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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.

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• mountainous regions, particularly where model and actual surface altitudes are dissimilar.  
• snow covered areas, particularly in extremely stable conditions.

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The ground surface temperature (skin temperature) and surface albedo over land are very different to those over the water.  The land-sea mask defines whether the grid points are land or sea points.  But in coastal areas grid points will not capture the detail of the coastline.  Hence, surface radiative fluxes computed over the ocean may also be used by the IFS over the adjacent land.   This is because, for reasons of computational cost, the radiation code has to be run on a grid that is six times more coarse than the operational model grid.  This can lead to large near-surface temperature forecast errors at coastal land points.  To combat this problem the radiation code was changed and involved modifying the surface albedo when radiation calls are made. This leads to more to realistic coastal land temperatures.  Discussion of the land-sea mask relates to the problem.

Despite the above IFS improvements, coastal temperatures (and dew points) still need to be viewed with caution, especially where urban areas are next to the sea.  The local drift of surface air from a land or sea source may differ significantly from model forecast low-level winds.  IFS and AIFS forecasts of coastal 2m temperatures can be in error where:

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• forecast Southern European coastal temperatures have been observed, at times, to be too low during a Mediterranean heatwave.
• forecast Baltic Sea coastal temperatures have been observed, at times, to be too low when model sea temperatures are incorrectly low. 

Discussion of the land-sea mask, meteograms, vertical profiles and grid point selection relates to the problem.

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Extensive concrete and buildings can possibly provide a source of heat (the heat island effect) and even moisture (from air-conditioning units).   Towns and cities are likely to have very different characteristics from other HTESSEL tiles which describe natural land coverage.   An urban tile in HTESSEL (introduced in Cy49r1) models the fluxes of heat, moisture and momentum and their effects around towns and cities.  Forecast screen temperatures in large urban areas, particularly cities and especially coastal cities, can still be a little low when compared to observations.   In particular, forecast screen temperatures can be too low on relatively clear, calm nights, and in winter where the urban area is surrounded by snow cover.   Users should assess the potential for deficiencies in low-level parameters and adjust as necessary.

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Fig9.2.1.1-2: Charts showing distribution of low cloud over Europe at 12UTC 26 Dec 2024.  Also shown are actual and forecast (T+12) vertical profiles for Essen and Muenchen and the errors between the forecast and observed 2m temperatures more generally.  The largest positive errors (reds and yellows, model T2m too high) are where the model has cleared the cloud too quickly and allowed incorrect insolation.   The negative  errors ((blues, model T2m too low) are where the model has maintained the cloud too and hindered insolation.  The cloud distribution is critical and users should anticipate likely deficiencies by monitoring available surface or satellite information. 

Snow cover effects

Analysis and forecast of snow depth, snow compaction, and snow cover are important for forecasting lower-layer and near-surface temperatures.  They can have a significant impact on forecast accuracy.  However, the relationship between snow cover and temperature is complex:

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• its age (the model facilitates slow, natural compression).
• melting.  Small amounts of snow on the ground tend to take too long to melt in IFS.  This is even if the temperature of the overlying air is well above 0°C).
• interception (of rain).
• addition of new snow.

The albedo is related to the extent (and age) of snow cover and snow characteristics in analysed and forecast fields have an effect on the radiation that could be absorbed.  This has a corresponding impact on forecasts of 2m and surface temperatures.    Better assessment of the albedo when the multi-layer snow scheme is introduced will allow faster response to changes in the radiative forcing.

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Currently snow is modelled by a multi-layer snow scheme allowing a fairly realistic heat transfer.

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In this example a single layer snow model was used in Cy47r3 and before.  There is a significant difference between the observed (black) and forecast T+72 Ensemble Control Forecast forecast (red) temperature structure at Murmansk.  The observed structure is much colder than that forecast, and in this case, surface snow cover appears to have been critical to the forecast.  The observed temperature structure could be due to stronger radiative cooling due to more extensive and/or deeper snow cover than is indicated in the IFS snow depth chart.  A multi-level snow model is used in Cy48r1 and later.

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Temperature  errors (particularly in biases during spring and autumn) are in part related to the representation of vegetation (in terms of cover and seasonality), and evaporation over bare soil.  Heat flux from bare soil is also problematic.   Soil temperature and soil moisture is modelled in IFS but there is not a great deal of directly measured observations available.  However, the impact of heat and moisture fluxes can be a significant contributor to 2m and surface temperature errors, and hence have an impact on humidity.

Leaf area index is a measure of vegetation coverage and determines the degree of shading and how much radiation is absorbed or reflected.  Leaf area index varies in the model, month by month.  The leaf area index will not be representative if there is anomalous weather.  For example, wind storms may strip leaves from trees, widespread fires may clear vegetation (and change the albedo).

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 Fig9.2.1.1-5: An example of 2m temperatures in wintertime anticyclonic conditions in complex terrain.  Temperature analysis at 09UTC 30 Dec 2024 covering southern Germany, Austria, eastern Alps and the Tirol (from INCA analysis).  Temperatures are around -10°C in valleys and at the same time up to +10°C on high ground above the low-level cold pools. The spectral representation of model orography means detailed features such as these simply cannot be represented in a model with 9km resolution.  This can lead to large forecast errors in temperatures at some stations.   Note also the fanning out of some of the coldest air as it exits the Inn valley southeast of Munich.  (INCA Central Europe is the Integrated nowcasting system for the Central European area).

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The effect of lakes is parameterised using FLake and a lake cover mask.  The sub-grid detail may not be completely captured and the energy fluxes may well be incorrectly estimated.  This is particularly true where frozen lakes are plentiful and/or forecast snow cover is uncertain.   These aspects can:

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• too little snow-cover and/or too much cloud is analysed then there is a risk forecast temperatures may be too high.
• too extensive snow-cover and/or too little cloud is analysed then there is a risk forecast temperatures may be too low. But in the case of too little cloud or more wind sometimes temperatures may be too high.
• the boundary layer structure is not successfully analysed then there is a risk forecast temperatures may correspondingly be in error.
• winds are too strong or too weak then forecast temperatures may have larger errors.  This is particularly at high latitudes in winter where radiative cooling is insufficiently offset by the limited insolation.

(FUG Associated associated with Cy50r1)