A Three-Dimensional Variational Data Analysis Method with Recursive Filter for Doppler Radars

By Jidong Gao, Ming Xue, Keith A. Brewster, Kelvin Droegemeier. 2004

269 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/f405228dee42e6c07028353a6f02f91c63258219

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Xuguang Wang
2. D. Stensrud
3. Aaron Johnson
4. Jidong Gao
5. Ming Xue
6. Juanzhen Sun
7. Ming Hu
8. Keith A. Brewster

In Environmental Engineering

1. Xuguang Wang
2. Aaron Johnson
3. Juanzhen Sun
4. D. Stensrud
5. Jidong Gao
6. Ming Xue
7. Ming Hu
8. Xiangyu Huang

Citations in the corpus

• Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations (2013, methodology): “…Weather Surveillance Radars-1988 Doppler (WSR88Ds) and surface observations were assimilated into the initial conditions of these members identically using a three-dimensional variational data assimilation (3DVAR; Xue et al. 2003; Gao et al. 2004) data and cloud analysis (Hu et al. 2006) system.”
• Convective‐scale assimilation of radar data: progress and challenges (2005, unknown): “Gao et al. (1999, 2004) described a 3D-Var algorithm that aimed specifically at the assimilation of radar radial velocity.”
• 3DVAR and Cloud Analysis with WSR-88D Level-II Data for the Prediction of the Fort Worth, Texas, Tornadic Thunderstorms. Part I: Cloud Analysis and Its Impact (2006, methodology): “The wind retrieval methods include the so-called simple adjoint method (Qiu and Xu 1992, 1994; Xu et al. 1994; Gao et al. 2001) and two-scalar method of Shapiro et al. (1995), among others .”
• Air-Sea Enthalpy and Momentum Exchange at Major Hurricane Wind Speeds Observed during CBLAST (2012, unknown): “For the current study, a two-dimensional variational analysis technique called SAMURAI was developed based primarily on the work of Ooyama (1987, 2002) and Gao et al. (2004).”
• Verification and Calibration of Neighborhood and Object-Based Probabilistic Precipitation Forecasts from a Multimodel Convection-Allowing Ensemble (2012, methodology): “All but three members used ARPS three-dimensional variational data assimilation (3DVAR) and cloud analysis package (Gao et al. 2004; Xue et al. 2003; Hu et al. 2006) to assimilate Weather Surveillance Radar-1988 Doppler (WSR-88D) radial velocity and reflectivity along with surface pressure,…”
• Assimilation of Reflectivity Data in a Convective-Scale, Cycled 3DVAR Framework with Hydrometeor Classification (2012, methodology): “…al. (1998), Hu et al. (2006a,b), and Schenkman et al. (2011) have shown success in simulating and forecasting convective storms with a cloud analysis scheme, when radial velocity data are also assimilated in a three-dimensional variational data assimilation (3DVAR) system (Gao et al. 1999, 2004).”
• Indirect Assimilation of Radar Reflectivity with WRF 3D-Var and Its Impact on Prediction of Four Summertime Convective Events (2013, methodology): “These systems include the Advanced Research and Prediction System 3D-Var (Gao et al. 2004; Gao and Stensrud 2012), the high-resolution radar data assimilation system at the Naval Research Laboratory (Zhao and Jin 2008), and the system using the 1D13D-Var method at Météo-France (Caumont et al.…”