Tropical Sea Surface Temperature (SST) Forecasts
El Niño is a global phenomenon involving complex interactions within the ocean-atmosphere system. Although a single index cannot describe the dynamics of El Niño, a single field, the sea surface temperatures (SSTs), provides a remarkably efficient summary of the timescales inherent in El Niño dynamics. PSD researchers use a dynamically-based statistical technique, Linear Inverse Modeling (LIM) to identify the evolutionary behavior of dynamical SST modes in the tropical oceans. The results of this technique allow experimental forecasts of tropical SSTs with skill competitive with that of numerical climate forecast models.
LIM forecasts are part of a consolidated effort of the National Oceanic and Atmospheric Administration (NOAA), NOAA's National Weather Service, and their funded institutions. For more information, see NOAA's Climate Diagnostics Bulletin.
SST anomalies are calculated relative to 1981-2010 climatology, smoothed by a three months' running mean, and projected onto a basis of 20 Empirical Orthogonal Functions (EOFs). This last step consolidates most of the predictable information contained in a map of tropical SSTs into a practical number of data structures. Using this reduced space, the lagged and contemporaneous covariance structure of SSTs is used to generate the best linear dynamical model of the multivariate SST field. Forecasts using this model are then made, and forecast error is analyzed to verify the validity of the linear model. More information about the method is available from Penland and Sardeshmukh (1995).
Activities and Outcomes
Seasonal forecasts of SST are updated before the 10th of each month.