Pengembangan Data Grid Suhu Udara Resolusi Tinggi Menggunakan Teknik Penggabungan Data Pengamatan In-Situ Dan Era5-Land Di Jawa Timur

Fatchiyah, Fatchiyah (2026) Pengembangan Data Grid Suhu Udara Resolusi Tinggi Menggunakan Teknik Penggabungan Data Pengamatan In-Situ Dan Era5-Land Di Jawa Timur. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pemantauan suhu udara yang akurat sangat penting dalam memahami dinamika perubahan iklim maupun mikroklimat, terutama pada wilayah dengan kondisi iklim dan topografi yang kompleks. Tantangan utamanya adalah keterbatasan jumlah stasiun pengamatan, sehingga cakupan data suhu yang representatif sulit diperoleh. Penggabungan antara data suhu in-situ dengan data model beresolusi tinggi, seperti ERA5-Land dapat menjadi alternatif solusi, meskipun data tersebut sering menunjukkan penurunan akurasi pada wilayah dengan topografi beragam. Penelitian ini menerapkan metode Kriging with External Drift (KED) untuk mengoptimalkan kualitas penggabungan data suhu in-situ dan ERA5-Land, dengan penekanan pada pemilihan model semivariogram terbaik dari lima model Spherical, Exponential, Gaussian, Linear, dan Power. Evaluasi akurasi dilakukan menggunakan RMSE, MAE dan MSE dimana nilai terendah menunjukkan kinerja paling akurat. Analisis mencakup parameter suhu rata-rata, maksimum, dan minimum, pada skala temporal harian, bulanan, dan musiman, serta mempertimbangkan pengaruh jarak antar stasiun dan faktor ketinggian. Hasil penelitian mengindikasikan bahwa model Exponential memberikan performa paling unggul pada seluruh skenario pengujian. Keunggulan ini berkaitan dengan kondisi topografi Jawa Timur yang kompleks, yang terdiri dari dataran rendah, pegunungan dan lembah, sehingga menghasilkan pola autokorelasi suhu dengan penurunan bertahap. Produk grid suhu resolusi tinggi yang dihasilkan terbukti lebih representatif dibandingkan ERA5-Land data mentah dan dapat menyediakan informasi suhu pada wilayah tanpa stasiun pengamatan, sehingga mendukung analisis variabilitas iklim, kajian perubahan iklim, serta perencanaan dan mitigasi bencana di Jawa Timur.

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Accurate air temperature monitoring is essential for understanding climate change dynamics and microclimatic conditions, especially in regions with complex climate characteristics and topographic variability. One of the main challenges is the limited number of observation stations, which hinders the acquisition of spatially representative temperature data. Integrating in-situ temperature measurements with high-resolution model data such as ERA5-Land offers a potential solution, although model-based temperature data often exhibit reduced accuracy in areas with diverse topography. This study applies the Kriging with External Drift (KED) method to optimize the fusion of in-situ air temperature data and ERA5-Land, with a focus on selecting the best semivariogram model among five candidates Spherical, Exponential, Gaussian, Linear, and Power. Accuracy evaluation was conducted using RMSE, MAE, and MSE, where lower values indicate higher performance. The analysis covers mean, maximum, and minimum temperature parameters across daily, monthly, and seasonal temporal scales, while also considering the effects of station spacing and elevation. The findings show that the Exponential model consistently provides the best performance across all evaluation scenarios. This superiority is associated with the complex topography of East Java, consisting of lowlands, mountainous regions, and valleys, which produces a gradually declining spatial autocorrelation pattern in air temperature. The resulting high-resolution temperature grid is more representative than raw ERA5-Land data and can provide temperature information in areas without observation stations, thereby supporting climate variability analysis, climate change assessments, and disaster planning and mitigation in East Java.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Kata Kunci: data suhu, ERA5-Land, KED, Semivariogram Keywords: Air temperature, ERA5-Land, KED, Semivariogram
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Fatchiyah Fatchiyah
Date Deposited:	28 Jan 2026 09:05
Last Modified:	28 Jan 2026 09:05
URI:	http://repository.its.ac.id/id/eprint/130813

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