Page History

...

Fig9.2.1.1: An example where ENS ensemble forecast temperatures differ substantially from observed data.  The plot shows the Continuous Ranked Probability Score (CRPS).

...

These biases are not corrections to be made to every temperature forecast but merely highlight areas where errors have been identified when averaged over an extended period.  Users should consider the effects outlined below  

Diurnal

...

range of temperatures

The amplitude of the diurnal cycle is generally underestimated over land (a deficiency shared by most forecasting models).  This is especially the case in Europe during summer when the underestimation of temperature range reaches ~2°C across large areas.  Near-surface temperatures are generally too warm during night-time and slightly too cold during the day.  However, the degree to which the amplitude of the diurnal cycle is underestimated depends on region and season.  Night-time 2m temperatures are about 1–2°C too warm and surface temperatures about 2°C too warm.  

...

Currently snow is modelled as a single layer of snow which allows too much heat to be transferred up from the underlying ground.  A multi-layer snow scheme under development will enable more realistic heat transfer and better assessment of the albedo.  This will allow faster response to changes in the radiative forcing.  In wintertime in northernmost European countries when actual minimum temperatures are well below average (e.g. with snow cover), forecasts temperatures often are much too high (even by as much as 10°C).

Turbulent

...

mixing

Biases in near-surface temperatures during winter conditions are very sensitive to the representation of turbulent mixing in stable boundary layers.  Comparison with radiosondes in the lower 200m of the atmosphere suggests underestimation of the temperature gradient; this is particularly pronounced at lower latitudes.  Full resolution of the details of the temperature structure in the lowest layers of the atmosphere is not possible with current computational resources.

...

Temperature  biases (particularly during spring and autumn) are in part related to the representation of vegetation (in terms of cover and seasonality), and evaporation over bare soil.

Orography and

...

geographical effects

• Lake temperatures can have an effect on forecast of temperatures, particularly in deciding whether the lake is frozen or not.
• Overnight 2m temperatures tend to be too cold over rugged or mountainous areas.

...

Errors in the representation of evaporation and/or soil moisture can also impact forecasts of near-surface humidity.   In particular, spring evaporation is too high, and summer vegetation gets into stress conditions too quickly (over-depletion of soil moisture).  Evaporation over bare soil is also problematic. 

Orography and Geographical effects

• Lake temperatures can have an effect on forecast of dew-point temperatures, particularly in deciding whether the lake is frozen or not.  Proximity of a lake can have an influence on the humidity at a downwind location. 

...

Summary of Soil temperature errors:

HRES mean and the ENS Ensemble mean values of soil moisture slightly overestimate the diurnal cycle of soil temperature:

...