Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM

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Abstract

Extraction of wind and temperature information from stratospheric ozone assimilation is examined within the context of the Navy Global Environmental Model (NAVGEM) hybrid 4-D variational assimilation (4D-Var) data assimilation (DA) system. Ozone can improve the wind and temperature through two different DA mechanisms: (1) through the <q>flow-of-the-day</q> ensemble background error covariance that is blended together with the static background error covariance and (2) via the ozone continuity equation in the tangent linear model and adjoint used for minimizing the cost function. All experiments assimilate actual conventional data in order to maintain a similar realistic troposphere. In the stratosphere, the experiments assimilate simulated ozone and/or radiance observations in various combinations. The simulated observations are constructed for a case study based on a 16-day cycling truth experiment (TE), which is an analysis with no stratospheric observations. The impact of ozone on the analysis is evaluated by comparing the experiments to the TE for the last 6 days, allowing for a 10-day spin-up. Ozone assimilation benefits the wind and temperature when data are of sufficient quality and frequency. For example, assimilation of perfect (no applied error) global hourly ozone data constrains the stratospheric wind and temperature to within ĝ1/4 2ĝ€-mĝ€-sĝ'1 and ĝ1/4 1ĝ€-K. This demonstrates that there is dynamical information in the ozone distribution that can potentially be used to improve the stratosphere. This is particularly important for the tropics, where radiance observations have difficulty constraining wind due to breakdown of geostrophic balance. Global ozone assimilation provides the largest benefit when the hybrid blending coefficient is an intermediate value (0.5 was used in this study), rather than 0.0 (no ensemble background error covariance) or 1.0 (no static background error covariance), which is consistent with other hybrid DA studies. When perfect global ozone is assimilated in addition to radiance observations, wind and temperature error decreases of up to ĝ1/4 3ĝ€-mĝ€-sĝ'1 and ĝ1/4 1ĝ€-K occur in the tropical upper stratosphere. Assimilation of noisy global ozone (2ĝ€-% errors applied) results in error reductions of ĝ1/4ĝ€-1ĝ€-mĝ€-sĝ'1 and ĝ1/4ĝ€-0.5ĝ€-K in the tropics and slightly increased temperature errors in the Northern Hemisphere polar region. Reduction of the ozone sampling frequency also reduces the benefit of ozone throughout the stratosphere, with noisy polar-orbiting data having only minor impacts on wind and temperature when assimilated with radiances. An examination of ensemble cross-correlations between ozone and other variables shows that a single ozone observation behaves like a potential vorticity (PV) <q>charge</q>, or a monopole of PV, with rotation about a vertical axis and vertically oriented temperature dipole. Further understanding of this relationship may help in designing observation systems that would optimize the impact of ozone on the dynamics.

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Allen, D. R., Hoppel, K. W., & Kuhl, D. D. (2018). Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM. Atmospheric Chemistry and Physics, 18(4), 2999–3026. https://doi.org/10.5194/acp-18-2999-2018

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