overwrite one dataframe with values from another dataframe based on repeated datetime indexes

you just need to use combine_first backwards. We can also use 'Location' as index instead groupby.cumcount

df3 = (df1.set_index('Location', append=True)
          .combine_first(df.set_index('Location', append=True))
          .reset_index(level='Location')
          .reindex(columns=df.columns)
          .sort_values('Location'))

print(df3)

                     Location  MeanT   MaxT   MinT
2020-05-18-12:00:00         2   28.0    0.0    9.0
2020-05-19-12:00:00         2  912.0  991.0  915.0
2020-05-20-12:00:00         2  936.0  917.0  965.0
2020-05-18-12:00:00         3    2.0    7.0    7.0
2020-05-19-12:00:00         3  918.0  977.0  901.0
2020-05-20-12:00:00         3  974.0  971.0  927.0
2020-05-18-12:00:00         4   10.0   12.0   25.0
2020-05-19-12:00:00         4  979.0  929.0  953.0
2020-05-20-12:00:00         4  988.0  955.0  939.0
2020-05-18-12:00:00         5    1.0    8.0   11.0
2020-05-19-12:00:00         5  969.0  983.0  940.0
2020-05-20-12:00:00         5  902.0  904.0  916.0
2020-05-18-12:00:00         6   25.0   10.0   26.0
2020-05-19-12:00:00         6  983.0  942.0  965.0
2020-05-20-12:00:00         6  928.0  994.0  933.0