Model:

Updated:

2 times per day, from 05:00 and 17:00 UTC

Greenwich Mean Time:

12:00 UTC = 07:00 EST

Resolution:

Parameter:

Mean relative humidity between ca. 3000 and 6000 m above the ground

Description:

This map presents the mean relative humidity between about 3000 and 6000m a.s.l. - equivalent to the atmospheric layer between 10,000 and 20,000 ft. This is the atmospheric region where middle and high stratus clouds form. They are typically fringing a warm ridge along the anticyclonic sector of a frontal zone. In general, middle and high stratus clouds are a good indicator for the run of the jet stream. Mean Relative Humidity in the layer between about 600 and 3000 m above ground

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://en.wikipedia.org/wiki/Numerical_weather_prediction(as of Feb. 9, 2010, 20:50 UTC).