Modal Interference Drives Madden-Julian Oscillation Evolution and Predictability

David Marsico

NOAA Physical Sciences Laboratory

Tuesday, Dec 09, 2025, 2:00 pm MT
DSRC Room GC402

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Abstract

A data-driven dynamical filter is developed to characterize Madden-Julian Oscillation (MJO) variability, by representing tropical variability with nonorthogonal empirical-dynamical modes that allow for constructive and destructive interference. We find that two intraseasonal atmospheric modes, an “MJO-fast” mode (~45 day period) and a newly-identified “MJO-slow” mode (~70 day period), alongside El Niño-Southern Oscillation modes that are not entirely removed by temporal filtering, explain nearly all observed Real-time Multivariate MJO (RMM) index-based variability. The fastest growing, and most predictable, MJO events are initiated primarily by the MJO-fast mode over the Indian Ocean, with subsequent progression across the Maritime Continent resulting from destructive and then constructive interference of the MJO-fast and MJO-slow modes. These events, which we demonstrate can be identified at forecast initialization time, are shown to be forecasts of opportunity in the ECMWF operational forecast model, with MJO skill extended by roughly a week compared to all other forecasts.

Bio: David did his undergraduate work at Haverford College in Pennsylvania, where he majored in mathematics. He then got a PhD in mathematics from UW-Madison 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. He is now a Research Scientist II at PSL where he has been since 2023.