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The multivariate ENSO index, abbreviated as MEI, is a method used to characterize the intensity of an El Niño Southern Oscillation (ENSO) event. Given that ENSO arises from a complex interaction of a variety of climate systems, MEI is regarded as the most comprehensive index for monitoring ENSO since it combines analysis of multiple meteorological and oceanographic components.
El Niño–Southern Oscillation (ENSO) is a global climate phenomenon that emerges from variations in winds and sea surface temperatures over the tropical Pacific Ocean. Those variations have an irregular pattern but do have some semblance of cycles. The occurrence of ENSO is not predictable.
Often, studies that wish to use multivariate analysis are stalled by the dimensionality of the problem. These concerns are often eased through the use of surrogate models, highly accurate approximations of the physics-based code. Since surrogate models take the form of an equation, they can be evaluated very quickly.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Indeed, the term El Niño–Southern Oscillation (ENSO) is an implicit acknowledgment that the phenomenon underlies variability in several locations at once. It was later noticed that associated teleconnections occurred all over North America, as embodied by the Pacific–North American teleconnection pattern .
Much of the LIM PDO predictability arises from ENSO and the global trend rather than extra-tropical processes and is thus limited to ~4 seasons. The prediction is consistent with the seasonal footprinting mechanism [ 36 ] in which an optimal SST structure evolves into the ENSO mature phase 6–10 months later that subsequently impacts the North ...
In several recent studies, it is shown that the Indian Ocean Dipole (IOD) has a much more significant effect on the rainfall patterns in south-east Australia than the El Niño-Southern Oscillation (ENSO) in the Pacific Ocean. [16] [17] [18] It is further demonstrated that IOD-ENSO interaction is a key for the generation of Super El Ninos. [19]
The Tropical Atmosphere Ocean (TAO) project is a major international effort that instrumented the entire tropical Pacific Ocean, with approximately 70 deep ocean moorings. ...