scholarly journals Creating a More Realistic Idealized Supercell Thunderstorm Evolution via Incorporation of Base-State Environmental Variability

2019 ◽  
Vol 147 (11) ◽  
pp. 4177-4198
Author(s):  
Casey E. Davenport ◽  
Conrad L. Ziegler ◽  
Michael I. Biggerstaff
Keyword(s):  
Vertical Velocity ◽  
Environmental Variability ◽  
Convective System ◽  
Time Interval ◽  
State Variables ◽  
Relative Proximity ◽  
Realistic Result ◽  
Storm Evolution ◽  
Fixed Base ◽  
Supercell Thunderstorm

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.

scholarly journals A Heuristic Approach for Precipitation Data Assimilation: Characterization Using OSSEs

2019 ◽  
Vol 147 (9) ◽  
pp. 3445-3466 ◽  
Author(s):  
Andrés A. Pérez Hortal ◽  
Isztar Zawadzki ◽  
M. K. Yau
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Grid Point ◽  
Wrf Model ◽  
Ensemble Member ◽  
Absolute Difference ◽  
Time Interval ◽  
State Variables ◽  
Vertical Column ◽  
A New Technique

Abstract We introduce a new technique for the assimilation of precipitation observations, the localized ensemble mosaic assimilation (LEMA). The method constructs an analysis by selecting, for each vertical column in the model, the ensemble member with precipitation at the ground that is locally closest to the observed values. The proximity between the modeled and observed precipitation is determined by the mean absolute difference of precipitation intensity, converted to reflectivity and measured over a spatiotemporal window centered at each grid point of the model. The underlying hypothesis of the approach is that the ensemble members that are locally closer to the observed precipitation are more probable to be closer to the “truth” in the state variables than the other members. The initial conditions for the new forecast are obtained by nudging the background states toward the mosaic of the closest ensemble members (analysis) over a 30 min time interval, reducing the impacts of the imbalances at the boundaries between the different selected members. The potential of the method is studied using observing system simulation experiments (OSSEs) employing a small ensemble of 20 members. The ensemble is produced by the WRF Model, run at a horizontal grid spacing of 20 km. The experiments lend support to the validity of the hypothesis and allow the determination of the optimal parameters for the approach. In the context of OSSE, this new data assimilation technique is able to produce forecasts with considerable and long-lived error reductions in the fields of precipitation, temperature, humidity, and wind.

Impulsive finite-time observer design for uncertain positive linear systems with L2-gain analysis

2020 ◽  
Vol 42 (10) ◽  
pp. 1871-1881 ◽  
Author(s):  
Morteza Motahhari ◽  
Mohammad Hossein Shafiei
Keyword(s):  
Linear Systems ◽  
Finite Time ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
The State ◽  
Observer Design ◽  
Linear Matrix ◽  
Time Interval ◽  
State Variables ◽  
L2 Gain

This paper is concerned with the design of a finite-time positive observer (FTPO) for continuous-time positive linear systems, which is robust regarding the L2-gain performance. In positive observers, the estimation of the state variables is always nonnegative. In contrast to previous positive observers with asymptotic convergence, an FTPO estimates positive state variables in a finite time. The proposed FTPO observer, using two Identity Luenberger observers and based on the impulsive framework, estimates exactly the state variables of positive systems in a predetermined time interval. Furthermore, sufficient conditions are given in terms of linear matrix inequalities (LMIs) to guarantee the L2-gain performance of the estimation error. Finally, the performance and robustness of the proposed FTPO are validated using numerical simulations.

scholarly journals The Impact of Covariance Localization for Radar Data on EnKF Analyses of a Developing MCS: Observing System Simulation Experiments

2013 ◽  
Vol 141 (11) ◽  
pp. 3691-3709 ◽  
Author(s):  
Ryan A. Sobash ◽  
David J. Stensrud
Keyword(s):  
System Simulation ◽  
Three Dimensional ◽  
Radar Data ◽  
Convective System ◽  
State Variables ◽  
Simulation Experiments ◽  
Length Scales ◽  
Convective Scale ◽  
The Impact ◽  
Prior State

Abstract Several observing system simulation experiments (OSSEs) were performed to assess the impact of covariance localization of radar data on ensemble Kalman filter (EnKF) analyses of a developing convective system. Simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) observations were extracted from a truth simulation and assimilated into experiments with localization cutoff choices of 6, 12, and 18 km in the horizontal and 3, 6, and 12 km in the vertical. Overall, increasing the horizontal localization and decreasing the vertical localization produced analyses with the smallest RMSE for most of the state variables. The convective mode of the analyzed system had an impact on the localization results. During cell mergers, larger horizontal localization improved the results. Prior state correlations between the observations and state variables were used to construct reverse cumulative density functions (RCDFs) to identify the correlation length scales for various observation-state pairs. The OSSE with the smallest RMSE employed localization cutoff values that were similar to the horizontal and vertical length scales of the prior state correlations, especially for observation-state correlations above 0.6. Vertical correlations were restricted to state points closer to the observations than in the horizontal, as determined by the RCDFs. Further, the microphysical state variables were correlated with the reflectivity observations on smaller scales than the three-dimensional wind field and radial velocity observations. The ramifications of these findings on localization choices in convective-scale EnKF experiments that assimilate radar data are discussed.

scholarly journals Diagnosing Convective Dependencies on Near-Storm Environments Using Ensemble Sensitivity Analyses

2019 ◽  
Vol 147 (2) ◽  
pp. 495-517 ◽  
Author(s):  
Christopher A. Kerr ◽  
David J. Stensrud ◽  
Xuguang Wang
Keyword(s):  
Wind Shear ◽  
Initial Conditions ◽  
Wrf Model ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Vertical Wind ◽  
Sensitivity Analyses ◽  
Convective System ◽  
Mesoscale Convective ◽  
Storm Evolution

AbstractConvection intensity and longevity is highly dependent on the surrounding environment. Ensemble sensitivity analysis (ESA), which quantitatively and qualitatively interprets impacts of initial conditions on forecasts, is applied to very short-term (1–2 h) convective-scale forecasts for three cases during the Mesoscale Predictability Experiment (MPEX) in 2013. The ESA technique reveals several dependencies of individual convective storm evolution on their nearby environments. The three MPEX cases are simulated using a previously verified 36-member convection-allowing model (Δx = 3 km) ensemble created via the Weather Research and Forecasting (WRF) Model. Radar and other conventional observations are assimilated using an ensemble adjustment Kalman filter. The three cases include a mesoscale convective system (MCS) and both nontornadic and tornadic supercells. Of the many ESAs applied in this study, one of the most notable is the positive sensitivity of supercell updraft helicity to increases in both storm inflow region deep and shallow vertical wind shear. This result suggests that larger values of vertical wind shear within the storm inflow yield higher values of storm updraft helicity. Results further show that the supercell storms quickly enhance the environmental vertical wind shear within the storm inflow region. Application of ESA shows that these storm-induced perturbations then affect further storm evolution, suggesting the presence of storm–environment feedback cycles where perturbations affect future mesocyclone strength. Overall, ESA can provide insight into convection dependencies on the near-storm environment.

a retrospective view of Richardson's book on weather prediction*

1967 ◽  
Vol 48 (8) ◽  
pp. 514-551 ◽  
Author(s):  
George W. Platzman
Keyword(s):  
Vertical Velocity ◽  
Stability Criterion ◽  
Weather Prediction ◽  
Pressure Change ◽  
Time Interval ◽  
Time Step ◽  
Initial Field ◽  
Static Approximation ◽  
Modern Development ◽  
The Stability

In 1922 Lewis F. Richardson published a comprehensive numerical method of weather prediction. He used height rather than pressure as vertical coordinate but recognized that a diagnostic equation for the vertical velocity is a necessary corollary to the quasi-static approximation. His vertical-velocity equation is the principal, substantive contribution of the book to dynamic meteorology. A comparison of Richardson's model with one now in operational use at the U. S. National Meteorological Center shows that, if only the essential attributes of these models are considered, there is virtually no fundamental difference between them. Even the vertical and horizontal resolutions of the models are similar. Richardson made a forecast at two grid points in central Europe and obtained catastrophic results, in particular a surface pressure change of 145 mb in 6 hours. This failure resulted partly, as Richardson believed, from inadequacies of upper wind data. Underlying this was a more fundamental difficulty which he did not seem to recognize clearly at the time he wrote his book: the impossibility of using observed winds to calculate pressure change from the pressure-tendency equation, a principle stated many years earlier by Margules. However, he did point in the direction in which a remedy was later found: suppression or smoothing of the initial field of horizontal velocity divergence. The 6-hr time interval used by Richardson violates the condition for computational stability, a constraint then unknown. It is sometimes said that this is one of the reasons his calculation failed, but that interpretation is misleading because the stability criterion becomes relevant only after several time steps have been made. Since Richardson did not go beyond a calculation of initial tendencies—in other words, he took only one time step—violation of the stability criterion had no effect on the result. Richardson's book surely must be recorded as a major scientific achievement. Nevertheless, it appears to have had little influence in the decades that followed, and indeed, the modern development of numerical weather prediction, which began about twenty-five years later, did not evolve primarily from Richardson's work. Shaw said it would be misleading to regard the book as “a soliloquy on the scientific stage,” but in fact that is what it proved to be. The intriguing problem of explaining this strange irony is one that leads beyond the obvious facts that when Richardson wrote, computers were nonexistent and upper-air data insufficient.

The Effects of an Airborne Inter-Arrival Spacing Tool on Pilot Workload and Acceptability

2002 ◽  
Vol 46 (1) ◽  
pp. 111-115
Author(s):  
Katrin G. Helbing ◽  
Todd Eischeid ◽  
Rosa M. Oseguera-Lohr
Keyword(s):  
Time Interval ◽  
Airline Pilots ◽  
Subjective Evaluations ◽  
Spacing Interval ◽  
Fixed Base ◽  
Automated Tools ◽  
Langley Research Center ◽  
The Impact ◽  
Task Simulation ◽  
Terminal Area

An airborne inter-arrival spacing tool was developed by NASA Langley Research Center to aid pilots in maintaining a time-based spacing interval behind another aircraft in the arrival sequence. A number of display features, including numeric speed commands, a speed pointer on the Fast/Slow Indicator, and graphical depiction of the desired aircraft position on the navigation display, were developed to assist pilots in maintaining the proper speed to achieve the required spacing interval. Because the use of such automated tools requires the acceptance of the user population, a study was conducted to assess the impact on user workload and acceptability. The tool was tested in a full-task simulation in a Boeing-757 full-mission, fixed-base simulator. Subject pilots were paired with a confederate pilot to complete tasks in both the pilot flying and pilot not flying positions. This paper presents the subjective evaluations of the inter-arrival spacing tool. The qualitative workload data from eight current B-757 airline pilots are compared from the perspectives of tool usability and acceptability, and the ability to attain and maintain the appropriate time interval spacing. Results of the study indicate that the pilots who participated in the study were comfortable using the Advanced Terminal Area Approach Spacing (ATAAS) tool and were confident in the automated spacing guidance that the tool provided. The ATAAS tool did not increase perceived pilot workload as compared to an approach conducted under standard (current-day) conditions.

scholarly journals Estimating the Maximum Vertical Velocity at the Leading Edge of a Density Current

2020 ◽  
Vol 77 (11) ◽  
pp. 3683-3700
Author(s):  
Dylan W. Reif ◽  
Howard B. Bluestein ◽  
Tammy M. Weckwerth ◽  
Zachary B. Wienhoff ◽  
Manda B. Chasteen
Keyword(s):  
Vertical Velocity ◽  
Wind Shear ◽  
Potential Temperature ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Leading Edge ◽  
Density Current ◽  
Convective System ◽  
Density Currents ◽  
Spatiotemporal Resolution

AbstractThe maximum upward vertical velocity at the leading edge of a density current is commonly <10 m s−1. Studies of the vertical velocity, however, are relatively few, in part owing to the dearth of high-spatiotemporal-resolution observations. During the Plains Elevated Convection At Night (PECAN) field project, a mobile Doppler lidar measured a maximum vertical velocity of 13 m s−1 at the leading edge of a density current created by a mesoscale convective system during the night of 15 July 2015. Two other vertically pointing instruments recorded 8 m s−1 vertical velocities at the leading edge of the density current on the same night. This study describes the structure of the density current and attempts to estimate the maximum vertical velocity at their leading edges using the following properties: the density current depth, the slope of its head, and its perturbation potential temperature. The method is then be applied to estimate the maximum vertical velocity at the leading edge of density currents using idealized numerical simulations conducted in neutral and stable atmospheres with resting base states and in neutral and stable atmospheres with vertical wind shear. After testing this method on idealized simulations, this method is then used to estimate the vertical velocity at the leading edge of density currents documented in several previous studies. It was found that the maximum vertical velocity can be estimated to within 10%–15% of the observed or simulated maximum vertical velocity and indirectly accounts for parameters including environmental wind shear and static stability.

ON A NEW APPROACH TO FORECASTING TORNADO-DANGEROUS SITUATIONS AND OTHER DANGEROUS CONVECTIVE PHENOMENA

2019 ◽  
Vol 47 (1) ◽  
pp. 135-137
Author(s):  
B.Ya. Shmerlin ◽  
M.A. Novitskii ◽  
O.V. Kalmikova
Keyword(s):  
Velocity Field ◽  
Vertical Velocity ◽  
Lead Time ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Threshold Value ◽  
Convective Cell ◽  
Point Of View ◽  
Convective System ◽  
New Approach

In many studies indices of convective instability (hereinafter simply indices) are used to analyze and predict tornado-dangerous situations. For calculating the meteorological fields from which indices were subsequently calculated, the WRF-ARW version 3.4 was used – the non-hydrostatic, regional weather forecasting system. In the works (Novitskii et al, 2016; 2018) as an example of the calculation of 10 tornadoes that occurred at different times in the European territory of the Russian Federation, we show that the most informative from the point of view of forecasting tornado-dangerous situations and providing a minimum number of false warnings is the STP (significant tornado parameter) index. The characteristic time, during which STP index exceeds threshold value, is within the order of an hour, the size of the regions of localization of the values of the indices above the threshold is within the order of several tens kilometers. We proposed along with the STP index to involve the vertical velocity field, calculated in the WRF model, in the analysis and forecast of tornado-dangerous situations. We show that the value of the STP index above the threshold leads within the WRF model to the formation of a localized intense convective cell in the vertical velocity field in the vicinity of the maximum value of the index and at the moment of reaching this value. The possibility of using the STP index to predict tornado-dangerous situations with a lead time of up to three days with an accuracy of 150 km in space and several hours in time is demonstrated. A new approach to short-term forecasting of tornadoes is proposed. It is based on calculating the fields that are visible on the radar screen, using the WRF model forecast. Such fields are the fields of maximum radar reflectivity, upper cloud boundary and integral vertical water content. The comparison of the prognostic fields with the real fields that the radar sees allows us to specify a real convective system at the time of its formation in which the STP index will subsequently reach a threshold value and a tornado will appear. This can enlarge a lead time of tornado warnings to several hours, which currently averages 13 minutes. The approach can also be used for forecasting other dangerous convective phenomena, as well as in any other forecast models for current forecast correction by using incoming radar (satellite) information.

Environmental Controls on Tropical Mesoscale Convective System Precipitation Intensity

2020 ◽  
Vol 77 (12) ◽  
pp. 4233-4249
Author(s):  
Kathleen A. Schiro ◽  
Sylvia C. Sullivan ◽  
Yi-Hung Kuo ◽  
Hui Su ◽  
Pierre Gentine ◽  
...  
Keyword(s):  
Water Vapor ◽  
Vertical Velocity ◽  
Large Scale ◽  
Mesoscale Convective System ◽  
Air Entrainment ◽  
Precipitation Intensity ◽  
Convective System ◽  
Tropospheric Temperature ◽  
Environmental Controls ◽  
Mesoscale Convective

AbstractUsing multiple independent satellite and reanalysis datasets, we compare relationships between mesoscale convective system (MCS) precipitation intensity Pmax, environmental moisture, large-scale vertical velocity, and system radius among tropical continental and oceanic regions. A sharp, nonlinear relationship between column water vapor and Pmax emerges, consistent with nonlinear increases in estimated plume buoyancy. MCS Pmax increases sharply with increasing boundary layer and lower free tropospheric (LFT) moisture, with the highest Pmax values originating from MCSs in environments exhibiting a peak in LFT moisture near 750 hPa. MCS Pmax exhibits strikingly similar behavior as a function of water vapor among tropical land and ocean regions. Yet, while the moisture–Pmax relationship depends strongly on mean tropospheric temperature, it does not depend on sea surface temperature over ocean or surface air temperature over land. Other Pmax-dependent factors include system radius, the number of convective cores, and the large-scale vertical velocity. Larger systems typically contain wider convective cores and higher Pmax, consistent with increased protection from dilution due to dry air entrainment and reduced reevaporation of precipitation. In addition, stronger large-scale ascent generally supports greater precipitation production. Last, temporal lead–lag analysis suggests that anomalous moisture in the lower–middle troposphere favors convective organization over most regions. Overall, these statistics provide a physical basis for understanding environmental factors controlling heavy precipitation events in the tropics, providing metrics for model diagnosis and guiding physical intuition regarding expected changes to precipitation extremes with anthropogenic warming.

Nonlinear Forecast Error Growth of Rapidly Intensifying Hurricane Harvey (2017) Examined through Convection-Permitting Ensemble Assimilation of GOES-16 All-Sky Radiances

2020 ◽  
Vol 77 (12) ◽  
pp. 4277-4296
Author(s):  
Masashi Minamide ◽  
Fuqing Zhang ◽  
Eugene E. Clothiaux
Keyword(s):  
Forecast Error ◽  
Sensitivity Analyses ◽  
Convective System ◽  
Potential Contribution ◽  
Rapid Intensification ◽  
Convective Activity ◽  
State Variables ◽  
Probabilistic Forecasts ◽  
Moisture State ◽  
Infrared Radiances

AbstractThe dynamics and predictability of the rapid intensification (RI) of Hurricane Harvey (2017) were examined using convection-permitting initialization, analysis, and prediction from a cycling ensemble Kalman filter (EnKF) that assimilated all-sky infrared radiances from the Advanced Baseline Imager on GOES-16. The EnKF analyses were able to evolve the various scales of the radiance fields associated with Harvey close to those observed, including those associated with scattered individual convective cells before the onset of rapid intensification (RI) and the organized vortex-scale convective system during and after RI. This was true for more than 3 days of a continuous assimilation cycling. Deterministic forecasts initialized from the EnKF analyses captured the rapidly deepening intensity of Harvey more than 24 h prior to its onset. To explore the predictability of Harvey’s intensity during RI, ensemble probabilistic forecasts and sensitivity analyses were conducted. It was found that significant ensemble spread growth was induced by initial perturbations individually in either the wind or moisture fields. The nonlinear interactions between wind and moisture perturbations further limited the predictability of the intensification process of Harvey by increasing the uncertainty in the simulated wind and moisture distributions and modifying the convective activity and its feedback on vortex flow. This study highlights both the importance of better initializing the dynamic and moisture state variables simultaneously and the potential contribution of satellite all-sky radiance assimilation on constraining them and their associated convective activity that impacts RI of tropical cyclones.

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