Skip to main content
Ctrl+K
Community Inversion Framework - Home

Getting Started

  • Overview
  • How to install
  • Using the CIF in Docker
    • Gitlab CI file .gitlab-ci.yml

References

  • Publications
  • Main CIF projects
    • The Global Carbon Project - CH4
      • Downloading and preprocessing EDGAR dataset
      • Grouping GCP emission files by category
      • Generating inputs for LMDZ from GCP standard files
    • CAMS55 - global inversion-optimised greenhouse gas fluxes and concentrations
    • SMART-CH4 - Satellite-based methane quantification
      • Regional inversions of TROPOMI CH4 in South America
      • Global inversions of CH4 and isotopic signatures
    • Inversions in the project VERIFY
      • Methane net total emissions in Europe (WP4)
        • Prepare emissions for WP4 protocol
        • Inversions with surface stations
        • Inversions with TROPOMI data
      • Nitrous oxide net total emissions in Europe (WP4)

User Guide

  • Documentation
    • General options
    • Yaml configuration
    • General input and output structures in the CIF
      • Observations
      • Control vectors
      • Observation vectors
      • Other input data
      • Files for checks
    • Pandas and xarray in pyCIF
    • Paths and variables in Yaml
    • Plugins in pyCIF
      • Plugins: what are they?
        • classes package
      • Requirements and dependencies in pyCIF
        • Available plugins
      • Chemistries chemistry
        • CHIMERE/gasJtab CHIMERE/gasJtab
        • ICON-ART/std ICON-ART/std
        • LMDZ/SACS LMDZ/SACS
        • TM5/SINK-TIPP TM5/SINK-TIPP
      • Controlvects controlvect
        • Standard CIF control vector standard/std
      • Datastreams datastream
        • Backgrounds datastream
        • Fields datastream
        • Fluxes datastream
        • Meteos datastream
      • Datavects datavect
        • Standard CIF data vector standard/std
      • Domains domain
        • CHIMERE HCOORD/VCOORD domain CHIMERE/std
        • Dynamico grid dynamico/std
        • FLEXPART/std FLEXPART/std
        • Gridded NetCDF domain gridded_netcdf/std
        • ICON-ART/std ICON-ART/std
        • LMDZ dynamico domain LMDZ/dynamico
        • LMDZ regular lat-lon domain LMDZ/regular
        • LMDz grid LMDZ/std
        • Unstructured grid NetCDF domain gridded_netcdf/unstructured
        • dummy/std dummy/std
        • wrfchem/std wrfchem/std
      • Measurements measurements
        • Concatenation of observations from parsers standard/std
        • Random generation of observations random/param
      • Minimizers minimizer
        • M1QN3/std M1QN3/std
        • congrad/std congrad/std
        • scipy/std scipy/std
      • Models model
        • CHIMERE/std CHIMERE/std
        • CHIMERE with OpenACC annotations CHIMERE/acc
        • ICOsahedral Nonhydrostatic weather- and climate model with Aerosols and Reactive Trace gases ICON-ART/std
        • LMDZ/std LMDZ/std
        • LMDZ with regular and dynamico grids LMDZ/reg-ico
        • LMDz with OpenACC annotations LMDZ/acc
        • Lagrangian/std Lagrangian/std
        • SatWetCH4 v.1 Juliette Bernard et al., 2024 satwetch4/std
        • TM5/std TM5/std
        • Template for model implementation template/std
        • dummy/std dummy/std
        • wrfchem/std wrfchem/std
      • Modes mode
        • 4DVAR variational inversions 4dvar/std
        • Analytical inversions analytic/std
        • Ensemble Square-Root Filter EnSRF/std
        • Footprints or backward mode footprint/std
        • Forward run forward/std
        • Response functions response-functions/std
        • Test of the adjoint adj-tl_test/std
        • post-proc/std post-proc/std
      • Obsoperators obsoperator
        • FLEXINVERT/std FLEXINVERT/std
        • Main CIF observation operator standard/std
      • Obsparsers obsparser
        • CO2M pseudo_data CO2M/pseudo_data
        • Integrated Carbon Observing System (ICOS) data ICOS/std
        • NOAA-ESRL Observation Package (ObsPack) Data Products obspack/std
        • TROPOMI XCH4 retrievals – Official RPRO product TROPOMI/CH4-RPRO
        • TROPOMI XCH4 retrievals – Official product TROPOMI/CH4-official
        • TROPOMI XCH4 retrievals from SRON TROPOMI/CH4-SRON
        • TROPOMI XCH4 retrievals from the University of Bremen TROPOMI/CH4-WFMD
        • TROPOMI-GOSAT XCH4 retrievals from Balasus TROPOMI/CH4-BLENDED
        • Template plugin for observation parsers template/std
        • VERIFY/std VERIFY/std
        • WDCGG/std WDCGG/std
      • Obsvects obsvect
        • standard/std standard/std
      • Platforms platform
        • Bologna’s ECMWF cluster ECMWF/ecs
        • CSC-Puhti’s FMI cluster FMI/Puhti
        • CSCS - Swiss National Supercomputing Centre EMPA/daint
        • Centre de Calcul Recherche et Technologie (AMD/rome) TGCC-CCRT/AMD
        • Centre de Calcul Recherche et Technologie (skylake) TGCC-CCRT/std
        • Centre de Calcul Recherche et Technologie with NVIDIA environnement TGCC-CCRT/nvidia
        • Docker container for pycif docker/cif
        • ESPRI Spirit/SpiritX cluster with NVIDIA environment ESPRI/spirit-nvidia
        • LAERO’s cluster LAERO/nuwa
        • LSCE’s cluster LSCE/obelix
        • LSCE’s cluster with NVIDIA environnement LSCE/obelix-nvidia
      • Simulators simulator
        • dummy_txt/std dummy_txt/std
        • gausscost/std gausscost/std
        • gausscost/FLEXPART gausscost/FLEXPART
      • Transforms transform
        • Basic transform
        • Complex transform
        • System transform
    • Documentation on the various models supported by the CIF
      • LMDZ-SACS documentation
        • Overview: What is LMDZ-SACS?
        • Use LMDS-SACS with CIF
        • Compilation
        • Input files
        • Output files
      • CHIMERE documentation
        • General information
        • Main departures from the standard distribution
        • Installation
        • Compiling
        • CHIMERE documentation
    • Configuration
      • Yaml configuration
      • File name formats and dates
      • Control vectors
        • Standard pyCIF control vector
      • Measuremens
      • Metos
        • Gaussian Toy Model
      • Minimizers
        • M1QN3
        • CONGRAD
      • Models
        • Gaussian Toy Model
        • CHIMERE
        • LMDZ-Dispersion-SACS
        • FLEXPART
      • Modes
        • Forward simulations
        • Test of the adjoint and of the linear-tangent
        • Variational inversions
        • Footprints
      • Observation operators
        • Standard pyCIF observation operator
      • Observation vectors
        • Standard pyCIF observation vector
      • Simulators
        • Gaussian cost function
  • Tutorials for users
    • Tutorials dedicated to CHIMERE
      • First forward simulation with CHIMERE and ready-made input files
        • 1. Prepare the executable
        • 2. Locate the input files provided directly for CHIMERE
        • 3. Elaborate the yaml for the CIF, using ready-made files
        • 4. Run the system
        • 5. Check what has been done in the workdir:
      • Combining various ready-made inputs for CHIMERE
        • Preprocessing plugins
      • Prepare inputs and run a forward simulation with CHIMERE
        • 1. Preparing inputs from scratch or raw data
        • 2. Elaborate the yaml for the CIF
        • 3. Prepare the executable:
        • 4. Run the system
        • 5. Check what has been done in the workdir:
        • 6. Examples factorisation flux
      • Making a new domain
      • Generating meteo from ECMWF
      • Generating emission files from raw data
      • Generating boundary condition files from raw data
    • Tutorials dedicated to LMDZ
      • First forward simulation with LMDz-SACS
    • How to run a first forward simulation
      • First forward simulation with the toy Gaussian Model
      • First forward simulation with LMDz-SACS
      • First forward simulation with CHIMERE and ready-made input files
        • 1. Prepare the executable
        • 2. Locate the input files provided directly for CHIMERE
        • 3. Elaborate the yaml for the CIF, using ready-made files
        • 4. Run the system
        • 5. Check what has been done in the workdir:
      • Prepare inputs and run a forward simulation with CHIMERE
        • 1. Preparing inputs from scratch or raw data
        • 2. Elaborate the yaml for the CIF
        • 3. Prepare the executable:
        • 4. Run the system
        • 5. Check what has been done in the workdir:
        • 6. Examples factorisation flux
      • Observations
    • How to run a first comparison between a simulation and observations
      • Observation vector (obsvect)
      • Comparison between a forward simulation with surface observations
      • Comparison between a forward simulation and satellite data
    • How to run a first inversion
      • First inversion with the toy-gaussian model
      • First inversion with CHIMERE
    • How to run a simulation with elaborated inputs
      • Combining various ready-made inputs for CHIMERE
        • Preprocessing plugins
      • Prepare inputs and run a forward simulation with CHIMERE
        • 1. Preparing inputs from scratch or raw data
        • 2. Elaborate the yaml for the CIF
        • 3. Prepare the executable:
        • 4. Run the system
        • 5. Check what has been done in the workdir:
        • 6. Examples factorisation flux
    • How to make super-observations
    • How to run TL and adjoint tests
    • How to run further inversions from a first one
      • Extending an inversion
      • Automatic resubmission of jobs
      • Shortening an inversion
    • How to run a forward simulation using the results of an inversion
    • How to run response functions
      • Prepare the YAML configuration file
      • Before running the full simulation
      • Running
    • How to use transformations to control the inputs and/or outputs of a CIF run
      • General principles of using transformations: examples for building the inputs of a CTM and/or elaborating on its outputs
      • Using transformations to build a vector control for an inversion
    • How to post-process the output netcdf files of the CIF
      • Reading and plotting the data in controlvect.nc
      • Reading and plotting the data of obsvect
    • How to add autocompletion for YAML configuration files in your editor
    • How to run a first forward simulation
      • First forward simulation with CHIMERE and ready-made input files
        • 1. Prepare the executable
        • 2. Locate the input files provided directly for CHIMERE
        • 3. Elaborate the yaml for the CIF, using ready-made files
        • 4. Run the system
        • 5. Check what has been done in the workdir:
  • Examples of configuration files
    • Examples for ICONART
    • Examples for dummy
    • Examples for FLEXPART
    • Examples for CHIMERE
    • Examples for LMDZ
    • Examples for tutorials
      • Examples for newmodel
      • Examples for gcp-ch4
    • Examples for basics
    • Examples for TM5

Contributing

  • Contributing to the Community Inversion Framework
    • Code of Conduct
    • Good practices regarding Git and Gitlab
    • Contributing to the code development and reporting/fixing bugs
    • Contributing to the documentation
  • Tutorials for developers
    • How to add, register and initialize a new plugin
    • How to implement a new model
      • Include the model sources to the CIF
      • Create and register the plugin module
      • Create a domain for your model
      • Define the “mapper” of your model
        • 1. Setting an empty mapper
        • 2. Setting the mapper with output concentrations
        • 3. Running the model executable
        • 4. Setting the mapper with input fluxes
      • Generate a monitor file compatible with the CIF
      • Pre-process observations to fit in model realm
      • Preparing inputs
      • Comparing outputs to observations
    • How to add a new type of flux data to be processed by the CIF into a model’s inputs
    • How to add a new type of data for boundary conditions to be processed by the CIF into a model’s inputs
    • How to add a new formula for computing the equivalent of satellite data
    • How to add a new basic transformation
    • Developments around CHIMERE
    • Miscellaneous hints
    • Main principles for using pytest to manage tests of the CIF
    • Modifying a model to use with EnSRF
    • Parallel computing in CIF
  • Repository
  • Show source
  • Suggest edit
  • .rst

Measurements measurements

Contents

  • Available Measurements measurements
  • Documentation
    • Description

Measurements measurements#

Available Measurements measurements#

The following measurements are implemented in pyCIF so far:

  • Concatenation of observations from parsers standard/std
  • Random generation of observations random/param

Documentation#

Description#

Measurements are used to generate CIF-compatible observation data sets.

previous

wrfchem/std wrfchem/std

next

Concatenation of observations from parsers standard/std

Contents
  • Available Measurements measurements
  • Documentation
    • Description

By VERIFY project

© Copyright 2025, VERIFY project.