diff --git a/docs/FunctionDescriptions.md b/docs/FunctionDescriptions.md
index 3e77e97cbbee247ce9a48a8d2fe5024b59732670..b6dad5a13f67c12920ee2e6dc49da9f48627868d 100644
--- a/docs/FunctionDescriptions.md
+++ b/docs/FunctionDescriptions.md
@@ -710,19 +710,57 @@ Key word overview:
       if there is one available in the succeeding sampling interval. If not, BAD - flag gets assigned.
     * `"nearest_shift"`: every grid point gets assigned the flag in its range. ( range = +/- `freq`/2 ).
     * Extra flag fields like "comment", just get shifted along with the flag. 
-      Only inserted flags for empty intervals will signified by the set flag routine of the current flagger..
+      Only inserted flags for empty intervals will get signified by the set flag routine of the current flagger.
       Set `set_shift_comment` to `True`,  to apply setFlags signification to all flags.
 2. Aggregations:
-    * `"fagg"`: all falgs in a sampling interval get aggregated with the function passed to `agg_method`
+    * `"fagg"`: all flags in a sampling interval get aggregated with the function passed to `agg_method`
                 , and the result gets assigned to the last grid point.
     * `"bagg"`: all flags in a sampling interval get aggregated with the function passed to `agg_method`
                 , and the result gets assigned to the next grid point.
     * `"nearest_agg"`: all flags in the range (+/- freq/2) of a grid point get 
                        aggregated with the function passed to agg_method and assigned to it.
 
+## `deharmonize`
 
+### Signature
+```
+deharmonize(co_flagging)
+```
+### Parameters
+| parameter | data type | default value | description |
+| --------- | --------- | ------------- | ----------- |
+| co_flagging       | boolean     |               |  |
 
 
+### Description
+
+After having calculated flags on an equidistant frequency grid, generated by 
+a call to a harmonization function, you may want to project
+that new flags on to the original data index, or just restore the 
+original data shape. Then a call to `deharmonize` will do exactly that.
+
+`deharmonize` will check for harmonization information for the variable it is 
+applied on (automatically generated by any call to a harmonization function of that variable) 
+and than:
+
+1. Overwrite the harmonized data series with the original dataseries and its timestamps.
+2. Project the calculated flags onto the original index, by inverting the 
+  flag projection method used for harmonization, meaning, that:
+    * if the flags got shifted or aggregated forward, either the flag associated with the ultimatly preceeding 
+      original timestamp, to the harmonized flag (`co_flagging`=`False`),
+      or all the flags, coverd by the harmonized flags preceeding sampling intervall (`co_flagging`=`True`)
+      get overwritten with the harmonized flag - if they are "better" than this harmonized flag. 
+      (According to the flagging order of the current flagger.) 
+    * if the flags got shifted or aggregated backwards, either the flag associated with the first succeeding 
+      original timestamp, to the harmonized flag (`co_flagging`=`False`),
+      or all the flags, coverd by the harmonized flags succeeding sampling intervall (`co_flagging`=`True`)
+      get overwritten with the harmonized flag - if they are "better" than this harmonized flag. 
+      (According to the flagging order of the current flagger.)  
+    * if the flags got shifted or aggregated to the nearest harmonic index, 
+      either the flag associated with the flag, nearest, to the harmonized flag (`co_flagging`=`False`),
+      or all the flags, covered by the harmonized flags range (`co_flagging`=`True`)
+      get overwritten with the harmonized flag - if they are "better" than this harmonized flag. 
+      (According to the flagging order of the current flagger.)