How does data assimilation affect subseasonal Tropical Pacific forecasts?

Data assimilation can improve predictions of some aspects of the Tropical Pacific Ocean but not others. Credit: NOAA

Ocean processes in the tropical Pacific have an important role in modulating global climate. Research shows that data assimilation methods and robust observational data in this region make a big difference in producing accurate forecasts, but the impact of these methods hasn’t been well-studied for timescales shorter than seasonal (subseasonal). A new study, supported by the Climate Program Office’s Climate Variability & Predictability (CVP) Program, outlines the specific impacts of using data assimilation on subseasonal predictions in the tropical Pacific. CVP-supported scientists Aneesh Subramanian, Matthew Mazloff, Kris Karnauskas, and Charlotte DeMott worked with an international team of researchers for this project, which aims to improve our understanding of air-sea interaction processes and biases using observation sensitivity experiments and global forecast models. This work was funded by CVP as a pre-field modeling study to support the ongoing Tropical Pacific Observing System (TPOS), a multinational observing project designed to understand and predict tropical Pacific variability, inform policymakers, and benefit society.