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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]

In this paper, statistical properties of rainfall are derived from 14 years of Tropical Rainfall Measuring Mission data to optimize the use of flight hours for the upcoming High Altitude Ice Crystals (HAIC)/High Ice Water Content (HIWC) program. This program aims to investigate the convective processes responsible for the generation of the high ice water content that has been recognized as a threat to civil aviation. The probability that convective cells are conducive to HIWC is also further investigated using three years of C-band polarimetric radar data. Further insights into the variability of convective rainfall and favorable conditions for HIWC are also gained using two different methods to characterize the large-scale atmospheric conditions around Darwin, Australia (the Madden-Julian oscillation and the Darwin atmospheric regimes), and the underlying surface type (oceanic vs continental). The main results from the climatology relevant to flight-plan decision making are (i) convective cells conducive to HIWC should be found close to Darwin, (ii) at least 90% of convective cells are conducive to HIWC at 10- and 12-km flight levels, (iii) multiple flights per day in favorable large-scale conditions will be needed so as to utilize the 150 project flight hours, (iv) the largest numbers of HIWC radar pixels are found around 0300 and 1500 local time, and (v) to fulfill the requirement to fly 90 h in oceanic convection and 60 h in or around continental convection, a minimum 'acceptable' size of the convective area has been derived and should serve as a guideline for flight-decision purposes. [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]

Comparisons are made between the reflectivity Z, median volume diameter D0, and rain rate R from a dual-frequency profiler and the C-band polarimetric radar (C-POL), which are both located near Darwin, Australia. Examples from the premonsoon “buildup” regime and the monsoon (oceanic) regime are used to illustrate the excellent agreement between the dual-profiler retrievals and the polarimetric radar-based retrievals. This work builds on similar works that were limited in scope to shallow tropical showers and predominantly stratiform rain events. The dual-frequency profiler retrievals of D0 and R herein are based on ensemble statistics, whereas the polarimetric radar retrievals are based on algorithms derived by using one season of disdrometer data from Darwin along with scattering simulations. The latest drop shape versus D relation is used as well as the canting angle distribution results obtained from the 80-m fall bridge experiment in the scattering simulations. The scatterplot of D0 from dual-frequency profiler versus Zdr measurements from C-POL is shown to be consistent not only with the theoretical simulations and prior data but also within prior predicted error bars for both stratiform rain as well as convective rain. Based on dual-frequency profiler–retrieved gamma drop size distribution parameters, a new smoothly varying “separator” indexing scheme has been developed that classifies between stratiform and convective rain types, including a continuous “transition” region between the two. This indexing technique has been applied on a number of low-elevation-angle plan position indicator (PPI) sweeps with the C-POL from the two regime examples, to construct “unconditioned” histograms of D0 in stratiform and convective rain (to within the sensitivity of the radar). With reference to the latter, it is demonstrated that the distribution of D0 is different in the buildup example than in the monsoon example, because of the differences in both the microphysical and kinematic features between the two regimes. In particular, (i) the mean D0 is significantly larger in the buildup example than in the monsoon example, irrespective of rain type; (ii) the histogram width (or standard deviation) is much larger for the buildup example than the monsoon example, irrespective of rain type; and (iii) the histogram skewness is negative for the monsoon regime example because of a lack of larger D0 values, whereas the buildup histogram is positively skewed irrespective of rain type. [ABSTRACT FROM AUTHOR]

A model of rain shaft microphysics that solves the stochastic advection–coalescence–breakup equation in an atmospheric column was used to simulate the evolution of a stratiform rainfall event during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) in Darwin, Australia. For the first time, a dynamic simulation of the evolution of the drop spectra within a one-dimensional rain shaft is performed using realistic boundary conditions retrieved from real rain events. Droplet size distribution (DSD) retrieved from vertically pointing radar (VPR) measurements are sequentially imposed at the top of the rain shaft as boundary conditions to emulate a realistic rain event. Time series of model profiles of integral parameters such as reflectivity, rain rate, and liquid water content were subsequently compared with estimates retrieved from vertically pointing radars and Joss–Waldvogel disdrometer (JWD) observations. Results obtained are within the VPR retrieval uncertainty estimates. Besides evaluating the model’s ability to capture the dynamical evolution of the DSD within the rain shaft, a case study was conducted to assess the potential use of the model as a physically based interpolator to improve radar retrieval at low levels in the atmosphere. Numerical results showed that relative improvements on the order of 90% in the estimation of rain rate and liquid water content can be achieved close to the ground where the VPR estimates are less reliable. These findings raise important questions with regard to the importance of bin resolution and the lack of sensitivity for small raindrop size (<0.03 cm) in the interpretation of JWD data, and the implications of using disdrometer data to calibrate radar algorithms. [ABSTRACT FROM AUTHOR]

Two different frequency radar wind profilers (920 and 50 MHz) were used to retrieve rain rates from a long-lasting rainfall event observed near Darwin, Northern Territory, Australia, during the 1993-94 wet season. In this technique, 50-MHz data are used to derive the vertical air motion parameters (vertical velocity and spectral width); the 920-MHz data are then used to obtain the precipitation characteristics with the vertical air motion corrections. A comparison of the retrieved rain rates with rain gauge measurements shows excellent agreement. A detailed examination of the mean vertical velocity and spectral width corrections in the rain retrieval shows that the error due to an uncorrected mean vertical velocity can be as large as 100%, and the error for an uncorrected spectral width was about 10% for the range of mean vertical velocity and spectral width considered. There was a strong functional dependence between the retrieved mean vertical velocity and percentage difference between observed and retrieved rain rates with and without vertical air motion corrections. The corresponding functional dependence with and without the spectral width corrections was small but significant. An uncorrected upward mean vertical velocity overestimates rain rates, whereas an uncorrected downward mean vertical velocity underestimates rain rates. Uncorrected spectral width estimates have a tendency to overestimate rain rates. There are additional errors in the width correction because of antenna beam mismatching. A method is discussed to quantitatively evaluate this effect, and it is shown to be relatively small compared to the first-order mean vertical velocity correction. [ABSTRACT FROM AUTHOR]