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Journal Article

A statistical model for isolated convective precipitation events


Moseley,  Christopher
Climate Modelling, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;
Wave Driven Circulations, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Moseley, C., Henneberg, O., & Haerter, J. O. (2019). A statistical model for isolated convective precipitation events. Journal of Advances in Modeling Earth Systems, 11, 360-375. doi:10.1029/2018MS001383.

Cite as: http://hdl.handle.net/21.11116/0000-0001-6FFB-9
We present a highly simplified model to describe the diurnal evolution of a convective cloud field in idealized large eddy simulations. The life cycles of individual precipitation events are detected by a storm tracking algorithm which records the autonomous appearance and decay, as well as the merging and fragmentation of convective precipitation cells. Conditioned on the area covered by each cell, the tracking method records the time evolution of the precipitation intensity, the anomalies of near-surface temperature and moisture, convective available potential energy, and convective inhibition. For tracks that do not merge or split (termed solitary), many of these quantities show generic, often nearly linear relations that hardly depend on the forcing conditions of the simulations, such as surface temperature. This finding allows us to propose a simple idealized model of precipitation events, where the surface precipitation area is circular and a cell's precipitation intensity falls off linearly with the distance from the respective cell center. The drop-off gradient is nearly independent of track duration and cell size. Multiple track properties, that is, track duration, peak, and mean intensity, as well as the associated cell area can hence be specified by knowing only one remaining parameter. In contrast to the simple and robust behavior of solitary tracks, tracks that result from merging of two or more cells show a much more complicated behavior. The most intense, long lasting, and largest tracks stem from tracks involved in repeated merging. ©2019. The Authors.