The focus of this study is the assessment of the main range and geophysical corrections needed to derive accurate sea level time series from satellite altimetry in the Indonesia seas, the ultimate aim being the determination of sea level trend for this region. Due to its island nature, this is an area of large complexity for altimetric studies, a true laboratory for coastal altimetry. For this reason, the selection of the best corrections for sea level anomaly estimation from satellite altimetry is of particular relevance in the Indonesian seas. The same happens with the mean sea surface adopted in the sea level anomaly computation due to the large gradients of the mean sea surface in this part of the ocean. This study has been performed using altimetric data from the three reference missions, TOPEX/Poseidon, Jason-1 and Jason-2, extracted from the Radar Altimeter Database System. Analyses of sea level anomaly variance differences, function of distance from the coast and at altimeter crossovers were used to assess the quality of the various corrections and mean sea surface models. The selected set of corrections and mean sea surface have been used to estimate the sea level anomaly time series. The rate of sea level rise for the Indonesian seas was found to be 4.2 ± 0.2 mm/year over the 23-year period (1993–2015).

This paper discusses extreme magnitudes of residual water levels and their probabilistic behaviors. The study area is situated in the west of Java Sea, NW of Java Island. The discussion relies on recent two decades’ Sea Surface Height (SSH) from two offshore points of observation in the west of Java Sea and Water Level (WL) from a tide station in Tanjung Priok port of Jakarta. The dataset of SSH is obtained by satellite altimetry on 10-day basis observation, while WL is recorded on hourly basis. Residuals are extracted from SSH and WL by removing their mean values (i.e. Mean Sea Surface, Mean Sea Level) and the tide. They range within the order of sub-meters. These count already for at least one-third of the tidal amplitude in the region. To these residuals, their mean and extreme patterns are explored. The chances of positive residuals are at least tripled with respect to the negative ones. The nearshore point, i.e. Tanjung Priok, experiences a greater magnitude of residuals than those in the offshore area. Here, we apply Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) methods respectively for Block Maxima/Minima (BM) and Peak Over Threshold (POT) samplings of residuals. It is found that, the extreme positive and negative residuals at 100-year return period are within less than ±1 m in Tanjung Priok and just less than half-meter in the offshore area. While higher residuals are observed during the East monsoon in the offshore area, Tanjung Priok experiences higher residuals during the West monsoon. This is thought due to the prevailing wave fields, which are governed by the monsoonal winds.

The Eastern Indonesian waters are significant in influencing the global climate system and oceanic connectivity. However, the Indonesian Through Flow (ITF) facilitates the movement of waters from the Pacific Ocean to the Indian Ocean. This flow vertically mixes water masses in the Eastern regions, leading to the concentration of phytoplankton. In addition, the distribution of phytoplankton, indicative of chlorophyll-a concentration, is influenced by upwelling and downwelling phenomena. Chlorophyll-a, responsible for capturing carbon and producing oxygen in marine ecosystems, is important in regulating climate change. Moreover, oceanographic conditions play a significant role in the dispersion of chlorophyll-a concentration. Therefore, this study adopted ocean colour remote sensing technology to assess chlorophyll-a distribution. Monthly ocean colour data was collected by the multi-temporal Sentinel-3 Ocean and Land Colour Instrument (OLCI). The analysis output included chlorophyll-a concentration associated with currents and the El Nino Southern Oscillation (ENSO). Data processing using the Case-2 Regional Coast Colour (C2RCC) processor resulted in an average chlorophyll-a concentration in the Eastern Indonesian waters ranging from 0.16 to 0.52. The results showed higher chlorophyll-a levels during the southeast monsoon (July to September) and lower levels during the northwest monsoon (January to March).

Global mean sea level (GMSL) and El Niño Southern Oscillation (ENSO) has a high correlation. This study aims to investigate the impact of ENSO on the Indonesian seas using satellite altimetry for a period 24 years (1993 - 2016). The correlations between ENSO and sea level variability were performed by ENSO indices. The effect of ENSO to the Indonesian seas is significant which is shown by the correlation index of -0.84, -0.85 and 0.70 for Multivariate ENSO Index (MEI), Oceanic Niño Index (ONI), and Southern Oscillation Index (SOI), respectively. The eastern areas of Indonesian seas have a highest impact of ENSO.

The regional sea level budget and interannual sea level changes around Taiwan and Philippines are studied using altimetry, GRACE, and in-situ hydrographic data during 1993‒2021. Results show that the average sea level trend around Taiwan and Philippines during 1993–2021 derived from the altimetric data is 3.6 ± 0.2 mm/yr. Over 2002–2021, the study shows closure of sea level budget in the eastern ocean of Taiwan and Philippines within the observed data uncertainties, and the ocean mass accounts for 88%–100% of the observed sea level rise. In contrast, the sea level budget is not closed in the western ocean of Taiwan and Philippines, probably due to the lack of complete coverage by in-situ ocean observing systems. In addition, both regional sea level anomalies and their steric component around Taiwan and Philippines exhibit pronounced interannual and decadal variabilities. The trade wind stress associated with El Niño–Southern Oscillation and Pacific Decadal Oscillation offers a compelling explanation for the interannual and decadal signals of sea level anomalies in the southern ocean of Taiwan, with negative correlations of − 0.78 to − 0.64, indicating that trade wind stress makes a negative contribution to interannual-to-decadal sea level variability. In the northwestern ocean of Taiwan, the sea level variation is strongly influenced by the local monsoon system and shallow bathymetry with an annual amplitude of 90.3 ± 2.9 mm, larger than those in other regions around Taiwan and Philippines, where ocean mass is dominant with a high correlation with the sea level (+ 0.75 to + 0.78).