Model:

Updated:

Update monthly

Greenwich Mean Time:

12:00 UTC = 13:00 BST

Resolution:

1.0° x 1.0°

Parameter:

Geopotential in 500 hPa (solid, black lines) and Temperature advection in K/6h (colored lines)

Description:

The map "T-Adv 500" shows the advection of cold or warm air at 500 hPa level. Negative values indicate cold advection, while positive values indicate warm air advection. Advection of warm or cold air causes the geopotential height to respectively rise or drop, producing vertical rising and sinking motion of air. There is, however, not a direct relationship between temperature advection and resultant vertical motion in the atmosphere since other lifting and sinking mechanisms can complicate the picture, e.g. vorticity advection (see "V-Adv maps").
In weather forecasting, temperature advection maps are often used to locate the postion of wam and cold fronts. Cold advection is common behind cold fronts, while warm advection is common behind warm fronts and ahead of cold fronts. Higher in the atmosphere temperature advection is getting less pronounced, as horizontal much more uniform in temperature and the flow is more zonal.

Introduction to seasonal forecasting:

The production of seasonal forecasts, also known as seasonal climate forecasts, has undergone a huge transformation in the last few decades: from a purely academic and research exercise in the early '90s to the current situation where several meteorological forecast services, throughout the world, conduct routine operational seasonal forecasting activities. Such activities are devoted to providing estimates of statistics of weather on monthly and seasonal time scales, which places them somewhere between conventional weather forecasts and climate predictions.
 
In that sense, even though seasonal forecasts share some methods and tools with weather forecasting, they are part of a different paradigm which requires treating them in a different way. Instead of trying to answer to the question "how is the weather going to look like on a particular location in an specific day?", seasonal forecasts will tell us how likely it is that the coming season will be wetter, drier, warmer or colder than 'usual' for that time of year. This kind of long term predictions are feasible due to the behaviour of some of the Earth system components which evolve more slowly than the atmosphere (e.g. the ocean, the cryosphere) and in a predictable fashion, so their influence on the atmosphere can add a noticeable signal.
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