Towards improved estimation of the atmosphere - terrestrial biosphere CO2 exchange over India using a diagnostic satellite based model

Several countries across the world have initiated considerable efforts to curb Greenhouse Gas emissions to limit the increase in global temperature to 2°C. However, planning of proper emission reduction policies and their successful implementation require accurate carbon budgeting. The objective of this study is to accurately quantify various sources and sinks of carbon dioxide over Indian domain using inverse modelling techniques. 

In order to better represent and quantify the atmosphere-biosphere CO₂ exchange fluxes and ecosystem behaviour in the inverse modeling framework, the Vegetation Photosynthesis and Respiration Model (VPRM) is employed over Indian region. VPRM is a satellite based assimilation scheme with very simple model structure, so as to facilitate successive optimization of parameters in the inverse modelling framework. As an initial step, we evaluated the VPRM model with eddy covariance observations over India from two different vegetation types (Betul; Deciduous forest and Sundarbans; Evergreen forest) for the year 2017. The comparison reveals that the model needs further refinement in parametrization even though the VPRM showed better performance than other existing terrestrial biosphere models (e.g ., TRENDY and Carbon Tracker (CT)) over Indian domain. Among the VPRM products (Net ecosystem exchange (NEE), Gross Primary Productivity (GPP), and Ecosystem Respiration (Re)), the ecosystem respiration shows large deviations from observation. The analysis, based on the soil moisture (SM) data from IITM monsoon mission project shows that the SM plays a significant role, which is currently missing in the VPRM respiration calculations. Further, the study attempts to utilize Solar induced Fluorescence (SIF) as a proxy to estimate GPP and to be included in VPRM for the better representation of biospheric fluxes over India. Preliminary results will be presented and discussed.