Inversions with surface stations
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1. Prepare the data to assimilate
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Constraints are put into a CIF monitor file for a set of core stations: 
     
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         .. literalinclude:: /python_examples/make_monitor_core_stations.py
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1. Automatically make one job per year
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One job per year is run, based on the following configuration file yml.sed:
     
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         .. literalinclude:: yaml-examples/config_chimere_inv_1Y.yaml.sed
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To fill-in a .sed file, you may use :bash:`cat` to replace the variables, as illustrated in the script for a job in 2015:


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         .. literalinclude:: /python_examples/job_1Y
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3. Post-processing
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Post-processing of the results include:
     
a. Maps of fluxes and increments
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          .. literalinclude:: /python_examples/maps_fluxes_controlvect.py
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b. Time series of mixing ratios and maps of statistical indicators at the stations
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Time series of mixing ratios at the stations make it easy to compare the observation, the prior and the analysis (obtained with the posterior emissions).

The maps of statistical indicators at the stations show the ratios of the posterior to the prior values of the bias, RMS, correlation for example.
        
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          .. literalinclude:: /python_examples/ts_monit_concs.py
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c. Yearly emission budgets for various regions
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Examples here of regions are EU27+UK, EU27 countries, groups of countries:
        
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          .. literalinclude:: /python_examples/sum_per_country_per_year.py
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        .. Example of region masks built from shape files:
        
        
        
d. Time series of emissions for various regions
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Examples here of regions are EU27+UK, EU27 countries, groups of countries:

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          .. literalinclude:: /python_examples/ts_fluxes_controlvect.py
              :language: python