#249, add notes, change sample to example

GRIB2_CodeFlag_1_4_CodeTable_en.csv

@@ -8,7 +8,7 @@ Type of data,,5,,Control and perturbed forecast products,,,,Operational
 Type of data,,6,,Processed satellite observations,,,,Operational
 Type of data,,7,,Processed radar observations,,,,Operational
 Type of data,,8,,Event probability,,,,Operational
-Type of data,,9,,Sample Data,(see Note 1),249a,,Operational
+Type of data,,9,,Example Data,(see Note 1),249a,,Operational
 Type of data,,10,,ML based forecast,(see Note 2),249b,,Operational
 Type of data,,11-191,,Reserved,,,,Operational
 Type of data,,192-254,,Reserved for local use,,,,Operational

notes/CodeFlag_notes.csv

@@ -150,3 +150,9 @@ noteID,note
 153,"The option quantile needs two additional arguments: 1) The total number of quantiles and 2) the quantile value."
 154,"These parameters are intended to be used with templates 4.121 and 4.122 in which the spatiotemporal criteria is encoded used to get a categorical yes/no per grid point of each ensemble member."
 155,"Scale Factor of Lower Limit, Scaled Value of Lower Limit, Scale Factor of Upper Limit and Scaled Value of Upper Limit must be set to missing. This entry is intended for, but not limited to, entries 5 to 7 in Code table 4.2 discipline 0 category 191."
+249a,Data for demonstrational purposes only.
+249b,Forecast from Machine Learning (ML) model.
+249c,"Combination of different forecast products to produce a smooth, continuous forecast by applying weights to each individual prediction system which depend on the lead time and forecast skill (for example, seamless prediction using nowcasting to short-range to medium-range)."
+249d,Ensemble members are initialised from different initial condition.
+249e,"Model physics are perturbed (for example, with methods like SPPT, SPP, SKEB, etc.)."
+249f,Combination of 7 and 8.