How Does AR Recon Dropsonde Data Influence Extreme Precipitation Prediction in California? - A Case Study

The United States state of California is vulnerable to extreme precipitation events which have led to widespread associated hazards including flooding, landslides, infrastructure damage and economic losses. Atmospheric Rivers (ARs) are responsible for much of the extreme precipitation across the state of California, and despite their associated hazards, can provide well-needed precipitation during periods of drought. In order to properly prepare for AR storms - both by mitigating flood risk and improving water storage management - we must improve the forecasting of such events. Not all regions in the world are observed uniformly, and certain regions present gaps in observational data that, if filled, could improve forecast performance through data assimilation. In an attempt to fill these data gaps and improve AR forecasting, the AR Reconnaissance (AR Recon) project uses aircraft to release dropsondes and collect targeted observations over the North Pacific within areas associated with impactful landfalling ARs. Here we evaluate the influence of such dropsonde data on forecast accuracy during a particularly influential sequence of ARs from January 6-18, 2023. AR Recon efforts during this event consisted of 13 operations, 23 flights, and 625 dropsondes. Upper-and-lower-level dynamics, moisture transport, and 3-day precipitation forecasts from control (CTRL; includes dropsonde data assimilation) and denial (DENY; excludes dropsonde data) runs of the NCEP Global Forecast System (GFS) were compared against the Global Data Assimilation System (GDAS) analysis and Stage IV observations. Differences between AR prediction in CTRL and DENY runs demonstrate varied intensities and locations of synoptic features, indicating the importance of improving these forecasts. Dropsonde inclusion leads to an improvement in the GFS model initial conditions as well as forecasts of large-scale circulation patterns, moisture transport, and precipitation during this case study. Results emphasize the importance of data collection during influential precipitation events in California.