The seas along the Northern Coast of Papua constitute a region with complex oceanographic conditions as they are situated within the Indo-Pacific warm pool (IPWP). The geographical location in the southern hemisphere induces upwelling during the west monsoon season (December-January-February). Additionally, interannual phenomena such as the El Niño Southern Oscillation (ENSO) can impact the intensity of upwelling in these waters. This study aimed to compare the upwelling intensity in the seas along the Northern Coast of Papua during neutral phases and ENSO phases. The main indicators of upwelling are sea surface temperature (SST) and Ekman mass transport (EMT). The data utilized in this study include SST from GHRSST and surface wind from ASCAT. The data processing employed the monthly composite method with spatiotemporal analysis based on anomaly results derived from monthly climatology. The analysis results reveal that El Niño 2015–2016 led to an increase in upwelling intensity ranging from 1.82 to 4.00 m/s2, while La Niña 2010–2011 resulted in a weakening of upwelling intensity ranging from 4.95 to 6.56 m/s2 in the seas along the Northern Coast of Papua. On the basis of correlation and regression analysis, it can be concluded that offshore EMT significantly influences upwelling anomalies in the southeastern waters, whereas the northwestern waters are more influenced by the shifting IPWP during ENSO.
The seas of Southern Java are located at the eastern equatorial Indian Ocean and therefore, they are strongly influenced by the Indian Ocean Dipole (IOD). Strong negative IOD occurred in 2016. However, none of the previous studies investigated its effect on the seas of Southern Java. This study aims to reveal the influence of the strong negative IOD in 2016 on the upwelling intensity along the seas of Southern Java as represented by surface temperature and chlorophyll-a. This research was conducted using satellite-based data and the analysis was based on climatology, and anomaly for 15 years (2007–2021). The data used includes sea surface temperature (OISST), wind (ASCAT), IOD index (DMI), chlorophyll-a (OC-CCI), and sea level anomaly (altimetry). The findings show that the strong negative IOD in 2016 had a significant impact on sea surface temperatures which made these waters warmer. The most visible impact is through the sea surface temperature anomaly map where in 2016 throughout the year it experienced a positive anomaly with a value of 2°C higher than the climatological average. The value of chlorophyll-a in these waters has also dropped drastically which, when viewed from the anomaly map, has a value of 0.2 mg/m3 lower than the climatological average, especially during the upwelling month. This means that, strong negative IOD in 2016 reduced the upwelling intensity along the seas of Southern Java. We also found the propagation of downwelling Kelvin waves from the Indian Ocean to the Southern Java waters which bring warm temperatures and cause downwelling events during the strong negative IOD in 2016 that hampers coastal upwelling along the seas of Southern Java.
Banjir Kanal Barat (BKB) and Banjir Kanal Timur (BKT) are widely used for various community activities such as residential areas, industry, fish cultivation, and auction. Community activity around BKB and BKT will affect N and P nutrient inputs, which further affects phytoplankton abundance. In this study, phytoplankton biomass was estimated through chlorophyll-a (chl-a) measurements. The purpose of this study was to determine the distribution of the chl-a and determine the influence of phosphate and nitrate in front of the estuary from BKB and BKT. Sampling was carried out at 8 stations from each estuary and was carried out in the dry season. The concentration of chl-a, phosphate, and nitrate is further described in the form of a distribution pattern based on the interpolation method with ArcGIS 10.2 software. The results showed that the average ± sd of chl-a, respectively was 15,781 ± 16.90 mg/m3 and 17,710 ± 15.31 mg/m3, phosphate was 0.0174 ± 0.0057 ppm and 0.0096 ± 0.0164 ppm, nitrate was 2.9086 ± 1.1824 ppm and 1.6919 ± 1.6316 ppm. The distribution pattern of chlorophyll-a and phosphate decreases in concentration towards the sea, while nitrate forms an irregular pattern and has a different pattern in each estuary. Nutrient phosphate has a positive correlation with chlorophyll-a.
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