UCI CTM model simulations used for deriving the spillover of tropospheric ozone into the stratosphere
Data files
May 06, 2024 version files 528.86 MB
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README.md
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trp2str_air.nc
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trp2str_e90.nc
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trp2str_Fig-data.xlsx
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trp2str_O3f.nc
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trp2str_O3S.nc
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trp2str_S10.nc
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trp2str_S30.nc
Abstract
The world has made great strides in phasing out the halocarbons that drive ozone loss, such as the chlorofluorocarbons 11 and 12. While living with the well-documented depletion of the ozone layer, we are now watching the slow recovery (increase) of stratospheric ozone over this century after our phaseout of halocarbon production and use. Projecting this recovery date also depends on the impact of other changing greenhouse gases on stratospheric chemistry as well as changes in tropospheric ozone. Both observations and models identify tropospheric ozone as increasing due to air-quality pollution in the lower atmosphere. Here, using a global chemistry-transport model, we find that this ozone increase carries over into the stratosphere at rates affecting the recovery expected from the decay of atmospheric halocarbons. This process is inherently included in our chemistry-climate models but is not diagnosed as such. The ozone assessments need to consider that what happens in the troposphere does not stay in the troposphere, complicating our interpretation of ozone changes over this century.
README: UCI CTM model simulations used for deriving the spillover of tropospheric ozone into the stratosphere
https://doi.org/10.5061/dryad.dr7sqvb66
These datasets are used in the derivation of the spillover of tropospheric ozone into the stratosphere as discussed in the manuscript: Prather, M. J. (2024) The Spillover of Tropospheric Ozone Increases has hidden the Extent of Stratospheric Ozone Depletion by Halogens, AGU Advances, ms#: 2023AV001154R
The goal of these model simulations with the UCI CTM is to separate the effect of tropospheric chemistry-driven increases in ozone from stratospheric. Hence some ozone tracers have only stratospheric chemistry, while the primary ozone calculation uses tropospheric-plus-stratospheric chemistry. The datasets include the CTM output necessary to separate ozone into stratospheric and tropospheric with a set of monthly samples over the final year of the calculation.
Description of the data and file structure
The raw CTM output files consist of 12 snapshots at the end of the month (2400H 31 Jan 2001 to 2400H 31 Dec 2001 of the 3D distribution of dry-air, e90, and ozone. Each is given as kg in the 320 (longitude) x 160 (latitude) x 57 (pressure level), using the standard T159N80 lat-long grid. The UCI CTM was initialized with a spunup simulation on 1 Jan 2000 and run for 24 months with the results here taken from the final 12 months. These datasets are used to sample the ozone as either stratosphere or troposphere and identify differences across the four different ways of simulation ozone – see the references paper for details.
For details about the UCI CTM and the emissions and boundary conditions, see the recent Elementa paper, including the tables and references in the appendix: Prather, M.J. and Xin Zhu (2024) Lifetimes and timescales of tropospheric ozone, Elementa: Science of the Anthropocene, 12 (1): 00112, doi: 10.1525/elementa.2023.00112
Four ozone values are reported:
- O3f = full ozone simulated with ASAD tropospheric chemistry linked to Linoz stratospheric chemistry.
- O3S = a second ozone tracer in the full chemistry case, but one that experiences only Linoz chemistry in the stratosphere plus a lower tropospheric boundary condition (LBC) of 30 ppb.
- S10 = a Linoz-only simulation with a 10 ppb LBC.
- S30 = a Linoz-only simulation with a 30 ppb LBC (almost identical to O3S).
As in the CTM simulations, the e90 tracer value is used to separate the stratosphere from the troposphere. The threshold here is 90 ppb.
The diagnostics used in this analysis need to separate the stratosphere from the troposphere. The algorithm sequence here uses Matlab language and assumes that all arrays are only 3D (i.e., for a given month).
First define the e90 mole fraction in each cell: e90molfr = e90 ./ air;
Then find all troposphere cells: is_trop = find(e90molfr > 90e-9);
Then populate an O3 array like those in the NetCDF files here with only tropospheric values from the array O3f: O3trop(1:320,1:160,1:57) = NaN; and O3trop(is_trop) = O3f(is_trop);
The statistics on O3trop can be calculated easily using Matlab operators like nanmean() or nansum().
The spreadsheet (.csv file) contains the exact data used to plot Figures 2 and 3 in the primary paper. The basic variables (see reference paper and variable list above) are for
- O3f = ozone calculated with both trop. & strat. chemistry
- O3S = a separate tracer in the O3f calculation above that see only strat. chemistry (Linoz) with a lower boundary condition of 30 ppb.
- S10 = a separate calculation with Linoz-only and LBC = 10 ppb.
Fig.2 profiles: Profiles provide the ozone value (in ppm = micromoles per mole of dry air) for the ozone values above. The 'layer' number, altitude Z* (km), and pressure P (hPa) of the layer are given. NaN's are given where no such value exists (e.g., tropospheric values at 32 km).
Fig.3 2D colorplot: This 2D array of stratospheric ozone values in ppb (nanomoles per mole of dry air) is plotted with the Matlab pcolor() command. The axes (latitude by altitude) are labelled.
Sharing/Access information
This data is not available elsewhere.
Code/Software
The primary paper linked to this data set describes the analysis and the Elementa paper noted above contains a description of the current version of the UCI CTM. The netcdf files can be read and analyzed under many operating systems and programming languages.
Methods
This dataset was calculated using the UC Irvine Chemistry-Transport Model (CTM). The ozone simulations with this model are documented further in recent publications noted below.
The calculations used monthly snapshot 3D data on dry-air mass, O3 mass, and e90 mass (to determine tropospheric cells as e90 > 90 ppb). The 4D data sets (longitude/320, latitude/160, pressure level/57, and month/12) are archived here as NetCDF files.
References:
- Prather, M.J. and Xin Zhu (2024) Lifetimes and timescales of tropospheric ozone, Elementa: Science of the Anthropocene, 12 (1): 00112, doi: 10.1525/elementa.2023.00112
- Sand, Maria, R. B. Skeie, M. Sandstad, S. Krishnan, G. Myhre, H. Bryant, R. Derwent, D. Hauglustaine, F. Paulot, M. Prather & D. Stevenson (2023) A multi-model assessment of the Global Warming Potential of hydrogen, Nature Communications: Earth & Environment, 4:203, doi: 10.1038/s43247-023-00857-8.