diff --git a/mlair/data_handler/data_handler_mixed_sampling.py b/mlair/data_handler/data_handler_mixed_sampling.py
index c56499dc543fb3805b02a7353aa32598703d9ec3..c62e18f2b69c5cc33d1bd86f5f288b61f53cdaf3 100644
--- a/mlair/data_handler/data_handler_mixed_sampling.py
+++ b/mlair/data_handler/data_handler_mixed_sampling.py
@@ -218,7 +218,7 @@ class DataHandlerSeparationOfScalesSingleStation(DataHandlerMixedSamplingWithFil
                 res_filter.append(data_filter.shift({dim: -w * delta}))
             res_filter = xr.concat(res_filter, dim=window_array).chunk()
             res.append(res_filter)
-        res = xr.concat(res, dim="filter")
+        res = xr.concat(res, dim="filter").compute()
         return res
 
     def estimate_filter_width(self):
diff --git a/mlair/helpers/statistics.py b/mlair/helpers/statistics.py
index 0b73bc27bf5621b4e6fb88bbd449d4002cd7f9ba..a8ba9795404e9f18a5ddb7449995fdc5a93eb409 100644
--- a/mlair/helpers/statistics.py
+++ b/mlair/helpers/statistics.py
@@ -669,8 +669,9 @@ class KolmogorovZurbenkoFilterMovingWindow(KolmogorovZurbenkoBaseClass):
                       self.filter_dim: wl}
             iter_vars = df_itr.coords["variables"].values
             for var in iter_vars:
-                df_itr_var = df_itr.sel(variables=[var]).chunk()
+                df_itr_var = df_itr.sel(variables=[var])
                 for _ in np.arange(0, itr):
+                    df_itr_var = df_itr_var.chunk()
                     rolling = df_itr_var.rolling(**kwargs)
                     if self.method == "median":
                         df_mv_avg_tmp = rolling.median()