Note: HRES and Ensemble Control Forecast are scientifically, structurally and computationally identical. With effect from Cy49r1, Ensemble Control Forecast output is equivalent to HRES output where shown in the diagrams. At the time of the diagrams, HRES had resolution of 9km and ensemble members had a resolution of 18km.
Modelling the structure of the lowest, near surface, layers is very important for analysis and forecasting, especially for cold temperatures at 2m. For this reason there are many model levels in the boundary layer. Capturing the structure of the temperature and moisture can be difficult and often imprecise. The structure is particularly difficult to define where there are low level inversions or complex orography. Modelling wind shear and mixing processes also has an impact.
Forecasting the development and persistence of cloud is very important. Cloud coverage affects both the albedo and radiative balance between surface and boundary layer air.
Cloud containing super-cooled liquid water is often 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:
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.
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.
Defining anticyclonic inversions is often a problem, particularly in winter with colder or sub-zero temperatures in the lower boundary layer. Low level cloud cover tends to be shallower in the forecast and break too easily. Greater incoming radiation can raise the near surface temperatures too much and/or too quickly. Sub-zero temperatures can be very low to rise.
Users should assess how well the model has analysed the structure of the inversion and take into account the extent and persistence of the cloud area under the inversion during the past few days.
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. Forecast values shown in red; observed values shown in black. DT:00UTC 19 Jan 2025; T+12 VT12UTC 19 Jan 2025. There was a large anticyclone over Europe at this time with extensive low cloud but with some breaks mainly around the edges. In this case the Ensemble control (Ex-HRES) handled the boundary layer evolution rather poorly.
IFS forecasts of low Stratus or stratocumulus sheets depend upon correct and detailed modelling of the lowest layers of the model atmosphere. This depends upon valid data. In particular availability of:
Before accepting the the presence or absence of areas of stratus or low stratocumulus, users should assess how well the boundary has been modelled by IFS. Compare the analysed and observed structure of the boundary layer and assess critically the validity of the data used. Low level winds and turbulent effects can also play a part as turbulence from a breeze can clear stratus by mixing down drier air while stagnant air can aid persistence.
Fig9.1-3: An example of low stratus not captured by ensemble control (ex HRES). FigA shows an area of stratus running in across the White Sea. Kem' observation shows mist, but lies somewhat inland from the coast. FigB shows that the ensemble control (ex HIRES) missed the low cloud area. The vertical profile shows some reasons - 1: the radiosonde data is incomplete below 900hPa (unrealistic straight lines) and boundary layer detail is lost. However, the moisture up to about 940hPa is clear. 2: the model has not assimilated the radiosonde data and is far too dry. Also, model low level winds (not shown) are stronger than the almost calm conditions observed contributing to overturning of the lowest layers of the boundary layer.
Fig9.1-4: An example of low stratocumulus not captured by ensemble control (ex HRES). The cloud layer is thin - thin enough to show Kármán vortices. Ensemble vertical profiles reveal that none of the ensemble members managed to create low clouds although all are close to saturation (see vertical profile). Nevertheless, the forecast of cloud, thin or not, can have a large effect on insolation and radiative cooling.
(FUG Associated with Cy50r1)