Articles | Volume 15, issue 10
Atmos. Chem. Phys., 15, 5835–5850, 2015
https://doi.org/10.5194/acp-15-5835-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 15, 5835–5850, 2015
https://doi.org/10.5194/acp-15-5835-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 27 May 2015
Research article | 27 May 2015
Wind extraction potential from ensemble Kalman filter assimilation of stratospheric ozone using a global shallow water model
D. R. Allen et al.
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Cited
8 citations as recorded by crossref.
- All-Sky Microwave Radiances Assimilated with an Ensemble Kalman Filter M. Bonavita et al. 10.1175/MWR-D-19-0413.1
- Hybrid 4DVAR with a Local Ensemble Tangent Linear Model: Application to the Shallow-Water Model D. Allen et al. 10.1175/MWR-D-16-0184.1
- Challenges of Increased Resolution for the Local Ensemble Tangent Linear Model D. Allen et al. 10.1175/MWR-D-20-0016.1
- All‐sky satellite data assimilation at operational weather forecasting centres A. Geer et al. 10.1002/qj.3202
- Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM D. Allen et al. 10.5194/acp-18-2999-2018
- Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-16-8193-2016
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part II: Weak and Strong Coupling R. Ménard et al. 10.3390/atmos10120798
- The potential for geostationary remote sensing of NO<sub>2</sub> to improve weather prediction X. Liu et al. 10.5194/acp-21-9573-2021
8 citations as recorded by crossref.
- All-Sky Microwave Radiances Assimilated with an Ensemble Kalman Filter M. Bonavita et al. 10.1175/MWR-D-19-0413.1
- Hybrid 4DVAR with a Local Ensemble Tangent Linear Model: Application to the Shallow-Water Model D. Allen et al. 10.1175/MWR-D-16-0184.1
- Challenges of Increased Resolution for the Local Ensemble Tangent Linear Model D. Allen et al. 10.1175/MWR-D-20-0016.1
- All‐sky satellite data assimilation at operational weather forecasting centres A. Geer et al. 10.1002/qj.3202
- Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM D. Allen et al. 10.5194/acp-18-2999-2018
- Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-16-8193-2016
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part II: Weak and Strong Coupling R. Ménard et al. 10.3390/atmos10120798
- The potential for geostationary remote sensing of NO<sub>2</sub> to improve weather prediction X. Liu et al. 10.5194/acp-21-9573-2021
Latest update: 17 Jan 2022
Short summary
While direct wind observations are routinely made in the troposphere (0-10km), in the stratosphere (above 10km) wind observations are sparse. This study examines the potential of using ozone observations to infer stratospheric wind. This novel approach is tested with a data assimilation system based on a simplified model of the atmosphere, the so-called "shallow water model". It is shown that assimilation of ozone observations significantly benefits winds, particularly in the tropics.
While direct wind observations are routinely made in the troposphere (0-10km), in the...
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