Estimation of Surface CO2 Flux Using a Carbon Tracking System Based on Ensemble Kalman Filter

Abstract:

Estimation of the surface CO₂ flux is crucial to understand the mechanism of surface carbon source and sink. In Asia, there are large uptake regions such as forests in boreal and temperate regions. In this study, to diagnose the surface CO₂ flux in the globe and Asia, CO₂ observations were assimilated in the CarbonTracker developed by NOAA. The CarbonTracker is an inverse modeling system that estimates the surface CO₂ flux using an ensemble Kalman filter with atmospheric CO₂ measurements as a constraint. First, the capability of CarbonTracker as an analysis tool for estimating surface CO₂ flux in Asia was investigated. Different from the CarbonTracker developed by NOAA, a nesting domain centered on Asia was used with additional observations in Asia. In addition, a diagnostic tool to calculate the effect of individual CO₂ observations on estimating the surface CO₂ flux was developed using the analysis sensitivity to observation and information content in the CarbonTracker framework.

The results showed that CarbonTracker works appropriately for estimating surface CO₂ flux. The nesting domain centered in Asia produces a detailed estimate of the surface CO₂ fluxes and exhibited better agreement with the CO₂ observations in Asia. Additional observations provide beneficial impact on the estimated surface CO₂ flux in Asia and Europe. The analysis sensitivity showed seasonal variations with greater sensitivities in summer and lower sensitivities in winter. Strong correlation exists between the information content and the optimized surface CO₂ flux.