How Accurate Geomagnetic Regional Modeling Using Ordinary Kriging For Clustered Distributed Data?: New Insight From Indonesian Archipelago

Abstract

Indonesia relies only on the limited number of repeat station networks due to the archipelago setting with the extensive sea with the clustery distributed pattern. This paper explored geostatistical modeling to overcome that typical data characteristic. The modeling used repeat station data from the 1985 to 2015 epoch. The research used ordinary kriging (OK) compared to the Spherical Cap Harmonic Analysis (SCHA) and Polynomial. The results show that the root means square error (RMSE) of each declination, inclination, and total intensity vary among epochs. OK method for declination component produces smaller average RMSE (7.67 minutes) than SCHA (9.26 minutes) and Polynomial (7.97minutes). For the inclination component, OK has an average RMSE of 9.55 minutes, smaller than SCHA (10.05) but slightly higher than Polynomial (9.36 minutes). For the total intensity component, OK produce an average RMSE of 63.58 nT, smaller than SCHA (82.24 nT) and Polynomial (68.97 nT). The finding shows that the kriging method can be a promising method to model the regional geomagnetic field, especially in the area of limited available data and clustered distributed data.