Understanding long-term carbon dioxide (CO2) variability and its link with ENSO and climate parameters over India using satellite retrievals

India is primarily concerned with comprehending regional carbon source-sink response in tandem with changes in atmospheric carbon dioxide (CO₂) concentrations or human-caused anthropogenic emissions. Atmosphere CO₂ is the most significant greenhouse gas contributing to climate change and global warming. To develop a countrywide mitigation policy, it is therefore critical to identify underlying source-sink locations and their mechanisms at various temporal scales and regional levels. To better understand the variability of CO₂ and its relationship with the climate variables requires long-term observations. Recent advancements in high-resolution satellite measurements provide a viable opportunity to examine CO₂ variability at a regional level. In this work, we presented the long-term variations and growth rates of the Greenhouse Gas Observing Satellite (GOSAT) and Orbiting Carbon Observatory-2 (OCO-2) satellite retrieved column-averaged dry-air mole fraction of CO₂ (XCO₂ ) and the relationship of XCO₂ growth rate with ENSO and climate parameters (temperature, precipitation, soil moisture, and NDVI) over India for the period 2010 to 2021. Results revealed an increase of 2.54 (2.43) ppm/yr of XCO₂ in GOSAT (OCO-2) retrievals during overlapping measurement period (2015-2021). In addition, a wavelet analysis shows an increase in XCO₂ every year for GOSAT; however, OCO-2 decreases and increases in XCO₂ every 5-6 months. This is attributable to high resolutions measurements of OCO-2 favouring better capture of source (high XCO₂)-sink (low XCO₂) signal than GOSAT. The Principal Component Analysis (PCA) analysis on XCO₂ anomalies showed EOF-1 contributed mainly by the south and southeast of India. Further analysis demonstrated that the trend and seasonal cycle of XCO₂ regulates the variability. The XCO₂ growth rates strongly correlate with ENSO and NDVI (clear during major ENSO events), whereas precipitation and temperature show a weak correlation. Further, lag correlation analysis reveals that ENSO and climate parameters precede the GOSAT XCO₂ growth rates, with soil moisture, NDVI, and ENSO having a good correlation with 8,4 and 3 months of leads, respectively.