Authors: Coumba Niang, Ana Maria Mancho (ICMAT-CSIC), Víctor José García-Garrido, Elsa Mohino, Belén Rodriguez-Fonseca and Jezabel Curbelo
Source: Scientific Reports
Date of publication: 27 July 2020
The West African Monsoon (WAM) system is the main source of rainfall in the agriculturally based region of the Sahel. Understanding transport across the WAM is of crucial importance due to the strong impact of humidity and dust pathways on local cloud formation. In general, predicting rainfall in tropical Africa is exceedingly difficult; our standard weather models rarely provide accurate forecasts even a day out. That’s partly due to a lack of observations in the region and partly because those models were developed in more temperate regions like the United States and Europe, which have different climate and atmospheric dynamics.
In this article, an interdisciplinary team used daily averages of nearly 40 years of horizontal and vertical wind velocity observations from the European Centre for Medium-Range Weather Forecasts’ ERA-Interim meteorological analysis data set to identify the mean velocity fields during the month of August—the peak month of the monsoon. Climatologists have long used these mean climatological velocity fields to paint a broad picture of transport within the monsoon. Here the team applied a tool from dynamical systems theory called Lagrangian descriptors to gain deeper insights into the source and mixture of moisture and dust through the atmospheric features of the monsoon, including the African Easterly Jet and the Tropical Easterly Jet. Their method provides a geometrical partition in a 3D flow, which identifies mixing regions in the atmosphere for moisture-bearing particles originated on the ocean surface and dust-bearing ones coming from the land surface.
The new method could inform drought assessments because it can identify where humidity and dust mix and these conditions favor the formation of clouds. How these essential components for cloud formation are mixed up and in what proportion has not been previously described. For this reason, the tool opens new possibilities that could improve cloud parameterization or could provide more accurate drought indices. However further work is needed in this direction to achieve these goals.