Increasing the Efficiency of GOES-Chem Adjoint Model Runs Using a Python Ensemble Manager

Methane is a powerful greenhouse gas with uncertainty regarding the strengths and trends of its sources. These uncertainties make it difficult for researchers to determine the exact reasons behind methane's variable annual growth rate, and the stabilization of the atmospheric concentration over the past three decades. It is possible to estimate individual methane source emission values using satellite measurements and inverse modeling techniques, although data quality limits how well individual sources are resolved. GEOS-Chem Adjoint is the combination of an atmospheric chemical transport model (GEOS-Chem) with an adjoint model, and can be used to test the emissions source resolving power for actual and theoretical satellite retrievals of methane. In order to test the resolving power, the mathematical calculations require a large number of individual simulations to be run, but currently in the standard version of GEOS-Chem Adjoint each simulation needs to be manually set up and started. To overcome the need for manual setup and executions of model runs, a manager script was created using the Python programming language. The ensemble manager script automates the process of creating multiple unique simulations, and can run variable numbers of simulations to use resources on many different types of clustered computer systems. The python ensemble manager marks the first step in a larger project of testing the current accuracy of methane surface emission estimates, and helping to develop ways to help further constrain them.