results from the model are compared to observations including rain gauges, x-band radar and disdrometer data using the mean average error (MAE) and difference calculations (Forecast – Observed) to show biases and accuracy for the 72-hr rainfall forecast and rainfall probabilities.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner