The influence of data assimilation on the age of air calculated with a global chemistry‐transport model using ECMWF wind fields

Meijer, E.; Bregman, B.; Segers, Arjo; Velthoven, P. F. J. van

doi:10.1029/2004gl021158

Cited by 29 publications

(58 citation statements)

References 23 publications

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“…Using forecast rather than analyzed winds reduces the dispersion (Meijer et al 2004), as does the use of shorter intervals between analyses (Legras et al 2005). These findings suggest that the spurious dispersion found by using analysed winds at 6-hour intervals results from effectively ''freezing'' the noise introduced in the assimilation process, introducing artificially long correlation times in the winds by interpolating between 6-hour intervals.…”

Section: Transport In Modelsmentioning

confidence: 93%

Transport in the Middle Atmosphere

Shepherd

2007

Journal of the Meteorological Society of Japan

169

132

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An overview is provided of the current understanding of transport in the middle atmosphere. Over the past quarter century this subject has evolved from a basic recognition of the Brewer-Dobson circulation to a detailed appreciation of many key features of transport such as the stratospheric surf zone, mixing barriers, and the dynamics of filamentation. Whilst the elegant theoretical framework for middle atmosphere transport that emerged roughly twenty years ago never fulfilled its promise, useful phenomenological models have been developed together with innovative diagnostic methods. These advances were made possible by the advent of plentiful satellite and aircraft observations of long-lived chemical species together with developments in data assimilation and numerical modeling, and have been driven in large measure by the problem of stratospheric ozone depletion. This review is primarily focused on the stratosphere, where both the interest and the knowledge are the greatest, but a few remarks are also made on the mesosphere.

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Section: Transport In Modelsmentioning

confidence: 93%

Transport in the Middle Atmosphere

Shepherd

2007

Journal of the Meteorological Society of Japan

169

132

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“…Radiative heating rates (Q) are applied as vertical velocity in a quasi-isentropic trajectory model in the stratosphere to avoid the noisy (Manney et al, 2005b) and too high vertical velocities of meteorological assimilations (Meijer et al, 2004;Scheele et al, 2005;Monge-Sanz et al, 2007). Such an approach can be employed in the stratosphere, where radiative processes are determining the slow mean meridional circulation (Andrews et al, 1987).…”

Section: Model and Methodsmentioning

confidence: 99%

Long-term climatology of air mass transport through the Tropical Tropopause Layer (TTL) during NH winter

2008

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Abstract.A long-term climatology of air mass transport through the tropical tropopause layer (TTL) is presented, covering the period from 1962-2005. The transport through the TTL is calculated with a Lagrangian approach using radiative heating rates as vertical velocities in an isentropic trajectory model. We demonstrate the improved performance of such an approach compared to previous studies using vertical winds from meteorological analyses. Within the upper part of the TTL, the averaged diabatic ascent is 0.5 K/day during Northern Hemisphere (NH) winters 1992-2001. Climatological maps show a cooling and strengthening of this part of the residual circulation during the 1990s and early 2000s compared to the long-term mean. Lagrangian cold point (LCP) fields show systematic differences for varying time periods and natural forcing components. The interannual variability of LCP temperature and density fields is found to be influenced by volcanic eruptions, El Niño Southern Oscillation (ENSO), Quasi-Biennial Oscillation (QBO) and the solar cycle. The coldest and driest TTL is reached during QBO easterly phase and La Niña over the western Pacific, whereas during volcanic eruptions, El Niño and QBO westerly phase it is warmer and less dry.

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“…The results are not very sensitive to this choice. Our method of computing the mean age differs significantly from the method used by Meijer et al (2004). He calculated the age spectrum, starting with a delta function between 10 • S and 10 • N below 200 hPa, and integrated the TM4 model for 20 years in order to estimate the age at 20 km altitude.…”

Section: Methods To Calculate the Age Of Airmentioning

confidence: 99%

“…In a recent study by Meijer et al (2004), the stratospheric age of air in a CTM (the TM4 model), driven by different data sets from the European Centre for Medium-Range Weather Forecast (ECMWF), was compared to the age of air, calculated from observations (Andrews et al, 2001). The results showed that in the extratropics at 20 km altitude the simulated age of air was about half that of the observationbased age.…”

Section: Introductionmentioning

confidence: 99%

Stratospheric age of air computed with trajectories based on various 3D-Var and 4D-Var data sets

2005

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Abstract. The age of stratospheric air is computed with a trajectory model, using ECMWF ERA-40 3D-Var and operational 4D-Var winds. Analysis as well as forecast data are used. In the latter case successive forecast segments are put together to get a time series of the wind fields. This is done for different forecast segment lengths. The sensitivity of the computed age to the forecast segment length and assimilation method are studied, and the results are compared with observations and with results from a chemistry transport model that uses the same data sets. A large number of backward trajectories are started in the stratosphere, and from the fraction of these trajectories that has passed the tropopause the age of air is computed. First, for ten different data sets 50-day backward trajectories starting in the tropical lower stratosphere are computed. The results show that in this region the computed cross-tropopause transport decreases with increasing forecast segment length. Next, for three selected data sets (3D-Var 24-h and 4D-Var 72-h forecast segments, and 4D-Var analyses) 5-year backward trajectories are computed that start all over the globe at an altitude of 20 km. For all data sets the computed ages of air in the extratropics are smaller than the observation-based age. For 4D-Var forecast series they are closest to the observation-based values, but still 0.5-1.5 year too small. Compared to the difference in age between the results for the different data sets, the difference in age between the trajectory and the chemistry transport model results is small.

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The influence of data assimilation on the age of air calculated with a global chemistry‐transport model using ECMWF wind fields

Cited by 29 publications

References 23 publications

Transport in the Middle Atmosphere

Transport in the Middle Atmosphere

Long-term climatology of air mass transport through the Tropical Tropopause Layer (TTL) during NH winter

Stratospheric age of air computed with trajectories based on various 3D-Var and 4D-Var data sets

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