Global Gross Primary Productivity Estimation Using Passive Microwave Observations from China's Fengyun-3d Satellite

Abstract

In this study, we present the development and validation of a microwave-based global Gross Primary Productivity (GPP) estimation method, EDVI-GPP, using the microwave Emissivity Difference Vegetation Index (EDVI) retrieved from the China’s Fengyun-3D satellite for the period 2020-2022. Given the common issue of cloud cover contamination in optical remote sensing, microwave remote sensing is explored as a viable alternative due to its ability to penetrate clouds. The global EDVI-GPP model incorporates the effect of diffuse radiation from clouds on GPP and utilizes the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm to tune its key parameters of light use efficiency and the seasonality of vegetation water content index. In situ GPP measurements from 169 eddy covariance flux sites covering ten major ecosystem types around the globe are used to calibrate and validate the model performance. EDVI-GPP provides daily temporal resolution GPP estimations applicable under both clear and cloudy skies. At 8-day temporal resolution, the coefficients of determination between EDVI-GPP and in situ GPP measurements (R2=0.50) during 2020-2022 were comparable to MODIS-GPP (R2=0.46), PML-GPP (R2=0.55), GOSIF-GPP (R2=0.59), and FLUXCOM-GPP (R2=0.64), with a reduced bias of -0.27gC/m2/day. On a global scale, the annual averaged EDVI-GPP exhibited high spatial consistency (R=0.81~0.84) with the compared GPP products. EDVI-GPP also showed high temporal correlation with the compared GPP products for most vegetation types. The EDVI-GPP model quantified the mean global GPP from 2020 to 2022 as 140.83 ± 0.22 Pg C yr-1, which was in close agreement with other published estimates. By using the three-cornered hat (TCH) method to evaluate GPP uncertainty, we found that the EDVI-GPP product exhibited a large uncertainty in agricultural areas. This research marks a pioneering effort to incorporate microwave-derived variables into daily GPP estimation on a global scale, providing a less cloud-affected and reliable measurement.

Keywords: Gross Primary Productivity (GPP), Light use efficiency (LUE), Microwave Emissivity Difference Vegetation Index (EDVI), Fengyun-3D