Return to Revisions

answering your other question about how to get one Image for each month:

    // Set years and month
    var startYear = 1981;
    var endYear = 2019;
    var years = ee.List.sequence(startYear, endYear);
    var months = ee.List.sequence(1,12);
    // load the image collection
    var Daily = ee.ImageCollection('MODIS/MOD13A1').select(1)
    .filterBounds(YourBound);

    print(Daily, "Daily prec data from 1981-2019")

    // make monthly summed mosaics
   // loop over the years and months to get summed monthly images
   var byMonth = ee.ImageCollection(ee.FeatureCollection(years.map(function(y){
   var yearCollection = Daily.filter(ee.Filter.calendarRange(y, y, 'year'));
   var byYear = ee.ImageCollection.fromImages(
   months.map(function(m) {
   var summedImage = yearCollection.filter(ee.Filter.calendarRange(m, m, 'month'))
              .reduce(ee.Reducer.sum()); 
   var date = ee.Date.fromYMD(y, m, 5).format("MM_dd_YYYY");
  return summedImage.set('system:time_start', ee.Date.fromYMD(y, m, 5))
  .rename(date)
  .reduce(ee.Reducer.mean());
   //.set('month', m).set('year', y); // eventually set year and month 
   }));
   return byYear;
    })).flatten());
   // filter the empty one out
   var outputMonthly = byMonth.filter(ee.Filter.listContains('system:band_names', 
     'constant').not())
                .sort('system:time_start').toBands();
   print(outputMonthly);

  var features = outputMonthly.reduceRegions(YourBound, ee.Reducer.first(), 30);
  print(features);

    Export.image.toDrive({image: features,
  description: "CHIRPS_monthly_mean_1981-2019", 
  scale: 3000,
  folder: "CHIRPS_months",
  region: YourBound});