This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276.
Gap reference list
Gap reference list
This is the full list of gaps identified in GAIA-CLIM with a SMART analysis of each gap. Details of how and when such SMART remedies may be addressed for each gap are included in the full descriptions. The gaps each have unique gap identifier numbers of the form: X.XX, and full descriptions can be found at gaia-clim.eu/wiki/gX.XX; or by following the links in the Gap Identifiers below.
Below search function allows filtering the Catalogue of Gaps along different cross-section, e.g. the type of gap and sugested remedies, instrument technicque, ECVs, or the potential actors addressed.
Gap identifier |
Gap name |
| Lack of internationally recognised and adopted framework for assessment of fundamental observing capabilities | |
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Lack of a comprehensive review of current non-satellite observing capabilities for the study of ECVs across domains
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Lack of integrated user tools showing all existing observing capabilities for measuring ECVs with respect to satellite spatial coverage
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| Currently heterogeneous metadata standards hinder data discoverability and usability | |
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Relative paucity and geographical concentration of reference quality measurements, with limited
understanding of uncertainty in remaining measurements, limits ability to formally close satellite to non-satellite comparisons
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| Current poor spatial coverage of high-quality multi-wavelength lidar systems capable of characterising aerosols | |
| Lack of uptake of lidar measurements in data assimilation | |
| Need for a metrologically rigorous approach to long - term water vapour measurements from Raman lidars in the troposphere and UT/LS | |
| Tropospheric ozone profile data from non - satellite measurement sources is limited and improved capability is needed to characterise new satellite missions | |
| Lack of rigorous tropospheric ozone lidar error budget availability | |
| Lack of rigorous pure rotational Raman temperature lidar error budget availability limits utility for applications such as satellite characterisation | |
| Missing microwave standards maintained by national/international measurement institutes | |
| G2.18 | Better agreement needed on systematic and random components of the uncertainty in FTIR measurements and how to evaluate them |
| G2.22 | FTIR cell measurements carried out to characterize Instrument Line Shape have their own uncertainties |
| G2.24 | Lack of calibrated in-situ vertical profiles of CH4, CO2 (and CO) for improving the accuracy of FTIR (partial) column measurements of CH4, CO2 (and CO) |
| G2.26 | Poorly understood uncertainty in ozone cross-sections used in the spectral fit for DOAS, MAX-DOAS and Pandora data analysis |
| G2.27 | Lack of understanding of random uncertainties, air mass factor calculations, and vertical averaging kernels in the total ozone column retrieved by UV-visible spectroscopy |
| G2.30 | Metrologically incomplete uncertainty quantification for Pandora ozone measurements |
| G2.31 | Incomplete metrological understanding of the different retrieval methods, information content, and random and systematic uncertainties of MAX-DOAS tropospheric ozone measurements |
| G2.36 | Lack of traceable uncertainties in MWR measurements and retrievals |
| G2.37 | Need for more complete metrological characterisation of spectroscopic information |
| G3.01 | Incomplete knowledge of spatiotemporal atmospheric variability at the scale of the measurements and of their co-location |
| G3.02 | Missing standards for, and evaluation of, co-location criteria |
| G3.04 | Limited characterization of the multi-dimensional (spatiotemporal) smoothing and sampling properties of atmospheric remote sensing systems, and of the resulting uncertainties |
| G3.05 | Representativeness uncertainty assessment missing for higher-level data based on averaging of individual measurements |
| G3.06 | Missing comparison (validation) uncertainty budget decomposition including uncertainty due to sampling and smoothing differences |
| G4.01 | Lack of traceable uncertainty estimates for NWP and reanalysis fields & equivalent TOA radiances – relating to temperature and humidity |
| G4.08 | Estimates of uncertainties in ocean surface microwave radiative transfer |
| G4.09 | Imperfect knowledge of estimates of uncertainties in land surface microwave radiative transfer |
| G4.10 | Incomplete estimates of uncertainties in land surface infrared emissivity atlases |
| G4.12 | Lack of reference-quality data for temperature in the upper stratosphere and mesosphere |
| G5.01 | Vast number of data portals serving data under distinct data policies in multiple formats for fiducial reference-quality data inhibits their discovery, access, and usage for applications, such as satellite Cal/Val |
| G5.06 | Extraction, analysis, and visualization tools to exploit the potential of fiducial reference measurements are currently only rudimentary |
| G5.07 | Incomplete development and/or application and/or documentation of an unbroken traceability chain of data manipulations for atmospheric ECV validation systems |
| G5.09 | Need to propagate various fiducial reference quality geophysical measurements and uncertainties to TOA radiances and uncertainties to enable characterisation of satellite FCDRs |
| G5.11 | Non-operational provision of fiducial reference-measurement data and some satellite-derived products reduces their utility for monitoring and applications |
| G6.01 | Dispersed governance of high-quality measurement assets leading to gaps and redundancies in capabilities and methodological distinctions |
| G6.02 | Analysis and optimisation of geographical spread of observational assets to increase their utility for satellite Cal/Val, research, and services |
| G6.03 | Lack of sustained dedicated periodic observations to coincide with satellite overpasses to minimise co-location effects |
| G6.06 | Provision of reference-quality measurements where technically feasible on a continuous basis, to maximise opportunities for the validation of satellite and derived products |
| G6.12 | Under - capacity of workforce to exploit satellite data and satellite characterisation |