Model:

Updated:

2 times per day, from 10:00 and 23:00 UTC

Greenwich Mean Time:

12:00 UTC = 07:00 EST

Resolution:

0.2° x 0.2°

Parameter:

Wet bulb potential temperature (θw) in C

Description:

The ThetaW map - updated every 6 hours - shows the modelled wet bulb potential temperature at the 850hPa level. The theta w (θw) areas are encircled by isotherms - lines connecting locations with equal wet bulb potential temperature. When an air parcel, starting from a certain pressure level, is lifted dry adiabatically until saturation and subsequently is brought to a level of 1000 hPa along a saturated adiabat it reaches what is called the saturated potential wet-bulb temperature: θw. As long as an air parcel undergoes an adiabatisch process, be it either dry or saturated, and in both descending and ascending motions θw does not change. Even when precipitation is evaporating adiabatically θw does not change, therefore θw is "conservative".
An air mass is defined as a quantity of air with a horizontal extent of several hundred or thousand kilometres and a thickness of several kilometres, which is homogeneous in thermal characteristics. Such an air mass may form when air has been over an extensive and homogeneous part of the Earth's surface during a considerable amount of time. This is the so-called source area. In due time, by means of radiative exchange processes and contact with the Earth's surface, an equilibrium develops which is evident from the fact that θw has approximately the same value in the entire air mass both horizontally and vertically, Hence θw can be used to characterise an air mass, with both sensible and latent heat are accounted for.
Depending on possible source areas several main air mass types can be distinguished: polar air (P), midlatitude air (ML) and (sub)tropical air (T). Also, but these are less important arctic air (A) and equatorial air (E). These five main types can be subdivided in continental air (c) and maritime air (m).

Table 1: Characteristic values for θw at 850 hPa (in °C) for various air masses.

Summer		Winter
cA < 7	mA < 9	cA < -5	mA < -7
cP 7 - 12	mP 6 - 12	CP -6 – 2	mP -3 - 5
CML 11 – 16	mML 11 - 16	CML 1 – 8	mML 3 - 9
cT 15 - 19	mT 14 - 19	CT 8 – 14	mT 8 - 16
cE > 17	mE > 18	cE > 14	mE > 16

If the θw distribution is considered on a pressure surface, preferably 850 hPa, then extensive areas with a small or no gradient can be observed. These areas of homogeneous θw values may be associated with air masses. Often various homogeneous areas are separated from one another by relatively narrow transformation zones displaying a strong gradient. Here frontal zones intersect with the pressure surface. Generally speaking a surface front is located where at 850 hPa the 'warm boundary' of the zone with the large θw gradient is present.(Source: Wageningen University)

COAMPS:^®

The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS^®) has been developed by the Marine Meteorology Division (MMD) of the Naval Research Laboratory (NRL). The atmospheric components of COAMPS^®, described below, are used operationally by the U.S. Navy for short-term numerical weather prediction for various regions around the world.

The atmospheric portion of COAMPS^® represents a complete three-dimensional data assimilation system comprised of data quality control, analysis, initialization, and forecast model components. Features include a globally relocatable grid, user-defined grid resolutions and dimensions, nested grids, an option for idealized or real-time simulations, and code that allows for portability between mainframes and workstations. The nonhydrostatic atmospheric model includes predictive equations for the momentum, the non-dimensional pressure perturbation, the potential temperature, the turbulent kinetic energy, and the mixing ratios of water vapor, clouds, rain, ice, grauple, and snow, and contains advanced parameterizations for boundary layer processes, precipitation, and radiation.

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).