Objectively Diagnosing Characteristics of Mesoscale Organization from Radar Reflectivity and Ambient Winds

Author:

Short Ewan12ORCID,Lane Todd P.12,Vincent Claire L.12

Affiliation:

1. a School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Melbourne, Victoria, Australia

2. b ARC Centre of Excellence for Climate Extremes, The University of Melbourne, Melbourne, Victoria, Australia

Abstract

Abstract In the classical model of mesoscale convective systems (MCSs), a system generates new convective cells on the downshear side of its cold pool, with the cells fed at low levels from the front, and the stratiform cloud trailing behind the system in the upshear direction, where “front” and “behind” typically refer to the system’s ground-relative velocity. In this study we present an algorithm for identifying and tracking MCSs in radar reflectivity data, and objectively diagnosing organizational characteristics related to the classical model, namely, the offset of stratiform cloud from convective cloud relative to system velocity, the low-level inflow direction, and the shear-relative tilt and propagation directions. When applied to the 15-yr radar record covering the Darwin region of northern Australia, the algorithm indicates that 65%–80% of MCS observations are consistent with the classical model, at least when the four classifications can be made unambiguously. However, these observed characteristics occur almost entirely in the drier phases of the Australian monsoon. During the humid, active monsoon phase, observed characteristics consistent with the classical model are rare, and most systems exhibit nonclassical upshear propagation. Significance Statement In this study we developed a computer program for tracking large storms in radar data. The program tracks storms through time and space, recording their three-dimensional structure. Knowledge of this structure allows our program to automatically put storms into different, commonly used categories. These categories provide clues about the processes that can make storms grow, persist, or decay. Our computer program is useful because the classification process is very time consuming when done by humans. Also, when applied to radar datasets from northern Australia, our program suggests most large storms are consistent with standard theories of what make storms grow and persist. However, when the air is very humid, large storms inconsistent with standard theories become common.

Funder

Climate Extremes

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference43 articles.

1. Argonne National Laboratory, 2021: openradar/Tint. Accessed 1 February 2023, https://github.com/openradar/TINT.

2. Insights into convective momentum transport and its parametrization from idealized simulations of organized convection;Badlan, R. L.,2017

3. Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT;Belmonte Rivas, M.,2019

4. Statistical assessment of tropical convection-permitting model simulations using a cell-tracking algorithm;Caine, S.,2013

5. Climatology of linear mesoscale convective system morphology in the United States based on the random-forests method;Cui, W.,2021

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