IDENTIFICATION OF URBAN BIAS IN TEMPERATURE TRENDS ON JAVA ISLAND 1963-2022

Temperature change is a key indicator of climate change. However, with increasing urbanization, there is a factor of uncertainty in the calculation of temperature trends, especially in urban areas. With this uncertainty, it is necessary to learn more about urban bias in Indonesia, especially i...

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Bibliographic Details
Main Author: Fathan Mubina, Qonita
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/85184
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Temperature change is a key indicator of climate change. However, with increasing urbanization, there is a factor of uncertainty in the calculation of temperature trends, especially in urban areas. With this uncertainty, it is necessary to learn more about urban bias in Indonesia, especially in Java Island which has the highest level of urbanization in Indonesia. This study aims to identify urban bias in temperature trends on Java Island in the last two climate periods (1962-1992 and 1993-2022) and identify spatial variations of urban bias in temperature trends on Java Island. The data used in this study are observational data of surface temperature, nighttime brightness, population density and ERA5 (The European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis 5-th Generation) reanalysis surface temperature. Urban and rural classifications are calculated based on population density and nighttime brightness which are then derived into the degree of urbanization. Calculation of temperature trends using linear regression and calculation of urban bias with the urban minus rural method. In the identification of urban bias with observational data, positive urban bias is identified in the trend of maximum, average and diurnal range temperature anomalies. In the identification of urban bias with reanalysis data in the first period (1963-1992) there is only a positive urban bias in the minimum temperature anomaly trend, while in the second period (1993-2022) the majority of urban bias is positive with urban bias in the average temperature anomaly trend of 16%. In terms of spatial variation, the West Java region has the highest urban bias.