Anomaly technique for expression the Indian Ocean Dipole in South Java Sea

Aida Sartimbul,Mochammad Firdaus Ali,Erfan Rohadi,Zulfan Khaidar

doi:10.14419/ijet.v7i4.44.26857

Abstract

The longer period of time series of anomaly data was usually used to express the climatic phenomena. Even it is common, however, there were limited study discusses how powerful anomaly technique for understanding the climatic phenomena that occur in the period of time. The objective of this study is to understand the nature of anomaly, to identify an unusual fluctuation of data, and to detect the climate change impact to the Sea Surface Temperature (SST). The eleven years satellite Aqua Modis data and Dipole Mode Index were applied to this study. The raw data were averaged and removed seasonal trend using anomaly technique and then plotted to both MS Excel and Surfer ver. 6. The result shows that the monthly average of SST was indicated a seasonal/ sinusoidal pattern. Furthermore, anomaly analysis provides an unusual SST trend that has a direct impact on the climatic phenomenon as Indian Ocean Dipole. It is suggested that an anomaly technique may provide a good tool for expression unusual phenomena due to climate change.

Highlights

Oceanographic phenomena vary in space and time scale
The following paragraph will discuss about the strengthen and weakness of raw data and anomaly data for oceanographic data expression
An Anomaly analysis was match well with climatic index, they are suitable to be plotted together and be able to express the possible relation between Sea Surface Temperature (SST) anomaly and climate change phenomenon such as Indian Ocean Dipole

Summary

Introduction

Oceanographic phenomena vary in space and time scale. The smallest phenomena such as bubbles, capillary waves, even El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and thermohaline circulation and Milankovitch, occur from the narrowest (mm) to the widest (thousands of km) of space oceans and require the shortest time (0.001 sec.) to the longest (thousands of years) (1). The abundance of data due to the development of modern physics oceanographic instruments such as CTDs, current meters, satellite instruments capable of measuring many samples per unit of seconds, means that the average analysis is more utilized than individual analysis. This average analysis is generally plotted on time series charts based on raw data or just average, so seasonal trends are still visible. This method is not enough to explain the existence of deviation or anomalies in the time series graph

Objectives

Methods

Conclusion