2:30 PM - 2:45 PM
[ACG32-04] Carbon flux estimation using NICAM-TM 4D-Var and GOSAT data towards GOSAT-2 Level 4 product
Keywords:Carbon budget, Flux estimations of greenhouse gases, Atmospheric inverse model, Top-down approach, Satellite remote sensing
We are currently developing an inversion system for operational use to produce GOSAT-2 L4 products. The Non-hydrostatic ICosahedral Atmospheric Model (NICAM)-based Transport Model (NICAM-TM; Niwa et al., 2011) is used for simulating atmospheric CO2 and CH4 concentrations, and an inversion system based on the four-dimensional variational (4D-Var) method with NICAM-TM (NICAM-TM 4D-Var; Niwa et al., 2017a,b) is adopted to estimate global surface CO2 and CH4 fluxes. In this presentation, we will present test results of CO2 flux estimation with NICAM-TM 4D-Var using GOSAT data (not GOSAT-2 data), ground-based data, prior fluxes, and their error covariances. NICAM-TM is operated with a horizontal resolution of glevel-5 (an average grid resolution of 223 km) and 40 vertical layers, and its meteorological fields are nudged with JRA-55 data to simulate real atmospheric transport. NICAM-TM 4D-Var is run with stored meteorological data, which successfully reduces computational cost. CO2 surface fluxes have been estimated at every 223 km grid resolution and at monthly time resolution. Preliminary test results with single-year GOSAT data showed that flux differences between the prior fluxes and estimated fluxes from the GOSAT data inversion appear over a broad area of land regions, even over Siberia and South America where ground sites are sparse, while the ocean regions showed relatively fewer flux changes after the inversion. Our ongoing work includes inversions with multi-year data, the inclusion of other data, and tuning model parameters. The details will be presented at the meeting.
Acknowledgments. The model simulations are performed with the NIES supercomputer system and the Research Computation Facility for GOSAT-2 (RCF2). This research is partly supported by the Environment Research and Technology Development Fund (2-1701) of the Environmental Restoration and Conservation Agency of Japan.
Niwa et al. (2011), Journal of the Meteorological Society of Japan. Ser. II, 89(3), 255–268.
Niwa et al. (2017a), Geoscientific Model Development, 10(3), 1157–1174.
Niwa et al. (2017b), Geoscientific Model Development, 10(6), 2201–2219.