Understanding global land photosynthesis with the global, 0.05-degree solar-induced chlorophyll fluorescence derived from OCO-2 (GOSIF)

Abstract:

Solar-induced chlorophyll fluorescence (SIF) brings major advancements in measuring
terrestrial photosynthesis. Several recent studies have evaluated the potential of SIF retrievals
from the Orbiting Carbon Observatory-2 (OCO-2) in estimating gross primary productivity (GPP) based on GPP data from eddy covariance (EC) flux towers. However, the spatially and temporally sparse nature of OCO-2 data makes it challenging to use these data for many applications from the ecosystem to the global scale. Here, we developed a new global ‘OCO-2’ SIF data set (GOSIF) with high spatial and temporal resolutions (i.e., 0.05◦, 8-day) over the period 2000–2018 based on a data-driven approach. The predictive SIF model was developed based on discrete OCO-2 SIF
soundings, remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological reanalysis data. Our model performed well in estimating SIF (R² = 0.79, root mean squared error (RMSE) = 0.07 W m^-2 µm^-1 sr^-1). The resulting GOSIF product
has reasonable seasonal cycles, and captures the similar seasonality as both the coarse-resolution
OCO-2 SIF (1^°), directly aggregated from the discrete OCO-2 soundings, and tower-based GPP.

We then used GOSIF along with the enhanced vegetation index (EVI) to investigate how climatic factors drive the interannual variability (IAV) of global ecosystem productivity. We found that both productivity measures showed the dominant role of soil moisture in driving the IAV of global ecosystem productivity, particularly in arid and semi-arid areas. SIF was more sensitive to climate variability than was EVI. SIF was positively correlated with solar radiation in the humid regions, while no significant correlations were found between EVI and solar radiation. The stronger correlation of SIF with climate factors was also observed at the ecosystem level based on a number of EC flux sites, indicating that SIF had a higher ability in capturing the variations of GPP than did EVI.

We also used the GOSIF and linear relationships between SIF and GPP to map GPP globally at 0.05° and 8-day resolutions. The ensemble mean GPP from eight SIF-GPP relationships showed reasonable spatial and seasonal variations across the globe, and was generally highly correlated with flux tower GPP for 91 EC flux sites across the globe (R² = 0.74, RMSE = 1.92 g C m^-2 d^-1). The annual GPP based on the ensemble mean GPP is 135.5 ± 8.8 Pg C yr^-1, which is between the median estimate of non-process based methods and the median estimate of process-based models. With the availability of high-quality, gridded SIF observations from space (e.g., TROPOMI, FLEX), our novel approach does not rely on any other input data (e.g., climate data, soil properties) and therefore can map GPP solely based on satellite SIF observations and potentially lead to more accurate GPP estimates at regional to global scales.

These results demonstrated that our GOSIF product is effective for assessing terrestrial photosynthesis and ecosystem responses to climate change, and will be valuable for future ecosystem studies, such as detecting vegetation phenology, monitoring the impact of drought on ecosystem productivity, and benchmarking terrestrial biosphere and Earth system model.