Simple Adjoint Retrievals of Wet-Microburst Winds and Gust-Front Winds from Single-Doppler Radar Data

Xu, Qin; Gu, Hengfei; Qiu, Chongjian

doi:10.1175/1520-0450(2001)040<1485:sarowm>2.0.co;2

Cited by 19 publications

(13 citation statements)

References 14 publications

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“…The availability in real-time full- volume, full-resolution (level II) radar data (Crum et al 2003) and the important improvements in data assimilation techniques have also paved the way for radar data assimilation. Research efforts have been made in the last decade with an attempt to extract and assimilate meteorological information from Doppler radar observations into NWP models to improve the model capability of forecasting severe weather events (Shapiro et al 1995(Shapiro et al , 2003Qiu and Xu 1996;Sun 2004Sun , 2005Sun andCrook 1997,1998;Xu et al 1995Xu et al , 2001aGao et al 1999;Wu et al 2000;Weygandt et al 2002a,b;Snyder and Zhang 2003;Xiao et al 2005). While these studies were done mostly for isolated thunderstorms and mesoscale convective systems, it should be feasible and practical to apply these techniques to TC structure and intensity analyses and predictions.…”

mentioning

confidence: 99%

“…A variational approach developed by Xu et al (2001b) is used in this system to retrieve the three-dimensional wind fields and the thermodynamic perturbations associated with the retrieved winds from radar observations of radial velocity from one or more radars in the storm area. These retrieved fields are then assimilated into the COAMPS model to improve the mesoscale and storm-scale dynamical and thermodynamic features in the model initial fields.…”

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confidence: 99%

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High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

Zhao¹,

Jin²

2008

Bull. Amer. Meteor. Soc.

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mentioning

confidence: 99%

mentioning

confidence: 99%

High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

Zhao¹,

Jin²

2008

Bull. Amer. Meteor. Soc.

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“…The alias-robust VAD method (Xu et al 2001a) was used to provide the background wind for the automated radar-based wind analysis system (RWAS, Xu et al 2009a), while the latter was used to monitor low-level wind conditions over high-impact weather threatened areas in real time. The mesoscale environmental wind field produced by the RWAS was then used as the background and first guess for the simple adjoint (SA) method (Xu et al 2001) to retrieve three-dimensional wind field at high spatial and temporal resolutions from PAR observations. The SA method was further developed into a two-step method to retrieve the horizontal wind field on the conical surface of radar scan at each elevation first and then the vertical velocity in selected vertical cross-sections.…”

Section: Work Completedmentioning

confidence: 99%

Radar Data Quality Control and Assimilation at the National Weather Radar Testbed (NWRT)

Xu¹

2010

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Study and develop advanced approaches for radar data quality control (QC) and assimilation that will not only optimally utilize Doppler wind information from WSR-88D and Terminal Doppler Weather Radar (TDWR) but also take full advantage of rapid and flexible agile-beam scans from the phased array radar (PAR) at NWRT. OBJECTIVES Develop new variational methods to improve the existing radar wind analysis system so it can be applied to any radar scans to produce real-time vector wind displays and monitor data quality. Study radar data quality problems and develop statistically reliable quality control (QC) techniques. Explore new data assimilation techniques to optimally utilize the PAR scan capabilities. APPROACH Continue monitoring the real-time performances of the radar data QC packages (delivered to NRL and NCEP) with operational raw level-II data collected in different regions under various weather conditions (especially high-impact weather conditions). Develop reflectivity-velocity combined radar data QC and assimilation capabilities that expand and upgrade the existing radar data QC and assimilation packages. Use the modern information theory to study how to measure information content from observations for data assimilation and design data compression strategies for the existing and currently developed assimilation capabilities based on the information theory. Develop a new prototype ensemble hybrid filter to combine the merits of the ensemble-based filters (such as the ensemble Kalman filter) and variational data assimilation (such as the 3.5dVar delivered to NRL) for flow-dependent covariance estimation and high-resolution radar data assimilation. Toward this goal, the first step is to explore new ideas and sampling techniques to improve the covariance estimation and computational efficiency of the existing ensemble-based filters.

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“…Examples of past research include the simple adjoint method (Qiu and Xu 1992;Xu et al 1995;Xu et al 2001a;Xu et al 2001b). The simple adjoint method retrieves the unobserved cross-beam winds by tracking, using a system involving the time integration of a two-dimensional advection equation and its adjoint.…”

Section: Nssl's Approachmentioning

confidence: 99%

Development of NEXRAD Wind Retrievals as Input to Atmospheric Dispersion Models

Fast¹,

Newsom²,

Allwine³

et al. 2007

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SummaryTwo techniques that derive spatially varying wind fields from operational radar measurements have been evaluated in this study. Based on results, we propose that one technique be implemented operationally in a phased approach. The other technique would be suitable for operational implementation only after additional modifications have been made and evaluated. These two techniques would require additional funding to implement, maintain operational versions of these codes, and perform additional research to improve their accuracy.Atmospheric dispersion models (ADMs) are used by emergency-response organizations to address the consequences of potential airborne releases of harmful materials. The wind fields in ADMs are based on meteorological measurements and forecasts made by atmospheric models. In the United States, routine meteorological measurements from surface stations, towers, rawinsondes, and radar wind profilers are available to drive ADMs. Large metropolitan areas usually have a network of surface stations; however, the wind-speed and direction measurements from these stations are usually not representative of conditions above the surface. There are currently relatively few measurements that can characterize the winds above the surface. One potentially rich, yet untapped, source of meteorological data for routine use in ADMs is from the Next Generation Weather Radar (NEXRAD) systems with 141 nearly identical WSR-88D Doppler radar units installed throughout the United States.The objective of this study is to determine the feasibility that routinely collected data from the Doppler radars can appropriately be used in ADMs for emergency response. We have evaluated the computational efficiency and accuracy of two variational mathematical techniques that derive the u-and v-components of the wind from radial velocities obtained from Doppler radars. A review of the scientific literature indicated that the techniques employ significantly different approaches in applying the variational techniques: 2-D Variational (2DVar), developed by the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory and Variational Doppler Radar Analysis System (VDRAS), developed by the National Center for Atmospheric Research. We designed a series of numerical experiments in which both models employed the same horizontal domain and resolution encompassing Oklahoma City for a 2-week period during the summer of 2003 so that the computed wind retrievals could be fairly compared. Both models ran faster than real-time on one typical dual-processor computer, indicating that they could be used to generate wind retrievals in near real-time. The simpler approach of 2DVar allowed it to execute ~2.5 faster than VDRAS. The simpler approach of 2DVar allowed it to execute ~2.5 times faster than VDRAS.The accuracy of 2DVar and VDRAS is quantified by comparing the derived wind components with independent, meteorological measurements made by radar wind profilers. Both systems qualitatively reproduced the observed diurn...

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Simple Adjoint Retrievals of Wet-Microburst Winds and Gust-Front Winds from Single-Doppler Radar Data

Cited by 19 publications

References 14 publications

High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

Radar Data Quality Control and Assimilation at the National Weather Radar Testbed (NWRT)

Development of NEXRAD Wind Retrievals as Input to Atmospheric Dispersion Models

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