Towards high resolution atmospheric data-based greenhouse gas budgets by utilizing advances in supercomputing (GHGSUPER)
Description of the granted funding
Developments in HPC open new research possibilities and bring policy-relevant information concerning use of atmospheric data in greenhouse gas budgeting in support of national inventories. The project will employ new HPC resources for utilizing satellite greenhouse gas observations in atmospheric inverse modelling of GHG emissions and removals, and solutions for enhancing the performance of the models in spatial and temporal domains as well as producing computationally more effective model systems. Increasing quantities of satellite data need to be assimilated in an efficient way in GHG models while retaining the essential information content of the data. The project increases the readiness level for future high intensity satellite observations by developing methods to assimilate high resolution data into inverse models. New HPC resources will be employed for estimating CO2 and CH4 fluxes and their uncertainties by atmospheric inverse modelling in nationally relevant scales.
Show moreStarting year
2022
End year
2024
Granted funding
Funder
Research Council of Finland
Funding instrument
Targeted Academy projects
Other information
Funding decision number
351311
Fields of science
Geosciences
Research fields
Meteorologia ja ilmakehätieteet, ilmastotutkimus
Identified topics
climate policy, societal effects