scholarly journals Assimilation of Radar Radial Velocity, Reflectivity, and Pseudo–Water Vapor for Convective-Scale NWP in a Variational Framework

2019 ◽  
Vol 147 (8) ◽  
pp. 2877-2900 ◽  
Author(s):  
Anwei Lai ◽  
Jidong Gao ◽  
Steven E. Koch ◽  
Yunheng Wang ◽  
Sijie Pan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radial Velocity ◽  
Three Dimensional ◽  
Radar Data ◽  
Moist Convection ◽  
Severe Thunderstorm ◽  
Variational Framework ◽  
Convective Scale ◽  
Deep Moist Convection ◽  
Nwp Model

Abstract To improve severe thunderstorm prediction, a novel pseudo-observation and assimilation approach involving water vapor mass mixing ratio is proposed to better initialize NWP forecasts at convection-resolving scales. The first step of the algorithm identifies areas of deep moist convection by utilizing the vertically integrated liquid water (VIL) derived from three-dimensional radar reflectivity fields. Once VIL is obtained, pseudo–water vapor observations are derived based on reflectivity thresholds within columns characterized by deep moist convection. Areas of spurious convection also are identified by the algorithm to help reduce their detrimental impact on the forecast. The third step is to assimilate the derived pseudo–water vapor observations into a convection-resolving-scale NWP model along with radar radial velocity and reflectivity fields in a 3DVAR framework during 4-h data assimilation cycles. Finally, 3-h forecasts are launched every hour during that period. The performance of this method is examined for two selected high-impact severe thunderstorm events: namely, the 24 May 2011 Oklahoma and 16 May 2017 Texas and Oklahoma tornado outbreaks. Relative to a control simulation that only assimilated radar data, the analyses and forecasts of these supercells (reflectivity patterns, tracks, and updraft helicity tracks) are qualitatively and quantitatively improved in both cases when the water vapor information is added into the analysis.

scholarly journals Assimilation of Radar Data, Pseudo Water Vapor, and Potential Temperature in a 3DVAR Framework for Improving Precipitation Forecast of Severe Weather Events

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 182
Author(s):  
Anwei Lai ◽  
Jinzhong Min ◽  
Jidong Gao ◽  
Hedi Ma ◽  
Chunguang Cui ◽  
...  
Keyword(s):  
Water Vapor ◽  
Data Assimilation ◽  
Potential Temperature ◽  
Radar Data ◽  
Severe Weather ◽  
Moist Convection ◽  
Meiyu Front ◽  
Weather Events ◽  
Convective Scale ◽  
Deep Moist Convection

An improved approach to derive pseudo water vapor mass mixing ratio and in- cloud potential temperature was developed in this paper to better initialize numerical weather prediction (NWP) and build convective-scale predictions of severe weather events. The process included several steps. The first was to identify areas of deep moist convection, utilizing Vertically Integrated Liquid water (VIL) derived from a mosaicked 3D radar reflectivity field. Then, pseudo- water vapor and pseudo- in- cloud potential temperature observations were derived based on the VIL. For potential temperature, the latent heat initialization for stratiform cloud and moist adiabatic initialization for deep moist convection were used based on a cloud analysis method. The third step was to assimilate the derived pseudo- water vapor and potential temperature observations, together with radar radial velocity and reflectivity into a convective-scale NWP model during data assimilation cycles spanning several hours. Finally, 3-h forecasts were launched each hour during the data assimilation period. The effects of radar data and pseudo- observation assimilation on the prediction of rainfall associated with convective systems surrounding the Meiyu front in 2018 were explored using two real cases. Two sets of experiments, each including several experiments in each real case, were designed to compare the effects of assimilation radar and pseudo- observations on the ensuing forecasts. Relative to the control experiment without data assimilation and radar experiment, the analyses and forecasts of convections were found to be improved for the two Meiyu front cases after pseudo- water vapor and potential temperature information was assimilated.

scholarly journals A Spatial Filter Approach to Evaluating the Role of Convection on the Evolution of a Mesoscale Vortex

2013 ◽  
Vol 70 (7) ◽  
pp. 1954-1976 ◽  
Author(s):  
Glenn A. Creighton ◽  
Robert E. Hart ◽  
Philip Cunningham
Keyword(s):  
Three Dimensional ◽  
Spatial Separation ◽  
Spatial Filter ◽  
Tropical Cyclogenesis ◽  
Moist Convection ◽  
Mesoscale Vortex ◽  
Convective Scale ◽  
Vortical Hot Towers ◽  
Order Of Magnitude ◽  
Deep Moist Convection

Abstract A new spatial filter is proposed that exploits a spectral gap in power between the convective scale and the system (“vortex”) scale during tropical cyclone (TC) genesis simulations. Using this spatial separation, this study analyzes idealized three-dimensional numerical simulations of deep moist convection in the presence of a symmetric midlevel vortex to quantify and understand the energy cascade between the objectively defined convective scale and system scale during the early stages of tropical cyclogenesis. The simulations neglect surface momentum, heat, and moisture fluxes to focus on generation and enhancement of vorticity within the interior to more completely close off the energy budget and to be consistent for comparison with prior benchmark studies of modeled TC genesis. The primary contribution to system-scale intensification comes from the convergence of convective-scale vorticity that is supplied by vortical hot towers (VHTs). They contribute more than the convergence of system-scale vorticity to the spinup of vorticity in these simulations by an order of magnitude. Analysis of the change of circulation with time shows an initial strengthening of the surface vortex, closely followed by a growth of the mid- to upper-level circulation. This evolution precludes any possibility of a stratiform precipitation–induced top-down mechanism as the primary contributor to system-scale spinup in this simulation. Instead, an upscale cascade of rotational kinetic energy during vortex mergers is responsible for spinup of the simulated mesoscale vortex. The spatial filter employed herein offers an alternative approach to the traditional symmetry–asymmetry paradigm, acknowledges the highly asymmetric evolution of the system-scale vortex itself, and may prove useful to future studies on TC genesis.

scholarly journals An Observational and Modeling Study of the Processes Leading to Deep, Moist Convection in Complex Terrain

2014 ◽  
Vol 142 (8) ◽  
pp. 2687-2708 ◽  
Author(s):  
Tammy M. Weckwerth ◽  
Lindsay J. Bennett ◽  
L. Jay Miller ◽  
Joël Van Baelen ◽  
Paolo Di Girolamo ◽  
...  
Keyword(s):  
Water Vapor ◽  
Three Dimensional ◽  
Wrf Model ◽  
Convective Precipitation ◽  
Spatial And Temporal Variability ◽  
Moist Convection ◽  
Wind Fields ◽  
Vosges Mountains ◽  
Deep Moist Convection ◽  
Convection Initiation

Abstract A case study of orographic convection initiation (CI) that occurred along the eastern slopes of the Vosges Mountains in France on 6 August 2007 during the Convective and Orographically-Induced Precipitation Study (COPS) is presented. Global positioning system (GPS) receivers and two Doppler on Wheels (DOW) mobile radars sampled the preconvective and storm environments and were respectively used to retrieve three-dimensional tomographic water vapor and wind fields. These retrieved data were supplemented with temperature, moisture, and winds from radiosondes from a site in the eastern Rhine Valley. High-resolution numerical simulations with the Weather Research and Forecasting (WRF) Model were used to further investigate the physical processes leading to convective precipitation. This unique, time-varying combination of derived water vapor and winds from observations illustrated an increase in low-level moisture and convergence between upslope easterlies and downslope westerlies along the eastern slope of the Vosges Mountains. Uplift associated with these shallow, colliding boundary layer flows eventually led to the initiation of moist convection. WRF reproduced many features of the observed complicated flow, such as cyclonic (anticyclonic) flow around the southern (northern) end of the Vosges Mountains and the east-side convergent flow below the ridgeline. The WRF simulations also illustrated spatial and temporal variability in buoyancy and the removal of the lids prior to convective development. The timing and location of CI from the WRF simulations was surprisingly close to that observed.

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.

An Application of the Immersed Boundary Method for Recovering the Three-Dimensional Wind Fields over Complex Terrain Using Multiple-Doppler Radar Data

2012 ◽  
Vol 140 (5) ◽  
pp. 1603-1619 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Shao-Fan Chang ◽  
Juanzhen Sun
Keyword(s):  
Radial Velocity ◽  
Immersed Boundary Method ◽  
Doppler Radar ◽  
Synthesis Method ◽  
Three Dimensional ◽  
Simulated Data ◽  
Radar Data ◽  
Immersed Boundary ◽  
Wind Fields ◽  
Boundary Method

This study develops an extension of a variational-based multiple-Doppler radar synthesis method to construct the three-dimensional wind field over complex topography. The immersed boundary method (IBM) is implemented to take into account the influence imposed by a nonflat surface. The IBM has the merit of providing realistic topographic forcing without the need to change the Cartesian grid configuration into a terrain-following coordinate system. Both Dirichlet and Neumann boundary conditions for the wind fields can be incorporated. The wind fields above the terrain are obtained by variationally adjusting the solutions to satisfy a series of weak constraints, which include the multiple-radar radial velocity observations, anelastic continuity equation, vertical vorticity equation, background wind, and spatial smoothness terms. Experiments using model-simulated data reveal that the flow structures over complex orography can be successfully retrieved using radial velocity measurements from multiple Doppler radars. The primary advantages of the original synthesis method are still maintained, that is, the winds along and near the radar baseline are well retrieved, and the resulting three-dimensional flow fields can be used directly for vorticity budget diagnosis. If compared with the traditional wind synthesis algorithm, this method is able to merge data from different sources, and utilize data from any number of radars. This provides more flexibility in designing various scanning strategies, so that the atmosphere may be probed more efficiently using a multiple-radar network. This method is also tested using the radar data collected during the Southwest Monsoon Experiment (SoWMEX), which was conducted in Taiwan from May to June 2008 with reasonable results being obtained.

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.

scholarly journals An Evaluation of Clouds and Precipitation in Convection-Permitting Forecasts for South Africa

2019 ◽  
Vol 34 (1) ◽  
pp. 233-254 ◽  
Author(s):  
T. H. M. Stein ◽  
W. Keat ◽  
R. I. Maidment ◽  
S. Landman ◽  
E. Becker ◽  
...  
Keyword(s):  
South Africa ◽  
South African ◽  
Southern Africa ◽  
Deep Convection ◽  
Three Dimensional ◽  
Radar Data ◽  
Onset Of Convection ◽  
Convective Scale ◽  
Convection Parameterization ◽  
Vertical Development

Abstract Since 2016, the South African Weather Service (SAWS) has been running convective-scale simulations to assist with forecast operations across southern Africa. These simulations are run with a tropical configuration of the Met Office Unified Model (UM), nested in the Met Office global model, but without data assimilation. For November 2016, convection-permitting simulations at 4.4- and 1.5-km grid lengths are compared against a simulation at 10-km grid length with convection parameterization (the current UM global atmosphere configuration) to identify the benefits of increasing model resolution for forecasting convection across southern Africa. The simulations are evaluated against satellite rainfall estimates, CloudSat vertical cloud profiles, and SAWS radar data. In line with previous studies using the UM, on a monthly time scale, the diurnal cycle of convection and the distribution of rainfall rates compare better against observations when convection-permitting model configurations are used. The SAWS radar network provides a three-dimensional composite of radar reflectivity for northeast South Africa at 6-min intervals, allowing the evaluation of the vertical development of precipitating clouds and of the timing of the onset of deep convection. Analysis of four case study days indicates that the 4.4-km simulations have a later onset of convection than the 1.5-km simulations, but there is no consistent bias of the simulations against the radar observations across the case studies.

scholarly journals Improving the Model Convective Storm Quantitative Precipitation Nowcasting by Assimilating State Variables Retrieved from Multiple-Doppler Radar Observations

2014 ◽  
Vol 142 (11) ◽  
pp. 4017-4035 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Jian-Luen Chiou ◽  
Wei-Hao Chen ◽  
Hsin-Yu Yu
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Scale Up ◽  
Three Dimensional ◽  
Radar Data ◽  
State Variables ◽  
Weather System ◽  
Additional Information ◽  
Convective Scale ◽  
Fine Resolution

Abstract This research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions. It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model. Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.

scholarly journals Multipass Objective Analyses of Doppler Radar Data

2008 ◽  
Vol 25 (10) ◽  
pp. 1845-1858 ◽  
Author(s):  
Mario Majcen ◽  
Paul Markowski ◽  
Yvette Richardson ◽  
David Dowell ◽  
Joshua Wurman
Keyword(s):  
Radial Velocity ◽  
Computational Cost ◽  
Three Dimensional ◽  
Radar Data ◽  
Objective Analysis ◽  
Small Scale ◽  
Velocity Data ◽  
Wind Fields ◽  
Single Pass ◽  
Radial Velocity Data

Abstract This note assesses the improvements in dual-Doppler wind syntheses by employing a multipass Barnes objective analysis in the interpolation of radial velocities to a Cartesian grid, as opposed to a more typical single-pass Barnes objective analysis. Steeper response functions can be obtained by multipass objective analyses; that is, multipass objective analyses are less damping at well-resolved wavelengths (e.g., 8–20Δ, where Δ is the data spacing) than single-pass objective analyses, while still suppressing small-scale (<4Δ) noise. Synthetic dual-Doppler data were generated from a three-dimensional numerical simulation of a supercell thunderstorm in a way that emulates the data collection by two mobile radars. The synthetic radial velocity data from a pair of simulated radars were objectively analyzed to a grid, after which the three-dimensional wind field was retrieved by iteratively computing the horizontal divergence and integrating the anelastic mass continuity equation. Experiments with two passes and three passes of the Barnes filter were performed, in addition to a single-pass objective analysis. Comparison of the analyzed three-dimensional wind fields to the model wind fields suggests that multipass objective analysis of radial velocity data prior to dual-Doppler wind synthesis is probably worth the added computational cost. The improvements in the wind syntheses derived from multipass objective analyses are even more apparent for higher-order fields such as vorticity and divergence, and for trajectory calculations and pressure/buoyancy retrievals.

scholarly journals Impact of a Diagnostic Pressure Equation Constraint on Tornadic Supercell Thunderstorm Forecasts Initialized Using 3DVAR Radar Data Assimilation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Guoqing Ge ◽  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Three Dimensional ◽  
Radar Data ◽  
Pressure Equation ◽  
Supercell Thunderstorm ◽  
Weighting Coefficients ◽  
The Impact ◽  
Radar Data Assimilation ◽  
Equation Constraint

A diagnostic pressure equation constraint has been incorporated into a storm-scale three-dimensional variational (3DVAR) data assimilation system. This diagnostic pressure equation constraint (DPEC) is aimed to improve dynamic consistency among different model variables so as to produce better data assimilation results and improve the subsequent forecasts. Ge et al. (2012) described the development of DPEC and testing of it with idealized experiments. DPEC was also applied to a real supercell case, but only radial velocity was assimilated. In this paper, DPEC is further applied to two real tornadic supercell thunderstorm cases, where both radial velocity and radar reflectivity data are assimilated. The impact of DPEC on radar data assimilation is examined mainly based on the storm forecasts. It is found that the experiments using DPEC generally predict higher low-level vertical vorticity than the experiments not using DPEC near the time of observed tornadoes. Therefore, it is concluded that the use of DPEC improves the forecast of mesocyclone rotation within supercell thunderstorms. The experiments using different weighting coefficients generate similar results. This suggests that DPEC is not very sensitive to the weighting coefficients.

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