Impact of a Vertical Vorticity Constraint in Variational Dual-Doppler Wind Analysis: Tests with Real and Simulated Supercell Data

2012 ◽  
Vol 29 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Corey K. Potvin ◽  
Alan Shapiro ◽  
Ming Xue
Keyword(s):  
Vertical Velocity ◽  
Three Dimensional ◽  
Mass Conservation ◽  
Vorticity Equation ◽  
Vertical Vorticity ◽  
Advanced Regional Prediction System ◽  
Supercell Storm ◽  
Radar Networks ◽  
Regional Prediction ◽  
The Impact

Abstract One of the greatest challenges to dual-Doppler retrieval of the vertical wind is the lack of low-level divergence information available to the mass conservation constraint. This study examines the impact of a vertical vorticity equation constraint on vertical velocity retrievals when radar observations are lacking near the ground. The analysis proceeds in a three-dimensional variational data assimilation (3DVAR) framework with the anelastic form of the vertical vorticity equation imposed along with traditional data, mass conservation, and smoothness constraints. The technique is tested using emulated radial wind observations of a supercell storm simulated by the Advanced Regional Prediction System (ARPS), as well as real dual-Doppler observations of a supercell storm that occurred in Oklahoma on 8 May 2003. Special attention is given to procedures to evaluate the vorticity tendency term, including spatially variable advection correction and estimation of the intrinsic evolution. Volume scan times ranging from 5 min, typical of operational radar networks, down to 30 s, achievable by rapid-scan mobile radars, are considered. The vorticity constraint substantially improves the vertical velocity retrievals in our experiments, particularly for volume scan times smaller than 2 min.

scholarly journals The Impact of a Stochastically Perturbing Microphysics Scheme on an Idealized Supercell Storm

2017 ◽  
Vol 146 (1) ◽  
pp. 95-118 ◽  
Author(s):  
Xiaoshi Qiao ◽  
Shizhang Wang ◽  
Jinzhong Min
Keyword(s):  
Stochastic Methods ◽  
Microphysics Scheme ◽  
Advanced Regional Prediction System ◽  
Recursive Filters ◽  
Supercell Storm ◽  
Regional Prediction ◽  
Double Moment ◽  
The Impact ◽  
Temperature Tendency ◽  
Stochastically Perturbed

Abstract The concept of stochastic parameterization provides an opportunity to represent spatiotemporal errors caused by microphysics schemes that play important roles in supercell simulations. In this study, two stochastic methods, the stochastically perturbed temperature tendency from microphysics (SPTTM) method and the stochastically perturbed intercept parameters of microphysics (SPIPM) method, are implemented within the Lin scheme, which is based on the Advanced Regional Prediction System (ARPS) model, and are tested using an idealized supercell case. The SPTTM and SPIPM methods perturb the temperature tendency and the intercept parameters (IPs), respectively. Both methods use recursive filters to generate horizontally smooth perturbations and adopt the barotropic structure for the perturbation r, which is multiplied by tendencies or parameters from this parameterization. A double-moment microphysics scheme is used for the truth run. Compared to the multiparameter method, which uses randomly perturbed prescribed parameters, stochastic methods often produce larger ensemble spreads and better forecast the intensity of updraft helicity (UH). The SPTTM method better predicts the intensity by intensifying the midlevel heating with its positive perturbation r, whereas it performs worse in the presence of negative perturbation. In contrast, the SPIPM method can increase the intensity of UH by either positive or negative perturbation, which increases the likelihood for members to predict strong UH.

scholarly journals Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model

2013 ◽  
Vol 2013 ◽  
pp. 1-18
Author(s):  
Edward Natenberg ◽  
Jidong Gao ◽  
Ming Xue ◽  
Frederick H. Carr
Keyword(s):  
Doppler Radar ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Radar Data ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Upper Level ◽  
Using Data ◽  
Nwp Model ◽  
The Impact

A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

Impacts of Assimilating Measurements of Different State Variables with a Simulated Supercell Storm and Three-Dimensional Variational Method

2013 ◽  
Vol 141 (8) ◽  
pp. 2759-2777 ◽  
Author(s):  
Guoqing Ge ◽  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
Potential Temperature ◽  
Three Dimensional ◽  
Horizontal Wind ◽  
Cold Pool ◽  
State Variables ◽  
Wind Fields ◽  
Simulation Experiments ◽  
Supercell Storm ◽  
The Impact ◽  
Analysis Quality

Abstract This paper investigates the impacts of assimilating measurements of different state variables, which can be potentially available from various observational platforms, on the cycled analysis and short-range forecast of supercell thunderstorms by performing a set of observing system simulation experiments (OSSEs) using a storm-scale three-dimensional variational data assimilation (3DVAR) method. The control experiments assimilate measurements every 5 min for 90 min. It is found that the assimilation of horizontal wind can reconstruct the storm structure rather accurately. The assimilation of vertical velocity , potential temperature , or water vapor can partially rebuild the thermodynamic and precipitation fields but poorly retrieves the wind fields. The assimilation of rainwater mixing ratio can build up the precipitation fields together with a reasonable cold pool but is unable to properly recover the wind fields. Overall, data have the greatest impact, while have the second largest impact. The impact of is the smallest. The impact of assimilation frequency is examined by comparing results using 1-, 5-, or 10-min assimilation intervals. When is assimilated every 5 or 10 min, the analysis quality can be further improved by the incorporation of additional types of observations. When are assimilated every minute, the benefit from additional types of observations is negligible, except for . It is also found that for , , and measurements, more frequent assimilation leads to more accurate analyses. For and , a 1-min assimilation interval does not produce a better analysis than a 5-min interval.

scholarly journals High-Resolution, Rapid-Scan Dual-Doppler Retrievals of Vertical Velocity in a Simulated Supercell

2019 ◽  
Vol 36 (8) ◽  
pp. 1477-1500 ◽  
Author(s):  
Nathan A. Dahl ◽  
Alan Shapiro ◽  
Corey K. Potvin ◽  
Adam Theisen ◽  
Joshua G. Gebauer ◽  
...  
Keyword(s):  
Variational Method ◽  
Vertical Velocity ◽  
Traditional Method ◽  
Mass Conservation ◽  
Conservation Equation ◽  
Observation System ◽  
Near Surface ◽  
Rapid Scan ◽  
Close Range ◽  
The Impact

AbstractObservation system simulation experiments are used to evaluate different dual-Doppler analysis (DDA) methods for retrieving vertical velocity w at grid spacings on the order of 100 m within a simulated tornadic supercell. Variational approaches with and without a vertical vorticity equation constraint are tested, along with a typical (traditional) method involving vertical integration of the mass conservation equation. The analyses employ emulated radar data from dual-Doppler placements 15, 30, and 45 km east of the mesocyclone, with volume scan intervals ranging from 10 to 150 s. The effect of near-surface data loss is examined by denying observations below 1 km in some of the analyses. At the longer radar ranges and when no data denial is imposed, the “traditional” method produces results similar to those of the variational method and is much less expensive to implement. However, at close range and/or with data denial, the variational method is much more accurate, confirming results from previous studies. The vorticity constraint shows the potential to improve the variational analysis substantially, reducing errors in the w retrieval by up to 30% for rapid-scan observations (≤30 s) at close range when the local vorticity tendency is estimated using spatially variable advection correction. However, the vorticity constraint also degrades the analysis for longer scan intervals, and the impact diminishes with increased range. Furthermore, analyses using 30-s data also frequently outperform analyses using 10-s data, suggesting a limit to the benefit of increasing the radar scan rate for variational DDA employing the vorticity constraint.

Tornadogenesis in a Simulated Mesovortex within a Mesoscale Convective System

2012 ◽  
Vol 69 (11) ◽  
pp. 3372-3390 ◽  
Author(s):  
Alexander D. Schenkman ◽  
Ming Xue ◽  
Alan Shapiro
Keyword(s):  
Three Dimensional ◽  
Mesoscale Convective System ◽  
Surface Friction ◽  
Convective System ◽  
Grid Spacing ◽  
Near Surface ◽  
Advanced Regional Prediction System ◽  
Low Level ◽  
Regional Prediction ◽  
Mesoscale Convective

Abstract The Advanced Regional Prediction System (ARPS) is used to simulate a tornadic mesovortex with the aim of understanding the associated tornadogenesis processes. The mesovortex was one of two tornadic mesovortices spawned by a mesoscale convective system (MCS) that traversed southwestern and central Oklahoma on 8–9 May 2007. The simulation used 100-m horizontal grid spacing, and is nested within two outer grids with 400-m and 2-km grid spacing, respectively. Both outer grids assimilate radar, upper-air, and surface observations via 5-min three-dimensional variational data assimilation (3DVAR) cycles. The 100-m grid is initialized from a 40-min forecast on the 400-m grid. Results from the 100-m simulation provide a detailed picture of the development of a mesovortex that produces a submesovortex-scale tornado-like vortex (TLV). Closer examination of the genesis of the TLV suggests that a strong low-level updraft is critical in converging and amplifying vertical vorticity associated with the mesovortex. Vertical cross sections and backward trajectory analyses from this low-level updraft reveal that the updraft is the upward branch of a strong rotor that forms just northwest of the simulated TLV. The horizontal vorticity in this rotor originates in the near-surface inflow and is caused by surface friction. An additional simulation with surface friction turned off does not produce a rotor, strong low-level updraft, or TLV. Comparison with previous two-dimensional numerical studies of rotors in the lee of mountains shows striking similarities to the rotor formation presented herein. The findings of this study are summarized in a four-stage conceptual model for tornadogenesis in this case that describes the evolution of the event from mesovortexgenesis through rotor development and finally TLV genesis and intensification.

scholarly journals A study of the influence of forest gaps on fire–atmosphere interactions

2016 ◽  
Vol 16 (13) ◽  
pp. 8499-8509 ◽  
Author(s):  
Michael T. Kiefer ◽  
Warren E. Heilman ◽  
Shiyuan Zhong ◽  
Joseph J. Charney ◽  
Xindi Bian
Keyword(s):  
Sensible Heat Flux ◽  
Forest Canopies ◽  
Advanced Regional Prediction System ◽  
Forest Gaps ◽  
Low Intensity ◽  
Regional Prediction ◽  
Surface Sensible Heat Flux ◽  
Atmospheric Perturbations ◽  
The Impact ◽  
Enhanced Surface

Abstract. Much uncertainty exists regarding the possible role that gaps in forest canopies play in modulating fire–atmosphere interactions in otherwise horizontally homogeneous forests. This study examines the influence of gaps in forest canopies on atmospheric perturbations induced by a low-intensity fire using the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization. A series of numerical experiments are conducted with a stationary low-intensity fire, represented in the model as a line of enhanced surface sensible heat flux. Experiments are conducted with and without forest gaps, and with gaps in different positions relative to the fire line. For each of the four cases considered, an additional simulation is performed without the fire to facilitate comparison of the fire-perturbed atmosphere and the background state. Analyses of both mean and instantaneous wind velocity, turbulent kinetic energy, air temperature, and turbulent mixing of heat are presented in order to examine the fire-perturbed atmosphere on multiple timescales. Results of the analyses indicate that the impact of the fire on the atmosphere is greatest in the case with the gap centered on the fire and weakest in the case with the gap upstream of the fire. It is shown that gaps in forest canopies have the potential to play a role in the vertical as well as horizontal transport of heat away from the fire. Results also suggest that, in order to understand how the fire will alter wind and turbulence in a heterogeneous forest, one needs to first understand how the forest heterogeneity itself influences the wind and turbulence fields without the fire.

scholarly journals Sensitivity of Surface Analyses over the Western United States to RAWS Observations

2008 ◽  
Vol 23 (1) ◽  
pp. 145-158 ◽  
Author(s):  
David T. Myrick ◽  
John D. Horel
Keyword(s):  
United States ◽  
Wind Speed ◽  
Winter Season ◽  
Western United States ◽  
Cold Pool ◽  
Federal State ◽  
Advanced Regional Prediction System ◽  
Average Analysis ◽  
Regional Prediction ◽  
The Impact

Abstract Federal, state, and other wildland resource management agencies contribute to the collection of weather observations from over 1000 Remote Automated Weather Stations (RAWS) in the western United States. The impact of RAWS observations on surface objective analyses during the 2003/04 winter season was assessed using the Advanced Regional Prediction System (ARPS) Data Assimilation System (ADAS). A set of control analyses was created each day at 0000 and 1200 UTC using the Rapid Update Cycle (RUC) analyses as the background fields and assimilating approximately 3000 surface observations from MesoWest. Another set of analyses was generated by withholding all of the RAWS observations available at each time while 10 additional sets of analyses were created by randomly withholding comparable numbers of observations obtained from all sources. Random withholding of observations from the analyses provides a baseline estimate of the analysis quality. Relative to this baseline, removing the RAWS observations degrades temperature (wind speed) analyses by an additional 0.5°C (0.9 m s−1) when evaluated in terms of rmse over the entire season. RAWS temperature observations adjust the RUC background the most during the early morning hours and during winter season cold pool events in the western United States while wind speed observations have a greater impact during active weather periods. The average analysis area influenced by at least 1.0°C (2.5°C) by withholding each RAWS observation is on the order of 600 km2 (100 km2). The spatial influence of randomly withheld observations is much less.

scholarly journals A Doppler Radar Emulator with an Application to the Detectability of Tornadic Signatures

2007 ◽  
Vol 24 (12) ◽  
pp. 1973-1996 ◽  
Author(s):  
Ryan M. May ◽  
Michael I. Biggerstaff ◽  
Ming Xue
Keyword(s):  
Pulse Propagation ◽  
Doppler Radar ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Advanced Regional Prediction System ◽  
Adaptive Sensing ◽  
Regional Prediction ◽  
Sampling Intervals ◽  
Half Power ◽  
The Impact

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.

Use of a Vertical Vorticity Equation in Variational Dual-Doppler Wind Analysis

2009 ◽  
Vol 26 (10) ◽  
pp. 2089-2106 ◽  
Author(s):  
Alan Shapiro ◽  
Corey K. Potvin ◽  
Jidong Gao
Keyword(s):  
Stokes Equations ◽  
Value Added ◽  
Mass Conservation ◽  
Conservation Equation ◽  
Analysis Procedure ◽  
Vorticity Equation ◽  
Vertical Vorticity ◽  
Beltrami Flow ◽  
Wind Analysis ◽  
Equation Constraint

Abstract The utility of the anelastic vertical vorticity equation in a weak-constraint (least squares error) variational dual-Doppler wind analysis procedure is explored. The analysis winds are obtained by minimizing a cost function accounting for the discrepancies between observed and analyzed radial winds, errors in the mass conservation equation, errors in the anelastic vertical vorticity equation, and spatial smoothness constraints. By using Taylor’s frozen-turbulence hypothesis to shift analysis winds to observation points, discrepancies between radially projected analysis winds and radial wind observations can be calculated at the actual times and locations the data are acquired. The frozen-turbulence hypothesis is also used to evaluate the local derivative term in the vorticity equation. Tests of the analysis procedure are performed with analytical pseudo-observations of an array of translating and temporally decaying counterrotating updrafts and downdrafts generated from a Beltrami flow solution of the Navier–Stokes equations. The experiments explore the value added to the analysis by the vorticity equation constraint in the common scenario of substantial missing low-level data (radial wind observations at heights beneath 1.5 km are withheld from the analysis). Experiments focus on the sensitivity of the most sensitive analysis variable—the vertical velocity component—to values of the weighting coefficients, volume scan period, number of volume scans, and errors in the estimated frozen-turbulence pattern-translation components. Although the vorticity equation constraint is found to add value to many of these analyses, the analysis can become significantly degraded if estimates of the pattern-translation components are largely in error or if the frozen-turbulence hypothesis itself breaks down. However, tests also suggest that these negative impacts can be mitigated if data are available in a rapid-scan mode.

scholarly journals The Analysis and Prediction of the 8–9 May 2007 Oklahoma Tornadic Mesoscale Convective System by Assimilating WSR-88D and CASA Radar Data Using 3DVAR

2011 ◽  
Vol 139 (1) ◽  
pp. 224-246 ◽  
Author(s):  
Alexander D. Schenkman ◽  
Ming Xue ◽  
Alan Shapiro ◽  
Keith Brewster ◽  
Jidong Gao
Keyword(s):  
Three Dimensional ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Squall Line ◽  
Convective System ◽  
Data Types ◽  
Advanced Regional Prediction System ◽  
Engineering Research ◽  
Regional Prediction ◽  
Mesoscale Convective

Abstract The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution numerical simulations of a mesoscale convective system and associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8–9 May 2007. The simulation uses a 1000 km × 1000 km domain with 2-km horizontal grid spacing. The ARPS three-dimensional variational data assimilation (3DVAR) is used to assimilate a variety of data types. All experiments assimilate routine surface and upper-air observations as well as wind profiler and Oklahoma Mesonet data over a 1-h assimilation window. A subset of experiments assimilates radar data. Cloud and hydrometeor fields as well as in-cloud temperature are adjusted based on radar reflectivity data through the ARPS complex cloud analysis procedure. Radar data are assimilated from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network as well as from the Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA) network of four X-band Doppler radars. Three-hour forecasts are launched at the end of the assimilation window. The structure and evolution of the forecast MCS and LEV are markedly better throughout the forecast period in experiments in which radar data are assimilated. The assimilation of CASA radar data in addition to WSR-88D data increases the structural detail of the modeled squall line and MCS at the end of the assimilation window, which appears to yield a slightly better forecast track of the LEV.

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