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  • 1
    Publication Date: 2013-08-31
    Description: Results from idealized 3-D simulations of a dynamical-radiative-photochemical model of the stratosphere are presented for the Northern Hemisphere winter and spring. For a simulation of a quiescent winter, it is found that with current levels of CO2 only modest polar ozone depletion occurs, consistent with observations. For a second simulation with the same planetary wave amplitudes in the upper troposphere but with doubled CO2, the model predicts a northern hemisphere ozone hole comparable to that observed in Antarctica with almost complete ozone destruction at 20 km. Reasons for the marked difference between the simulations are identified.
    Keywords: ENVIRONMENT POLLUTION
    Type: NASA. Goddard Space Flight Center, Ozone in the Troposphere and Stratosphere, Part 2; p 467-474
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  • 2
    Publication Date: 2019-06-25
    Description: We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (+/-20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new 10 CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1- uncertainty of 2043-2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039-2050), and at Northern Hemisphere mid-latitudes in 2032 (2020-2044). In the Polar Regions, the return dates are 2060 (2055-2066) in the Antarctic in October and 2034 (2025-2043) in the Arctic in March. The earlier return dates in the NH reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5-17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, at around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10-20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ~15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ~15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model-model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that is more important to have multi-member (at least 3) ensembles for each scenario from every established participating model, rather than a large number of individual models.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN61684 , Atmospheric Chemistry and Physics (ISSN 1680-7316) (e-ISSN 1680-7324); 18; 11; 8409-8438
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  • 3
    Publication Date: 2019-10-26
    Description: Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry-Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics - such as their duration, deceleration of the polar night jet, and the tropospheric forcing - are also assessed: again, we find no evidence of future changes over the 21st century.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN61688 , Atmospheric Chemistry and Physics (ISSN 1680-7316) (e-ISSN 1680-7324); 18; 15; 11277-11287
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  • 4
    Publication Date: 2019-12-13
    Description: Previous multi-model intercomparisons have shown that chemistryclimate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARCIGAC (Stratospheretroposphere Processes And their Role in ClimateInternational Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to 30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, SOCOLv3.1, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NO(sub x)), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NO(sub x) than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistryclimate models.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN68927 , Atmospheric Chemistry and Physics (ISSN 1680-7316) (e-ISSN 1680-7324); 18; 21; 16155-16172
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  • 5
    Publication Date: 2019-07-13
    Description: We present an overview of state-of-the-art chemistry-climate and chemistry transport models that are used within phase 1 of the Chemistry-Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users.
    Keywords: Geosciences (General)
    Type: GSFC-E-DAA-TN55204 , Geoscientific Model Development (ISSN 1991-959X) (e-ISSN 1991-9603); 10; 2; 639-671
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