模式:

Times Series from the ECMWF

更新:
Update monthly
格林尼治平时:
12:00 UTC = 20:00 北京时间
Resolution:
1.0° x 1.0°
参量:
降水:
东亚降水(毫米或升/平方米)
描述:
降水图 - 每6小时更新一次 - 显示东亚地区模式计算的降水分布情况。 降水区用等雨量线标出。 然而,目前模式算出的降水还不是很可靠。如果您比较一下模式结果和降水实测值,您会 发现模式结果只能算得上降水的一级近似值。不过,这幅图对于专业气象预报员却是个重 参考。

Cluster of Ensemble Members:
20 members of an ensemble run are divided into different clusters which means groups with similar members according to the hierarchical "Ward method" The average surface pressure of all members in each cluster are computed and shown as isobares. The number of members in each cluster determines the probability of the forecast (see percentage)
Dendrogram:
A dendrogram shows the multidimensional distances between objects in a tree-like structure. Objects that are closest in a multidimensional data space are connected by a horizontal line forming a cluster. The distance between a given pair of objects (or clusters) are indicated by the height of the horizontal line. [http://www.statistics4u.info/fundstat_germ/cc_dendrograms]. The greater the distance the bigger the differences.
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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