diff --git a/CHANGELOG.md b/CHANGELOG.md
index d07edf7e29..cf169c6aa5 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,6 +8,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/)
 AQUA core complete list:
 
 AQUA diagnostics complete list:
+- ECmean: Enable time selection (#2761)
 
 ## [v0.19.10]
 
diff --git a/src/aqua_diagnostics/ecmean/cli_ecmean.py b/src/aqua_diagnostics/ecmean/cli_ecmean.py
index 8360581160..4affa553f6 100755
--- a/src/aqua_diagnostics/ecmean/cli_ecmean.py
+++ b/src/aqua_diagnostics/ecmean/cli_ecmean.py
@@ -50,6 +50,7 @@ def parse_arguments(arguments):
 def reader_data(model, exp, source,
                 catalog=None, regrid='r100',
                 keep_vars=None, loglevel='WARNING',
+                startdate=None, enddate=None,
                 reader_kwargs: dict = {}):
     """
     Simple function to retrieve and do some operation on reader data
@@ -60,6 +61,8 @@ def reader_data(model, exp, source,
         source (str): source of the data
         catalog (str, optional): catalog to be used, defaults to None
         regrid (str, optional): regrid method, defaults to 'r100'
+        startdate (str, optional): start date in the format YYYY-MM-DD, defaults to None
+        enddate (str, optional): end date in the format YYYY-MM-DD, defaults to None
         keep_vars (list, optional): list of variables to keep, defaults to None
         loglevel (str, optional): logging level, defaults to 'WARNING'
         reader_kwargs (dict, optional): list of reader_kwargs. Defaults to {}.
@@ -77,21 +80,22 @@ def reader_data(model, exp, source,
     # Try to read the data, if dataset is not available return None
     try:
         reader = Reader(
-            model=model, exp=exp, source=source, catalog=catalog, 
+            model=model, exp=exp, source=source, catalog=catalog,
             regrid=regrid, **reader_kwargs
         )
-        xfield = reader.retrieve()
-        if regrid is not None:
-            xfield = reader.regrid(xfield)
-
+        xfield = reader.retrieve(startdate=startdate, enddate=enddate, var=keep_vars)
     except Exception as err:
         reader_logger.error('Error while reading model %s: %s', model, err)
         return None
+    
+    # regrid after variable selection
+    if regrid is not None:
+        try: 
+            return reader.regrid(xfield)
+        except Exception as err:
+            reader_logger.error('Error while regridding model %s: %s', model, err)
+            return None
 
-    # return only vars that are available: slower but avoid reader failures
-    if keep_vars is None:
-        return xfield
-    return xfield[[value for value in keep_vars if value in xfield.data_vars]]
 
 def data_check(data_atm, data_oce, logger=None):
     """
@@ -289,11 +293,13 @@ def set_description(diagnostic, model, exp, year1, year2, config):
             logger.info('Loading atmospheric data %s', model)
             data_atm = reader_data(model=model, exp=exp, source=source_atm,
                                    catalog=catalog, keep_vars=atm_vars, regrid=regrid,
+                                   startdate=startdate, enddate=enddate,
                                    reader_kwargs=reader_kwargs)
 
             logger.info('Loading oceanic data from %s', model)
             data_oce = reader_data(model=model, exp=exp, source=source_oce,
                                    catalog=catalog, keep_vars=oce_vars, regrid=regrid,
+                                   startdate=startdate, enddate=enddate,
                                    reader_kwargs=reader_kwargs)
 
             # check the data
@@ -329,6 +335,7 @@ def set_description(diagnostic, model, exp, year1, year2, config):
             elif diagnostic == 'global_mean':
                 ecmean.store(yamlfile=filename_dict['yml'], tablefile=filename_dict['txt'])
             ecmean_fig = ecmean.plot(diagname=diagnostic, returnfig=True, storefig=False)
+
             if save_pdf:
                 logger.info('Saving PDF %s plot...', diagnostic)
                 outputsaver.save_pdf(fig=ecmean_fig, diagnostic_product=diagnostic,