home.md

@@ -12,33 +12,8 @@ graph LR
 ```
 
 ## [makematrix.r](makematrix.r)
-## (1) Loading data for different regions [makematrix.r]
-First step is to get the necessary data from esarchive and saving it in .RData format for separate regions.
-
-Regions selected are:
-
-| Region id | Region Name | Lower Left Corner | Upper Right Corner |
-| ------ | ------ | ------ | ------ | 
-| 1 | NorthAfrica | (28.13W,1N)| (36.56E,41N) | 
-| 2 | SouthAfrica |  (5.62E,35S)| (56.24E,1S) | 
-| 3 | MiddleEast | (35.16E,1S)| (66.09E,41N) | 
-| 4 | NorthwestAsia | (50.62E,36N)| (75.94E,51N) | 
-| 5 | SouthwestAsia |  (66.09E,5N)| (93.03E,36N) | 
-| 6 | NortheastAsia | (70.31EE,31N)| (151.87E,61N) | 
-| 7 | Australia | (101.25E,50S)| (181.41E,1S) | 
-| 8 | SouthAmerica | (85.78W,60S)| (29.53W,15N) | 
-| 9 | NorthAmerica | (160.31W,10N)| (49.22W,71N) | 
-| 10 | Europe | (19.69W,36N)| (50.62E,77N) | 
-
-data extracted is:
-
-*  od550duco <- DOD 550 nm coarse 
-* emidu <- [kg/m²]
-* ustar <- u* [m/s]
-* ustt <- u* threshold [m/s]
-* roughcor <- roughness correction
-* smoiscor <- moisture correction
 
+## [correlations.r](correlations.r)
 ## (2) Correlation between DOD-emission for different time of the day and season [correlations.r]
 (the following scripts and figures correspond to the analysis of the North African region, how)