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    the code of the file until where you have to start completion: %% |enso| documentation 
% |enso| computes a version of the Nino 3.4 SST index.  
%
% <CDT_Contents.html Back to Climate Data Tools Contents>
%% Syntax 
% 
%  idx = enso(sst,t) 
%  idx = enso(sst,t,lat,lon)
%  idx = enso(sst,t,lat,lon,'region',NinoRegion)
%  idx = enso(sst,t,mask)
%  idx = enso(...,'smoothing',months)   
% 
%% Description 
% 
% |idx = enso(sst,t)| calculates El Nino Southern Oscillation index from 
% a time series of sea surface temperatures sst and their corresponding 
% times |t|. sst can be a vector of sea surface temperatures that have been
% averaged over a region of interest, or sst can be a 3D matrix whose third
% dimension correponds to times |t|. If sst is a 3D matrix, a time series is
% automatically generated by averaging all the grid cells in sst for each
% time step. 
% 
% |idx = enso(sst,t,lat,lon)| calculates the Nino 3.4 index for 3D |sst| time
% series and corresponding grid coordinates |lat,lon|. Using this syntax,
% grid cells within the Nino 3.4 region are automatically determined and
% the Nino index is calculated from the area-averaged time series of ssts
% within that region. 
% 
% |idx = enso(sst,t,lat,lon,'region',NinoRegion)| allows any of the following
% Nino regions, ent
    
function will want to know exactly what geo coordinates correspond
% to each grid cell in the |sst| dataset, so use |meshgrid| to get the |lat,lon|
% arrays into 2D grids we'll call |Lat,Lon|: 

load pacific_sst.mat

% Get 2D grids from lat,lon arrays: 
[Lon,Lat] = meshgrid(lon,lat);

%% 
% The simplest way to use the |enso| function is to enter the 3D |sst| data, 
% the corresponding times |t|, and the grid cell coordinates, like this: 

idx = enso(sst,t,Lat,Lon); 

%% Plot it up real nice
% With that, we can now plot the Nino 3.4 anomalies. We'll use the
% <anomaly_documentation.html |anomaly|> function with thresholds of +/-
% 0.4 degrees to identify El Nino and La Nina periods, respectively: 

figure
anomaly(t,idx,'thresh',[-0.4 0.4]); 
axis tight
hline(0,'k') % places a horizontal line at 0
datetick('x','keeplimits')
ylabel 'Nino 3.4 SST anomaly (\circC)'

%% A bit of context
% For a bit more context, and to understand what the |enso| function is doing, 
% here's the mean sea surface temperature from the pacific_sst dataset,
% plotted with <imagescn_documentation.html |imagescn|> and using the <cmocean_documentation.html 
% |cmocean|> _thermal_ colormap: 

figure
imagescn(Lon,Lat,mean(sst,3))
cmocean thermal 

%%
% By default the |enso| function calculates the the Nino index using
% the lat,lon bounds of the Nino 3.4 box (5N-5S; 170W-120W). Here's the
% Nino 3.4 region on a map: 

% Define the Nino 3.4 box: 
latv = [-5 -5 5 5 -5]; 
lonv = [-170 -120 -120 -170 -170]; 

% Plot the Nino 3.4 box: 
hold on
plot(lonv,latv,'k-','linewidth',2)
text(-170,5,'The Nino 3.4 box!','vert','bottom','fontangle','italic')

%% 
% If you'd like to explore Nino indices in regions other than the default
% Nino 3.4 region, read on...

%% Example 2: A manual approach
% By default, the |enso| function calculates the area-weighted average sea 
% surface temperature within the Nino 3.4 box, then uses <deseason_documentation.html |deseason|>
% to remove seasonal cycles. The the mean is removed from the deseasoned
% time series to get the ENSO anomalies, and then smoothed using
% <scatstat1_documentation.html |scatstat1|> as a moving-average filter.
% The |enso| function allows you to override most of the steps of the Nino
% calculation or set them to your liking. Below are some examples of how to
% customize use of the |enso| function. 
%
%% Defining the Nino region
% To use one of the predefined Nino regions other than the default |'3.4'|,
% simply specify it like this: 

idx3 = enso(sst,t,Lat,Lon,'region','3'); 

%% 
% Loop through all the predefined Nino regions to compare: 

% List the predefined regions: 
regions = {'1+2','3','3.4','4','ONI'}; 

figure
hold on

% Loop through each region, calculate its Nino index, and plot: 
for k = 1:length(regions)
   tmp = enso(sst,t,Lat,Lon,'region',regions{k});
   plot(t,tmp)
end