This research paper is about synoptic climate specifically with in the upper air layers
using upper air layers maps analysis which are maps of thickness for the level 1000 – 500
MB, that their high average ranges between 100 – 5600 M above surface. This research paper
focuses on studying special and temporal variations of the atmosphere thickness above Iraqaccording
to this study, it is concluded that atmosphere thickness above Iraq increases
towards south with an average of 100 M as compared with north of Iraq. Regarding the
temporal variations, it is concluded that atmosphere thickness during hot months. In July, for
example, the atmosphere thickness becomes thicker than in January with an average of
(250)M in Iraq. It is also found at atmosphere thickness above Iraq increases in recent years,
especially in Baghdad.
When the atmosphere thickness reaches (5400)M, It is an indication of air front formation
on the surface. So, a follow up procedure of these locations above Iraq, which is represented
by a line on the weather maps, was used. It appears that the line direction moves away from
Iraq and goes toward Turkey in recent years, which means that air north, too.
By analyzing the weather maps of pressure air systems (1000)MB accompanied with line
thickness, it appears that air depressions mostly accompanies with line thickness (5400)M .
Whereas, within the pressure level maps (500)MB, It appears the upper trough of the air
depression the most frequent pressure system with thickness line of (5400)M.
The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine
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