Abstract. Observations from the OCO-2 satellite, launched in July 2014, have been used to estimate CO2 fluxes in many regions of the globe and provide new insight on the global carbon cycle. A challenge now is to not only estimate fluxes using satellite observations but also to understand how these fluxes are connected to variations in environmental conditions. In this study, we specifically evaluate the capabilities and limitations of utilizing current OCO-2 observations to infer connections between CO2 fluxes and underlying environmental variables. To do so, we adapt geostatistical inverse modeling to satellite-based applications and evaluate a case study for year 2016 using OCO-2. One unique aspect of the geostatistical approach is that we can use estimates of environmental and meteorological variables to help estimate CO2 fluxes in place of a traditional prior flux model. We are able to quantify the relationships between CO2 fluxes and a few environmental variables across global biomes; we find that a simple combination of air temperature, daily precipitation, and photosynthetically active radiation (PAR) can describe almost 90 % of the variability in CO2 fluxes as seen through OCO-2 observations. PAR is an adept predictor of fluxes across mid-to-high latitudes, whereas a combined set of air temperature and precipitation shows strong explanatory power across tropical biomes. However, we are unable to quantify relationships with additional environmental variables because many variables are correlated or colinear when passed through an atmospheric model and averaged across a total atmospheric column. Overall, we estimate a global net biospheric flux of −1.73 ± 0.53 GtC in year 2016, in close agreement with recent inverse modeling studies using OCO-2 retrievals as observational constraints.
Linking global terrestrial CO<sub>2</sub> fluxes and environmental drivers using OCO-2 and a geostatistical inverse model