Dynamical Filtering of Tropical Variability

David Marsico

CIRES CU Boulder - NOAA Physical Sciences Laboratory

Tuesday, Apr 23, 2024, 2:00 pm MT
DSRC Room 2A305

JOIN THE WEBINAR:

Abstract

In the sub-seasonal to seasonal prediction community, there is a need to decompose tropical variability into predictable and unpredictable components. In particular, there is a need to filter the predictable components into the MJO and other forms of variability, such as those associated with ENSO.

Most methods for doing this decomposition, and for identifying the MJO, have relied on indices obtained by projecting data onto a small number of empirical orthogonal functions.

In this talk, we demonstrate how a linear inverse model (LIM) can be used both as a filter of tropical variability relative to existing MJO indices, and as a way of defining its own MJO index. In particular, it is shown how a LIM-based dynamical index can more effectively filter out contributions to the MJO from other phenomena, such as those arising from ENSO.

Bio: David (Dave) did his undergraduate work at Haverford College in Pennsylvania, where he majored in mathematics. He then got a PhD in mathematics from UW-Madison (go Badgers) under the supervision of Sam Stechmann, where he focused on applied math and fluid dynamics.

After that, he spent three years as a postdoc at UC-Davis, where he held a joint appointment between the Department of Mathematics, where he continued his applied math work, and the Department of Land, Air, and Water Resources, where he developed regridding algorithms.