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News Article | December 14, 2016
Site: www.sciencenews.org

In a rare bright spot for global environmental news, atmospheric scientists reported in 2016 that the ozone hole that forms annually over Antarctica is beginning to heal. Their data nail the case that the Montreal Protocol, the international treaty drawn up in 1987 to limit the use of ozone-destroying chemicals, is working. The Antarctic ozone hole forms every Southern Hemisphere spring, when chemical reactions involving chlorine and bromine break apart the oxygen atoms that make up ozone molecules. Less protective ozone means that more ultraviolet radiation reaches Earth, where it can damage DNA and lead to higher rates of skin cancer, among other threats. The Montreal Protocol cut back drastically on the manufacture of ozone-destroying compounds such as chlorofluorocarbons, or CFCs, which had been used in air conditioners, refrigerators and other products. It went into force in 1989 and phased out CFCs by 2010. Earlier studies had hinted that the ozone hole was on the mend. The new work, reported in Science in June, is the most definitive yet (SN: 7/23/16, p. 6). A team led by Susan Solomon, an atmospheric chemist at MIT, looked not only at the month of October, when Antarctic ozone loss typically peaks, but also at September, when the hole is growing. The healing trend was most obvious in September. Satellite measurements showed that from 2000 to 2015, the average extent of the September ozone hole shrank by about 4.5 million square kilometers, to approximately 18 million square kilometers. Soundings taken by weather balloons over Antarctica confirmed the findings. CFC concentrations peaked above Antarctica in the late 1990s and early 2000s and have been dropping ever since, says Birgit Hassler, an atmospheric chemist at Bodeker Scientific in Alexandra, New Zealand. Each passing year allows scientists to gather more convincing data. The new study, Hassler says, “makes the whole development of the Antarctic ozone hole healing very transparent and understandable.” It is a fitting capstone to Solomon’s career. In the 1980s she led a team that proposed that chlorine compounds were to blame for Antarctic ozone loss. She then traveled to the frozen continent to conduct pioneering experiments that measured the accumulating chemicals there. “It’s very humbling now to be 30 years later and be able to say we have a clear fingerprint that the ozone hole is starting to get better,” she says. Solomon says that public engagement was key to solving the ozone problem, with people coming together to identify an issue that threatened society and develop new technologies to fix it. In that respect, the most successful environmental treaty in history holds lessons for dealing with a much bigger threat, she says — climate change. To fix the ozone layer, industry stopped using CFCs and similar compounds and replaced them with hydrofluorocarbons. Those chemicals, however, turned out to be powerful greenhouse gases that accelerated global warming. In October, the nations that ratified the Montreal Protocol agreed to expand it to cover hydrofluorocarbons as well (SN: 11/26/16, p. 13).


Cionni I.,German Aerospace Center | Eyring V.,German Aerospace Center | Lamarque J.F.,U.S. National Center for Atmospheric Research | Randel W.J.,U.S. National Center for Atmospheric Research | And 7 more authors.
Atmospheric Chemistry and Physics | Year: 2011

A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multi-model mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISS-PUCCINI) and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23 W m-2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of g-0.08 W m-2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of-0.05 W m-2, but which is within the stated range of-0.15 to +0.05 W m-2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1 W m-2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/). © 2011 Author(s).


Garny H.,German Aerospace Center | Grewe V.,German Aerospace Center | Dameris M.,German Aerospace Center | Bodeker G.E.,Bodeker Scientific | Stenke A.,ETH Zurich
Geoscientific Model Development | Year: 2011

Chemistry-climate models (CCMs) are commonly used to simulate the past andfuture development of Earth's ozone layer. The fully coupled chemistryschemes calculate the chemical production and destruction of ozoneinteractively and ozone is transported by the simulated atmospheric flow. Dueto the complexity of the processes acting on ozone it is not straightforwardto disentangle the influence of individual processes on the temporaldevelopment of ozone concentrations. A method is introduced here thatquantifies the influence of chemistry and transport on ozone concentrationchanges and that is easily implemented in CCMs and chemistry-transport models(CTMs). In this method, ozone tendencies (i.e. the time rate of change ofozone) are partitioned into a contribution from ozone production anddestruction (chemistry) and a contribution from transport of ozone(dynamics). The influence of transport on ozone in a specific region isfurther divided into export of ozone out of that region and import of ozonefrom elsewhere into that region. For this purpose, a diagnostic is used thatdisaggregates the ozone mixing ratio field into 9 separate fields accordingto in which of 9 predefined regions of the atmosphere the ozone originated.With this diagnostic the ozone mass fluxes between these regions areobtained. Furthermore, this method is used here to attribute long-termchanges in ozone to chemistry and transport. The relative change in ozonefrom one period to another that is due to changes in production ordestruction rates, or due to changes in import or export of ozone, arequantified. As such, the diagnostics introduced here can be used to attributechanges in ozone on monthly, interannual and long-term time-scales to theresponsible mechanisms. Results from a CCM simulation are shown here asexamples, with the main focus of the paper being on introducing the method. © Author(s) 2011.


Garny H.,German Aerospace Center | Dameris M.,German Aerospace Center | Randel W.,U.S. National Center for Atmospheric Research | Bodeker G.E.,Bodeker Scientific | Deckert R.,German Aerospace Center
Journal of the Atmospheric Sciences | Year: 2011

Drivers of upwelling in the tropical lower stratosphere are investigated using the E39C-A chemistry- climate model. The climatological annual cycle in upwelling and its wave forcing are compared to the interim ECMWF Re-Analysis (ERA-Interim). The strength in tropical upwelling and its annual cycle can be largely explained by local resolved wave forcing. The climatological mean forcing is due to both stationary planetaryscale waves that originate in the tropics and extratropical transient synoptic-scale waves that are refracted equatorward. Increases in atmospheric greenhouse gas (GHG) concentrations to 2050 force a year-round positive trend in tropical upwelling, which maximizes in the lowermost stratosphere. Tropical ascent is balanced by downwelling between 20° and 40°. Strengthening of tropical upwelling can be explained by stronger local forcing by resolved wave flux convergence, which is driven in turn by processes initiated by increases in tropical sea surface temperatures (SSTs). Higher tropical SSTs cause a strengthening of the subtropical jets and modification of deep convection affecting latent heat release. While the former can modify wave propagation and dissipation, the latter affects tropical wave generation. The dominant mechanism leading to enhanced vertical wave propagation into the lower stratosphere is an upward shift of the easterly shear zone due to the strengthening and upward shift of the subtropical jets. © 2011 American Meteorological Society.


Revell L.E.,NIWA - National Institute of Water and Atmospheric Research | Revell L.E.,University of Canterbury | Bodeker G.E.,Bodeker Scientific | Huck P.E.,Bodeker Scientific | And 3 more authors.
Atmospheric Chemistry and Physics | Year: 2012

Through the 21st century, anthropogenic emissions of the greenhouse gases N2O and CH4 are projected to increase, thus increasing their atmospheric concentrations. Consequently, reactive nitrogen species produced from N2O and reactive hydrogen species produced from CH 4 are expected to play an increasingly important role in determining stratospheric ozone concentrations. Eight chemistry-climate model simulations were performed to assess the sensitivity of stratospheric ozone to different emissions scenarios for N2O and CH4. Global-mean total column ozone increases through the 21st century in all eight simulations as a result of CO2-induced stratospheric cooling and decreasing stratospheric halogen concentrations. Larger N2O concentrations were associated with smaller ozone increases, due to reactive nitrogen-mediated ozone destruction. In the simulation with the largest N2O increase, global-mean total column ozone increased by 4.3 DU through the 21st century, compared with 10.0 DU in the simulation with the smallest N2O increase. In contrast, larger CH4 concentrations were associated with larger ozone increases; global-mean total column ozone increased by 16.7 DU through the 21st century in the simulation with the largest CH4 concentrations and by 4.4 DU in the simulation with the lowest CH4 concentrations. CH4 leads to ozone loss in the upper and lower stratosphere by increasing the rate of reactive hydrogen-mediated ozone loss cycles, however in the lower stratosphere and troposphere, CH4 leads to ozone increases due to photochemical smog-type chemistry. In addition to this mechanism, total column ozone increases due to H2O-induced cooling of the stratosphere, and slowing of the chlorine-catalyzed ozone loss cycles due to an increased rate of the CH4 + Cl reaction. Stratospheric column ozone through the 21st century exhibits a near-linear response to changes in N2O and CH4 surface concentrations, which provides a simple parameterization for the ozone response to changes in these gases. © 2012 Author(s).


Kuttippurath J.,University Pierre and Marie Curie | Bodeker G.E.,Bodeker Scientific | Roscoe H.K.,British Antarctic Survey | Nair P.J.,Center for Earth Science Studies
Geophysical Research Letters | Year: 2015

Equivalent effective stratospheric chlorine (EESC) construct of ozone regression models attributes ozone changes to EESC changes using a single value of the sensitivity of ozone to EESC over the whole period. Using space-based total column ozone (TCO) measurements, and a synthetic TCO time series constructed such that EESC does not fall below its late 1990s maximum, we demonstrate that the EESC-based estimates of ozone changes in the polar regions (70-90°) after 2000 may, falsely, suggest an EESC-driven increase in ozone over this period. An EESC-based regression of our synthetic "failed Montreal Protocol with constant EESC" time series suggests a positive TCO trend that is statistically significantly different from zero over 2001-2012 when, in fact, no recovery has taken place. Our analysis demonstrates that caution needs to be exercised when using explanatory variables, with a single fit coefficient, fitted to the entire data record, to interpret changes in only part of the record. Key Points Presents a thorough analysis on the EESC-based regression The EESC-based regression is inappropriate for estimating ozone trends Recommends a reinterpretation of the previous EESC-based trend estimates ©2014. American Geophysical Union. All Rights Reserved.


Hassler B.,University of Colorado at Boulder | Hassler B.,National Oceanic and Atmospheric Administration | Young P.J.,University of Colorado at Boulder | Young P.J.,National Oceanic and Atmospheric Administration | And 6 more authors.
Atmospheric Chemistry and Physics | Year: 2013

Climate models that do not simulate changes in stratospheric ozone concentrations require the prescription of ozone fields to accurately calculate UV fluxes and stratospheric heating rates. In this study, three different global ozone time series that are available for this purpose are compared: the data set of Randel and Wu (2007) (RW07), Cionni et al. (2011) (SPARC), and Bodeker et al. (2013) (BDBP). All three data sets represent multiple-linear regression fits to vertically resolved ozone observations, resulting in a spatially and temporally continuous stratospheric ozone field covering at least the period from 1979 to 2005. The main differences among the data sets result from regression models, which use different observations and include different basis functions. The data sets are compared against ozonesonde and satellite observations to assess how the data sets represent concentrations, trends and interannual variability. In the Southern Hemisphere polar region, RW07 and SPARC underestimate the ozone depletion in spring ozonesonde measurements. A piecewise linear trend regression is performed to estimate the 1979-1996 ozone decrease globally, covering a period of extreme depletion in most regions. BDBP overestimates Arctic and tropical ozone depletion over this period relative to the available measurements, whereas the depletion is underestimated in RW07 and SPARC. While the three data sets yield ozone concentrations that are within a range of different observations, there is a large spread in their respective ozone trends. One consequence of this is differences of almost a factor of four in the calculated stratospheric ozone radiative forcing between the data sets (RW07: -0.038 Wm-2, SPARC: -0.033 Wm-2, BDBP: -0.119 Wm-2), important in assessing the contribution of stratospheric ozone depletion to the total anthropogenic radiative forcing. © 2013 Author(s).


Kremser S.,Bodeker Scientific | Bodeker G.E.,Bodeker Scientific | Lewis J.,Bodeker Scientific
Geoscientific Model Development | Year: 2014

A Climate Pattern-Scaling Model (CPSM) that simulates global patterns of climate change, for a prescribed emissions scenario, is described. A CPSM works by quantitatively establishing the statistical relationship between a climate variable at a specific location (e.g. daily maximum surface temperature, Tmax) and one or more predictor time series (e.g. global mean surface temperature, Tglobal) - referred to as the "training" of the CPSM. This training uses a regression model to derive fit coefficients that describe the statistical relationship between the predictor time series and the target climate variable time series. Once that relationship has been determined, and given the predictor time series for any greenhouse gas (GHG) emissions scenario, the change in the climate variable of interest can be reconstructed - referred to as the "application" of the CPSM. The advantage of using a CPSM rather than a typical atmosphere-ocean global climate model (AOGCM) is that the predictor time series required by the CPSM can usually be generated quickly using a simple climate model (SCM) for any prescribed GHG emissions scenario and then applied to generate global fields of the climate variable of interest. The training can be performed either on historical measurements or on output from an AOGCM. Using model output from 21st century simulations has the advantage that the climate change signal is more pronounced than in historical data and therefore a more robust statistical relationship is obtained. The disadvantage of using AOGCM output is that the CPSM training might be compromised by any AOGCM inadequacies. For the purposes of exploring the various methodological aspects of the CPSM approach, AOGCM output was used in this study to train the CPSM. These investigations of the CPSM methodology focus on monthly mean fields of daily temperature extremes (Tmax and Tmin). The methodological aspects of the CPSM explored in this study include (1) investigation of the advantage gained in having five predictor time series over having only one predictor time series, (2) investigation of the time dependence of the fit coefficients and (3) investigation of the dependence of the fit coefficients on GHG emissions scenario. Key conclusions are (1) overall, the CPSM trained on simulations based on the Representative Concentration Pathway (RCP) 8.5 emissions scenario is able to reproduce AOGCM simulations of Tmax and Tmin based on predictor time series from an RCP 4.5 emissions scenario; (2) access to hemisphere average land and ocean temperatures as predictors improves the variance that can be explained, particularly over the oceans; (3) regression model fit coefficients derived from individual simulations based on the RCP 2.6, 4.5 and 8.5 emissions scenarios agree well over most regions of the globe (the Arctic is the exception); (4) training the CPSM on concatenated time series from an ensemble of simulations does not result in fit coefficients that explain significantly more of the variance than an approach that weights results based on single simulation fits; and (5) the inclusion of a linear time dependence in the regression model fit coefficients improves the variance explained, primarily over the oceans. © Author (s) 2014.


Hassler B.,University of Colorado at Boulder | Hassler B.,National Oceanic and Atmospheric Administration | Bodeker G.E.,Bodeker Scientific | Solomon S.,National Oceanic and Atmospheric Administration | And 2 more authors.
Geophysical Research Letters | Year: 2011

October mean total column ozone data from four Antarctic stations form the basis for understanding the evolution of the ozone hole since 1960. While these stations show similar emergence of the ozone hole from 1960 to 1980, the records are divergent in the last two decades. The effects of long-term changes in vortex shape and location are considered by gridding the measurements by equivalent latitude. A clear eastward shift of the mean position of the vortex in October with time is revealed, which changes the fraction of ozone measurements taken inside/outside the vortex for stations in the vortex collar region. After including only those measurements made inside the vortex, ozone behavior in the last two decades at the four stations is very similar. This suggests that dynamical influence must be considered when interpreting and intercomparing ozone measurements from Antarctic stations for detecting ozone recovery and ozone-related changes in Antarctic climate. © 2011 by the American Geophysical Union.


Bodeker G.E.,Bodeker Scientific | Kremser S.,Bodeker Scientific
Atmospheric Measurement Techniques | Year: 2015

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E). © Author(s) 2015.

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