Tide Gauge-Based Validation of Satellite Data for Sea Level Monitoring in Indonesian Coastal Regions

Sea level observation is critically important due to its significant impact on coastal areas, particularly in relation to erosion and flooding, which directly affect the livelihoods of coastal populations. The Meteorological, Climatological, and Geophysical Agency (BMKG) of Indonesia continually enhances its marine weather information services by providing comprehensive water level data across the archipelago. A key initiative in this effort is the development of Marine Automatic Weather Station (MAWS) at harbors, equipped with tide gauges that deliver real-time water level data.

Given the limitations in the temporal availabilty of ground-based data, satellite data remains indispensable for long-term sea level monitoring. However, observational data from MAWS stations are crucial for the verification of satellite data, thereby ensuring accuracy and reliability of long-term sea level assessments.

In this study, global ocean gridded Level 4 altimeter satellite data, derived through optimal interpolation and incorporating measurements from various Level 3 altimeter missions, was utilized to provide sea level anomaly data. Additionally, water level data observed from tide gauges at three locations, Kuala Tanjung (TBT) near the Malacca Strait, Rembang (RBG), and Pangkalan Bun (PBU) near the Java sea are employed. During the data processing, tidal components were substracted to isolate the sea level anomalies. Despite the limited availability of data, these tide gauge measurements, collected over approximately one year, were used for analysis.

The result indicated that sea level at a distance of 17.5 km from the TBT station increased 0.52 cm/ year. Similarly, sea level at 9.5 km from the RBG station increased by 0.47 cm/ year, while at a distance of 70.3 km from the PBU station, the sea level has increased by 0.43 cm/ year. Furthermore, verification of the satellite data using 2022-2023 observational data revealed that the TBT station had a MAE of 0.0814, RMSE of 0.0974, ME of -0.004917 , and a correlation of 0.4890. The RBG station recorded a MAE of 0.0379, RMSE of 0.0465, ME in 3.47 x 10^-4, and a correlation of 0.3276. The PBU station exhibited a MAE of 0.0576, RMSE of 0.07, ME of 1.19 x 10^-2, and a correlation of 0.2002.

These findings suggest that the RBG and PBU stations display a similar sea level trend, likely due to their close longitudinal proximity. In contrast, the TBT station, located in a different region, exhibited a higher sea level trend. However, when comparing the satellite data with observational data for the same period, it was found that while the TBT station had a higher correlation, it also had a higher error. Conversely, the RBG station, with lower error, demonstrated a lower correlation. The low correlation observed at the PBU station might be due to its greater distance from the satellite data collection point and the shorter observation period compared to the other stations.

In conclusion, continuous sea level monitoring is essential, and the validation of satellite data with ground-based observation data is critical for ensuring accuracy. Further research with extended observation periods will be beneficial and will enhance the accuracy of future sea level predictions.