描述:

抬升指数(LI)是一种表示自由对流高度以上不稳定能量大小的指数。它表示一个气块 从抬升凝结高度出发，沿湿绝热线上升到500百帕(海拔5500米左右高度)处所具有的 温度被该处实际大气温度所减得到的差值。比如，某一气块沿湿绝热线上升到500百帕 时的理论值为－14°C, 而该处的实际温度为－18°C, 那么抬升指数就是-4。 当差值为负数时，表明气块比其环境温度更暖，因此将会继续上升。该差值的绝对值 越大，出现对流天气的可能性也越大。差值为正数时，表示大气层结稳定。

值得注意的是，中国气象学家定义的抬升指数和上面的定义正好相反，他们用一个气块 沿湿绝热线上升到500百帕处所具有的温度减去该处实际大气温度得到的差值定义抬升 指数(大气科学辞典，P603)。因此获得的抬升指数值和我们此处的抬升指数值符号正好 相反。

抬升指数

天气现象

>0

不可能出现雷雨天气

0－ -3

可能出现雷雨天气

-3 - -5

很可能出现雷雨天气

-5 - -7

强对流(雷雨)天气

<-7

大气极端不稳定，强对流天气

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

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).