Transport mechanisms for synoptic, seasonal and interannual SF&amp;lt;sub&amp;gt;6&amp;lt;/sub&amp;gt; variations and &amp;quot;age&amp;quot; of air in troposphere

Patra, Prabir K.; Takigawa, Masayuki; Dutton, G. S.; Uhse, K.; Ishijima, Kentaro; Lintner, Benjamin R.; Miyazaki, Kazuyuki; Elkins, James W.

doi:10.5194/acp-9-1209-2009

Cited by 80 publications

(117 citation statements)

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“…The ACTM uses a horizontal resolution of approximately 2.8° × 2.8° (T42 spectral truncation) and 1.125° × 1.125° (T106 spectral truncation), with 32 pressure-sigma vertical layers (Patra et al, 2009(Patra et al, , 2014). In the model simulations, ocean fluxes of O 2 and N 2 were taken from the TransCom experimental protocol (Garcia and Keeling, 2001;Blaine, 2005), and CO 2 from Takahashi et al (2009).…”

Section: Atmospheric Transport Modelmentioning

confidence: 99%

“…Emissions of anthropogenic CO 2 were taken from the Emission Database for Global Atmospheric Research (EDGAR, version 4.2) inventory scaled to Carbon Dioxide Information Analysis Center (CDIAC) global totals. Meteorological data used in the model were adjusted to the Japanese 25-year ReAnalysis data (JRA-25) (Onogi et al, 2007), and the atmospheric transport field of the model was validated by Patra et al (2009). In addition, tagged tracer experiments were performed using the ACTM at T106 resolution to reveal the contributions of different geographical regions to the observed APO variations.…”

Section: Atmospheric Transport Modelmentioning

confidence: 99%

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Seasonal and short-term variations in atmospheric potential oxygen at Ny-Ålesund, Svalbard

Goto

Morimoto

Aoki

et al. 2017

Tellus B: Chemical and Physical Meteorology

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Oxygen in the atmosphere undergoes variations and changes in response to biospheric activities, ocean-atmosphere exchange and fossil fuel combustion. Continuous in situ measurements of atmospheric δ(O 2 /N 2 ) and CO 2 mole fraction were started at Ny-Ålesund, Svalbard (78.93°N, 11.83°E, 40 m a.s.l.) in November 2012. Atmospheric potential oxygen (APO) calculated from the measured O 2 and CO 2 values during November 2012-January 2015 show a clear seasonal cycle with a peak-to-peak amplitude of approximately 50 per meg. The seasonal cycle of APO simulated using an atmospheric transport model, with prescribed oceanic O 2 , N 2 and CO 2 fluxes at monthly time intervals, is in excellent agreement with the observed APO. However, in spring and early summer, high values of APO are observed irregularly on a timescale of hours to days. By comparing backward trajectories of air parcels released from the site with distributions of marine net primary production (NPP), and tagged tracer experiments made using the atmospheric transport model for APO, it is found that these high APO fluctuations are primarily attributable to O 2 emissions from the Greenland Sea, the Norwegian Sea and the Barents Sea, due to marine biological productivity. Marine net community production, estimated based on the sea-to-air O 2 flux derived from observed APO fluctuations, agrees with NPP obtained from satellite observations within an order of magnitude. The results obtained in this study have still some uncertainties, but our continuous observations of atmospheric δ(O 2 /N 2 ) and CO 2 mole fraction at Ny-Ålesund can play an important role in detecting possible changes in the carbon cycle in the near future.

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Section: Atmospheric Transport Modelmentioning

confidence: 99%

Section: Atmospheric Transport Modelmentioning

confidence: 99%

Seasonal and short-term variations in atmospheric potential oxygen at Ny-Ålesund, Svalbard

Goto

Morimoto

Aoki

et al. 2017

Tellus B: Chemical and Physical Meteorology

View full text Add to dashboard Cite

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“…is developed for simulations of long-lived gases in the atmosphere (Numaguti et al, 1997;Patra et al, 2009aPatra et al, , 2014. The ACTM simulations are performed at a horizontal resolution of T42 spectral truncation (~2.8 x 2.8 deg) with 67 sigma levels in the vertical and model top at~90 km.…”

Section: Actmmentioning

confidence: 99%

Age of Air as a diagnostic for transport time-scales in global models

Krol¹,

Bruine²,

Killaars³

et al. 2017

Preprint

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Abstract. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, three global circulation models and three chemistry transport models simulated five tracers with boundary conditions that grow linearly in time. This allows for an evaluation of the AoA and transport times associated with inter-hemispheric transport, vertical mixing in the troposphere, transport to and in the stratosphere, and transport of air masses between land and ocean. Since AoA is not a directly measurable quantity in the atmosphere, simulations of 222 Rn and SF 6 were also requested. 5We focus this first analysis on averages over the period 2000-2010, taken from longer simulations covering the 1988 -2014 period. We find that two models, NIES and TOMCAT, show substantially slower vertical mixing in the troposphere compared to other models (LMDZ, TM5, EMAC, and ACTM). However, while the TOMCAT model, as used here, has slow transport between the hemispheres and between land and ocean, the NIES model shows efficient horizontal mixing and a smaller latitudinal gradient in SF 6 compared to the other models and observations. We find consistent differences between models concerning 10 vertical mixing of the troposphere, expressed as AoA differences and modeled 222Rn gradients between 950 and 500 hPa.All models agree, however, on an interesting asymmetry in inter-hemispheric mixing, with faster transport from the Northern hemisphere surface to the Southern hemisphere than vice versa. This is attributed to a rectifier caused by a stronger seasonal cycle in boundary layer venting over Northern hemispheric landmasses, and possibly to a related asymmetric position of the inter-tropical convergence zone. The calculated AoA in the upper stratosphere varies considerably among the models (4 -7 15 years). Finally, we find that the inter-model differences are generally larger than differences in AoA that result from using the same model with a different resolution or convective parameterisation. Taken together, the AoA model inter-comparison provides a useful addition to traditional approaches to evaluate transport time scales. Results highlight that inter-model differences 1 Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-262 Manuscript under review for journal Geosci. Model Dev. Discussion started: 7 November 2017 c Author(s) 2017. CC BY 4.0 License. associated with resolved transport (advection) and parameterised transport (convection, boundary layer mixing) are still large, and require further analysis. For this purpose, all model output and analysis software is available.

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“…For GHG simulations, there are two types of atmospheric transport models: one is online (e.g., Patra et al, 2009) and the other is offline (e.g., Kawa et al, 2004;Krol et al, 2005). Online models include atmospheric general circulation models (AGCMs) which incorporate passive tracers of GHGs and simulate their movements.…”

mentioning

confidence: 99%

A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models

et al. 2017

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Abstract. A four-dimensional variational (4D-Var) method is a popular algorithm for inverting atmospheric greenhouse gas (GHG) measurements. In order to meet the computationally intense 4D-Var iterative calculation, offline forward and adjoint transport models are developed based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). By introducing flexibility into the temporal resolution of the input meteorological data, the forward model developed in this study is not only computationally efficient, it is also found to nearly match the transport performance of the online model. In a transport simulation of atmospheric carbon dioxide (CO 2 ), the data-thinning error (error resulting from reduction in the time resolution of the meteorological data used to drive the offline transport model) is minimized by employing high temporal resolution data of the vertical diffusion coefficient; with a low 6-hourly temporal resolution, significant concentration biases near the surface are introduced. The new adjoint model can be run in discrete or continuous adjoint mode for the advection process. The discrete adjoint is characterized by perfect adjoint relationship with the forward model that switches off the flux limiter, while the continuous adjoint is characterized by an imperfect but reasonable adjoint relationship with its corresponding forward model. In the latter case, both the forward and adjoint models use the flux limiter to ensure the monotonicity of tracer concentrations and sensitivities. Trajectory analysis for high CO 2 concentration events are performed to test adjoint sensitivities. We also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport. Both the offline forward and adjoint models have computational efficiency about 10 times higher than the online model. A description of our new 4D-Var system that includes an optimization method, along with its application in an atmospheric CO 2 inversion and the effects of using either the discrete or continuous adjoint method, is presented in an accompanying paper (Niwa et al., 2016).

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Transport mechanisms for synoptic, seasonal and interannual SF<sub>6</sub> variations and "age" of air in troposphere

Cited by 80 publications

References 38 publications

Seasonal and short-term variations in atmospheric potential oxygen at Ny-Ålesund, Svalbard

Seasonal and short-term variations in atmospheric potential oxygen at Ny-Ålesund, Svalbard

Age of Air as a diagnostic for transport time-scales in global models

A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 1: Offline forward and adjoint transport models

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