Modelo:

Actualizado:

Update monthly

Tiempo medio de Greenwich:

12:00 UTC = 07:00 MGZ

Resolutión:

1.0° x 1.0°

Parámetro:

Geopotential in 850 hPa (solid, black lines) and Vorticity advection in 10⁵/(s*6h) (colored lines)

Descripción:

The two types of vorticity advection are positive (PVA) and negative vorticity advection (NVA). The closed circles in the figure show the 850 hPa absolute vorticity lines, the others the 850 hPa height lines. When an air parcel is moving from an area higher vorticity to an area lower vorticity this is called: PVA (red color). The other way around is called: NVA (blue color). PVA is associated with upper-air divergence, i.e. upward vertical motion. NVA is associated with down ward vertical motion. Therefore, PVA  at 500 hPa is strongest above a surface low, while NVA at 500 hPa is strongest above a surface high.
In operational meteorology Vorticity advection maps are used to identify areas with vertical air motion to see where clouds, precipitation or clear conditions are likely to occur. Keep in mind, however, that PVA is not the same as upward vertical motion. Here temperature advection is important too.

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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