Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research

Atmosphere

Baozhang Chen¹  Yawen Kong¹  Simon Measho¹ 

[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

关键词: OCO-2;    GOSAT;    TCCON;    carbon dioxide;    CarbonTracker;    joint dataset;   

DOI  :  10.3390/atmos10070354

来源: DOAJ

【 摘 要 】

The global carbon cycle research requires precise and sufficient observations of the column-averaged dry-air mole fraction of CO ${}_2$ (XCO ${}_2$ ) in addition to conventional surface mole fraction observations. In addition, assessing the consistency of multi-satellite data are crucial for joint utilization to better infer information about CO ${}_2$ sources and sinks. In this work, we evaluate the consistency of long-term XCO ${}_2$ retrievals from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2) in comparison with Total Carbon Column Observing Network (TCCON) and the 3D model of CO ${}_2$ mole fractions data from CarbonTracker 2017 (CT2017). We create a consistent joint dataset and compare it with the long-term model data to assess their abilities to characterize the carbon cycle climate. The results show that, although slight increasing differences are found between the GOSAT and TCCON XCO ${}_2$ in the northern temperate latitudes, the GOSAT and OCO-2 XCO ${}_2$ retrievals agree well in general, with a mean bias ± standard deviation of differences of 0.21 ± 1.3 ppm. The differences are almost within ±2 ppm and are independent of time, indicating that they are well calibrated. The differences between OCO-2 and CT2017 XCO ${}_2$ are much larger than those between GOSAT and CT XCO ${}_2$ , which can be attributed to the significantly different spatial representatives of OCO-2 and the CT-transport model 5 (TM5). The time series of the combined OCO-2/GOSAT dataset and the modeled XCO ${}_2$ agree well, and both can characterize significantly increasing atmospheric CO ${}_2$ under the impact of a large El Niño during 2015 and 2016. The trend calculated from the dataset using the seasonal Kendall (S-K) method indicates that atmospheric CO ${}_2$ is increasing by 2−2.6 ppm per year.

【 授权许可】

Unknown