| Model: | AEMET: Hirlam Aemet "Agencia Estatal de Meteorología (AEMET)" |
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| Updated: | 4 times per day, from 0:00, 06:00, 12:00 and 18:00 GMT | |
| Greenwich Mean Time: | 12:00 GMT = 07:00 EST | |
| Resolution: | 0.05° x 0.05° | |
| Parameter: | Precipitation in mm (or litres per square metres) | |
| Description: |
The precipitation map - updated every 6 hours - shows the modeled precipitation in mm.
The precipitation areas are encircled
by isohyets - lines with equal amounts of precipitation. However, modeling precipitation is
still not very reliable. If you compare the modeled results with observed values you will
realize that the model is nothing better than a first order approach. Yet this chart is of some
use for forecasters. Note: Based on international convention meteorologists use the metric system. 100 mm of precipitation is equivalent to roughly 4 inches. |
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| 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 |
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| 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 GMT). | |