Tests of an Ensemble Kalman Filter for Mesoscale and Regional-Scale Data Assimilation. Part III: Comparison with 3DVAR in a Real-Data Case Study
By Z. Meng, Fuqing Zhang. 2008
175 citations recorded by the source corpus.
Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/05aa6b6a470de6c81c0673eb26a1c67ecad671cc
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
- C. Melhauser
- Fuqing Zhang
- C. Snyder
- Juanzhen Sun
- D. Dowell
- Ming Xue
- Louis J. Wicker
- Takemasa Miyoshi
In Environmental Engineering
In Global and Planetary Change
- C. Melhauser
- Fuqing Zhang
- Juanzhen Sun
- D. Dowell
- Ming Xue
- C. Snyder
- Louis J. Wicker
- Takemasa Miyoshi
Citations in the corpus
- 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).”
- Practical and Intrinsic Predictability of Severe and Convective Weather at the Mesoscales (2012, methodology): “Only quality-controlled radiosonde observations are assimilated every 12 h in D02, since an earlier study of Meng and Zhang (2008a) found only marginal benefit gained through the assimilation of additional data from surface and profiler observations.”