Since the last decade, Indonesia has continuously improved the accuracy of the national geoid model by conducting rapid gravity acquisition using airborne and terrestrial gravimetry. As gravity data have been collected thoroughly in all regions, the time has come to carry out Indonesia’s geoid modeling. We started our study by employing the Stokes and Second Helmert’s condensation method to our terrestrial gravity data in Yogyakarta, Indonesia, with a target area of 1∘× 1∘. The computation was based on the commonly applied remove-compute-restore process. We used a satellite-only geopotential model of GO_CONS_GCF_2_TIM_R6 up to degree 300 to remove and restore the long-wavelength part of the gravity field within the modeling process. Numerical results show that few cm of geoid model accuracy was achieved when we compared it to the validation points. Also, our best performance geoid is estimated to be better than the Earth Gravitational Model 2008 (EGM2008) geoid model by up to 2.8 cm in terms of standard deviation.

<p>Indonesia is an archipelago state lies between Indian and Pacific Oceans at the South East Asia region. Its unique geomorphological and geographical setting affect variabilities of instantaneous sea surface height (ISSH) concering to one of the sea reference surface i.e mean sea surface height (MSSH). The differences between both heights, known as sea level anomaly (SLA), can be recognized as one of the parameter that describes the dynamic phenomena of the ocean. We investigated the Spatiotemporal characteristics of long-term SLA in this research based on 30 years of sea-level data derived from the multi-mission of satellite Altimetry (Topex/Poseidon, Jason-1, Jason-2 and Jason-3). The Spatiotemporal of SLA characteristics in Indonesian waters indicate substantial variations due to the influences of geographical location, bathymetric depth, and seasonal patterns. The SLA rate in the Indonesian region provides values that vary between 3.4 mm/yr to 5.3 mm/yr that higher than 3.2 mm/yr global SLA rate. The impact caused by the phenomenon needs to be taken into account given the vulnerability and disaster that could endanger the islands and coastal area in Indonesia. <strong></strong></p>

<p align="justify"><em>We have utilized the Global Positioning System (GPS) data at 57 stations distributed over Sumatra Island to investigate spatio-temporal variations of the atmospheric precipitable water vapor (PWV). We focused on the annual and semi-annual cycles of the PWV. Our results show that Sumatra Island is divided into two distinct areas of annual and semi-annual cycles, where the boundary line between the areas is </em><em>approximately a</em><em>t</em><em> 2</em><em>^o</em><em>S. While the annual cycle dominates the area over the southern side of 2</em><em>^o</em><em>S, the semi-annual cycle is dominant over the northern side. Our results have further shown that</em><em> the maximum phase of annual cycle </em><em>occurs</em><em> between January-March with considerably large amplitudes (10-15 mm). On the other side, the maximum phase of the semi-annual cycle in general occurs around November and May, whose amplitude is approximately between 1-5 mm. Our results are consistent with other results using rainfall data.</em><em></em></p>