Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network)

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 19; p. 3868
• Main Authors: Labzovskii, Lev D., Kenea, Samuel Takele, Lindqvist, Hannakaisa, Kim, Jinwon, Li, Shanlan, Byun, Young-Hwa, Goo, Tae-Young
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2021
• Subjects: Algorithms; Annual variations; Carbon; Carbon cycle; Carbon dioxide; Climate change; CO2; Data sampling; El Nino; ENSO; Estimates; Footprints; FTIR; Global warming; Growth rate; Mathematical analysis; Remote sensing; Robustness; Sampling; Satellites; Seasonal variations; Uncertainty; Weather
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13193868

The CO2 growth rate is one of the key geophysical quantities reflecting the dynamics of climate change as atmospheric CO2 growth is the primary driver of global warming. As recent studies have shown that TCCON (Total Carbon Column Observing Network) measurement footprints embrace quasi-global coverage, we examined the sensitivity of TCCON to the global CO2 growth. To this end, we used the aggregated TCCON observations (2006-2019) to retrieve Annual Growth Rate of CO2 (AGR) at global scales. The global AGR estimates from TCCON (AGRTCCON) are robust and independent, from (a) the station-wise seasonality, from (b) the differences in time series across the TCCON stations, and from (c) the type of TCCON stations used in the calculation (“background” or “contaminated” by neighboring CO2 sources). The AGRTCCON potential error, due to the irregular data sampling is relatively low (2.4–17.9%). In 2006–2019, global AGRTCCON ranged from the minimum of 1.59 ± 2.27 ppm (2009) to the maximum of 3.27 ± 0.82 ppm (2016), whereas the uncertainties express sub-annual variability and the data gap effects. The global AGRTCCON magnitude is similar to the reference AGR from satellite data (AGRSAT = 1.57–2.94 ppm) and the surface-based estimates of Global Carbon Budget (AGRGCB = 1.57–2.85). The highest global CO2 growth rate (2015/2016), caused by the record El Niño, was nearly perfectly reproduced by the TCCON (AGRTCCON = 3.27 ± 0.82 ppm vs. AGRSAT = 3.23 ± 0.50 ppm). The overall agreement between global AGRTCCON with the AGR references was yet weakened (r = 0.37 for TCCON vs. SAT; r = 0.50 for TCCON vs. GCB) due to two years (2008, 2015). We identified the drivers of this disagreement; in 2008, when only few stations were available worldwide, the AGRTCCON uncertainties were excessively high (AGRTCCON = 2.64 ppm with 3.92 ppm or 148% uncertainty). Moreover, in 2008 and 2015, the ENSO-driven bias between global AGRTCCON and the AGR references were detected. TCCON-to-reference agreement is dramatically increased if the years with ENSO-related biases (2008, 2015) are forfeited (r = 0.67 for TCCON vs. SAT, r = 0.82 for TCCON vs. GCB). To conclude, this is the first study that showed promising ability of aggregated TCCON signal to capture global CO2 growth. As the TCCON coverage is expanding, and new versions of TCCON data are being published, multiple data sampling strategies, dynamically changing TCCON global measurement footprint, and the irregular sensitivity of AGRTCCON to strong ENSO events; all should be analyzed to transform the current efforts into a first operational algorithm for retrieving global CO2 growth from TCCON data.