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All Journal Geoid - Journal of Geodesy and Geomatics
Eko Yuli Handoko
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Engineering Environmental Science

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Analysis of Seasonal Patterns of Atmospheric Water Vapour and Rainfall in East Kalimantan and North Kalimantan Using the Lomb–Scargle Periodogram Method Agus Ariyanto; Eko Yuli Handoko; Putra Maulida
GEOID Vol. 21 No. 1 (2026)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v21i1.8767

Abstract

This study examines the seasonal trends of Precipitable Water Vapour (PWV) obtained from GNSS data (2021–2023) and decadal rainfall data from BMKG (2001–2020) in East and North Kalimantan, employing the Lomb–Scargle Periodogram (LSP) method. The findings indicate that PWV is mostly influenced by an equatorial semi-annual cycle (about 0.5 years), while precipitation typically adheres to a monsoonal annual pattern (around 1 year). The correlation between PWV and precipitation is not wholly linear, exhibiting significant local variability in coastal areas. The LSP approach is effective in identifying dominant frequencies, albeit it exhibits reduced sensitivity to non-stationary fluctuations in atmospheric signals.
Identification of the Best Semivariogram Model for the Blending of In-Situ and ERA5-Land Air Temperature Data Using the Kriging with External Drift Technique Fatchiyah; Eko Yuli Handoko; Ardhasena Sopaheluwakan; Robi Muharsyah
GEOID Vol. 21 No. 1 (2026)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v21i1.8768

Abstract

Accurate air temperature monitoring is essential for understanding climate dynamics and microclimates, particularly in regions with diverse topography. The limited number of observation stations often results in data that do not fully represent actual conditions. To address this gap, combining in-situ measurements with ERA5-Land reanalysis presents a promising alternative, although ERA5-Land may still exhibit biases in mountainous or urban areas. This study applies Kriging with External Drift (KED) to improve temperature estimation, focusing on identifying the most suitable semivariogram model. Daily and monthly analyses were conducted, with performance evaluated using RMSE, MAE, and MSE. The results indicate that the Spherical model consistently performs best for average and maximum temperatures, while the Exponential model provides better estimates for minimum temperature at the daily scale, and the Linear model at the monthly scale. These findings demonstrate that KED can significantly enhance temperature estimation in areas with sparse observations, while also highlighting the most reliable semivariogram models for different temperature parameters.
Co-Authors Agus Ariyanto Ardhasena Sopaheluwakan Danar Guruh Pratomo Duty Kendartiwastra Fatchiyah Putra Maulida Robi Muharsyah