Understanding and Quantifying the Predictability of Marine Ecosystem Drivers in the California Current System

The California Current upwelling system (CCS) supports one of the most productive marine ecosystems in the world and is a primary source of ecosystem services for the U.S. including fishing, shipping, and recreation. Despite the empirical evidence of ENSO influence upon the California Current marine ecosystems, the detailed influence of different ENSO events is unclear, and the degree of predictability of the various ecosystem drivers for specific tropical Pacific conditions has never been quantified. The goal of this proposal is to: 1) Use high-resolution ocean reanalysis of the CCS to link the physical drivers of the CCS ecosystem (temperature, upwelling velocity, alongshore & cross-shore transport) to local climate forcing functions (e.g. alongshore winds, wind stress curl, heat fluxes, precipitation and river runoff) at seasonal timescale; 2) Use long reanalysis products (e.g. SODAsi.3, 20CRv2c, CERA-20C) in combination with multiple linear regression and Singular Value Decomposition to objectively link the climate forcing functions variations in the CCS region with conditions (e.g. sea surface temperature, thermocline depth, sea surface height, tropical wind stresses) in the tropical Pacific that can optimally force them at seasonal timescales; and 3) Use Linear Inverse Modeling (LIM) and the North American Multi Model Ensemble (NMME) to determine the predictability and uncertainty of the forcing functions along the CCS region, compare the LIM and NMME forecast skills, and explore possible sources of error in the NMME models.

The proposed research will directly address the first objective of the call, “Explore how selected modes of climate or ocean variability relate to seasonal variations in fields such as sea level height and ocean temperature that are of primary relevance to predictability for the topical areas of the call, and evaluate the seasonal prediction skill of these modes”, in that it explores how the leading mode of tropical Pacific climate variability (e.g. ENSO) will affect a set of variables, including sea level height and ocean temperature, that are fundamental to ecosystem dynamics in the California Current System. The proposed study also sets the foundation for the development of a probabilistic prediction system, as described in objective 3 of the call, for use in predicting components of the ecosystem that are relevant to the marine resources managed by NOAA NMFS. This study will also utilize and evaluate the latest versions of the century-long SODAsi and 20CR reanalysis products, and also provide an evaluation of a NOAA-sponsored operational forecast system, the North American Multi-Model Ensemble (NMME) in the area of ecosystem predictions.

Climate Risk Area: Marine Ecosystems