The Development of a Terrain-Resolving Scheme for the Forward Model and Its Adjoint in the Four-Dimensional Variational Doppler Radar Analysis System (VDRAS)

Abstract The four-dimensional Variational Doppler Radar Analysis System (VDRAS) developed at the National Center for Atmospheric Research (NCAR) is significantly improved by implementing a terrain-resolving scheme to its forward model and adjoint based on the ghost cell immersed boundary method (GCIBM), which allows the topographic effects to be considered without the necessity to rebuild the model on a terrain-following coordinate system. The new system, called IBM_VDRAS, is able to perform forward forecast and backward adjoint model integration over nonflat lower boundaries, ranging from mountains with smooth slopes to buildings with sharp surfaces. To evaluate the performance of the forward model over complex terrain, idealized numerical experiments of a two-dimensional linear mountain wave and three-dimensional leeside vortices are first conducted, followed by a comparison with a simulation by the Weather Research and Forecasting (WRF) Model. An observing system simulation experiment is also conducted with the assimilation of simulated radar data to examine the ability of IBM_VDRAS in analyzing orographically forced moist convection. It is shown that the IBM_VDRAS can retrieve terrain-influenced three-dimensional meteorological fields including winds, thermodynamic, and microphysical parameters with reasonable accuracy. The new system, with the advanced radar data assimilation capability and the GCIBM terrain scheme, has the potential to be used for studying the evolution of convective weather systems under the influence of terrain.

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

Monthly Weather Review ◽

10.1175/mwr-d-11-00151.1 ◽

2012 ◽

Vol 140 (5) ◽

pp. 1603-1619 ◽

Cited By ~ 18

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.

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GSI-Based, Continuously Cycled, Dual-Resolution Hybrid Ensemble–Variational Data Assimilation System for HWRF: System Description and Experiments with Edouard (2014)

Monthly Weather Review ◽

10.1175/mwr-d-17-0068.1 ◽

2017 ◽

Vol 145 (12) ◽

pp. 4877-4898 ◽

Cited By ~ 20

Author(s):

Xu Lu ◽

Xuguang Wang ◽

Mingjing Tong ◽

Vijay Tallapragada

Keyword(s):

Data Assimilation ◽

Doppler Radar ◽

Three Dimensional ◽

Track Forecast ◽

Short Term ◽

Sea Level Pressure ◽

Maximum Wind ◽

System A ◽

Analysis System ◽

New System

A Gridpoint Statistical Interpolation analysis system (GSI)-based, continuously cycled, dual-resolution hybrid ensemble Kalman filter–variational (EnKF-Var) data assimilation (DA) system is developed for the Hurricane Weather Research and Forecasting (HWRF) Model. In this system, a directed moving nest strategy is developed to solve the issue of nonoverlapped domains for cycled ensemble DA. Additionally, both dual-resolution and four-dimensional ensemble–variational (4DEnVar) capabilities are implemented. Vortex modification (VM) and relocation (VR) are used in addition to hybrid DA. Several scientific questions are addressed using the new system for Hurricane Edouard (2014). It is found that dual-resolution hybrid DA improves the analyzed storm structure and short-term maximum wind speed (Vmax) and minimum sea level pressure (MSLP) forecasts compared to coarser, single-resolution hybrid DA, but track and radius of maximum wind (RMW) forecasts do not improve. Additionally, applying VR and VM on the control background before DA improves the analyzed storm, overall track, RMW, MSLP, and Vmax forecasts. Further applying VR on the ensemble background improves the analyzed storm and forecast biases for MSLP and Vmax. Also, using 4DEnVar to assimilate tail Doppler radar (TDR) data improves the analyzed storm and short-term MSLP and Vmax forecasts compared to three-dimensional ensemble–variational (3DEnVar) although 4DEnVar slightly degrades the track forecast. Finally, the new system improves overall RMW, MSLP, and Vmax forecasts upon the operational HWRF, while no improvement on track is found. The intensity forecast improvement during the intensifying period is due to the better analyzed structures for an intensifying storm.

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Assimilating C-Band Radar Data for High-Resolution Simulations of Precipitation: Case Studies over Western Sumatra

Remote Sensing ◽

10.3390/rs14010042 ◽

2021 ◽

Vol 14 (1) ◽

pp. 42

Author(s):

Bojun Zhu ◽

Zhaoxia Pu ◽

Agie Wandala Putra ◽

Zhiqiu Gao

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Doppler Radar ◽

Weather Prediction ◽

Wrf Model ◽

Active Phase ◽

Radar Data ◽

Skill Score ◽

Moist Convection ◽

Simulated Precipitation

Accurate high-resolution precipitation forecasts are critical yet challenging for weather prediction under complex topography or severe synoptic forcing. Data fusion and assimilation aimed at improving model forecasts, as one possible approach, has gained increasing attention in past decades. This study investigates the influence of the observations from a C-band Doppler radar over the west coast of Sumatra on high-resolution numerical simulations of precipitation around its vicinity under the Madden–Julian oscillation (MJO) in January and February 2018. Cases during various MJO phases were selected for simulations with an advanced research version of the weather research and forecasting (WRF) model at a cloud-permitting scale (~3 km). A 3-dimensional variational (3DVAR) data assimilation method and a hybrid three-dimensional ensemble–variational data assimilation (3DEnVAR) method, based on the NCEP Gridpoint Statistical Interpolation (GSI) assimilation system, were used to assimilate the radar reflectivity and the radial velocity data. The WRF-simulated precipitation was validated with the Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data, and the fractions skill score (FSS) was calculated in order to evaluate the radar data impacts objectively. The results show improvements in the simulated precipitation with hourly radar data assimilation 6 h prior to the simulations. The modifications with assimilation were validated through the observation departure and moist convection. It was found that forecast improvements are relatively significant when precipitation is more related to local-scale convection but rather small when the background westerly wind is strong under the MJO active phase. The additional simulation experiments, under a 1- or 2-day assimilation cycle, indicate better improvements in the precipitation simulation with 3DEnVAR radar assimilation than those with the 3DVAR method.

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Retrieval of three-dimensional wind fields from Doppler radar data using an efficient two-step approach

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-3-4459-2010 ◽

2010 ◽

Vol 3 (5) ◽

pp. 4459-4495 ◽

Cited By ~ 1

Author(s):

C. López Carrillo ◽

D. J. Raymond

Keyword(s):

Variational Approach ◽

Continuity Equation ◽

Doppler Radar ◽

Three Dimensional ◽

Relevant Information ◽

Radar Data ◽

Wind Fields ◽

Wind Retrieval ◽

Complex Sampling ◽

Doppler Radar Data

Abstract. In this work, we describe an efficient approach for wind retrieval from dual Doppler radar data. The approach produces a gridded field that not only satisfies the observations, but also satisfies the anelastic mass continuity equation. The method is based on the so-called three-dimensional variational approach to the retrieval of wind fields from radar data. The novelty consists in separating the task into steps that reduce the amount of data processed by the global minimization algorithm, while keeping the most relevant information from the radar observations. The method is flexible enough to incorporate observations from several radars, accommodate complex sampling geometries, and readily include dropsonde or sounding observations in the analysis. We demonstrate the usefulness of our method by analyzing a real case with data collected during the TPARC/TCS-08 field campaign.

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WRF-model sensitivity test and assimilation studies of Cempaka tropical cyclone

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/893/1/012029 ◽

2021 ◽

Vol 893 (1) ◽

pp. 012029

Author(s):

Fazrul Rafsanjani Sadarang ◽

Fitria Puspita Sari

Keyword(s):

Tropical Cyclone ◽

Doppler Radar ◽

Time Integration ◽

Wrf Model ◽

Radar Data ◽

Control Model ◽

Cyclone Track ◽

Tropical Cyclone Track ◽

Parameterization Schemes ◽

Assimilation Scheme

Abstract The WRF model was used to forecast the most intensive stage of Cempaka Tropical Cyclone (TC) on 27 - 29 November 2017. This study evaluates the combination of cumulus and microphysics parameterization and the efficiency of assimilation method to predict pressure values at the center of the cyclone, maximum wind speed, and cyclone track. This study tested 18 combinations of cumulus and microphysics parameterization schemes to obtain the best combination of both parameterization schemes which later on called as control model (CTL). Afterward, assimilation schemes using 3DVAR cycles of 1, 3, 6 hours, and 4DVAR, namely RUC01, RUC03, RUC06, and 4DV, were evaluated for two domains with grid size of each 30 and 10 km. GFS data of 0.25-degree and the Yogyakarta Doppler Radar data were used as the initial data and assimilation data input, respectively. The result of the parameterization test shows that there is no combination of parameterization schemes that constantly outperform all variables. However, the combination of Kain-Fritsch and Thompson can produce the best prediction of tropical cyclone track compared to other combinations. While, the RUC03 assimilation scheme was noted as the most efficient method based on the accuracy of track prediction and duration of model time integration.

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Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector–Derived Flow

Monthly Weather Review ◽

10.1175/mwr-d-18-0119.1 ◽

2018 ◽

Vol 146 (10) ◽

pp. 3461-3480 ◽

Cited By ~ 10

Author(s):

Jason M. Apke ◽

John R. Mecikalski ◽

Kristopher Bedka ◽

Eugene W. McCaul ◽

Cameron R. Homeyer ◽

...

Keyword(s):

Doppler Radar ◽

Deep Convection ◽

Motion Vector ◽

Three Dimensional ◽

Radar Data ◽

Severe Weather ◽

Lightning Flash ◽

Rapid Scan ◽

Total Lightning ◽

The Relationship

Abstract Rapid acceleration of cloud-top outflow near vigorous storm updrafts can be readily observed in Geostationary Operational Environmental Satellite-14 (GOES-14) super rapid scan (SRS; 60 s) mode data. Conventional wisdom implies that this outflow is related to the intensity of updrafts and the formation of severe weather. However, from an SRS satellite perspective, the pairing of observed expansion and updraft intensity has not been objectively derived and documented. The goal of this study is to relate GOES-14 SRS-derived cloud-top horizontal divergence (CTD) over deep convection to internal updraft characteristics, and document evolution for severe and nonsevere thunderstorms. A new SRS flow derivation system is presented here to estimate storm-scale (<20 km) CTD. This CTD field is coupled with other proxies for storm updraft location and intensity such as overshooting tops (OTs), total lightning flash rates, and three-dimensional flow fields derived from dual-Doppler radar data. Objectively identified OTs with (without) matching CTD maxima were more (less) likely to be associated with radar-observed deep convection and severe weather reports at the ground, suggesting that some OTs were incorrectly identified. The correlation between CTD magnitude, maximum updraft speed, and total lightning was strongly positive for a nonsupercell pulse storm, and weakly positive for a supercell with multiple updraft pulses present. The relationship for the supercell was nonlinear, though larger flash rates are found during periods of larger CTD. Analysis here suggests that combining CTD with OTs and total lightning could have severe weather nowcasting value.

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Investigation of Extreme Rainfall Patterns around Antalya and Muğla Cities in Türkiye by Using C Band Doppler Radar Data

10.5194/egusphere-egu21-14529 ◽

2021 ◽

Author(s):

Emir Yapıcı ◽

Ahmet Öztopal ◽

Erdem Erdi

Keyword(s):

Doppler Radar ◽

Three Dimensional ◽

Extreme Rainfall ◽

Radar Data ◽

Mediterranean Coast ◽

Extreme Rainfall Events ◽

Weather Radars ◽

Hourly Rainfall ◽

Raingauge Data ◽

Rainfall Patterns

As is known, rainfall varies spatially and temporally with regard to intensity and frequency. Floods, related to extreme rainfall cases, cause stress on geophysical system and community if climate change is considered. For this reason determining of extreme rainfall patterns is very important. While obtaining three dimensional status of hydrometors in atmosphere is not possible only by using ground station networks, it is possible by using weather radars. Therefore, weather radars provide significant contribution to studies about getting cloud and rainfall patterns. The aim of this study is to investigate spatial patterns of extreme rainfall events in Antalya and Mu&#287;la cities which are located on the Mediterranean coast of T&#252;rkiye. Firstly, hourly rainfall (RN1) and rain rate (SRI) products of 2 C band doppler radars and raingauge data between 2015 and 2020 will be processed by a software named MeteoRadar which is developed by &#304;stanbul Technical University. It is capable of reading, decoding, parallel processing and visualization. Secondly, extreme rainfall patterns will be obtained over 2 study areas. Finally, after validation by using raingauge data, results will be discussed in detail.Key Words: Antalya, Extreme rainfall, MeteoRadar, Mu&#287;la, RN1, SRI, Weather radar.

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Retrieved Thermodynamic Structure of Hurricane Rita (2005) from Airborne Multi-Doppler Radar Data

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-20-0195.1 ◽

2021 ◽

Author(s):

Annette M. Boehm ◽

Michael M. Bell

Keyword(s):

Wind Shear ◽

Doppler Radar ◽

Three Dimensional ◽

Vertical Wind Shear ◽

Vertical Motion ◽

Radar Data ◽

Vertical Wind ◽

Vertical Acceleration ◽

Hurricane Rita ◽

Doppler Radar Data

AbstractThe newly developed SAMURAI-TR is used to estimate three-dimensional temperature and pressure perturbations in Hurricane Rita on 23 September 2005 from multi-Doppler radar data during the RAINEX field campaign. These are believed to be the first fully three-dimensional gridded thermodynamic observations from a TC. Rita was a major hurricane at this time and was affected by 13 m s−1 deep-layer vertical wind shear. Analysis of the contributions of the kinematic and retrieved thermodynamic fields to different azimuthal wavenumbers suggests the interpretation of eyewall convective forcing within a three-level framework of balanced, quasi-balanced, and unbalanced motions. The axisymmetric, wavenumber-0 structure was approximately in thermal-wind balance, resulting in a large pressure drop and temperature increase toward the center. The wavenumber-1 structure was determined by the interaction of the storm with environmental vertical wind shear resulting in a quasi-balance between shear and shear-induced kinematic and thermo-dynamic perturbations. The observed wavenumber-1 thermodynamic asymmetries corroborate results of previous studies on the response of a vortex tilted by shear, and add new evidence that the vertical motion is nearly hydrostatic on the wavenumber-1 scale. Higher-order wavenumbers were associated with unbalanced motions and convective cells within the eyewall. The unbalanced vertical acceleration was positively correlated with buoyant forcing from thermal perturbations and negatively correlated with perturbation pressure gradients relative to the balanced vortex.

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A radar reflectivity operator with ice-phase hydrometeors for variational data assimilation (version 1.0) and its evaluation with real radar data

Geoscientific Model Development ◽

10.5194/gmd-12-4031-2019 ◽

2019 ◽

Vol 12 (9) ◽

pp. 4031-4051 ◽

Cited By ~ 1

Author(s):

Shizhang Wang ◽

Zhiquan Liu

Keyword(s):

Data Assimilation ◽

Three Dimensional ◽

Wrf Model ◽

Radar Data ◽

Poor Quality ◽

Variational Data Assimilation ◽

Radar Reflectivity ◽

Background Error ◽

Background Fields ◽

Ice Phase

Abstract. A reflectivity forward operator and its associated tangent linear and adjoint operators (together named RadarVar) were developed for variational data assimilation (DA). RadarVar can analyze both rainwater and ice-phase species (snow and graupel) by directly assimilating radar reflectivity observations. The results of three-dimensional variational (3D-Var) DA experiments with a 3 km grid mesh setting of the Weather Research and Forecasting (WRF) model showed that RadarVar was effective at producing an analysis of reflectivity pattern and intensity similar to the observed data. Two to three outer loops with 50–100 iterations in each loop were needed to obtain a converged 3-D analysis of reflectivity, rainwater, snow, and graupel, including the melting layers with mixed-phase hydrometeors. It is shown that the deficiencies in the analysis using this operator, caused by the poor quality of the background fields and the use of the static background error covariance, can be partially resolved by using radar-retrieved hydrometeors in a preprocessing step and tuning the spatial correlation length scales of the background errors. The direct radar reflectivity assimilation using RadarVar also improved the short-term (2–5 h) precipitation forecasts compared to those of the experiment without DA.

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