most recent model run

                               
New     Cluster GFS ENS

Archive - MOD - Surface pressure P

Base Time
Day Month Year
Base
Th 31.07 00 GMT
  • Print
  • Info
Zoom in

Surface pressure MOD Model

Model:

Ensemble forecast charts of several different numerical weather prediction (NWP) models

Updated:
2 times per day, from 05:00 and 17:00 GMT
Greenwich Mean Time:
12:00 GMT = 13:00 BST
Resolution:
Parameter:
Sea Level Pressure in hPa
Description:
The surface chart (also known as surface synoptic chart) presents the distribution of the atmospheric pressure observed at any given station on the earth's surface reduced to sea level. You can read the positions of the controlling weather features (highs, lows, ridges or troughs) from the distribution of the isobars (lines of equal sea level pressure). The isobars define the pressure field. The pressure field is the dominating player in the weather system. Additionally, this map helps you to identify synoptic-scale waves and gives you a first estimate on meso-scale fronts.
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 GMT).
Surface pressure MOD Th 31.07.2014 00 GMT
Mouseover effect [?]
Times:   
 
 
available      
 
selected      
 
available (previous base)     
 
not available