Upwelling index along the South Coast of Java from satellite imagery of wind stress and sea surface temperature

Abstract

Upwelling Index which is processed from satellite imagery of wind stress and Sea Surface Temperature (SST) were examined to describe upwelling and its dynamics along the southern coast of Java. Analysis in September as the peak of upwelling shows that the commonly use of Ekman Transport-based Upwelling Index mostly shows higher values on the western part of south coast of Java as the alongshore wind stress is stronger to the west. But on the contrary, the SST-based Upwelling Index shows a relatively intense and persistent upwelling on the eastern part of south coast of Java and strengthened in El Nino year of 2015. The intense upwelling is indicated by the lowest value of SST minimum and the maximum value of thermal gradient SST up to 75 km off shore. Thus, for upwelling areas that are not predominantly induced by offshore Ekman Transport, the dynamics of upwelling would be better seen through an SST-based upwelling index. The use of both upwelling indices, will complement each other so that upwelling and its dynamics can be precisely understood.

A Comparison of the Three Upwelling Indices in the South Java Sea Shelf

“…Since cross-correlation between UISST and UIC H L results in the highest correlation coefficient (0.74) with the smallest lag time (6-12 days) in the eastern points (Figure 11D), we suggested that South Java upwelling can be identified better using SST than through Ekman mass transport or wind, particularly in the east. This result was relevant to the studies mentioned earlier about the upwelling index in the South Java upwelling system (Wirasatriya et al, 2020;Naulita et al, 2020). In addition, our points of analysis, which are lying on the shelf, could be the reason UI based on the Ekman mass transport was not explained well by the upwelling event as stated by Aïssa et al (2014).…”

“…The SST Upwelling Index (UISST) is calculated as the SST difference between coastal and oceanic points at the same longitude (Alvarez et al, 2011;Kunarso et al, 2020;Naulita et al, 2020). As Alvarez et al (2011) applied for their longitudinal analysis, the oceanic points are located approximately 3° southward from the coast.…”

“…This technique arose because the surface cooling of the upwelled water reaching the sea surface is a potential proxy of the upwelling intensity. Naulita et al (2020) showed that the eastern part of their domain (> 108˚E) shows a large gradient of thermal difference, indicating higher UISST, but has the lowest value of UIET. Meanwhile, the chlorophyll-a-derived upwelling index was determined by applying a threshold that distinguishes between high concentrations of Chl-a when upwelling occurs and its low concentration when there is no upwelling.…”

“…Dewi et al (2020) used only UISST to investigate the South Java upwelling characteristics during ENSO. Naulita et al (2020) analyzed the South Java Upwelling Index based on wind and SST in the region between 106 and 114˚E. Here, we go inside to the shelf area for the first time.…”

Comment on bg-2020-486

“…However, locations of maximum amplitude of the upwelling signatures may differ in space among the variables due to dynamical upper-ocean responses to the wind forcing. One such example can be seen in a phase relation between the winds and SST along the Java coast; strong winds appear in the western area of the Java coast while the SST signal comes further east (Naulita et al, 2020). In addition to this local wind forcing, the Sumatra-Java coastal area is affected by remotely forced Kelvin waves propagating from regions further northwest along the Sumatra coast and from the equatorial Indian Ocean.…”