Wind and Temperature Retrievals in the 17 May 1981 Arcadia, Oklahoma, Supercell: Ensemble Kalman Filter Experiments

By D. Dowell, Fuqing Zhang, Louis J. Wicker, C. Snyder, N. A. Crook. 2004

301 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/3614f4a8c22510bf610ede8aaea27c5395a6d78c

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. D. Dowell
2. Louis J. Wicker
3. Juanzhen Sun
4. C. Snyder
5. Fuqing Zhang
6. Xuguang Wang
7. Z. Meng
8. Ming Xue

In Global and Planetary Change

1. D. Dowell
2. Louis J. Wicker
3. Juanzhen Sun
4. C. Snyder
5. Fuqing Zhang
6. Z. Meng
7. Ming Xue
8. Xuguang Wang

Citations in the corpus

• CONVECTIVE-SCALE WARN-ON-FORECAST SYSTEM: A vision for 2020 (2009, background): “Several other studies have assimilated simulated (Zhang et al. 2004; Tong and Xue 2005; Caya et al. 2005; Xue et al. 2006; Jung et al. 2008) or real radar observations (Xue et al. 2003; Dowell et al. 2004; Hu et al. 2006; Smith et al. 2008; Weygandt et al. 2008; Dowell and Wicker 2009; Aksoy et al.…”
• Operational Implementation of the 1D+3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model (2014, background): “Therefore, assessments with real radar observations have been limited to specific cases of convective organization (Dowell et al. 2004; Aksoy et al. 2009, 2010).”
• Ensemble kalman filter assimilation of doppler radar data with a compressible nonhydrostatic model : OSS experiments (2005, methodology): “We note that in Dowell et al. (2004), which employs warm rain microphysics, it is found that updating qr only when assimilating reflectivity observations helps to maintain a realistic structure of the precipitation core and to improve the velocity verification score.”
• Indirect Assimilation of Radar Reflectivity with WRF 3D-Var and Its Impact on Prediction of Four Summertime Convective Events (2013, background): “The potential of the EnKF’s application to the convective scale was shown by assimilating simulated or real reflectivity observations (e.g., Dowell et al. 2004, 2011; Tong and Xue 2005, 2008; Xue et al. 2006; Jung et al. 2008; Aksoy et al. * The National Center for Atmospheric Research is sponsored…”
• Multiple-Radar Data Assimilation and Short-Range Quantitative Precipitation Forecasting of a Squall Line Observed during IHOP_2002 (2007, methodology): “Dowell et al. (2004) applied an ensemble Kalman filter technique (Evensen 1994; Snyder and Zhang 2003; Zhang et al. 2004) to initialize the cloud model developed by Sun and Crook (1997, 1998).”
• A Multicase Comparative Assessment of the Ensemble Kalman Filter for Assimilation of Radar Observations. Part I: Storm-Scale Analyses (2009, methodology): “Three independent cases with various convective behavior (a supercell, a convective line, and a multicellular system) were considered, along with the benchmark supercell case of Dowell et al. (2004b). All cases are selected according to the same set of criteria which include: (i) isolated events, (i”
• Tests of an Ensemble Kalman Filter for Mesoscale and Regional-Scale Data Assimilation. Part I: Perfect Model Experiments (2006, unknown): “These models vary from idealized examples based on simplified equation sets to those based on the complete, primitive equations with assimilation of real observations (Houtekamer and Mitchell 1998, 2001; Hamill and Snyder 2000; Keppenne 2000; Anderson 2001; Mitchell et al. 2002; Keppenne and Rieneck”
• Tests of an Ensemble Kalman Filter for Mesoscale and Regional-Scale Data Assimilation. Part III: Comparison with 3DVAR in a Real-Data Case Study (2008, background): “For example, encouraging results in real-data applications have been obtained in an ocean general circulation model (Keppenne and Rienecker 2002), as well as global (Whitaker et al. 2004, 2008; Houtekamer et al. 2005) and limitedarea models ( Dowell et al. 2004; Barker 2005; Fujita et al. 2005).”
• Additive Noise for Storm-Scale Ensemble Data Assimilation (2009, methodology): “Dowell et al. (2004a) reported only minor improvement (2% reduction in root-mean-square innovation) through the use of covariance inflation.”
• A Hybrid ETKF-3DVAR Data Assimilation Scheme for the WRF Model. Part I: Observing System Simulation Experiment (2008, unknown): “Studies more recently have included limited-area models resolving meso- and convective scales (e.g., Snyder and Zhang 2003; Dowell et al. 2004; Tong and Xue 2005; Meng and Zhang 2008; Liu et al. 2008; Dirren et al. 2007; Torn and Hakim 2008).”
• Tornadogenesis: Our current understanding, forecasting considerations, and questions to guide future research (2009, background): “…radars], continually increasing computing power, used not just for simulations but also to improve diagnoses of storm morphology via data assimilation (Snyder and Zhang, 2003; Dowell et al., 2004; Zhang and Snyder, 2007), and a growing interest in severe convective storms worldwide.”