Journal article

Global Detection and Analysis of Coastline-Associated Rainfall Using an Objective Pattern Recognition Technique

Martin Bergemann, Christian Jakob, Todd P Lane



Coastally associated rainfall is a common feature, especially in tropical and subtropical regions. However, it has been difficult to quantify the contribution of coastal rainfall features to the overall local rainfall. The authors develop a novel technique to objectively identify precipitation associated with land-sea interaction and apply it to satellite-based rainfall estimates. The Maritime Continent, the Bight of Panama, Madagascar, and the Mediterranean are found to be regions where land-sea interactions play a crucial role in the formation of precipitation. In these regions ~40%-60% of the total rainfall can be related to coastline effects. Because of its importance for the climate sys..

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University of Melbourne Researchers


Awarded by Australian Research Council's Centre of Excellence for Climate System Science

Funding Acknowledgements

We acknowledge the Australian Research Council's Centre of Excellence for Climate System Science (CE110001028) for funding this work. We would also like to thank Rit Carbone from NCAR and Chris Holloway from University of Reading for their useful suggestions and comments in the early stage of this work. Furthermore, we thank the three anonymous reviewers for their valuable comments and suggestions to improve the quality of the publication. The CMORPH satellite-based rainfall estimates were obtained from the Climate Prediction Center (CPC) of the National Oceanic and Atmospheric Administration (NOAA). The tools utilized for the pattern recognition are supplied by the open source image processing library OpenCV. The source code and documentation can be retrieved from GitHub (