SUB-SEASONAL FORECASTS OF ATMOSPHERIC RIVERS IMPACTING CALIFORNIA AND SOUTHERN EUROPE UTILIZING STREAMFUNCTION ANOMALIES

• Main Author: Rueter, Niklas H.
• Other Authors: Nuss, Wendell A., Meteorology (MR), Boothe, Mark A.
• Format: Thesis
• Language: unknown
• Published: Monterey, CA; Naval Postgraduate School 2022
• Subjects: atmospheric rivers; ARs; streamfunction; California; U.S. West Coast; geopotential height; anomalies; sub-seasonal; forecasts; Southern Europe; Lisbon; San Francisco; Iberian Peninsula; vertical integral of divergence of geopotential flux; North Atlantic
• Online Access: https://hdl.handle.net/10945/71540

Atmospheric rivers (ARs) are narrow plumes of moisture that transport a large flux of water vapor into the mid-latitudes. This source of precipitation is vital for the U.S. West Coast, especially California, where seasonal precipitation is highly dependent on these ARs and accounts for up to half its annual precipitation. Due to the reliance on ARs for precipitation, effective water management has become crucial in the U.S. West as wildfires worsen and populations grow, increasing the demand on the entire region’s reservoirs. It is imperative that AR events are forecasted and communicated as early as possible. That is the goal of this thesis, to extend the prediction of ARs into the sub-seasonal timescale. Analysis of streamfunction anomalies (SFA) and the vertical integral of the divergence of geopotential flux (DGF) were done via an anomaly box off the west coast of British Columbia, with the process replicated for a climatologically similar region in the North Atlantic, showing good success to at least 40 days prior to an AR event for both San Francisco and Lisbon, Portugal. This lead time of conditions supporting ARs impacting these two regions is invaluable for forecasters and affiliated stakeholders. While this method will not forecast specific AR events, it can statistically indicate whether more ARs will be likely at the sub-seasonal time scale. The past 28 years of data (1994–2021) were analyzed for trends in SFA and DGF across both anomaly boxes. Approved for public release. Distribution is unlimited. Outstanding Thesis Lieutenant Commander, United States Navy