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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. [ABSTRACT FROM AUTHOR]

A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The paper highlights the algorithm's ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features. [ABSTRACT FROM AUTHOR]

This article investigates the source and impact of artifacts produced by ordered linear interpolation techniques on variationally retrieved updraft intensities. Qualitative reasoning for the generation of periodic perturbations in gridded products is presented, and a simple analytical investigation into the impact of gridding artifacts on updraft retrieval is carried out. By projecting a nonconvergent flow typical of Darwin, Australia, onto the viewing geometry of a scanning radar, a numerical assessment of the impact of gridding artifacts is carried out. A simple enhancement to ordered linear interpolation, mixed-order linear interpolation, is proposed to reduce gridding artifacts. Radial velocity grids produced using both techniques are used to investigate the generation of spurious updrafts, with the simple ordered linear interpolation technique producing erroneous updrafts on the order of 2 m s−1. To investigate the impact on vertical velocities retrieved from a real weather event, radar-derived measurements taken during the active monsoon phase of Tropical Warm Pool International Cloud Experiment are gridded using both techniques, and vertical velocities are retrieved and contrasted. [ABSTRACT FROM AUTHOR]