Title: Historical Data Reconstruction for the California Coastal Currents using 3D Empirical Orthogonal Functions and Multivariate Regression

Presenter(s): Danielle Lafarga,

Date: 24 October 2024 2:35 pm – 3:05 pm ET

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About Speaker: Danielle Lafarga,

Abstract: Many studies analyze ocean temperature variance, computing empirical orthogonal functions (EOFs) one layer at a time(2D). However, surface phenomena like El Nio extend into deeper layers, exemplifying how crucial it is to examine their three-dimensional structure to fully understand their impact. This research aims to compute 3D EOFs for different areas of the Pacific Ocean to answer how much and what variability can be explored across ocean layers using ahigh-resolution, eddy-resolving model known as the Global Ocean Physics Reanalysis (GLORYS). The model’s fine resolution allows for detailed analysis of smaller-scale dynamics, such as those along the coasts of California, Oaxaca, and Costa Rica. Nevertheless, the volume of data presents a memory challenge for 3D calculations. To address this, we propose an algorithm that enables 3D EOF computation on computers with limited memory (16GB RAM), making high-resolution analysis feasible.Computing 3D EOFs is crucial for understanding our oceans and how ocean dynamics can extend through multiple layers. This research aligns with NOAA’s mission to understand and predict changes in climate, weather, oceans, and coasts. By providing a more comprehensive view of ocean variability, the results also contribute valuable insights into the habitats of fish species protected by NOAA Fisheries, aiding in the preservation and management of marine ecosystems.The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentor, Dr. Michael Jacox of NOAA SWFSC Environmental Research Division, and NOAA collaborator Dr. Michael Alexander of NOAA Atmosphere Ocean Processes and Predictability (AOPP) Division. The NERTO aligns NOAA CSCCESSRST-II’s goal of to understand and predict changes in climate and weather. The NERTO project deepened the intern’s understanding of remote sensing technology, big data computing, and participation in NOAA mission-aligned activities through extensive collaborations with NOAA employees.