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The best analysis is that which allows the IFS models  to subsequently produce forecasts that verify nearest to the actual evolution.  The analysis is not necessarily true to the observations in every respect, though of course the analysis processes (4D-Var and LDAS) try to assimilate them to best effect.  For the purposes of the ensemble, the analysis process also tries to quantify the uncertainty of our estimate of the initial state.  Advanced analysis procedures have to be used to assimilate non-conventional observations. 

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• passive technologies sense natural radiation emitted by the earth and atmosphere or solar radiation reflected, refracted or retransmitted by the earth and atmosphere.
  
  • Contamination of atmospheric signals over land and over coastlines can be a problem, although increasingly new ways are being found to utilise such data. For example with cycle 45r1 introduced in June 2018 ECMWF began assimilating non-surface-sensitive infra-red channel data over land, and all sky micro-wave sounding data over coasts.
    
• active technologies emit radiation and sense how much is transmitted, reflected or scattered back.  For example:
  • the GPS radio occultation satellite-to-satellite signal is very sensitive to the temperature and humidity structure of the atmosphere particularly to the sharp moisture and temperature gradients beneath the boundary layer inversion,
  • Scatterometers derive surface-wind vectors from back-scattered radar signals from sea-surface ripples,
  • the Advanced Scatterometer (ASCAT) also enables soil moisture pseudo-observations that observe subsurface/subcanopy sub-surface and sub-canopy climate-related features such as water content of sub-canopy and continental surfaces.
    

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Satellite data is vital for an effective analysis and the use satellite observations is increasing rapidly.

Fig2.4.-1: Pie chart showing the proportion of data types used by the IFC assimilation.  ATMS predominate. Ground-based observations constitute a relatively small proportion.

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Users need to be aware of potential problems with the forecast due to deficiencies in coverage of data or conflict of observations with background fields.  Users should inspect:

• the data coverage (use obs drop down menu to select observation type) to show if and where there are deficiencies in data availability. 
• the analysis increments and analysis increment charts to show the location of significant differences between observed and background values.

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