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contributor authorColin, Maxime
contributor authorSherwood, Steven
contributor authorGeoffroy, Olivier
contributor authorBony, Sandrine
contributor authorFuchs, David
date accessioned2019-10-05T06:50:30Z
date available2019-10-05T06:50:30Z
date copyright12/18/2018 12:00:00 AM
date issued2018
identifier otherJAS-D-18-0036.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263588
description abstractAbstractConvection is often assumed to be controlled by the simultaneous environmental fields. But to what extent does it also remember its past behavior? This study proposes a new framework in which the memory of previous convective-scale behavior, ?microstate memory,? is distinguished from macrostate memory, and conducts numerical experiments to reveal these memory types. A suite of idealized, cloud-resolving radiative?convective equilibrium simulations in a 200-km square domain is performed with the Weather Research and Forecasting (WRF) Model. Three deep convective cases are analyzed: unorganized, organized by low-level wind shear, and self-aggregated. The systematic responses to sudden horizontal homogenization of various fields, in various atmospheric layers, designed to eliminate their specific microstructure, are compared in terms of precipitation change and time of recovery to equilibrium. Results imply a substantial role for microstate memory. Across organization types, microstructure in water vapor and temperature has a larger and longer-lasting effect on convection than in winds or hydrometeors. Microstructure in the subcloud layer or the shallow cloud layer has more impact than in the free troposphere. The recovery time scale dramatically increases from unorganized (2?3 h) to organized cases (24 h or more). Longer-time-scale adjustments also occur and appear to involve both small-scale structures and domain-mean fields. These results indicate that most convective microstate memory is stored in low-level thermodynamic structures, potentially involving cold pools and hot thermals. This memory appears strongly enhanced by convective organization. Implications of these results for parameterizing convection are discussed.
publisherAmerican Meteorological Society
titleIdentifying the Sources of Convective Memory in Cloud-Resolving Simulations
typeJournal Paper
journal volume76
journal issue3
journal titleJournal of the Atmospheric Sciences
identifier doi10.1175/JAS-D-18-0036.1
journal fristpage947
journal lastpage962
treeJournal of the Atmospheric Sciences:;2018:;volume 076:;issue 003
contenttypeFulltext


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