The study examines extreme daily precipitation and temperature trends in coastal Odisha, India by calculating 18 weather indices (8 temperature indices and 10 rainfall indices) using the RClimDex software package for the period 1980-2010. Statistical significance of the indices was determined through trend analysis using linear regression and non-parametric Mann-Kendall test. Results indicated, a strong and significant trend in temperature indices while the weak and non-significant trend in precipitation indices. The positive trend in Tmax mean, Tmin mean, TN90p (warm nights), TX90p (warm days), diurnal temperature range, warm spell duration indicator, consecutive dry days indicates increasing the frequency of warming events in coastal Odisha. Similarly, positive trend in highest maximum 1-day precipitation, highest maximum 2-consecutive day precipitation, highest maximum 3 consecutive day precipitation, highest maximum 5-consecutive day precipitation, number of heavy precipitation days (64.5mm), number of very heavy precipitation days (124.5mm) and negative trend in the number of rainy days (R2.5mm), consecutive wet days indicate changes toward the more intense and poor distribution of precipitation in coastal Odisha. Extreme precipitation and temperature events negatively impacted rice yield, with a sharp decline observed in all coastal districts. The study highlights the need for new technology/management practices to minimize these impacts.

The exchange of CO₂ between the air–water interfaces of estuaries is crucial from the perspective of the global carbon cycle and climate change feedback. In this regard, we evaluated the air–water CO₂ exchanges in two major estuaries—the Mahanadi estuary (ME) and the Dhamra estuary (DE) in the northern part of the Bay of Bengal, India. Biogeochemical properties of these estuarine waters were quantified in three distinct seasons, namely, pre-monsoon (March to May), monsoon (June to October), and post-monsoon (November to February). The significant properties of water, such as the water temperature, pH, salinity, nutrients, dissolved oxygen, chlorophyll-a (chl a), and photosynthetic pigment fluorescence of phytoplankton, were estimated and correlated with CO₂ fluxes. We found that the ME acted as a source of CO₂ fluxes in the monsoon and post-monsoon, while DE acted as a sink during the monsoon. The stepwise regression model showed that the fluxes were primarily driven by water temperature, pH, and salinity, and they correlated well with the phytoplankton characteristics. The chl a content, fluorescence yield, and phycobilisomes-to-photosystem II fluorescence ratios were major drivers of the fluxes. Therefore, for predicting air–water CO₂ exchanges precisely in a large area over a seasonal and annual scale in the estuaries of the Bay of Bengal, India, critical key parameters such as water temperature, pH, salinity, chl a, and fluorescence yield of phytoplankton should be taken into consideration. However, the responses of phytoplankton, both in terms of production and CO₂ capture, are critical research areas for a better understanding of air–water CO₂ exchanges in coastal ecology under climate change scenarios.