International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies


:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

ISSN 2228-9860
eISSN 1906-9642



  • Rainfall Estimation from Himawari-8 Imagery during the 2017 Wet Monsoon Season in the West Coast of Peninsular Malaysia

    Nur Atiqah Hazali (School of Chemistry and Environmental Studies, Faculty of Applied Sciences, Universiti Teknologi MARA (UiTM), 40450 Shah Alam Selangor, MALAYSIA),
    Arnis Asmat (School of Chemistry and Environmental Studies, Faculty of Applied Sciences, Universiti Teknologi MARA (UiTM), 40450 Shah Alam Selangor, MALAYSIA, Climate Change & Carbon Footprint Research Group, Universiti Teknologi MARA (UiTM), 40450, Shah Alam, Selangor, MALAYSIA),
    Wan Mohd Naim Wan Mohd (Faculty of Architecture Planning and Survey, Universiti Teknologi MARA (UiTM), 40450, Shah Alam, Selangor, MALAYSIA).

    Disciplinary: Remote Sensing, Atmospheric Science, Environmental Study, Hydrology.

    ➤ FullText

    doi: 10.14456/ITJEMAST.2022.73

    Keywords: Rainfall estimation; cloud brightness temperature; Himawari-8; IMSRA algorithm; Advanced Himawari-8 Imagery (AHI); Multispectral Rainfall Algorithm (IMSRA); Auto-estimator (AE); Nonlinear Inversion (NI); IMSRA Model.

    Short duration and high rainfall density are the main factors that cause hydrometeorological disasters such as floods and landslides. In disaster mitigation, knowing the rainfall characteristics is important but hampered due to data availability. One of the essential data sources for rainfall estimation is from cloud brightness temperature of Himawari-8 imagery. Using three selective methods were used on twenty-three very heavy rainfall events (>60mm/hour) that happened in the wet season (Northeast and Inter-Monsoon) in 201. These rainfall time frames were used to estimate rainfall using cloud brightness temperature in infrared (IR) of band 14 (11.2 micrometers). The results showed the estimated rainfall for all methods is quite variable. Underestimates of rainfall were found using INSAT Multispectral Rainfall Algorithm (IMSRA), meanwhile, Auto-estimator (AE) and Nonlinear Inversion (NI) have produced overestimates of rainfall. In either case, promising results of rainfall estimates from IMSRA with Mean=31.474, Bias=-0.568, and Root Mean Square (RMSE)=49.343mm which is closer to ground measurement. In essence, the Himawari cloud brightness temperature is an important source in rainfall estimates and the infrared range can be explored in accommodating the rainfall variability.

    Paper ID: 13A4J

    Cite this article:

    Hazali, N. A., Asmat, A., and Wan Mohd, W. M. N. (2022). Rainfall Estimation from Himawari-8 Imagery during the 2017 Wet Monsoon Season in the West Coast of Peninsular Malaysia. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 13(4), 13A4J, 1-13. http://TUENGR.COM/V13/13A4J.pdf DOI: 10.14456/ITJEMAST.2022.73


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