I am an epidemiologist, not a climatologist so my reply relies more on practical experience than on academic training. The ENSO can be characterized be several indicators. You will find a list with explanations at https://www.ncdc.noaa.gov/teleconnections/enso/

These indicators are either georeferenced (eg sea surface temperature) or not (eg southern oscillation index). Finding teleconnections might be achieved modelling local climatic / meteorological features (eg rainfall) with these indicators, accounting for possible time lags. This is a complex task, notably for design and practical implementation. However you will easily find most of the necessary datasets following the above-cited links, and the statistical methodology is well established. R is an excellent platform for doing this (see eg package raster and friends), though more specific software might be useful at some stages.

monthly NINO 3.4 SST index may be downloaded from http://www.cgd.

ucar.edu/cas/catalog/climind/TNI_N34/index.html#Sec5.

http://earthobservatory.nasa.gov

Hi Bappa, 

The most popular method as far as I know is Empirical orthogonal function (EOF) analysis.  There is an independent r function that can calculate EOF with required data provided. Here is two link, one for R package and another EOF analysis using R blog discussion: 

"Computes EOFs (a type of principal component analysis) for combinations of data sets, typically from the NCEP reanalysis and corresponding data from climate models."

http://www.inside-r.org/packages/cran/clim.pact/docs/EOF

Empirical Orthogonal Function (EOF) Analysis for gappy data: 

http://www.r-bloggers.com/empirical-orthogonal-function-eof-analysis-for-gappy-data/ 

Here is a reference paper: 

On the Interpretation of EOF Analysis of ENSO, Atmospheric Kelvin Waves, and the MJO by Paul E. Roundy

Since the main indicator of ENSO is eastern tropical pacific SST anomaly so definitely you need a global SST as there are couple of Nino indices. 

I hope that helps.

Thanks