[ncl-talk] composite of SSTA based on snow composite

[Sujata Mandke]

Dear NCL community,
Greetings!

	I want to make figure similar to the one attached.
 This figure caption is self explanatory as follows
Figure I(a). Composite time series of monthly mean sea surface 
temperature anomaly (SSTA) over the Nino3 region for a 30-month
 period (solid lines) and composite Indian summer monsoon rainfall
 anomaly (bars). The rainfall composites (in mm/day) are calculated 
based on plus (light shading) or minus (dark shading) one standard 
deviation. The SSTA composites are based on the rainfall composite.
If the June to September (JJAS) rainfall anomaly is greater than
one standard deviation away from normal, then the SSTA starting 
from the June of the year before (-) the monsoon to the October
 of the year following (+) the monsoon contributes to the composite.
This figure  is from following paper
Kirtaman, BP and Shukla, J:Influence of the Indian 
summer monsoon on ENSO, QJRMS (2000),126,213-239.

Instead of JJAS Indian summer monsoon rainfall, i want to
plot December to March (DJFM) season averaged Eurasian 
snow strong/weak composite as bars.Overlapped over these bars, 
composite time series of the monthly mean SSTA over Nino3 
for 30-month period based on strong/weak composite DJFM 
Eurasian snow is to be plotted (as line) from December 
of year before (-) to April of subsequent year (+), 
corresponding to strong/weak DJFM Eurasian snow composite. 

The strong and weak composite of DJFM Eurasian snow is 
estimated (NCL script attached). Further, I do not know, 
how to calculate composite SST anomaly over Nino3 
corresponding to strong/weak DJFM Eurasian snow composite.
Some guidelines to proceed further in this SSTA composite 
estimate would be of great help.

I had searched NCL-talk archives for this problem and 
found previous posts on composite, but none similar 
to the one required for the above mentioned purpose. 

I am using NCL version 6.4.0 on linux machine. 
Any suggestion/support would be greatly appreciated.

 Many thanks in advance.
With best regards
Dr. Sujata Mandke
Scientist , IITM, PUNE
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