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This git project is an aggregate of the scripts used for my master thesis project on the relationship between modeled DOD and emission fluxes for a 1-year (2012) simulation. (All scripts used are in R)
The simulation uses Marticorena emission scheme with 1º lat and 1.406248º lon of grid resolution and an ouput time step of 3h.
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) |
| 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
## (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)
The correlations.r script computes the R coefficient between modeled emissions and DOD on an annual and seasonal basis for every time step.
It also computes the coefficient considering a possible time-lag between emissions and DOD.
Finally, it produces this kind of plot:
## (3) Calculation of the let <img src="http://latex.codecogs.com/gif.latex?u^{*}_{t_{sd}}" border="0"/> applying the moisture and roughnes correction to <img src="http://latex.codecogs.com/gif.latex?u^{*}_t" border="0"/> [ustt_sd.r]
In this script we apply the folloring conversion:
## Data analysis of other regions
The data analysis done in this work has only considered data refering North Africa.
In order to do it for other regions one should made the following changes to the code:
* change load("NorthAfrica_......RData") -> load("RegionofInterest_......RData") at the begining of all scripts.