Articles | Volume 13, issue 6
https://doi.org/10.5194/acp-13-3501-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-3501-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Limitations of wind extraction from 4D-Var assimilation of ozone
D. R. Allen
Remote Sensing Division, Naval Research Laboratory, Washington, DC, USA
K. W. Hoppel
Remote Sensing Division, Naval Research Laboratory, Washington, DC, USA
G. E. Nedoluha
Remote Sensing Division, Naval Research Laboratory, Washington, DC, USA
D. D. Kuhl
Remote Sensing Division, Naval Research Laboratory, Washington, DC, USA
N. L. Baker
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
L. Xu
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
T. E. Rosmond
Science Applications International Corporation, Forks, WA, USA
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Cited
12 citations as recorded by crossref.
- Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-16-8193-2016
- Wind extraction potential from ensemble Kalman filter assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-15-5835-2015
- The growing impact of satellite observations sensitive to humidity, cloud and precipitation A. Geer et al. 10.1002/qj.3172
- Improved hurricane forecasting from a variational bogus and ozone data assimilation (BODA) scheme: case study Y. Liu & W. Zhang 10.1007/s00703-016-0460-2
- Flow‐dependent wind extraction in strong‐constraint 4D‐Var Ž. Zaplotnik et al. 10.1002/qj.4497
- Wind extraction potential from 4D-Var assimilation of stratospheric O<sub>3</sub>, N<sub>2</sub>O, and H<sub>2</sub>O using a global shallow water model D. Allen et al. 10.5194/acp-14-3347-2014
- An intermediate‐complexity model for four‐dimensional variational data assimilation including moist processes Ž. Zaplotnik et al. 10.1002/qj.3338
- 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
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part II: Weak and Strong Coupling R. Ménard et al. 10.3390/atmos10120798
- Inferring atmospheric dynamics from aerosol observations in 4D‐Var Ž. Zaplotnik et al. 10.1002/qj.3743
- 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
12 citations as recorded by crossref.
- Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-16-8193-2016
- Wind extraction potential from ensemble Kalman filter assimilation of stratospheric ozone using a global shallow water model D. Allen et al. 10.5194/acp-15-5835-2015
- The growing impact of satellite observations sensitive to humidity, cloud and precipitation A. Geer et al. 10.1002/qj.3172
- Improved hurricane forecasting from a variational bogus and ozone data assimilation (BODA) scheme: case study Y. Liu & W. Zhang 10.1007/s00703-016-0460-2
- Flow‐dependent wind extraction in strong‐constraint 4D‐Var Ž. Zaplotnik et al. 10.1002/qj.4497
- Wind extraction potential from 4D-Var assimilation of stratospheric O<sub>3</sub>, N<sub>2</sub>O, and H<sub>2</sub>O using a global shallow water model D. Allen et al. 10.5194/acp-14-3347-2014
- An intermediate‐complexity model for four‐dimensional variational data assimilation including moist processes Ž. Zaplotnik et al. 10.1002/qj.3338
- 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
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part II: Weak and Strong Coupling R. Ménard et al. 10.3390/atmos10120798
- Inferring atmospheric dynamics from aerosol observations in 4D‐Var Ž. Zaplotnik et al. 10.1002/qj.3743
- 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
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