Structure of the lower atmosphere and boundary layer

The IFS atmospheric model has many levels in the lower atmosphere to capture the all important boundary layer but precision is difficult.  This is because there are difficulties modelling the detail of radiation exchanges at the surface the lack of uniform and widespread observations.  This affects the development and persistence of cloud, and hence also the albedo and radiative balance between surface and boundary layer air.  

Cloud containing super-cooled liquid water (SLW) is frequently observed by aircraft and by remote sensing.  But the processes and consequent effects associated with super-cooled liquid water in the cloud are difficult to model precisely because:

  • super-cooled liquid water is important for radiation considerations.
  • super-cooled liquid water can increase cloud lifetime (liquid drops can remain suspended while ice crystals grow and fall out).
  • there is a fine balance between turbulent production of water droplets, nucleation of ice, deposition growth and fallout.
  • there are uncertainties in turbulent mixing, ice microphysics, vertical resolution.

The structure of the boundary layer is crucial.  This is particularly so where there is a well-marked inversion, with or without a sharp change in humidity.  Users should note:

  • stratocumulus tends to be under-predicted over land in anti-cyclones or may dissipate too quickly.

  • incorrect definition of the boundary layer in the physics schemes can mean incorrect identification, formation or dispersal of low cloud.
  • observed, analysed and forecast temperatures can be very different to one another in hilly or mountainous regions.

Problems in handling low cloud can have a significant impact on the temperature and moisture structure of the boundary layer and impact 2 m temperatures.  A revised warm-phase microphysics and revised boundary layer clouds and shallow convection were introduced in 2018.

The user should assess carefully the model representation of temperature and moisture structure in the lower atmosphere.


Fig9.1-1: A comparison of observed (orange) and model analysed/forecast (green) temperature and dewpoint structures.  Errors are due to assimilation issues coupled with the difficulties handling the cloud physics.  In this case the surface cool and moist layer was analysed to be slightly deeper than in reality.   This retarded fog clearance and therefore delayed heating and overturning of the boundary layer through the morning.  So by 12UTC the forecast inversion was too low compared with reality and it had also not captured the stratocumulus from the convective overturning within the boundary layer.  Consequently the true radiation balance around midday was not captured.

 

Fig9.1-2: Examples of the difficulty of describing the boundary layer temperature and moisture structure.  Dew-point is used here as a measure of moisture.  Values as analysed or forecast shown in blue; observed values shown in orange.

At Stuttgart, Budapest and Nis the lowest ~500 m is poorly represented.  Solar radiation in the atmospheric model is depleted/enhanced by the presence/absence of fog or low stratus cloud.  At Bucaresti the temperature structure of the lowest layers is modelled quite well, but the moisture structure near the subsidence inversion is not.  Differences in boundary layer moisture have a strong influence on the development of stratocumulus as surface temperatures rise during the morning. 

Consequences from an error in the forecast location of a front 

Errors in the forecast location of a front lead to large errors in the predicted airmass and surface parameters at a given location.  When a front is misplaced, dissimilar air masses either side of the front mean the structure of the atmosphere can be very different from that actually experienced.   The differences between forecast and observations can be over the whole depth of the atmosphere when a front is misplaced.  Large 2-metre temperature errors can occur.

The user should consider carefully the advance of frontal zones and use ensemble output to assess the uncertainty in timing.  Model representation of temperature and moisture structure in the lower atmosphere can be considerably different from actual observed values if a front is faster or slower than predicted.    

An example - passage of cold front in the Balkans late June 2023

The cold front was associated with very thick cloud cover and patchy rain.  2m temperatures were low for this time of year under the frontal cloud, and in the post-frontal cold air temperatures were only between 13°C and 20°C.  The T+72 forecast for Bucaresti showed no cloud, temperature 29°C, and SW'ly low-level winds.  But observations showed thick cloud layers, temperature 19°C, and NE'ly low-level winds.  However, the ensemble members showed uncertainty in the position of the cold front and the spread in temperature was very large in the whole boundary layer.


Fig9.1-3: Errors in 2m temperature over the Balkans T+72 DT12UTC 25 June, VT 12UTC 28 June 2023.  The cold front advanced further than predicted with extensive cloud depressing temperatures ahead of the front and allowing an inflow of colder air to the rear.  Colours show where forecast temperatures are too warm (red and purple), too cold (blue).

Fig9.1-4: Vertical profile showing differences structure of the airmass at Bucaresti.  The T+72 forecast for Bucaresti (red) showed no cloud, temperature 29°C, and Sw'ly low-level winds.  The radio sonde data showed thick cloud layers, temperature 19°C, and NE'ly low level winds.