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I've been using the MODIS-Aqua/L3SMI dataset to investigate sea surface temperatures (SST) for a specific region.

What I'd like to do is for a specific time epriod (could be day, week or month), find out how many of the previous weeks have had a SST anomaly of > 1 degree over the average.

To start with I've calculated the mean SST for the region over the previous ten years.

var collection = ee.ImageCollection('NASA/OCEANDATA/MODIS-Aqua/L3SMI')
  .select('sst')
  .map(function(image){return image.clip(EEZ)});

// Define reference conditions from the first 10 years of data.
 var reference = collection.filterDate('2002-01-01', '2012-12-31')

// Sort chronologically in descending order.
  .sort('system:time_start', false);

print('reference', reference)

// Compute the mean of the first 10 years.
 var mean = reference.mean();

 print('ref mean', mean)

Then subtracted than mean from the mean SST from another series of images from the region to get the SST anomaly.

var series = collection.filterDate('2016-01-01', '2018-12 31').map(function(image) {
    return image.subtract(mean).set('system:time_start', 
 image.get('system:time_start'));
 });

 print('SSTanomaly', series)

From here however, I'm not sure how to calculate how many consecutive weeks this anomaly is 1 or more before a specific date (could be a day, week or month).

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