Dynamics, stratospheric ozone, and climate change

Dynamics affects the distribution and abundance of stratospheric ozone directly through transport of ozone itself and indirectly through its effect on ozone chemistry via temperature and transport of other chemical species. Dynamical processes must be considered in order to understand past ozone changes, especially in the northern hemisphere where there appears to be significant low-frequency variability which can look “trend-like” on decadal time scales. A major challenge is to quantify the predictable, or deterministic, component of past ozone changes. Over the coming century, changes in climate will affect the expected recovery of ozone. For policy reasons it is important to be able to distinguish and separately attribute the effects of ozone-depleting substances and greenhouse gases on both ozone and climate. While the radiative-chemical effects can be relatively easily identified, this is not so evident for dynamics — yet dynamical changes (e.g., changes in the Brewer-Dobson circulation) could have a first-order effect on ozone over particular regions. Understanding the predictability and robustness of such dynamical changes represents another major challenge. Chemistry-climate models have recently emerged as useful tools for addressing these questions, as they provide a self-consistent representation of dynamical aspects of climate and their coupling to ozone chemistry. We can expect such models to play an increasingly central role in the study of ozone and climate in the future, analogous to the central role of global climate models in the study of tropospheric climate change.

Impact of long-range correlations on trend detection in total ozone

Total ozone trends are typically studied using linear regression models that assume a first-order autoregression of the residuals [so-called AR(1) models]. We consider total ozone time series over 60°S–60°N from 1979 to 2005 and show that most latitude bands exhibit long-range correlated (LRC) behavior, meaning that ozone autocorrelation functions decay by a power law rather than exponentially as in AR(1). At such latitudes the uncertainties of total ozone trends are greater than those obtained from AR(1) models and the expected time required to detect ozone recovery correspondingly longer. We find no evidence of LRC behavior in southern middle-and high-subpolar latitudes (45°–60°S), where the long-term ozone decline attributable to anthropogenic chlorine is the greatest. We thus confirm an earlier prediction based on an AR(1) analysis that this region (especially the highest latitudes, and especially the South Atlantic) is the optimal location for the detection of ozone recovery, with a statistically significant ozone increase attributable to chlorine likely to be detectable by the end of the next decade. In northern middle and high latitudes, on the other hand, there is clear evidence of LRC behavior. This increases the uncertainties on the long-term trend attributable to anthropogenic chlorine by about a factor of 1.5 and lengthens the expected time to detect ozone recovery by a similar amount (from ∼2030 to ∼2045). If the long-term changes in ozone are instead fit by a piecewise-linear trend rather than by stratospheric chlorine loading, then the strong decrease of northern middle- and high-latitude ozone during the first half of the 1990s and its subsequent increase in the second half of the 1990s projects more strongly on the trend and makes a smaller contribution to the noise. This both increases the trend and weakens the LRC behavior at these latitudes, to the extent that ozone recovery (according to this model, and in the sense of a statistically significant ozone increase) is already on the verge of being detected. The implications of this rather controversial interpretation are discussed.

An assessment of the surface ozone trend in Ireland relevant to air pollution and environmental protection

Hourly data (1994–2009) of surface ozone concentrations at eight monitoring sites have been investigated to assess target level and long–term objective exceedances and their trends. The European Union (EU) ozone target value for human health (60 ppb–maximum daily 8–hour running mean) has been exceeded for a number of years for almost all sites but never exceeded the set limit of 25 exceedances in one year. Second highest annual hourly and 4th highest annual 8–hourly mean ozone concentrations have shown a statistically significant negative trend for in–land sites of Cork–Glashaboy, Monaghan and Lough Navar and no significant trend for the Mace Head site. Peak afternoon ozone concentrations averaged over a three year period from 2007 to 2009 have been found to be lower than corresponding values over a three–year period from 1996 to 1998 for two sites: Cork–Glashaboy and Lough Navar sites. The EU long–term objective value of AOT40 (Accumulated Ozone Exposure over a threshold of 40 ppb) for protection of vegetation (3 ppm–hour, calculated from May to July) has been exceeded, on an individual year basis, for two sites: Mace Head and Valentia. The critical level for the protection of forest (10 ppm–hour from April to September) has not been exceeded for any site except at Valentia in the year 2003. AOT40–Vegetation shows a significant negative trend for a 3–year running average at Cork–Glashaboy (–0.13±0.02 ppm–hour per year), at Lough Navar (–0.05±0.02 ppm–hour per year) and at Monaghan (–0.03±0.03 ppm–hour per year–not statistically significant) sites. No statistically significant trend was observed for the coastal site of Mace head. Overall, with the exception of the Mace Head and Monaghan sites, ozone measurement records at Irish sites show a downward negative trend in peak values that affect human health and vegetation.

Forecasting with difference and trend stationary models

Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.

Rule Type Identification using TRCM for trend analysis in Twitter

This paper considers the use of Association Rule Mining (ARM) and our proposed Transaction based Rule Change Mining (TRCM) to identify the rule types present in tweet’s hashtags over a specific consecutive period of time and their linkage to real life occurrences. Our novel algorithm was termed TRCM-RTI in reference to Rule Type Identification. We created Time Frame Windows (TFWs) to detect evolvement statuses and calculate the lifespan of hashtags in online tweets. We link RTI to real life events by monitoring and recording rule evolvement patterns in TFWs on the Twitter network.

Should system dynamics be described as a 'hard' or 'deterministic' systems approach?

This paper explores the criticism that system dynamics is a ‘hard’ or ‘deterministic’ systems approach. This criticism is seen to have four interpretations and each is addressed from the perspectives of social theory and systems science. Firstly, system dynamics is shown to offer not prophecies but Popperian predictions. Secondly, it is shown to involve the view that system structure only partially, not fully, determines human behaviour. Thirdly, the field's assumptions are shown not to constitute a grand content theory—though its structural theory and its attachment to the notion of causality in social systems are acknowledged. Finally, system dynamics is shown to be significantly different from systems engineering. The paper concludes that such confusions have arisen partially because of limited communication at the theoretical level from within the system dynamics community but also because of imperfect command of the available literature on the part of external commentators. Improved communication on theoretical issues is encouraged, though it is observed that system dynamics will continue to justify its assumptions primarily from the point of view of practical problem solving. The answer to the question in the paper's title is therefore: on balance, no.

The prediction of Northern Hemisphere tropical cyclone extended life cycles by the ECMWF Ensemble and Deterministic Prediction Systems. Part I: tropical cyclone stage

This study has explored the prediction errors of tropical cyclones (TCs) in the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) for the Northern Hemisphere summer period for five recent years. Results for the EPS are contrasted with those for the higher-resolution deterministic forecasts. Various metrics of location and intensity errors are considered and contrasted for verification based on IBTrACS and the numerical weather prediction (NWP) analysis (NWPa). Motivated by the aim of exploring extended TC life cycles, location and intensity measures are introduced based on lower-tropospheric vorticity, which is contrasted with traditional verification metrics. Results show that location errors are almost identical when verified against IBTrACS or the NWPa. However, intensity in the form of the mean sea level pressure (MSLP) minima and 10-m wind speed maxima is significantly underpredicted relative to IBTrACS. Using the NWPa for verification results in much better consistency between the different intensity error metrics and indicates that the lower-tropospheric vorticity provides a good indication of vortex strength, with error results showing similar relationships to those based on MSLP and 10-m wind speeds for the different forecast types. The interannual variation in forecast errors are discussed in relation to changes in the forecast and NWPa system and variations in forecast errors between different ocean basins are discussed in terms of the propagation characteristics of the TCs.

Institutional investors: arbitrageurs or rational trend chasers?

This paper studies the relationship between institutional investor holdings and stock misvaluation in the U.S. between 1980 and 2010. I find that institutional investors overweigh overvalued and underweigh undervalued stocks in their portfolio, taking the market portfolio as a benchmark. Cross-sectionally, institutional investors hold more overvalued stocks than undervalued stocks. The time-series studies also show that institutional ownership of overvalued portfolios increases as the portfolios' degree of overvaluation. As an investment strategy, institutional investors' ride of stock misvaluation is neither driven by the fund flows from individual investors into institutions, nor industry-specific. Consistent with the agency problem explanation, investment companies and independent investment advisors have a higher tendency to ride stock misvaluation than other institutions. There is weak evidence that institutional investors make positive profit by riding stock misvaluation. My findings challenge the models that view individual investors as noise traders and disregard the role of institutional investors in stock market misvaluation.