Analysis Of Spatiotemporal Abnormal Variations Clustering Patterns For Global Oceanic Net Primary Production

As a measure of the photosynthetic capacity of phytoplankton,oceanic net primary productivity is an important content of global change research.Marine anomaly variations are an abnormal decrease or increase of marine environmental parameters,which covers a specified spatial domain and lasts for a specified temporal duration.For example,the monthly mean variation of oceanic net primary productivity.Abnormal variations patterns for global oceanic net primary production has obvious cycle and seasonal characteristics at global and regional scales,and is responsible and driving for the El Nino-Southern Oscillation.Although current studies have analyzed the response of chlorophyll a concentration to two types of ENSO events,few studies have studied the abnormal changes of the relationship between oceanic net primary productivity and the two types of ENSO events,and it is difficult to describe the continuous dynamic evolution of abnormal changes and association mechanism with ENSO.Based on this,this paper revises the Dual-constraint Spatio Temporal Clustering Approach to explore the spatiotemporal clusters of global net primary productivity,using the long time series satellite remote sensing data,so as to analyze the spatial distribution and spatial migration of oceanic net primary productivity spatiotemporal clusters in response to two types of ENSO events.The specific work is as follows:1)Collection and analysis the nearly 20 years of oceanic net primary productivity data set,research the spatial distribution characteristics of mean,trend and standard deviation of global regional oceanic net primary productivity,using empirical orthogonal function the spatiotemporal modal distribution of oceanic net primary productivity.The results show that(1)Oceanic net primary productivity has zonal distribution characteristics,there is an obvious trend of change for the oceanic net primary productivity in the equatorial region,and there is a significant difference in the distribution between coastal areas and the oceanic net primary productivity in the ocean.(2)Oceanic net primary productivity in the equatorial Pacific Ocean(PO)has a reverse east-west distribution with 155°E as the boundary.During the period of El Nino events,the oceanic net primary productivity with an abnormal decreased intensity locate in the equatorial eastern PO,while the oceanic net primary productivity with an abnormal increased intensity locate in the equatorial western PO.During the period of La Nina events,the oceanic net primary productivity with an abnormal increased intensity locate in the equatorial eastern PO,while the oceanic net primary productivity with an abnormal decreased intensity locate in the equatorial western PO.(3)Oceanic net primary productivity and ENSO events have the same cycle on the time scale,the main change cycle is 18 months and 28 months.2)Revises the Dual-constraint SpatioTemporal Clustering Approach to explore the spatiotemporal evolution clusters of global net primary productivity using the satellite remote sensing data set from January 1998 to December 2017,and analyzes the relationships between the net primary productivity spatiotemporal clusters and ENSO events.In views of spatiotemporal distribution and spatial migration of global net primary productivity.The main results show that:(1)During the period of Eastern Pacific(EP)El Nino events,the spatiotemporal evolution clusters with an abnormal decreased intensity mainly locate in either the equatorial mid-eastern PO or the equatorial eastern PO,while the spatiotemporal evolution clusters with an abnormal increased intensity mainly locate in the equatorial western PO and the central South Pacific.During the period of Central Pacific(CP)El Nino events,the spatiotemporal evolution clusters with an abnormal decreased intensity mainly locate in the equatorial central PO,and the spatiotemporal evolution clusters with an abnormal increased intensity mainly locate in the equatorial western PO and the central South Pacific.(2)During the period of EP La Nina events,the spatiotemporal evolution clusters with an abnormal increased intensity locate in the equatorial central or the central eastern PO,the equatorial Atlantic ocean and the equatorial Indian ocean,while the spatiotemporal evolution clusters with an abnormal decreased intensity locate in the east-central South Pacific.During the period of Central Pacific(CP)La Nina events,the spatiotemporal evolution clusters with an abnormal increased intensity mainly locate in the equatorial central PO,and the spatiotemporal evolution clusters with an abnormal decreased intensity mainly locate in the mid-western South Pacific.(3)During the period of EP ENSO events,the spatiotemporal evolution clusters have a trend of moving to the east.During the period of CP ENSO events spatiotemporal evolution clusters have a tendency to arise and disappear in the central equatorial PO.3)Based on the development rule of ENSO events and abnormal variations clustering patterns for global oceanic net primary production,an ENSO event classification index is proposed to describe the subcategories of two types of ENSO events.(1)The newly defined ENSO index based on the anomalous evolution clusters of oceanic net primary production can clearly distinguish the occurrence,development and extinction processes of different types of ENSO events,as well as the degree and duration of the anomalous change of thematic properties of the spatiotemporal evolution clusters in different stages.(2)The new index can describe the position of oceanic net primary production anomalies change in key regions in different development stages of ENSO events according to the center of mass of spatiotemporal evolution clusters.(3)Compared with the existing judgment and classification results of ENSO events,the new index has a strict definition and can detect weak and short duration ENSO events.The types and intensities of ENSO events in the past 20 years are summarized,which is of great significance for the in-depth understanding of the physical mechanism behind different types of ENSO events and the prediction and prediction of extreme climate events.Figure[36]table[4]reference[58]...