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Multi-Integral Long Term Forecasting Model (MILTFM).
 
 
 
Multi-Integral Long Term Forcasting Model (MILTFM) 
by Benjamin BOYRARD and Philip HUGGINS
 
 
After studying hurricanes for many years I decided to push my fascination for cyclonic phenomenon to a higher level.  
In 1996 I developed  the first version of my own personal long term forcasting model. 

Here are the seasonal forcast since 1996 in comparisment with the actual number of cyclones that did occured on those years:  
 
 
FORECASTED
OCCURED
 
Year
n° of tropical Cyclones
n° of Hurricanes
n° of Major Hurricanes
  
n° of tropical Cyclones
n° of Hurricanes
n° of Major Hurricanes
1996
10
6
3
  
13
 10
 6
1997
15
10
6
  
7
3
1
1998
15
8
6
  
14
10
3
1999
12
10
5
  
12
8
5
2000
12
6
3
  
14
10
3
2001
not issued
not issued
not issued
  
15
9
4
2002
12
7
3
 
12
4
2
2003
14
7
3
 
16
7
3
2004
13
7
4
 
14
9
6
2005
14
8
5
 
28
?
?
2006
2007

Here is a superficial look at how the analysis are done and results are established.  
First I'll have a look at the actual sea surface temperature (SST) and its evolution as well as the sea surface temperature anomalies (SSTA) and compare those values with climatological data. This, however, is done not only on a large scale (the entire Atlantic Bassin) but also by regions.  
A mathematical function is given to caracterise the delimited surface, called surface function (Sf).  
The SST and SSTA, point by point is then intergrated in the Sf which will give a close approximation of the average SST and SSTA of the corresponding region. 
Values are then analyse each week after new readings.  
Variations are then extrapolitated from derived functions with climatology.  
Relative hygrometric (quantity of moisture in the air) estimations derived from water vapor satellite imagery are also integrated into the model.  
An approaching hurricane season with a tendancy of above average low, mid and upper tropospheric hygrometry generally will lead to longer periods of high atmospheric instability.  
There is then a higher chance of tropical distrubances developping into cyclones.  
(see hurricane information  for cyclogenesis conditions) 

Other factors such as the precipitation level, vertical temperature gradient, upper tropospheric  
circulation and barometric (reading of atmospheric pressure) variations are also vital in determine the potential number of Cape Verde and Barbadian cyclones.  
To have an estimation on the potential intensity (minimal or major hurricanes) of those cyclones, we will analyse the general atmospheric pathern over the Atlantic and that especially of the African Jet Stream.  
The study of large scale synoptic maps (featuring the implacements of low pressure zones, high pressure zones or anticyclones and the corresponding isobares, cold fronts, and other readings given by ships or weather bouees) is also necessary.  
An arbitary diagramme is established based on the average cyclonic formation during the last 50 years.  
It gives the number of cyclones per region:  
 
 
REGION
POSSIBLE NUMBER OF TROPICAL CYCLONES
Cape Verde
3
W-Atlantic
2
Caribbean Sea
1
Gulf of Mexico
2
NW-Atlantic
1
TOTAL:
9*
*:  In a typical average Atlantic hurricane season, one can potentially expect 3 Cape Verde cyclones, 2 Barbadian type, 1 Caribbean, 2 Mexican, and 1 off the eastern coast of the U.S, giving an average number of 9 cyclones per year.  
 

 
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