Nitrous oxide (N2O), which decomposes in the stratosphere to form nitrogen oxides (NOx), is currently the dominant anthropogenic ozone‐depleting substance emitted. Ozone depletion potentials (ODPs) ...of specific compounds, commonly evaluated for present‐day conditions, were developed for long‐lived halocarbons and are used by policymakers to inform decision‐making around protection of the ozone layer. However, the effect of N2O on ozone will evolve in the future due to changes in stratospheric dynamics and chemistry induced by rising levels of greenhouse gases. Despite the fact that NOx‐induced ozone loss slows with increasing concentrations of CO2 and CH4, we show that ODPN2O for year 2100 varies under different scenarios and is mostly larger than ODPN2O for year 2000. This occurs because the traditional ODP approach is tied to ozone depletion induced by CFC‐11, which is also sensitive to CO2 and CH4. We therefore suggest that a single ODP for N2O is of limited use.
Key Points
The ozone depletion potential of N2O (ODP‐N2O) is sensitive to CO2 and CH4
ODP‐N2O in 2100 is larger than in 2000 and varies by up to a factor of 2
A single‐valued ODP‐N2O is of limited use
Measurements of BrO suggest that inorganic bromine (Br(sub y)) at and above the tropopause is 4 to 8 ppt greater than assumed in models used in past ozone trend assessment studies. This additional ...bromine is likely carried to the stratosphere by short-lived biogenic compounds and their decomposition products, including tropospheric BrO. Including this additional bromine in an ozone trend simulation increases the computed ozone depletion over the past approx.25 years, leading to better agreement between measured and modeled ozone trends. This additional Br(sub y) (assumed constant over time) causes more ozone depletion because associated BrO provides a reaction partner for ClO, which increases due to anthropogenic sources. Enhanced Br(sub y) causes photochemical loss of ozone below approx.14 km to change from being controlled by HO(sub x) catalytic cycles (primarily HO2+O3) to a situation where loss by the BrO+HO2 cycle is also important.
Arctic ozone loss and climate change Rex, M.; Salawitch, R. J.; von der Gathen, P. ...
Geophysical research letters,
February 2004, Letnik:
31, Številka:
4
Journal Article
Recenzirano
Odprti dostop
We report the first empirical quantification of the relation between winter‐spring loss of Arctic ozone and changes in stratospheric climate. Our observations show that ∼15 DU additional loss of ...column ozone can be expected per Kelvin cooling of the Arctic lower stratosphere, an impact nearly three times larger than current model simulations suggest. We show that stratospheric climate conditions became significantly more favorable for large Arctic ozone losses over the past four decades; i.e., the maximum potential for formation of polar stratospheric clouds increased steadily by a factor of three. Severe Arctic ozone loss during the past decade occurred as a result of the combined effect of this long‐term climate change and the anthropogenic increase in stratospheric halogens.
Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to ...complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.
During polar spring, periods of elevated tropospheric bromine drive near complete removal of surface ozone. These events impact the tropospheric oxidative capacity and are an area of active research ...with multiple approaches for representing the underlying processes in global models. We present a method for parameterizing emissions of molecular bromine (Br2) over the Arctic using satellite retrievals of bromine monoxide (BrO) from the Ozone Monitoring Instrument (OMI). OMI retrieves column BrO with daily near global coverage, and we use the GEOS‐Chem chemical mechanism, run online within the Goddard Earth Observing System Earth System Model to identify hotspots of BrO likely associated with polar processes. To account for uncertainties in modeling background BrO, hotspots are only identified where the difference between OMI and modeled columns exceeds a statistical threshold. The resulting hotspot columns are a lower‐limit for the portion of OMI BrO attributable to bromine explosion events. While these hotspots are correlated with BrO measured in the lower troposphere over the Arctic Ocean, a case study of missing detections of near‐surface BrO is identified. Daily flux of Br2 is estimated from hotspot columns of BrO using internal model parameters. When the emissions are applied, BrO hotspots are modeled with a 5% low bias. The sensitivity of the resulting ozone simulations to the treatment of background uncertainties in the BrO column is demonstrated. While periods of isolated, large (>50%) decreases in surface ozone are modeled, this technique does not simulate the low ozone observed at coastal stations and consistently underestimates ozone loss during March.
Plain Language Summary
During polar spring, high levels of bromine‐containing molecules drive near complete removal of surface ozone (O3), impacting the chemistry of the troposphere and the biological uptake of mercury. Global models currently have multiple mechanisms for representing the underlying processes that produce brominated molecules in polar regions. We estimate molecular bromine (Br2) emissions from measurements of bromine monoxide (BrO) collected over the Arctic by a satellite instrument. An atmospheric model, run without polar emissions of Br2, is used to estimate how much of the satellite BrO signal is due to background processes in the stratosphere and troposphere and isolate the portion of the signal likely associated with Arctic emissions. We account for uncertainties in the model representation of background BrO using a statistical threshold. Because of the catalytic nature of bromine‐mediated ozone depletion, we focus our initial efforts on developing a lower‐limit estimate of Arctic emissions. The amount of BrO attributed to polar processes and the resulting impact on O3 are sensitive to the magnitude of the statistical threshold, with a better representation of surface O3 achieved with a lower threshold. While the satellite‐based emissions result in periodic decreases in surface O3 in late spring, modeled O3 is consistently high with respect to observations, particularly during early spring.
Key Points
BrO hotspots are isolated from satellite signals using modeled columns of BrO and a bias threshold to account for model uncertainties
We estimate Arctic Br2 emissions from BrO signals and demonstrate the sensitivity of modeled O3 to the BrO hotspot detection threshold
Simulations with satellite‐based Br2 emissions overestimate springtime Arctic surface O3 with few ozone depleting events modeled in March
Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework ...are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.