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  • 11
    Online Resource
    Online Resource
    Copernicus GmbH ; 2020
    In:  Atmospheric Chemistry and Physics Vol. 20, No. 14 ( 2020-07-22), p. 8627-8639
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 20, No. 14 ( 2020-07-22), p. 8627-8639
    Abstract: Abstract. Various observation-based datasets have confirmed positive zonal mean column ozone trends at midlatitudes as a result of the successful implementation of the Montreal Protocol. However, there is still uncertainty about the longitudinal variation of these trends and the direction and magnitude of ozone changes at low latitudes. Here, we use the extended Copernicus Climate Change Service (C3S) dataset (1979–2017) to investigate the long-term variations in total column ozone (TCO) over the Tibetan Plateau (TP) for different seasons. We use piecewise linear trend (PWLT) and equivalent effective stratospheric chlorine loading (EESC)-based multivariate regression models with various proxies to attribute the influence of dynamical and chemical processes on the TCO variability. We also compare the seasonal behaviour of the relative total ozone low (TOL) over the TP with the zonal mean at the same latitude. Both regression models show that the TP column ozone trends change from negative trends from 1979 to 1996 to small positive trends from 1997 to 2017, although the later positive trend based on PWLT is not statistically significant. The wintertime positive trend starting from 1997 is larger than that in summer, but both seasonal TP recovery rates are smaller than the zonal means over the same latitude band. For TP column ozone, both regression models suggest that the geopotential height at 150 hPa (GH150) is a more suitable and realistic dynamical proxy compared to a surface temperature proxy used in some previous studies. Our analysis also shows that the wintertime GH150 plays an important role in determining summertime TCO over the TP through persistence of the ozone signal. For the zonal mean column ozone at this latitude, the quasi-biennial oscillation (QBO) is nonetheless the dominant dynamical proxy. We also use a 3-D chemical transport model to diagnose the contributions of different proxies for the TP region. The role of GH150 variability is illustrated by using two sensitivity experiments with repeating dynamics of 2004 and 2008. The simulated ozone profiles clearly show that wintertime TP ozone concentrations are largely controlled by tropics to midlatitude pathways, whereas in summer variations associated with tropical processes play an important role. These model results confirm that the long-term trends of TCO over the TP are dominated by different processes in winter and summer. The different TP recovery rates relative to the zonal means at the same latitude band are largely determined by wintertime dynamical processes.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 12
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 24, No. 2 ( 2024-01-19), p. 789-806
    Abstract: Abstract. Exposure to air pollution is a leading public health risk factor in India, especially over densely populated Delhi and the surrounding Indo-Gangetic Plain. During the post-monsoon seasons, the prevailing north-westerly winds are known to influence aerosol pollution events in Delhi by advecting pollutants from agricultural fires as well as from local sources. Here we investigate the year-round impact of meteorology on gaseous nitrogen oxides (NOx=NO+NO2). We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P aboard TROPOMI, alongside a back-trajectory model (ROTRAJ) to investigate the balance of local and external sources influencing air pollution changes in Delhi, with a focus on different emissions sectors. Our analysis shows that accumulated emissions (i.e. integrated along the trajectory path, allowing for chemical loss) are highest under westerly, north-westerly and northerly flow during pre-monsoon (February–May) and post-monsoon (October–February) seasons. According to this analysis, during the pre-monsoon season, the highest accumulated satellite TCNO2 trajectories come from the east and north-west of Delhi. TCNO2 is elevated within Delhi and the Indo-Gangetic Plain (IGP) to the east of city. The accumulated NOx emission trajectories indicate that the transport and industry sectors together account for more than 80 % of the total accumulated emissions, which are dominated by local sources ( 〉 70 %) under easterly winds and north-westerly winds. The high accumulated emissions estimated during the pre-monsoon season under north-westerly wind directions are likely to be driven by high NOx emissions locally and in nearby regions (since NOx lifetime is reduced and the boundary layer is relatively deeper in this season). During the post-monsoon season the highest accumulated satellite TCNO2 trajectories are advected from Punjab and Haryana, where satellite TCNO2 is elevated, indicating the potential for the long-range transport of agricultural burning emissions to Delhi. However, accumulated NOx emissions indicate local (70 %) emissions from the transport sector are the largest contributor to the total accumulated emissions. High local emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary layer, aid the build-up of emissions locally and along the trajectory path. This indicates the possibility that fire emissions datasets may not capture emissions from agricultural waste burning in the north-west sufficiently to accurately quantify their influence on Delhi air quality (AQ). Analysis of daily ground-based NO2 observations indicates that high-pollution episodes ( 〉 90th percentile) occur predominantly in the post-monsoon season, and more than 75 % of high-pollution events are primarily caused by local sources. But there is also a considerable influence from non-local (30 %) emissions from the transport sector during the post-monsoon season. Overall, we find that in the post-monsoon season, there is substantial accumulation of high local NOx emissions from the transport sector (70 % of total emissions, 70 % local), alongside the import of NOx pollution into Delhi (30 % non-local). This work indicates that both high local NOx emissions from the transport sector and the advection of highly polluted air originating from outside Delhi are of concern for the population. As a result, air quality mitigation strategies need to be adopted not only in Delhi but in the surrounding regions to successfully control this issue. In addition, our analysis suggests that the largest benefits to Delhi NOx air quality would be seen with targeted reductions in emissions from the transport and agricultural waste burning sectors, particularly during the post-monsoon season.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2024
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 13
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2021
    In:  Geophysical Research Letters Vol. 48, No. 4 ( 2021-02-28)
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 48, No. 4 ( 2021-02-28)
    Abstract: Large mean Arctic ( 〉 63°N) chemical ozone destruction in 2019/20 of 78 DU, similar to other extreme cold winters in the past 2 decades Anomalously weak wintertime dynamical replenishment of only ∼60 DU contributed strongly to the very low observed ozone column in March Ozone recovery caused 20 DU less mean Arctic ozone loss in March 2020 than would have occurred with stratospheric halogens at 1995 levels
    Type of Medium: Online Resource
    ISSN: 0094-8276 , 1944-8007
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2021
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 14
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 126, No. 6 ( 2021-03-27)
    Abstract: Very large OClO and very low NO 2 slant columns were observed by GOME‐2A during Arctic winter 2019/20 Chemical total column ozone loss of 88 DU and 106 DU was derived from TROPOMI satellite observations and the chemical transport model Chemical ozone loss derived from OMPS‐LP satellite data reached 2.1 ppmv (80%) near the 450 K potential temperature level (∼18 km)
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2021
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
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  • 15
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 21, No. 5 ( 2021-03-04), p. 3317-3343
    Abstract: Abstract. As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 16
    Online Resource
    Online Resource
    Copernicus GmbH ; 2022
    In:  Atmospheric Chemistry and Physics Vol. 22, No. 16 ( 2022-08-23), p. 10635-10656
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 22, No. 16 ( 2022-08-23), p. 10635-10656
    Abstract: Abstract. We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, we use the Copernicus Climate Change Service (C3S) data (1979–2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases (〉 15 DU, Dobson units) during winter–spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show that, compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the Southern Hemisphere (SH) mid latitudes, while for A_ERAI in the NH mid latitudes, simulated ozone trends remain negative. Similarly, in the lower stratosphere, B_ERA5 shows positive ozone recovery trends for both NH and SH mid latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid latitudes. Furthermore, we analyse age of air (AoA) trends to diagnose transport differences between the two reanalysis data sets. Simulation B_ERA5 shows a positive AoA trend after 1998 and somewhat older age in the NH lower stratosphere compared to A_ERAI, indicating that a slower Brewer–Dobson circulation does not translate into reduced wintertime ozone buildup in the NH extratropical lower stratosphere. Overall, our results show that models forced by the most recent ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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