Komparasi Dataset Suhu Udara Berbasis Penginderaan Jauh Dalam Mengestimasi Suhu Udara Bulanan di Provinsi Papua Barat

Arif Faisol, Bertha Ollin Paga, Baso Daeng

Abstract


Abstrak. Pada umumnya data suhu udara diperoleh dari hasil pengamatan pada stasiun iklim Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Metode ini dapat digunakan untuk merepresentasikan suhu udara suatu wilayah yang berada pada radius ≤ 10 km dari lokasi stasiun iklim, sehingga dibutuhkan sebuah solusi alternatif untuk mendapatkan data suhu udara yang dapat merepresentasikan wilayah yang lebih luas, salah satunya memanfaatkan dataset suhu udara berbasis penginderaan jauh. Penelitian ini bertujuan membandingkan performa sejumlah dataset suhu udara berbasis penginderaan jauh, yaitu Climatic Research Unit gridded Time Series (CRU-TS), Climatologies at High Resolution for the Earth Land Surface Areas (CHELSA), dan TerraClimate dalam mengestimasi curah hujan bulanan di Provinsi Papua Barat. Penelitian ini terdiri atas 6 (enam) tahapan utama, yaitu; (1) inventarisasi data yang bertujuan mengumpulkan dataset suhu udara dan data suhu udara hasil perekaman pada Automatic Weather Station (AWS) tahun 1996 sampai tahun 2019, (2) ekstraksi data, (3) screening data untuk mengganti nilai ekstrim dengan nilai rata-rata, (4) evaluasi data untuk membandingkan dataset dengan data AWS, (5) komparasi data untuk membandingkan performa dataset, dan (6) rekomendasi yang bertujuan untuk menentukan dataset yang paling sesuai untuk digunakan di Provinsi Papua Barat. Hasil penelitian menunjukkan bahwa CHELSA, TerraClimate, dan CRU-TS sangat akurat dalam mengestimasi suhu udara bulanan di Provinsi Papua Barat yang ditunjukkan dengan nilai RBIAS < 0,1. Disamping itu CHELSA, TerraClimate, dan CRU-TS memiliki tingkat keeratan hubungan yang sedang terhadap data AWS dengan nilai r = 0,36 – 0,68. Sehingga TerraClimate, CHELSA, dan CRU-TS dapat digunakan sebagai solusi alternatif untuk mendapatkan informasi suhu udara bulanan di Provinsi Papua Barat.

Comparison of Remote Sensing-Based Air Temperature Dataset in Estimating Monthly Air Temperature in West Papua

Abstract. Air temperature is one of the important components in agriculture. Generally, air temperature data is obtained from climate stations of the Meteorological, Climatological, and Geophysical Agency (BMKG). These methods represented an area within a radius of 10 km from the climate station, therefore an alternative solution is needed for a larger area. The utilization of the air temperature dataset is one alternative solution. This research aims to compare Climatic Research Unit gridded Time Series (CRU-TS), Climatologies at High Resolution for the Earth Land Surface Areas (CHELSA), and TerraClimate as an air temperature dataset in estimating the monthly temperature in West Papua. The main stages in this research are data inventory, data extraction, data screening, data evaluation, data comparison, and data recommendation. The data used in this research are CRU-TS, TerraClimate, CHELSA, and local AWS data recording from 1996 to 2019. The research showed that CRU-TS, TerraClimate, and CHELSA are very accurate in estimating the monthly temperature in West Papua as indicated by RBIAS < 0.1. Furthermore, CRU-TS, TerraClimate, and CHELSA have a moderate correlation with AWS data in estimating monthly air temperature with r= 0.36 - 0.68. Therefore, CRU-TS, TerraClimate, and CHELSA can be used as an alternative solution to obtain monthly air temperature information in West Papua.    


Keywords


Climatic Research; Earth Land Surface Areas;TerraClimate; Automatic Weather Station

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References


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DOI: https://doi.org/10.17969/rtp.v15i1.25319

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