Update README.md

README.md

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 ## Motivation
 
-(Add a few sentences stating why this cookbook will be useful. What skills will you, "the chef", gain once you have reached the end of the cookbook?)
+Several meteorological and land surface factors have been found to impact Saharan dust emissions and transport. Dust mobilization occurs when surface wind speed of suitable magnitude is above a threshold velocity, often computed based on soil characteristics, vegetation, and solid particles. The purpose of this cookbook is to understand the relationship between dust and some meteorological variables using self-organizing maps ([SOM](ttps://medium.com/machine-learning-researcher/self-organizing-map-som-c296561e2117)), random forest regression ([RF](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html)), and principal component analysis (PCA). The question we are really interested in with this cookbook is to know which variables are the most predictive of dust emissions. 
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+For experimenting purpose, we consider PM10 concentration (PM10), 2m temperature (T2), 2m relative humidity (rh2), planetary boundary layer height (PBLH), 10m wind speed (wind_speed_10m), 925hPa wind speed (wind_speed_925hPa), horizontal wind at 10m (U10), meridional wind at 10m (V10), and convective rainfall (RAINC). This cookbook seeks to establish a clear relationship between the meteorological variables and dust (PM10).
 
 ## Authors