Abstract
Green house gas (GHG) satellites such as Orbiting Carbon Observatory 2 (OCO2), Sentinel 5P (TROPOMI), GHGSat offer global coverage of measuring column averaged carbon-di-oxide (XCO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> ) and methane (XCH4). Though GHG satellites are a scalable method of measuring GHG emissions, they are limited by coarse spatial and/or temporal resolutions and missing data. Based on the statistical interpolation technique, fixed rank kriging (FRK), in this work, we have developed a novel nested kriging approach, N-FRK to address the above challenges of GHG satellite data, in particular of OCO2 satellite. Compared to the spatiotemporal resolution of 1.2×2.2km2 and 16 days of OCO2 satellite, we have increased the temporal resolution to 1 day and spatial resolution to 1.11×1.11km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> using N-FRK. The daily spatial maps at 111, 11.1, 1.11 km resolutions have been generated using FRK and N-FRK techniques and validated across 13 or subset of the 13 sensor sites of total carbon column observing network (TCCON) for the year 2019. As part of validation, we present the R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , root mean square error (RMSE), and bias metrics and we see good agreement between the estimated data and sensor data.
Published Version
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