2018
DOI: 10.5194/acp-18-2999-2018
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Extraction of wind and temperature information from hybrid 4D-Var assimilation of stratospheric ozone using NAVGEM

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 "flow-of-the-day" ensemble background error covariance that is blended together with the static background error covariance and (2) via the ozone continuity equation in the tangen… Show more

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Cited by 4 publications
(5 citation statements)
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“…4a and 4b, respectively. The matrix C static specifies various horizontal and vertical correlations among variables, complete descriptions of which can be found in sections 3.8 and 4 and appendix B of Daley and Barker (2001a) and in section 2.2 of Allen et al (2014). Figure 4e shows the vertical correlation of geopotential (temperature) errors, the width of which increases with height, consistent with a similar broadening of model layers with height in Fig.…”
Section: (Iii) Digital Filtersupporting
confidence: 55%
See 1 more Smart Citation
“…4a and 4b, respectively. The matrix C static specifies various horizontal and vertical correlations among variables, complete descriptions of which can be found in sections 3.8 and 4 and appendix B of Daley and Barker (2001a) and in section 2.2 of Allen et al (2014). Figure 4e shows the vertical correlation of geopotential (temperature) errors, the width of which increases with height, consistent with a similar broadening of model layers with height in Fig.…”
Section: (Iii) Digital Filtersupporting
confidence: 55%
“…The current NRL Atmospheric Variational DAS (NAVDAS) is based around a four-dimensional variational (4DVAR) algorithm solved in observation space using an accelerated representer (AR) method. An overview of NAVDAS-AR relevant to the 0-100-km NAVGEM is provided here; more complete descriptions of specific aspects are provided elsewhere (see, e.g., Daley and Barker 2001a;Xu et al 2005;Kuhl et al 2013;Allen et al 2014).…”
Section: ) Data Assimilation Algorithm (I) Formulationmentioning
confidence: 99%
“…To summarize, for the two periods considered, we observe that means of analysis differences between the two experiments range from ±2.0 K in the upper stratosphere, ±0.1 K in the lower stratosphere and ±0.25 K F I G U R E 6 Zonal mean cross-section of (a) temperature, (b) relative humidity and (c) zonal wind analysis differences between O3EXP and CONTROL from 12 July to 10 September 2016 F I G U R E 7 As Figure 6, but from 12 November to 31 December 2016 in troposphere for the temperature, ±3.0% in the lower troposphere and ±1.0% in UTLS for the relative humidity and ±2.0 m⋅s −1 in the upper stratosphere, ±0.2 m⋅s −1 in the lower stratosphere and ±0.1 m⋅s −1 in troposphere for the zonal wind component. It is interesting to note that the patterns and observed areas of differences in temperature and zonal wind analyses are similar to those presented in the work by Allen et al (2018) on the use of ozone for temperature and wind information extraction.…”
Section: Impact On Analysessupporting
confidence: 80%
“…It is interesting to note that the patterns and observed areas of differences in temperature and zonal wind analyses are similar to those presented in the work by Allen et al . (2018) on the use of ozone for temperature and wind information extraction.…”
Section: Resultsmentioning
confidence: 99%
“…The retrieval of satellite data and direct assimilation of radiances will play a critical role in this regard. Encouraging results are emerging, such as the positive effect of ozone assimilation on the wind fields (e.g., Allen et al 2018).…”
Section: Interactions Among Earth-system Componentsmentioning
confidence: 99%