模式:

FMI (Hirlam Model from finnish meteorological institute)

更新:
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
格林尼治平时:
12:00 UTC = 20:00 北京时间
Resolution:
0.068025° x 0.068025°
参量:
海平面气压:
地面图,海平面气压(百帕)
描述:
地面图(也称海平面天气图)显示根据本站气压实测值换算到海平面上的气压值的 分布情况。从中能够看出大的天气形势,如高、低压中心,槽、脊线位置等等。 此外,这幅图还能帮助您识别天气尺度系统,同时还可用于粗略地估计中尺度锋 面的位置。

Spaghetti plots:
are a method of viewing data from an ensemble forecast.
A meteorological variable e.g. pressure, temperature is drawn on a chart for a number of slightly different model runs from an ensemble. The model can then be stepped forward in time and the results compared and be used to gauge the amount of uncertainty in the forecast.
If there is good agreement and the contours follow a recognisable pattern through the sequence then the confidence in the forecast can be high, conversely if the pattern is chaotic i.e resembling a plate of spaghetti then confidence will be low. Ensemble members will generally diverge over time and spaghetti plots are quick way to see when this happens.

Spaghetti plot. (2009, July 7). In Wikipedia, The Free Encyclopedia. Retrieved 20:22, February 9, 2010, from http://en.wikipedia.org/w/index.php?title=Spaghetti_plot&oldid=300824682
FMI:
FMI
At the Finnish Meteorological Institute, results from several numerical weather prediction models are utilized. Most of all, these include products from the European Centre of Medium Range Forecasts (ECMWF), located in Reading in the United Kingdom. For shorter range forecasts, more detailed forecasts are produced in-house using a limited area models (LAMs) called HIRLAM and HARMONIE, which are being developed by FMI as an international co-operation programme with a number of European countries.
NWP:
Numerical weather prediction uses current weather conditions as input into mathematical models of the atmosphere to predict the weather. Although the first efforts to accomplish this were done in the 1920s, it wasn't until the advent of the computer and computer simulation that it was feasible to do in real-time. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful requires the use of some of the most powerful supercomputers in the world. A number of forecast models, both global and regional in scale, are run to help create forecasts for nations worldwide. Use of model ensemble forecasts helps to define the forecast uncertainty and extend weather forecasting farther into the future than would otherwise be possible.

Wikipedia, Numerical weather prediction, http://zh.wikipedia.org/wiki/數值天氣預報(as of Feb. 9, 2010, 20:50 UTC).