G2.22 FTIR cell measurements carried out to characterize Instrument Line Shape have their own uncertainties

Gap abstract: 

For the retrieval of information about the vertical distribution of target species from FTIR spectra, it is important to know the FTIR instrument line shape (ILS). Therefore, regular cell measurements are carried out to characterize the ILS of the FTIR spectrometers. However, these cell measurements have their own uncertainties since these are obtained using optimal estimation: an ILS retrieval comes along with an uncertainty and an averaging kernel. In particular the averaging kernel for an ILS retrieval is often not adequately considered (Hase, 2012). Inaccurate knowledge of the ILS mainly affects the retrieved vertical profile (e.g. for water vapour and ozone profile retrievals). The uncertainty on the ILS leads to larger uncertainties on the retrieved column-averaged concentrations of CH4 and CO2 (XCH4, XCO2). In other words, the uncertainties on the ILS retrieved from cell measurements will propagate to the total uncertainty budget of the retrieved species. Although the technical know-how is present within the NDACC IR working group, the actual implementation of the ILS uncertainty characterisation and propagation is not complete. In particular further harmonization between the different FTIR retrieval software packages is required.

Part I Gap description

Primary gap type: 
  • Knowledge of uncertainty budget and calibration
ECVs impacted: 
  • Water vapour
  • Ozone
  • Carbon Dioxide
  • Methane
User category/Application area impacted: 
  • Operational services and service development (meteorological services, environmental services, Copernicus Climate Change Service (C3S) and Atmospheric Monitoring Service (CAMS), operational data assimilation development, etc.)
  • International (collaborative) frameworks and bodies (space agencies, EU institutions, WMO programmes/frameworks etc.)
  • Climate research (research groups working on development, validation and improvement of ECV Climate Data Records)
Non-satellite instrument techniques involved: 
  • FTIR
  • This gap should be considered at the same time as G2.18 as it is a contributing component to the broader uncertainty characterisation.

Detailed description: 

The retrieval of vertical profile information for target gases from ground-based high-spectral-resolution FTIR solar absorption spectra is based on the analysis of the observed shape(s) of the absorption line(s) of the target species in the recorded spectra. Since the observed shape is a convolution of the intrinsic absorption line shape with the instrument line shape (ILS), the analysis must account for the ILS. Therefore, the ILS must be known highly accurately. To this end, a cell filled with a known gas concentration at a known temperature and pressure is put into the FTIR instrument and a spectrum of the cell gas is taken. The cell spectrum allows the retrieval of the ILS using optimal estimation as described by Rodgers (2000), and such a retrieved ILS comes with its uncertainty. The uncertainty on the retrieved ILS is a combination of the smoothing uncertainty, the noise, the forward model parameters, etc. This uncertainty will propagate into the total uncertainty budget of the retrieved target gas’ profile and total abundance.

In summary, one can state that the cell measurement serves as a calibration of the target gas retrieval but that this calibration method is itself indebted with some uncertainty that must be accounted for in the total uncertainty budget of the retrieval result, which is the target gas vertical profile and total abundance.

Operational space missions or space instruments impacted: 
  • Copernicus Sentinel 4/5
  • MetOp
  • MetOp-SG
  • Polar orbiters
  • Geostationary satellites
  • Infrared nadir
  • Other, please specify:

All missions/instruments that use ground-based FTIR data for validation

Validation aspects addressed: 
  • Geophysical product (Level 2 product)
Gap status after GAIA-CLIM: 
  • GAIA-CLIM has partly closed this gap

Progress has been made within GAIA-CLIM, to identify the contribution of the ILS uncertainty to the total uncertainty budget and to make it better traceable and better characterised. The uncertainty propagation routines that were developed during QA4ECV & GAIA-CLIM are such that the integration of the ILS uncertainty propagation is a straightforward extension. However, the harmonization between the different retrieval software packages is not complete yet, and the implementation at all FTIR stations should still be done consistently.

Part II Benefits to resolution and risks to non-resolution

Identified benefitUser category/Application area benefittedProbability of benefit being realisedImpacts
Better uncertainty characterization of the FTIR data products
  • All users and application areas will benefit from it
  • High
Better characterized ground-based FTIR data yield improved utilization as reference data
Identified riskUser category/Application area at riskProbability of risk being realisedImpacts
Missing contribution to total uncertainty budget of the ground-based FTIR data products
  • All users and application areas will suffer from it.
  • High
Underestimation of total uncertainty associated with ground-based FTIR data products.
Inconsistent characterisation of FTIR data between different NDACC sites (not at all stations the quality of the cell retrievals is analysed in the same manner)
  • All users and application areas will suffer from it.
  • High
Reduced confidence in network wide data consistency.

Part III Gap remedies

Gap remedies: 

Remedy 1: Regular cell measurements and ILS retrievals are to be performed in a consistent manner

Primary gap remedy type: 
Secondary gap remedy type: 
Proposed remedy description: 

Regular cell measurements have to be performed at all NDACC sites and ILS retrievals have to be performed in a consistent manner regarding both, the technical setup of the retrieval (regularization, retrieval paramaters, cell measurement setup etc.) as well as the calculation of the total random and systematic uncertainty on the retrieved ILS. Ideally, the random and systematic uncertainties on the retrieved ILS are expressed as full uncertainty covariance matrix, but it is unrealistic and a computational burden to determine and propagate such full covariance matrices. A good approach would be to characterise the leading ILS uncertainty contributions, smoothing/noise, random/systematic and accordingly work on a realistic and not oversimplifying approach to accurately estimate and propagate the ILS uncertainties towards the retrieved target gas.

The second step in the proposal would be to implement this ILS uncertainty characterisation in both existing retrieval software packages PROFFIT and SFIT4. The outcome is a FTIR NDACC network-wide harmonized uncertainty budget that includes the propagated ILS uncertainty.


Improved traceability of uncertainties is a core objective of GAIA-CLIM and shall benefit applications including but not limited to satellite characterisation by FTIR instruments.

Measurable outcome of success: 

Traceable ILS uncertainty will allow a traceable estimation of the FTIR product uncertainty due to ILS uncertainties.

Expected viability for the outcome of success: 
  • High
Scale of work: 
  • Consortium
Time bound to remedy: 
  • Less than 3 years
Indicative cost estimate (investment): 
  • Low cost (< 1 million)
Indicative cost estimate (exploitation): 
  • Yes
Potential actors: 
  • Academia, individual research institutes
  • Hase F., Improved instrumental line shape monitoring for the ground-based, high-resolution FTIR spectrometers of the Network for the Detection of Atmospheric Composition Change, Atmos. Meas. Tech., 5, 603–610, doi:10.5194/amt-5-603-2012, 2012.
  • Rodgers, C. D., Inverse Methods for Atmospheric Sounding: Theory and Practice, Ser. Atmos. Oceanic Planet. Phys., Vol. 2, 1st ed., World Sci., Hackensack, N. J., 2000.