Why seasonal prediction of California winter precipitation is challenging

This image, captured by the Suomi NPP satellite's VIIRS instrument, compares snow cover in the Sierra Nevada Mountains in 2017 and 2018. Credit: NOAA

Due to the recurrent and severe drought conditions, there is an urgent demand for reliable seasonal prediction of precipitation in California. Being the nation’s most populous state and one that plays a crucial role in the U.S. economy, including agriculture and food supplies, accurate prediction of CA precipitation several months ahead becomes exceptionally important for disaster preparation and mitigation as well as for drought and water restriction policy-making purposes. However, predictive skill for CA winter precipitation remains limited, and relies heavily on tropical sea surface temperature (SST) anomalies, such as the El Niño–Southern Oscillation (ENSO).

In a new Bulletin of the American Meteorological Society, authors Xianan Jiang, Duane Waliser, Peter Gibson, Gang Chen, and Weina Guan analyzed long-term hindcasts from multiple atmosphere–ocean coupled models to examine the underlying processes that limit seasonal prediction skill for CA winter precipitation.

Read more at the link below.