Toward Low-Latency Estimation of Atmospheric CO2 Growth Rates Using Satellite Observations: Evaluating Sampling Errors of Satellite and In Situ Observing Approaches

The atmospheric CO2 growth rate is a fundamental measure of climate forcing. NOAA's growth rate estimates, derived from in situ observations at the marine boundary layer (MBL), serve as the benchmark in policy and science. However, NOAA's MBL-based method encounters challenges in accurately estimating the whole-atmosphere CO2 growth rate at sub-annual scales. Here we introduce the Growth Rate from Satellite Observations (GRESO) method as a complementary approach to estimate the whole-atmosphere CO2 growth rate utilizing satellite data. Satellite CO2 observations offer extensive atmospheric coverage that extends the capability of the current NOAA benchmark. We assess the sampling errors of the GRESO and NOAA methods using 10 atmospheric transport model simulations. The simulations generate synthetic OCO-2 satellite and NOAA MBL data for calculating CO2 growth rates, which are compared against the global sum of carbon fluxes used as model inputs. We find good performance for the NOAA method (R = 0.93, RMSE = 0.12 ppm year(-1) or 0.25 PgC year(-1)). GRESO demonstrates lower sampling errors (R = 1.00; RMSE = 0.04 ppm year(-1) or 0.09 PgC year(-1)). Additionally, GRESO shows better performance at monthly scales than the NOAA method (R = 0.76 vs. 0.47, respectively). Due to CO2's atmospheric longevity, the NOAA method accurately captures growth rates over 5-year intervals. GRESO's robustness across partial coverage configurations (ocean or land data) shows that satellites can be promising tools for low-latency CO2 growth rate information, provided the systematic biases are minimized using in situ observations. Along with accurate and calibrated NOAA in situ data, satellite-derived growth rates can provide information about the global carbon cycle at sub-annual scales. Plain Language Summary Accurately estimating the rate of carbon dioxide increase in the atmosphere is crucial for measuring and understanding climate change. The growth rate estimates from NOAA, based on ocean surface air observations, are the standard in science and policy. However, NOAA does not provide growth rate estimates at fine temporal scales, and the atmospheric sampling error of their annual estimates is unknown. We present a new method called the Growth Rate from Satellite Observations (GRESO). Satellites sample more of the atmosphere and can thus enhance NOAA growth rate estimates. We evaluate the atmospheric sampling errors of the NOAA and satellite-based methods with 10 atmospheric transport models. We find that satellite estimates have lower sampling errors and can provide an advantage for fine temporal scale growth rate estimation. On annual and 5-year scales, NOAA estimates are reliable due to the persistence of carbon dioxide in the atmosphere. Together, the NOAA and satellite-based growth rate methods can better inform us about the global carbon cycle.