School of Earth Sciences - Research Publications
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ItemGlobal and regional impacts differ between transient and equilibrium warmer worlds(NATURE PUBLISHING GROUP, 2020-01-01)under exclusive licence to Springer Nature Limited. There has recently been interest in understanding the differences between specific levels of global warming, especially the Paris Agreement limits of 1.5 °C and 2 °C above pre-industrial levels. However, different model experiments1–3 have been used in these analyses under varying rates of increase in global-average temperature. Here, we use climate model simulations to show that, for a given global temperature, most land is significantly warmer in a rapidly warming (transient) case than in a quasi-equilibrium climate. This results in more than 90% of the world’s population experiencing a warmer local climate under transient global warming than equilibrium global warming. Relative to differences between the 1.5 °C and 2 °C global warming limits, the differences between transient and quasi-equilibrium states are substantial. For many land regions, the probability of very warm seasons is at least two times greater in a transient climate than in a quasi-equilibrium equivalent. In developing regions, there are sizable differences between transient and quasi-equilibrium climates that underline the importance of explicitly framing projections. Our study highlights the need to better understand differences between future climates under rapid warming and quasi-equilibrium conditions for the development of climate change adaptation policies. Yet, current multi-model experiments1,4 are not designed for this purpose.
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ItemThe role of climate variability in Australian drought(NATURE PUBLISHING GROUP, 2020-02-24)The Poisson regression model remains an important tool in the econometric analysis of count data. In a pioneering contribution to the econometric analysis of such models, Lung-Fei Lee presented a specification test for a Poisson model against a broad class of discrete distributions sometimes called the Katz family. Two members of this alternative class are the binomial and negative binomial distributions, which are commonly used with count data to allow for under-and over-dispersion, respectively. In this paper we explore the structure of other distributions within the class and their suitability as alternatives to the Poisson model. Potential difficulties with the Katz likelihood leads us to investigate a class of point optimal tests of the Poisson assumption against the alternative of over-dispersion in both the regression and intercept only cases. In a simulation study, we compare score tests of ‘Poisson-ness’ with various point optimal tests, based on the Katz family, and conclude that it is possible to choose a point optimal test which is better in the intercept only case, although the nuisance parameters arising in the regression case are problematic. One possible cause is poor choice of the point at which to optimize. Consequently, we explore the use of Hellinger distance to aid this choice. Ultimately we conclude that score tests remain the most practical approach to testing for over-dispersion in this context.