Calculating daily max and min temperature data from GLDAS over several years using Google Earth Engine

Question

I am still new to the Google Earth Engine and try to calculate the daily max and min temperature based on the GLDAS. Could you advise me on how I correct this code to calculate daily max and min temperature?

var startDate = ee.Date('2018-01-01');
var endDate = ee.Date('2021-01-01');

// Specify Country names
var worldcountries = ee.FeatureCollection('FAO/GAUL/2015/level2');

var filterCountry = ee.Filter.eq('ADM2_NAME', 'Kurgantepa district');

var country = worldcountries.filter(filterCountry);

Map.addLayer(country);
Map.centerObject(country, 10);

var dataset = ee.ImageCollection("NASA/GLDAS/V021/NOAH/G025/T3H")
  .select('Tair_f_inst')
  .filterDate(startDate, endDate);

var list_dataset = dataset.toList(dataset.size());

print(list_dataset);


var getTemperature = function(image) {

  var value_temperat = ee.Image(image)
    .reduceRegion(ee.Reducer.first(), country)
    .get('Tair_f_inst');

var temperat_K = ee.Number(value_temperat); 

  return temperat_K;
};

var count = dataset.size();

var temperat_list = dataset.toList(count).map(getTemperature);

print("Tair_f_inst list", temperat_list);

var allDates = ee.List(dataset.aggregate_array('system:time_start'));

var allDatesSimple = allDates.map(function(date){
  return ee.Date(date).format().slice(0,10);
  });

print(allDatesSimple);

var len = temperat_list.size();

print(len);

var paired = allDatesSimple.zip(temperat_list);

print (paired);

var title = {
  title: 'Daily Temperature',
  hAxis: {title: 'Time'},
  vAxis: {title: 'Temperature (K)'},
};

var chartDaily = ui.Chart.image.seriesByRegion({
  imageCollection: dataset, 
  regions: country,
  reducer: ee.Reducer.mean(),
  band: 'Tair_f_inst',
  scale: 5000,
  xProperty: 'system:time_start',
  seriesProperty: 'SITE'
}).setOptions(title)
  .setChartType('ColumnChart');

print(chartDaily);

var myFeatures = ee.FeatureCollection(paired.map(function(el){
  el = ee.List(el); // cast every element of the list
  var geom = country;
  return ee.Feature(null, {
    'date': ee.String(el.get(0)),
    'value':ee.Number(el.get(1))
  });
}));

//print(myFeatures);

// Export features, specifying corresponding names.
Export.table.toDrive(myFeatures,
"Temperature", //my task
"GEE_Folder", //my export folder
"daily_temperat",  //file name
"CSV");

Answer 1

GLDAS products have images with climatic elements for each three hours so, you will have 8 values per day of temperatures. In this case, you need to map your temperatures list for slicing each eight values. In these slices, you can apply a min reducer for minimum temperatures and a max reducer for maximum temperatures. However, produced temperatures list must be paired with distinct dates list (not with original dates list with 8 times values). Following script works as expected.

var startDate = ee.Date('2018-01-01');
var endDate = ee.Date('2021-01-01'); 

// Specify Country names
var worldcountries = ee.FeatureCollection('FAO/GAUL/2015/level2');

var filterCountry = ee.Filter.eq('ADM2_NAME', 'Kurgantepa district');

var country = worldcountries.filter(filterCountry);

Map.addLayer(country);
Map.centerObject(country, 10);

var dataset = ee.ImageCollection("NASA/GLDAS/V021/NOAH/G025/T3H")
  .select('Tair_f_inst')
  .filterDate(startDate, endDate);

var list_dataset = dataset.toList(dataset.size());

print(list_dataset);

var getTemperature = function(image) {

  var value_temperat = ee.Image(image)
    .reduceRegion(ee.Reducer.mean(), country)
    .get('Tair_f_inst');

  return value_temperat;

};

var count = dataset.size();

var temperat_list = dataset.toList(count).map(getTemperature);

//print("Tair_f_inst list", temperat_list);

var len = temperat_list.size();

var list = ee.List.sequence(0, len.subtract(1), 8);

var temp_list = list.map(function(ele){

  var start = ee.Number(ele).int(); 
  var end = ee.Number(ele).add(8).int(); 

  var new_list = ee.List([]);
  var element = ee.List(temperat_list.slice(start, end)).reduce(ee.Reducer.min());

  new_list = new_list.add(element);
  
  var element2 = ee.List(temperat_list.slice(start, end)).reduce(ee.Reducer.max());

  new_list = new_list.add(element2);

  return new_list;

});

print("temp_list", temp_list);

var allDates = ee.List(dataset.aggregate_array('system:time_start'));

var allDatesSimple = allDates.map(function(date){
  return ee.Date(date).format().slice(0,10);
  }).distinct();

print("distinct dates list", allDatesSimple);

var len = temperat_list.size();

//print(len);

var paired = allDatesSimple.zip(temp_list);

print ("paired list", paired);

var title = {
  title: 'Daily Temperature',
  hAxis: {title: 'Time'},
  vAxis: {title: 'Temperature (K)'},
};

var chartDaily = ui.Chart.image.seriesByRegion({
  imageCollection: dataset, 
  regions: country,
  reducer: ee.Reducer.mean(),
  band: 'Tair_f_inst',
  scale: 5000,
  xProperty: 'system:time_start',
  seriesProperty: 'SITE'
}).setOptions(title)
  .setChartType('ColumnChart');

//print(chartDaily);

var myFeatures = ee.FeatureCollection(paired.map(function(el){
  el = ee.List(el); // cast every element of the list
  var geom = country;
  return ee.Feature(null, {
    'date': ee.String(el.get(0)),
    'Tmin':ee.Number(ee.List(el.get(1)).get(0)),
    'Tmax':ee.Number(ee.List(el.get(1)).get(1))
  });
}));

//print(myFeatures);

// Export features, specifying corresponding names.
Export.table.toDrive(myFeatures,
"Temperature", //my task
"GEE_Folder", //my export folder
"daily_temperat",  //file name
"CSV");

After running above script in GEE console editor, you can see an extract of obtained CSV as follows:

system:index,Tmax,Tmin,date,.geo
0,283.12159660270623,274.85638262774495,2018-01-01,
1,283.22070862366274,274.42199638297967,2018-01-02,
2,283.75842133943024,275.1772416948198,2018-01-03,
3,281.7471648894989,275.3844425785649,2018-01-04,
4,280.8100086933858,274.43567458144184,2018-01-05,
5,282.165957064242,273.98338400351037,2018-01-06,
6,282.7080238960885,275.0355672750387,2018-01-07,
7,281.14597712336354,274.04015618401604,2018-01-08,
8,280.4689321432028,273.21697956806906,2018-01-09,
9,281.3570821951102,273.7503255208333,2018-01-10,
10,275.70246337340757,273.3154177279086,2018-01-11, 
.
.
.