Proceedings of the 11th International Carbon Dioxide Conference

As the world's third largest CO₂ emitter, accurately estimating India’s terrestrial carbon fluxes to the atmosphere is critical to the global carbon budget estimates. Moreover, India is part of the tropical terrestrial biospheric system, one of the highly variable and uncertain components of the global carbon cycle. A high-resolution estimation of its carbon sources and sinks is necessary to implement the country’s climate change action plans and mitigation strategy effectively. Regional inverse modelling studies that utilise atmospheric CO₂ observations can significantly improve our understanding of the underlying processes in the exchange of carbon between the land and atmosphere over the Indian region. Currently, the inverse estimation of CO₂ fluxes from India is constrained by the availability of adequate continuous atmospheric CO₂ observations and modelling capabilities. Most of the currently available in-situ observations are influenced by local flux and transport variations, resulting in strong CO₂ variability. A transport modelling system capable of simulating fine-scale transport and flux variabilities is necessary to represent these observed variabilities in an inverse modelling system. We have investigated the capability of a high-resolution Lagrangian transport modelling system, Weather Research and Forecast - Stochastic Time-Inverted Lagrangian Transport (WRF-STILT), to represent these observed CO₂ variabilities in an inverse modelling system. Our WRF-STILT model reasonably represents these variabilities better than the coarse resolution transport models, which are used for global carbon flux optimisations. Further, we have explored the potential of using these observations in a regional inverse modelling system to optimise terrestrial biospheric fluxes over the Indian region. The evaluation of our transport modelling system and the initial results of the inverse estimations will be discussed in detail during the presentation.