Search Results

You are looking at 1 - 10 of 27 items for

  • Author or Editor: Michael I. Biggerstaff x
  • Refine by Access: All Content x
Clear All Modify Search
Eun-Kyoung Seo and Michael I. Biggerstaff

Abstract

The impact of model microphysics on the retrieval of cloud properties based on passive microwave observations was examined using a three-dimensional, nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over ocean. Two microphysical schemes, based on similar bulk two-class liquid and three-class ice parameterizations, were used to simulate storms with differing amounts of supercooled cloud water typical of both the tropical oceanic environment, in which there is little supercooled cloud water, and midlatitude continental environments in which supercooled cloud water is more plentiful. For convective surface-level rain rates, the uncertainty varied between 20% and 60% depending on which combination of passive and active microwave observations was used in the retrieval. The uncertainty in surface rain rate did not depend on the microphysical scheme or the parameter settings except for retrievals over stratiform regions based on 85-GHz brightness temperatures TB alone or 85-GHz TB and radar reflectivity combined. In contrast, systematic differences in the treatment of the production of cloud water, cloud ice, and snow between the parameterization schemes coupled with the low correlation between those properties and the passive microwave TB examined here led to significant differences in the uncertainty in retrievals of those cloud properties and latent heating. The variability in uncertainty of hydrometeor structure and latent heating associated with the different microphysical parameterizations exceeded the inherent variability in TB–cloud property relations. This was true at the finescales of the cloud model as well as at scales consistent with satellite footprints in which the inherent variability in TB–cloud property relations are reduced by area averaging.

Full access
Eun-Kyoung Seo and Michael I. Biggerstaff

Abstract

Empirical orthogonal function (EOF) analysis of radiance vectors associated with emission and scattering indices for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) has been performed to examine the regional variability in relations between brightness temperature and rain rate over portions of the tropical oceans known to exhibit regional differences due to different thermodynamic environments and different large-scale forcing. The TMI indices and rain rates used in this study are the products of the Goddard profiling algorithm (GPROF), version 6. The EOF framework reduces the nine-dimensional space of the brightness temperatures and their polarizations to just two dimensions associated with the EOF coefficients. Vertical profiles of reflectivity from the TRMM precipitation radar (PR) are used to show that the statistically obtained EOFs represent bulk physical characteristics of raining clouds. Hence, EOF analysis provides an efficient framework for diagnosing regional differences in cloud structures that affect brightness temperature–rain-rate relations. The EOF framework revealed fundamental differences in the behavior of TMI surface rain-rate retrievals versus retrievals that are based on the PR aboard the TRMM satellite. In EOF space, TMI rain rates were bimodally distributed, with one mode indicating higher rain rates with greater high-density ice and rainwater content in the cloud and the other mode being consistent with moderately heavy warm rain from shallow convection. In contrast, the PR rain-rate distribution showed high rain rates being assigned over a much greater diversity of cloud structures. The manifold of EOF space constructively shows that, of the regions examined here, the tropical northwestern Pacific Ocean region produces the greatest occurrence of particularly strong cumulonimbus clouds.

Full access
Michael I. Biggerstaff and Steven A. Listemaa

Abstract

An improved algorithm for the partitioning of radar reflectivity into convective and stratiform rain classifications has been developed and tested using data from the Houston, Texas, Weather Surveillance Radar-1988 Doppler. The algorithm starts with output from the current operational version of the Tropical Rainfall Measuring Mission (TRMM) convective/stratiform classification scheme for the ground-based validation sites and corrects the output based on physical characteristics of convective and stratiform rain diagnosed from the three-dimensional structure of the radar reflectivity field. The modified algorithm improved the performance of echo classification by correcting two main sources of error. Heavy stratiform rain, originally classified as convective, and the periphery of convective cores, originally classified as stratiform, were both reclassified by the modified algorithm. When applied to a large dataset of convective storms comprising squall lines, unorganized convection, and embedded convection, it was found that roughly 25% of the total echo area and 14% of the total rain volume were reclassified. The magnitudes of the differences between the original and modified algorithms varied with the morphology of the storm system, suggesting that the quality of current echo classification information supplied by the TRMM program could vary by location depending on the structure of the dominant precipitation systems within a given region. The analysis presented here helps to establish the level of uncertainty in the existing echo classification products available from TRMM.

Full access
Michael I. Biggerstaff and Robert A. Houze Jr.

Abstract

A high-resolution composite analysis covering the entire breadth of the northern portion of a mature leading-line, trailing stratiform squall-line system reveals that mean subsidence observed in the transition zone consisted of two different types of average downdraft: one at upper levels that was mechanically forced and one at lower levels that was microphysically forced. Both the upper-level and lower-level mean downdrafts in the transition zone appeared to be the average effect of convective-scale vertical drafts associated with convective structures that moved relative to the front edge of the convective line. The structure of individual upper-level convective-scale downdrafts suggested that they may have been partially composed of gravity waves excited by the interaction of the penetrative convective updrafts of the mature and dissipating convective cells with the stable ambient flow. The lower-level mean downdraft extended from midlevels to near the surface but was maximum near the melting level and was associated with air of low equivalent potential temperature. It was likely microphysically driven by cooling associated with melting and evaporation.

The upper-level and lower-level subsidence in the transition zone had little effect on the radar reflectivity minimum observed at middle to low levels in the transition zone. The primary microphysical process affecting the development of the reflectivity minimum appears to have been the inability of small ice crystals to form, grow, or persist at midlevels in the transition zone. Consequently, less aggregation could occur in the transition zone just above the melting level than in the secondary band at the same altitude.

Full access
Ryan M. May, Michael I. Biggerstaff, and Ming Xue

Abstract

A Doppler radar emulator was developed to simulate the expected mean returns from scanning radar, including pulse-to-pulse variability associated with changes in viewing angle and atmospheric structure. Based on the user’s configuration, the emulator samples the numerical simulation output to produce simulated returned power, equivalent radar reflectivity, Doppler velocity, and Doppler spectrum width. The emulator is used to evaluate the impact of azimuthal over- and undersampling, gate spacing, velocity and range aliasing, antenna beamwidth and sidelobes, nonstandard (anomalous) pulse propagation, and wavelength-dependent Rayleigh attenuation on features of interest.

As an example, the emulator is used to evaluate the detection of the circulation associated with a tornado simulated within a supercell thunderstorm by the Advanced Regional Prediction System (ARPS). Several metrics for tornado intensity are examined, including peak Doppler velocity and axisymmetric vorticity, to determine the degradation of the tornadic signature as a function of range and azimuthal sampling intervals. For the case of a 2° half-power beamwidth radar, like those deployed in the first integrated project of the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), the detection of the cyclonic shear associated with this simulated tornado will be difficult beyond the 10-km range, if standard metrics such as azimuthal gate-to-gate shear from a single radar are used for detection.

Full access
Daniel P. Betten, Michael I. Biggerstaff, and Louis J. Wicker

Abstract

A visualization technique that allows simultaneous spatial analysis of complex flow behavior from thousands of Lagrangian trajectories is presented and tested using a high temporal and spatial resolution cloud model. The utility of the trajectory mapping technique is illustrated by showing that the source height of the air trajectories is a good proxy to the model-derived equivalent potential temperature. Moreover, the history of the forcing of vertical momentum is related to instantaneous vertical motion patterns shown to be elucidated in the trajectory mapping framework. The robustness of the trajectory mapping method was evaluated by integrating tendency terms and comparing Lagrangian-derived quantities to instantaneous values in the model. The original trajectory maps were also compared to those where the original fields have been filtered and/or the available data frequency are limited to the spatial and temporal scales typical of research radar datasets. The trajectory mapping method was applied to a supercell observed on 29 May 2004 to demonstrate that trajectory behavior for the observed case compares well to those from the higher-resolution numerical model output.

Full access
Casey E. Davenport, Conrad L. Ziegler, and Michael I. Biggerstaff

Abstract

Convective environments are known to be heterogeneous in both time and space, yet idealized models use fixed base-state environments to simulate storm evolution. Recently, the base-state substitution (BSS) technique was devised to account for environmental variability in a controlled manner while maintaining horizontal homogeneity; BSS involves updating the background environment to reflect a new storm-relative proximity sounding at a prescribed time interval. The study herein sought to assess the ability of BSS to more realistically represent the structure and evolution of an observed supercell thunderstorm in comparison to simulations with fixed base-state environments. An extended dual-Doppler dataset of an intensifying supercell thunderstorm in a varying inflow environment was compared to idealized simulations of the same storm; simulations included those with fixed background environments, as well as a BSS simulation that incorporated environmental variability continuously via tendencies to the base-state variables based on changes in a series of observed soundings. While the simulated supercells were generally more intense than what was measured in the observations, broad trends in reflectivity, vertical velocity, and vertical vorticity were more similar between the observed and BSS-simulated supercell; with a fixed environment, the supercell either shrunk in size and weakened over time, or grew upscale into a larger convective system. Quantitative comparisons examining distributions, areas, and volumes of vertical velocity and vorticity further confirm these differences. Overall, BSS provides a more realistic result, supporting the idea that a series of proximity soundings can sufficiently represent the effects of environmental variability, enhancing accuracy over fixed environments.

Free access
Rachel L. Miller, Conrad L. Ziegler, and Michael I. Biggerstaff

Abstract

This case study analyzes a nocturnal mesoscale convective system (MCS) that was observed on 25–26 June 2015 in northeastern Kansas during the Plains Elevated Convection At Night (PECAN) project. Over the course of the observational period, a broken line of elevated nocturnal convective cells initiated around 0230 UTC on the cool side of a stationary front and subsequently merged to form a quasi-linear MCS that later developed strong, surface-based outflow and a trailing stratiform region. This study combines radar observations with mobile and fixed mesonet and sounding data taken during PECAN to analyze the kinematics and thermodynamics of the MCS from 0300 to 0630 UTC. This study is unique in that 38 consecutive multi-Doppler wind analyses are examined over the 3.5 h observation period, facilitating a long-duration analysis of the kinematic evolution of the nocturnal MCS. Radar analyses reveal that the initial convective cells and linear MCS are elevated and sustained by an elevated residual layer formed via weak ascent over the stationary front. During upscale growth, individual convective cells develop storm-scale cold pools due to pockets of descending rear-to-front flow that are measured by mobile mesonets. By 0500 UTC, kinematic analysis and mesonet observations show that the MCS has a surface-based cold pool and that convective line updrafts are ingesting parcels from below the stable layer. In this environment, the elevated system has become surface based since the cold pool lifting is sufficient for surface-based parcels to overcome the CIN associated with the frontal stable layer.

Free access
Steven A. Rutledge, Robert A. Houze Jr., Michael I. Biggerstaff, and Thomas Matejka

Abstract

The 10–11 June mesoscale convective system observed in Kansas during PRE-STORM is studied using a variety of observations including conventional radar, satellite, and single-Doppler radar. This storm, at maturity, consisted of a strong line of convection trailed by a broad region of stratiform rain. The PRE-STORM Doppler radar observations show that the general airflow pattern is similar to that seen in previously analyzed cases; however, since the Doppler observations were quite extensive in time and space, they permit several details of the airflow to be revealed for the first time.

A rear inflow jet, front-to-rear flow aloft, and a mesoscale updraft and downdraft were all present. The mesoscale downdraft commenced at the top of the slanted rear inflow jet. Sublimation and evaporation of hydrometeors in this flow apparently generated the necessary cooling to drive the mesoscale downdraft circulation. The intensity and slope of the rear inflow jet varied with location in the storm, which apparently led to differences in both the intensity and depth of the mesoscale downdraft. The intrusion of this inflow jet into the rear of storm occurred at quite high levels and was probably responsible for disruption of the continuous oval cloud shield as viewed by satellite.

The front-to-rear flow situated above the rear inflow jet contained mesoscale upward motion. Vertical velocities obtained by the EVAD (Extended Velocity–Azimuth Display) method reveal a strong mesoscale updraft, with speeds approaching 50 cm s−1. Vertically pointing observations indicated that convective-scale updrafts and downdrafts were present within 20 km of the convective line. Convective-scale features were not observed in the remaining portion of the trailing stratiform region.

Full access
Corey K. Potvin, Alan Shapiro, Michael I. Biggerstaff, and Joshua M. Wurman

Abstract

The vortex detection and characterization (VDAC) technique is designed to identify tornadoes, mesocyclones, and other convective vortices in multiple-Doppler radar data and retrieve their size, strength, and translational velocity. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which comprise a broad-scale flow), and modified combined Rankine vortex. The vortex and its environmental flow are allowed to translate. A cost function accounting for the discrepancy between the model and observed radial winds is evaluated over space and time so that observations can be used at the actual times and locations they were acquired. The model parameters are determined by minimizing this cost function.

Tests of the technique using analytically generated, numerically simulated, and one observed tornadic wind field were presented by Potvin et al. in an earlier study. In the present study, an improved version of the technique is applied to additional real radar observations of tornadoes and other substorm-scale vortices. The technique exhibits skill in detecting such vortices and characterizing their size and strength. Single-Doppler experiments suggest that the technique may reliably detect and characterize larger (>1-km diameter) vortices even in the absence of overlapping radar coverage.

Full access