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.