Analysis of Extreme Heat Land Surface Temperature at a Tropical City (1988-2022): A Study on the Variability of Hot Spot during El Niño Southern Oscillation (ENSO)
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Keywords:
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Spatial-temporal, Extreme Land Surface Temperature, ENSO
Abstract
Weather and climate in Malaysia, situated in Southeast Asia, are influenced by El Niño Southern Oscillation (ENSO), monsoons, Madden Julian Oscillation (MJO), and Indian Ocean Dipole (IOD). Previous studies on ENSO’s impact on temperature lacked detailed spatial information due to limited meteorological stations and cost constraints. This study utilizes remote sensing techniques, employing Landsat satellite data and Oceanic Niño Index (ONI) data, to analyze the spatial pattern of extreme land surface temperature distribution during ENSO events. Preprocessing includes radiometric and atmospheric corrections before converting digital numbers to land surface temperature values. Results indicate increased hotspot areas (>30°C) during El Niño events, with respective hotspot areas of 89.32 km² and 97.8 km² in 2015 and 2016, and 61.23 km² and 59.73 km² during La Niña in August and October 2018. Heat concentration areas remained consistent during the 1998 El Niño (89.32 km²) and the 2011 La Niña (55.82 km²). These findings highlight ENSO’s influence on altering hotspot distribution patterns. The increased hotspot area during El Niño events (34-36 km²) led to a 20-30% surge in electricity consumption as residents and offices in Kuching City, Sarawak, sought temperature regulation. This spatial information aids the government in identifying affected areas and implementing suitable measures to mitigate the impact of El Niño events.
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Baum, S., S. Horton, D. Low Choy, and B. Gleeson (2009). Climate Change, Health Impacts and Urban Adaptability: Case Study of Gold Coast City. Research Monograph, 11; 68
Berger, C., J. Rosentreter, M. Voltersen, C. Baumgart, C. Schmullius, and S. Hese (2017). Spatio temporal Analysis of The Relationship Between 2d/3d Urban Site Characteristics and Land Surface Temperature. Remote Sensing of Environment, 193; 225–243
Buyantuyev, A. and J. Wu (2010). Urban Heat Islands and Landscape Heterogeneity: Linking Spatiotemporal Variations in Surface Temperatures to Land-cover and Socioeconomic Patterns. Landscape Ecology, 25; 17–33
Cai, Z., G. Han, and M. Chen (2018). Do Water Bodies Play an Important Role In the Relationship Between Urban Form and Land Surface Temperature? Sustainable Cities and Society, 39; 487–498
Chen, C. C., B. McCarl, and H. Hill (2002). Agricultural Value of ENSO Information Under Alternative Phase Definition. Climatic Change, 54(3); 305–325
Drosdowsky, W. and M. C. Wheeler (2014). Predicting the Onset of the North Australian Wet Season with the POAMA Dynamical Prediction System. Weather and Forecasting, 29(1); 150–161
Halpert, M. S. and C. F. Ropelewski (1992). Surface Temperature Patterns Associated with the Southern Oscillation. Journal of Climate, 4; 577–593
IPCC (2014). Intergovernmental Panel Climate Change. IPCC
Iyengar, R. (2015). A Heat Wave in Pakistan Has Killed Around 140 People. Time
Kemarau, R. A. and O. V. Eboy (2020a). Land Coverage Indices and Its Impact on Land Surface Temperature Pattern in Small Medium Sizes, Kota Kinabalu City for The Year 1991, 2011 and 2018. Journal of Built Environment, Technology and Engineering, 7; 30–35
Kemarau, R. A. and O. V. Eboy (2020b). Urbanization and It Impacts to Land Surface Temperature on Small Medium Size City For Year 1991, 2011 And 2018: Case Study Kota Kinabalu. Journal of Borneo Social Transformation Studies (JOBSTS), 6(1); 5–15
Kemarau, R. A. and O. V. Eboy (2021a). Application of Remote Sensing on El Niño Extreme Effect in Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). Malaysian Journal of Applied Sciences, 6(1); 46–56
Kemarau, R. A. and O. V. Eboy (2021b). The Influence Of El Niño Southern Oscillation on Urban Heat Island Formation at Tropical City: Case of Kuching City, Sarawak. GEOGRAFIA. Malaysian Journal of Society and Space, 17(4); 288–304
Kogan, F. and W. Guo (2017). Strong 2015–2016 El Niño and Implication to Global Ecosystems From Space Data. International Journal of Remote Sensing, 38(1); 161–178
Kuok, K. K., S. M. Kueh, and P. C. Chiu (2019). Bat Optimisation Neural Networks for Rainfall Forecasting: Case Study for Kuching City. Journal of Water and Climate Change, 10(3); 569–579
Li, J., C. Song, L. Cao, F. Zhu, X. Meng, and J. Wu (2011). Impacts of Landscape Structure on Surface Urban Heat Islands: A Case Study of Shanghai, China. Remote Sensing of Environment, 115(12); 3249–3263
Lin, L., C. Chen, and M. Luo (2018). Impacts Of El Niño–southern Oscillation on Heat Waves in the Indochina Peninsula. Atmospheric Science Letters, 19(11); e856
Mahmud, M. (2018). Peristiwa El Nino dan Pengaruh IOD Terhadap Hujan di Malaysia. e-BANGI, 13(2); 166–177
Moura, M. M., A. R. Dos Santos, J. E. M. Pezzopane, R. S. Alexandre, S. F. da Silva, S. M. Pimentel, M. S. S. de Andrade, F. G. R. Silva, E. R. F. Branco, and T. R. Moreira (2019). Relation Of El Niño And La Niña Phenomena to Precipitation, Evapotranspiration and Temperature in the Amazon Basin. Science of the Total Environment, 651; 1639–1651
NOAA Climate Prediction Center (2019). Cold and Warm Episodes by Season. Database of the Climate Prediction Center, National Weather Service, U.S. Department of Commerce
Parker, D. E. (2010). Urban Heat Island Effects on Estimates of Observed Climate Change. Wiley Interdisciplinary Reviews: Climate Change, 1(1); 123–133
Siniarovina, A. U. S. (2021). Impact of ENSO Events on Temperature in the City of Kuching, Sarawak. Interview
Sum, L. P., T. M. Latif, T. Serin, K. H. Maidin, A. Q. Al-Amin, J. Liew, S. M. Alatas, L. C. Hur, S. Wong, and F. N. Ashikin (2016). El Niño-a Review of Scientific Understanding and the Impacts of 1997/98 Event In Malaysia. A Report Prepared by the Task Force On El Niño For the Academy of Sciences Malaysia September
Tan, M. L., L. Juneng, F. T. Tangang, J. X. Chung, and R. Radin Firdaus (2021). Changes in Temperature Extremes and Their Relationship With Enso in Malaysia From 1985 to 2018. International Journal of Climatology, 41; 2564–2580
Tawang, A. b., T. A. b. T. Ahmad, et al. (2003). Stabilization of Upland Agriculture Under El Nino induced Climatic Risks: Regional and Farm Level Risk Management and Coping Mechanisms in the Kedah-perlis Region, Malaysia. CGPRT Centre
Thirumalai, K., P. N. DiNezio, Y. Okumura, and C. Deser (2017). Extreme Temperatures in Southeast Asia Caused by El Niño and Worsened by Global Warming. Nature Communications, 8(1); 15531
WHO (2016). World Health Organization. World Health Organization
Xu, L., X. Xie, and S. Li (2013). Correlation Analysis of the Urban Heat Island Effect and the Spatial and Temporal Distribution of Atmospheric Particulates Using TM Images in Beijing. Environmental Pollution, 178; 102–114
Yang, Q., X. Huang, and J. Li (2017). Assessing the Relationship Between Surface Urban Heat Islands and Landscape Patterns Across Climatic Zones in China. Scientific Reports,7(1); 1–11
Yang, S., Z. Li, J. Y. Yu, X. Hu, W. Dong, and S. He (2018). El Niño–Southern Oscillation and its Impact in the Changing Climate. National Science Review, 5(6); 840–857
Yu, J.-Y., H. Paek, E. S. Saltzman, and T. Lee (2015). The Early 1990s Change in ENSO–PSA–SAM Relationships and its Impact on Southern Hemisphere Climate. Journal of Climate, 28(23); 9393–9408
Zhang, Y., H. Balzter, B. Liu, and Y. Chen (2016). Analyzing the Impacts of Urbanization and Seasonal Variation on Land Surface Temperature Based on Subpixel Fractional Covers Using Landsat Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(4); 1344–1356
Zhou, D., J. Xiao, S. Bonafoni, C. Berger, K. Deilami, Y. Zhou, S. Frolking, R. Yao, Z. Qiao, and J. A. Sobrino (2018). Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives. Remote Sensing, 11(1); 48
Authors
Eboy, O. V. ., & Kemarau, R. A. . (2023). Analysis of Extreme Heat Land Surface Temperature at a Tropical City (1988-2022): A Study on the Variability of Hot Spot during El Niño Southern Oscillation (ENSO). Science and Technology Indonesia, 8(3), 388–396. https://doi.org/10.26554/sti.2023.8.3.388-396
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