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

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  • 1 School of Earth, Atmosphere and Environment, Faculty of Science, and ARC Centre of Excellence for Climate System Science, Monash University, Melbourne, Victoria, Australia
  • | 2 School of Earth Sciences, and ARC Centre of Excellence for Climate System Science, University of Melbourne, Melbourne, Victoria, Australia
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Abstract

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 system, the Maritime Continent is a region of particular interest, with high overall amounts of rainfall and large fractions resulting from land–sea interactions throughout the year. To demonstrate the utility of this study’s identification method, the authors investigate the influence of several modes of variability, such as the Madden–Julian oscillation and the El Niño–Southern Oscillation, on coastal rainfall behavior. The results suggest that during large-scale suppressed convective conditions, coastal effects tend to modulate the rainfall over the Maritime Continent leading to enhanced rainfall over land regions compared to the surrounding oceans. The authors propose that the novel objective dataset of coastally influenced precipitation can be used in a variety of ways, such as to inform cumulus parameterization or as an additional tool for evaluating the simulation of coastal precipitation within weather and climate models.

Corresponding author address: Martin Bergemann, School of Earth, Atmosphere and Environment, Monash University, Melbourne VIC 3800, Australia. E-mail: martin.bergemann@monash.edu

Abstract

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 system, the Maritime Continent is a region of particular interest, with high overall amounts of rainfall and large fractions resulting from land–sea interactions throughout the year. To demonstrate the utility of this study’s identification method, the authors investigate the influence of several modes of variability, such as the Madden–Julian oscillation and the El Niño–Southern Oscillation, on coastal rainfall behavior. The results suggest that during large-scale suppressed convective conditions, coastal effects tend to modulate the rainfall over the Maritime Continent leading to enhanced rainfall over land regions compared to the surrounding oceans. The authors propose that the novel objective dataset of coastally influenced precipitation can be used in a variety of ways, such as to inform cumulus parameterization or as an additional tool for evaluating the simulation of coastal precipitation within weather and climate models.

Corresponding author address: Martin Bergemann, School of Earth, Atmosphere and Environment, Monash University, Melbourne VIC 3800, Australia. E-mail: martin.bergemann@monash.edu
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