TY - JOUR
T1 - Climate extremes walking together
T2 - Evidence from recent compounding climate hazards after Remal
AU - Ghosh, Surajit
AU - Dawn, Arpan
AU - Kour, Sneha
AU - Mallick, Archita
AU - Chowdhury, Anuva
AU - Kundu, Kaushiki
AU - De Sarkar, Kounik
AU - Rahman, Md Rayhanur
AU - Sharma, Prashanti
AU - Rajakaruna, Punsisi
AU - Rahman, Md Munsur
AU - Nath, Arun Jyoti
AU - Shaw, Rajib
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2025/2/15
Y1 - 2025/2/15
N2 - On May 26, 2024, Tropical Cyclone (TC) Remal made a devastating landfall along the coastal regions of India and Bangladesh. The sequence of disastrous events began with prevailing heatwaves, followed by the cyclone's landfall and subsequent heavy rainfall coupled with early onset of monsoon led to floods, landslides, and the resurgence of hot spells. It illustrates the complexity of managing such cascading effects of compound climate hazards. Multisource Earth Observation (EO) data with Google Earth Engine (GEE) was used to study the dynamics of Remal and its cascading impacts. IbTracks, INSAT-3D, GPM, Sentinel-1, and PlanetScope data were involved in analyzing the cyclone's progression and impacts. Remal's slow progression extended the impact of the cyclone as it hovered over Bangladesh for more than 50 h. As observed from the GPM data, the right side of the cyclone's path experienced more extensive and severe flooding than the left. Flood extent mapping using the Sentinel-1 data and Otsu thresholding depicted Jogipara, Assam in India and Jashore, Narail, and Khulna in Bangladesh as among the worst affected regions. Additionally, the early onset of the monsoon and the cyclonic rainfall in the area triggered landslides in Assam and Meghalaya during this period. The present study advocates the usage of multisource EO data and GEE for quick assessment of compound hazards started Remal. The study also highlights the need for a deeper understanding to develop a more robust district disaster management plan integrating EO data for actionable disaster risk reduction strategies for compounding climate hazards.
AB - On May 26, 2024, Tropical Cyclone (TC) Remal made a devastating landfall along the coastal regions of India and Bangladesh. The sequence of disastrous events began with prevailing heatwaves, followed by the cyclone's landfall and subsequent heavy rainfall coupled with early onset of monsoon led to floods, landslides, and the resurgence of hot spells. It illustrates the complexity of managing such cascading effects of compound climate hazards. Multisource Earth Observation (EO) data with Google Earth Engine (GEE) was used to study the dynamics of Remal and its cascading impacts. IbTracks, INSAT-3D, GPM, Sentinel-1, and PlanetScope data were involved in analyzing the cyclone's progression and impacts. Remal's slow progression extended the impact of the cyclone as it hovered over Bangladesh for more than 50 h. As observed from the GPM data, the right side of the cyclone's path experienced more extensive and severe flooding than the left. Flood extent mapping using the Sentinel-1 data and Otsu thresholding depicted Jogipara, Assam in India and Jashore, Narail, and Khulna in Bangladesh as among the worst affected regions. Additionally, the early onset of the monsoon and the cyclonic rainfall in the area triggered landslides in Assam and Meghalaya during this period. The present study advocates the usage of multisource EO data and GEE for quick assessment of compound hazards started Remal. The study also highlights the need for a deeper understanding to develop a more robust district disaster management plan integrating EO data for actionable disaster risk reduction strategies for compounding climate hazards.
KW - Climate extremes
KW - Compound hazards
KW - Disaster risk reduction
KW - Earth observation
KW - Flood
KW - Google Earth Engine
KW - Remal
KW - Tropical cyclone
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U2 - 10.1016/j.ijdrr.2024.104974
DO - 10.1016/j.ijdrr.2024.104974
M3 - Article
AN - SCOPUS:85217203315
SN - 2212-4209
VL - 118
JO - International Journal of Disaster Risk Reduction
JF - International Journal of Disaster Risk Reduction
M1 - 104974
ER -