Journal article

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

Martin Bergemann, Christian Jakob, Todd P Lane

JOURNAL OF CLIMATE | AMER METEOROLOGICAL SOC | Published : 2015

University of Melbourne Researchers

Grants

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 (http://dx.doi.org/10.5281/zenodo.18173).