The Madden-Julian oscillation (MJO) is a tropical weather system that has an important influence in the tropics and beyond; however, many of its characteristics are poorly understood, including their initiation and termination. Here we define Madden-Julian events as contiguous time periods with an active MJO, and we show that both the durations and the sizes of these events are well described by a double power-law distribution. Thus, small events have no characteristic scale, and the same for large events; nevertheless, both types of events are separated by a characteristic duration of about 27 days (this corresponds to half a cycle, roughly). Thus, after 27 days, there is a sharp increase in the probability that an event becomes extinct. We find that this effect is independent of the starting and ending phases of the events, which seems to point to an internal mechanism of exhaustion rather than to the effect of an external barrier. Our results would imply an important limitation of the MJO as a driver of subseasonal predictability.
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http://dx.doi.org/10.1103/PhysRevE.108.054214 | DOI Listing |
Sci Rep
November 2024
Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 2-15 Natsushima-Cho, Yokosuka City, 237-0061, Kanagawa, Japan.
This study investigated the vertical structure of 6 cross-equatorial northerly surge (CENS) events during the Year of Maritime Continent-Cold Surge Observation in 2021 (YMC-CSO2021) campaign. These events, named CENS1 (Jan. 18-20), CENS2 (Jan.
View Article and Find Full Text PDFClim Dyn
May 2024
Department of Oceanography, Dalhousie University, 1355 Oxford St, Halifax, NS B3H 4R2 Canada.
Subseasonal-to-seasonal (S2S) prediction is a global effort to forecast the state of the atmosphere and ocean with lead times between two weeks and a season. This study explores the feasibility of S2S prediction of the ocean using a variety of tools including statistical analysis, a statistical-dynamical mixed layer model, and a regional, high-resolution ocean circulation model based on physical principles. Ocean predictability on S2S timescales is analyzed by compositing winter sea surface temperature (SST) anomalies in the North Atlantic with respect to the state of the Madden-Julian Oscillation (MJO).
View Article and Find Full Text PDFSci Adv
October 2024
Department of Physical Oceanography and Instrumentation, Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany.
El Niño typically induces cooling in the Southwest Pacific Ocean during austral summers, usually leading to decreased marine heatwave frequency and severity. However, the 2016 extreme El Niño unexpectedly coincided with the longest and most extensive marine heatwave ever recorded in the region. This heatwave, spanning over 1.
View Article and Find Full Text PDFNat Commun
July 2024
Artificial Intelligence Innovation and Incubation Institute, Fudan University, Shanghai, China.
Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical weather predictions generated by the European Centre for Medium-Range Weather Forecasts (ECMWF), but have not yet surpassed conventional models at subseasonal timescales. This paper introduces FuXi Subseasonal-to-Seasonal (FuXi-S2S), a machine learning model that provides global daily mean forecasts up to 42 days, encompassing five upper-air atmospheric variables at 13 pressure levels and 11 surface variables.
View Article and Find Full Text PDFChaos
June 2024
Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, 05508-090 Sao Paulo, Brazil.
The equatorial region of the Earth's atmosphere serves as both a significant locus for phenomena, including the Madden-Julian Oscillation (MJO), and a source of formidable complexity. This complexity arises from the intricate interplay between nonlinearity and thermodynamic processes, particularly those involving moisture. In this study, we employ a normal mode decomposition of atmospheric reanalysis ERA-5 datasets to investigate the influence of nonlinearity and moisture on amplitude growth, propagation speed, and mode coupling associated with equatorially trapped waves.
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