A Lagrangian approach for investigating anomalies in the moisture transport during drought episodes

A. Drumond; R. Nieto; L. Gimeno

doi:10.18172/cig.2925

Authors

A. Drumond Universidade de Vigo
R. Nieto Universidade de Vigo
L. Gimeno Universidade de Vigo

DOI:

https://doi.org/10.18172/cig.2925

Keywords:

moisture transport, drought, Lagrangian approach

Abstract

The present work proposes a Lagrangian diagnostic scheme to investigate the anomalous moisture transport before, during, and after the occurrence of drought episodes. The Lagrangian approach proposed here uses the model FLEXPART integrated with the ERA-Interim data set and it has been successfully applied in previous studies concerning the climatological characterization of the sources and sinks of moisture in several regions around the world. The drought episodes will be identified and characterized through the SPEI index. The anomalies of the moisture sources for the area affected will be analyzed, as well as the impact of the droughts on the moisture transport from the area affected towards its climatological sinks (previous studies suggest that some heat wave episodes can be associated with anomalies in moisture transport). In other words, the methodology proposes to investigate the role of the area affected as a receptor/source of moisture during the drought episodes. As an example of applicability of the methodology, the severe drought episode over central U.S. in 2012 is analyzed. An analysis of the 2012 anomalies suggests that there was some reduction in the contribution from the local and continental climatological moisture sources for the central U.S. mainly from June to October. The period from July to October 2012 was also characterized by the reduction of the moisture transport from the drought area towards its climatological sinks located over northeastern North America. A better understanding not only of the transport of humidity, but also of the relationship between sources/sinks of moisture and of possible impacts generated by variations in the sources is crucial for a more accurate weather forecast, helping to minimize the consequences of the natural hazards.

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