A revised global ozone dry deposition estimate based on a new two-layer parameterisation for air–sea exchange and the multi-year MACC composition reanalysis

Luhar, Ashok K.; Woodhouse, Matthew T.; Galbally, Ian E.

doi:10.5194/acp-18-4329-2018

Cited by 35 publications

(65 citation statements)

References 47 publications

(119 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Comparison with modern measurements from the TOAR database suggests that surface ozone has increased by 32-71%, with large uncertainty, in rural air in the temperate and polar zones of the northern hemisphere, and by much smaller amounts in the southern hemisphere. This estimate depends much more on the modern region chosen for comparison than on (Hardacre et al, 2015;Bariteau et al, 2010;Luhar et al 2017Luhar et al , 2018.…”

Section: Conclusion and Recommendations For Design Of A Future Globamentioning

confidence: 99%

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Tarasick

Galbally

Cooper

et al. 2019

Elementa: Science of the Anthropocene

Self Cite

158

168

View full text Add to dashboard Cite

From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients.There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol -1 , but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30-70%, with large uncertainty, between the period of historic observations, 1896-1975, and the modern period (1990-2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify.The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1-5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5-20% in sensitivity to tropospheric ozone from 1970-1995. Biases and standard deviations of satellite retrieval comparisons are often 2-3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

show abstract

Section: Conclusion and Recommendations For Design Of A Future Globamentioning

confidence: 99%

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Tarasick

Galbally

Cooper

et al. 2019

Elementa: Science of the Anthropocene

Self Cite

158

168

View full text Add to dashboard Cite

show abstract

“…Three significant differences exist in our choice of parameters compared to the work of Luhar et al (2018). Firstly, we use the Sherwen et al 2019 .6 nM, which is a significant increase from the global mean of 58.9 ± 34.9 nM found by MacDonald et al (2014). Secondly, we include a variable thickness for the reaction-diffusion sub-layer (Eq.…”

Section: Modellingmentioning

confidence: 99%

Influences of oceanic ozone deposition on tropospheric photochemistry

et al. 2020

View full text Add to dashboard Cite

Abstract. The deposition of ozone to seawater is an important ozone sink. Despite constituting as much as a third of the total ozone deposition, it receives significantly less attention than the deposition to terrestrial ecosystems. Models have typically calculated the deposition rate based on a resistance-in-series model with a uniform waterside resistance. This leads to models having an essentially uniform deposition velocity of approximately 0.05 cm s−1 to seawater, which is significantly higher than the limited observational dataset. Following from Luhar et al. (2018) we include a representation of the oceanic deposition of ozone in the GEOS-Chem model of atmospheric chemistry and transport based on its reaction with sea-surface iodide. The updated scheme halves the calculated annual area-weighted mean deposition velocity to water from 0.0464 cm s−1 (25th and 75th percentiles of 0.0461 cm s−1 and 0.0471 cm s−1 respectively) to 0.0231 cm s−1 (25th and 75th percentiles of 0.0121 cm s−1 and 0.0303 cm s−1 respectively). The calculated ozone deposition velocity varies from 0.009 cm s−1 in polar waters to 0.040 cm s−1 at the tropics. This improves comparisons to observations. The variability is driven mainly by the temperature-dependent rate constant for the reaction between iodide and ozone, the temperature dependence of the solubility, and variations in the ocean iodide concentration. The calculated annual deposition flux of ozone to the ocean is reduced from 222 to 122 Tg yr−1, and overall deposition of ozone to all surface types reduces from 862 to 758 Tg yr−1. Tropospheric ozone burdens and global mean OH increase from 324 to 328 Tg, and from 1.17×106 to 1.18×106 molec.cm-3, respectively. A total of 34 % of surface grid boxes experience a 10 % or greater increase in ozone concentration. Comparisons between observations of surface ozone and the model are improved with the new parameterization notably around the Southern Ocean. Process-level representation of oceanic deposition of ozone thus appears essential for representing the concentration of surface ozone over the planet.

show abstract

“…A reason for gaps in our understanding is that the observational dataset of iodide and iodate remains relatively sparse (Chance et al, 2014(Chance et al, , 2019b. Despite this paucity in observations, iodine's role in the Earth system has driven multidisciplinary interest in the distribution of iodine compounds in seawater from a number of different research communities, including paleoceanography (Lu et al, 2016(Lu et al, , 2018Zhou et al, 2015), atmospheric composition (Saiz-Lopez et al, 2014;Sherwen et al, 2016a), and air-quality prediction (Sarwar et al, 2015;Luhar et al, 2017Luhar et al, , 2018.…”

Section: Introductionmentioning

confidence: 99%

A machine learning based global sea-surface iodide distribution

Sherwen¹,

Chance²,

Tinel³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Iodide in the sea-surface plays an important role in the Earth system. It modulates the oxidising capacity of the troposphere and provides iodine to terrestrial ecosystems. However, our understanding of its distribution is limited due to a paucity of observations. Previous efforts to generate global distributions have generally fitted sea-surface iodide observations to relatively simple functions of sea-surface temperature (Chance et al., 2014; MacDonald et al., 2014). This approach fails to account for coastal influences and variation in the bio-geochemical environment. Here we use a machine learning regression approach (Random Forest Regression) to generate a high resolution (0.125° x 0.125°, ∼ 12.5 km), monthly dataset of present-day global sea-surface iodide. We use a compilation of iodide observations (Chance et al., 2019b) that is 45 % larger than has been used previously (Chance et al., 2014) as the dependent variable and co-located ancillary parameters (temperature, nitrate, phosphate, salinity, shortwave radiation, topographic depth, mixed layer depth, and chlorophyll-a) from global climatologies as the independent variables. We investigate the regression models generated using different combinations of ancillary parameters and select the ten best-performing models to be included in an ensemble prediction. We then use this ensemble of models, combined with global fields of the ancillary parameters, to predict a new high resolution global sea-surface iodide field. Sea-surface temperature is the most important variable in all of the top ten models. We estimate a global average sea-surface iodide concentration of 106 nM (with an uncertainty of ∼ 20 %), which is within the range of previous estimates (60–130 nM). Similar to previous work, higher concentrations are predicted for the tropics than for the extra-tropics. Unlike the previous parameterisations, higher concentrations are also predicted for shallow areas such as coastal regions and the South China Sea. Compared to previous work, the new parameterisation better captures observed variability. The iodide concentrations calculated here are significantly higher (40 % on a global basis) than the commonly used MacDonald et al. (2014) parameterisation, with implications for our understanding of iodine in the atmosphere. The global iodide dataset is made freely available to the community (DOI: https://doi.org/10/gfv5v3) and as new observations are made, we will update the global dataset through a "living data" model.

show abstract

A revised global ozone dry deposition estimate based on a new two-layer parameterisation for air–sea exchange and the multi-year MACC composition reanalysis

Cited by 35 publications

References 47 publications

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Influences of oceanic ozone deposition on tropospheric photochemistry

A machine learning based global sea-surface iodide distribution

Contact Info

Product

Resources

About