DOI: 10.11648/j.ajrs.20261402.17 ISSN: 2328-580X

Rainfall–Surface Temperature Coupling and Compound Dry-Hot Persistence Across Northwestern Bangladesh: A 25-Year Multi-Sensor Earth Observation Analysis

Nafia Muntakim, Md. Hossain, Zihad Ahmed, Md. Rahman
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Understanding how rainfall variability regulates land-surface thermal conditions is essential for climate-sensitive regions where water availability, vegetation dynamics, and heat stress interact. However, the temporal persistence and spatial heterogeneity of rainfall–surface temperature relationships remain insufficiently characterized in northwestern Bangladesh. This study integrates 25 years (2001–2025) of multi-source Earth observation data, including Terra MODIS land-surface temperature (MOD11A2), MODIS vegetation index (MOD13A2), and CHIRPS precipitation, to quantify pre-monsoon hydrothermal coupling across 16 districts of the Rajshahi and Rangpur divisions. A total of 275 quality-controlled 8-day March–May composites were analyzed using Mann–Kendall trend tests, Sen's slope estimation, fixed-effects distributed lag models, and a locally standardized compound dry-hot persistence indicator. Mean daytime land-surface temperature ranged from 27.93°C in Kurigram to 31.38°C in Chapai Nawabganj. No district exhibited a significant daytime land-surface temperature trend after false-discovery-rate correction, whereas NDVI increased significantly across all districts. The distributed-lag model showed that 10 mm of concurrent rainfall was associated with a 0.164°C lower daytime land-surface temperature (95% CI: −0.224 to −0.103°C), while rainfall during the preceding 8–16 days was associated with a weaker effect (−0.093°C per 10 mm). The 16–24-day rainfall effect was not significant. Rainfall sensitivity varied considerably among districts, ranging from −0.538°C per 10 mm in Rajshahi to −0.123°C per 10 mm in Lalmonirhat. These findings demonstrate that satellite-derived hydrothermal responses are spatially heterogeneous and highlight the value of multi-sensor Earth observation frameworks for identifying location-specific climate adaptation priorities.

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