We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in the MBC value does not necessarily match a model's own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate

CFC↗

NASA NTRS2014

Multimodel Estimates of Atmospheric Lifetimes of Long-Lived Ozone-Depleting Substances: Present and Future

We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in theMBC value does not necessarilymatch a model's own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate.

CH3CCl3↗

NASA NTRS2011

Global Multi-Year O3-CO Correlation Patterns from Models and TES Satellite Observations

The correlation between measured tropospheric ozone (O3) and carbon monoxide (CO) has been used extensively in tropospheric chemistry studies to explore the photochemical characteristics of different regions and to evaluate the ability of models to capture these characteristics. Here, we present the first study that uses multi-year, global, vertically resolved, simultaneous and collocated O3 and CO satellite (Tropospheric Emission Spectrometer) measurements, to determine this correlation in the middle/lower free troposphere for two different seasons, and to evaluate two chemistry-climate models. We find results that are fairly robust across different years, altitudes and timescales considered, which indicates that the correlation maps presented here could be used in future model evaluations. The highest positive correlations (around 0.8) are found in the northern Pacific during summer, which is a common feature in the observations and the G-PUCCINI model. We make quantitative comparisons between the models using a single-figure metric (C), which we define as the correlation coefficient between the modeled and the observed O3-CO correlations for different regions of the globe. On a global scale, the G-PUCCINI model shows a good performance in the summer (C =0.71) and a satisfactory performance in the winter (C = 0.52). It captures midlatitude features very well, especially in the summer, whereas the performance in regions like South America or Central Africa is weaker. The UKCA model (C = 0.46/0.15 for July-August/December-January on a global scale) performs better in certain regions, such as the tropics in winter, and it captures some of the broad characteristics of summer extratropical correlations, but it systematically underestimates the O3-CO correlations over much of the globe. It is noteworthy that the correlations look very different in the two models, even though the ozone distributions are similar. This demonstrates that this technique provides a powerful global constraint for understanding modeled tropospheric chemical processes. We investigated the sources of the correlations by performing a series of sensitivity experiments. In these, the sign of the correlation is, in most cases, insensitive to removing different individual emissions, but its magnitude changes downwind of emission regions when applying such perturbations. Interestingly, we find that the O3-CO correlation does not solely reflect the strength of O3 photochemical production, as often assumed by earlier studies, but is more complicated and may reflect a mixture of different processes such as transport.

Voulgarakis, A.↗