Abstract
El Niño–Southern Oscillation (ENSO) and its relationships with marine environmental parameters comprise a very complicated and interrelated system. Traditional spatiotemporal techniques face great challenges in dealing with which, how, and where the marine environmental parameters in different zones help to drive, and respond to, ENSO events. Remote sensing products covering a 15-year period from 1998 to 2012 were used to quantitatively explore these patterns in the Pacific Ocean (PO) by a prevail quantitative association rule mining algorithm, that is, a priori, within a mining framework. The marine environmental parameters considered were monthly anomaly of sea surface chlorophyll-a (CHLA), monthly anomaly of sea surface temperature (SSTA), monthly anomaly of sea level anomaly (SLAA), monthly anomaly of sea surface precipitation (SSPA), and monthly anomaly of sea surface wind speed (WSA). Four significant discoveries are found, namely: (1) Association patterns among marine environmental parameters and ENSO events were found primarily in five sub-regions of the PO: the western PO, the central and eastern tropical PO, the middle of the northern subtropical PO, offshore of the California coast, and the southern PO; (2) In the western and the middle and east of the equatorial PO, the association patterns are more complicated than other regions; (3) The following factors were found to be predicators of and responses to La Niña events: abnormal decrease of SLAA and WSA in the east of the equatorial PO, abnormal decrease of SSPA and WSA in the middle of the equatorial PO, abnormal decrease of SSTA in the eastern and central tropical PO, and abnormal increase of SLAA in the western PO; (4) Only abnormal decrease of CHLA in the middle of the equatorial PO was found to be a predicator of and response to El Niño events. These findings will help to improve our abilities to identify the marine association patterns in factors relating to ENSO events.
Highlights
Marine association pattern refers to an association relationship with a direction among two and more marine environmental parameters
sea surface temperature (SST) drop in the central Pacific, east–west SST gradients increase, and Equatorial trades strengthen, which leads to the spatiotemporal distribution of the upper mixed layer, thermocline, and nutrients; this distribution indirectly dominates primary productivity and spatiotemporal changes in CHL concentration [14,15]
The spatiotemporal resampling was used to generate the datasets with a spatial resolution of 1◦ in grid projection and with a time resolution of one month, the monthly anomalies were calculated by removal of seasonal effects with the z-score algorithm [26,34]
Summary
Marine association pattern refers to an association relationship with a direction among two and more marine environmental parameters. Association rule mining techniques have been widely used to obtain the interrelationships among geographical parameters, including the interrelationship between bird species richness and geographical parameters [31], the spatial distribution of aerosol optical depth and its affecting factors [32], the spatial co-location patterns between the fish distribution and marine parameters [33], and the teleconnection among regional or global marine parameters [27,30,34] The purpose of this manuscript is to quantitatively explore, using remote sensing products and within an association rule mining framework, what are those marine environmental parameters and which ones are sensitive to ENSO events.
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