Validation and assessment of satellite-based columnar CO₂ and CH₄ mixing ratios from GOSAT and OCO-2 satellites over India

<p>Satellite observations of column-averaged carbon dioxide (XCO<span class="inline-formula">₂</span>) and methane (XCH<span class="inline-formula">₄</span>) mixing ratios provide essential data for monitoring greenhouse gas (GHG) emissions. However, the accuracy of emission estimates depends on the precision and bias of satellite retrievals, which require validation against ground-based reference measurements. This study presents a systematic validation of XCO<span class="inline-formula">₂</span> and XCH<span class="inline-formula">₄</span> data from GOSAT (Greenhouse gases Observing SATellite) and OCO-2 (Oribiting Carbon Observatory-2) satellites over South India using ground-based Fourier transform spectrometer (FTS) observations at Gadanki (13.5° N, 79.2° E) collected from October 2015 to July 2016. Satellite products from National Institute for Environmental Studies, Japan (NIES), NASA's Atmospheric CO<span class="inline-formula">₂</span> Observations from Space (ACOS) project, USA (ACOS), and the University of Leicester, UK (UoL) were evaluated using a three-step spatial-temporal pairing method. Results show that the UoL's proxy XCH<span class="inline-formula">₄</span> product meets the European Space Agency's Climate Change Initiative (ESA CCI) bias requirement (<span class="inline-formula"><i>&lt;</i>10</span> ppb) across all spatial windows, while the NIES XCH<span class="inline-formula">₄</span> product meets the requirement only for intermediate spatial scales. For XCO<span class="inline-formula">₂</span>, NASA ACOS and OCO-2 products meet the CCI bias requirement (<span class="inline-formula"><i>&lt;</i>0.5</span> ppm), while NIES XCO<span class="inline-formula">₂</span> exceeds this threshold. All products satisfy the precision requirement (<span class="inline-formula"><i>&lt;</i>8</span> ppm for XCO<span class="inline-formula">₂</span> and <span class="inline-formula"><i>&lt;</i>34</span> ppb for XCH<span class="inline-formula">₄</span>) with substantial margins. In addition, FLEXPART model simulations using regional emission inventories revealed that agricultural activities dominate seasonal methane enhancements, contributing approximately 55 %, followed by waste and wetland emissions. The model captured seasonal trends but underestimated the amplitude of observed variations, highlighting the influence of changing background methane levels. These findings demonstrate the suitability of recent satellite products for regional GHG monitoring and emphasise the need for expanding ground-based FTS networks across South Asia to support improved emission assessments.</p>