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ItemThe response of nonlinear feedbacks associated with the Indian Ocean Dipole to global warmingNG, BENJAMIN ( 2015)The Indian Ocean Dipole (IOD) is an interannual mode of variability in the tropical Indian Ocean which has the potential to severely impact the surrounding countries. A prominent feature of the IOD is its positive skewness, where positive IOD events tend to be larger than negative events resulting in stronger impacts. Models from the Coupled Model Intercomparison Project phase 5 (CMIP5) show a threefold increase in the frequency of extreme events by 2100. However, the contribution of feedbacks associated with the IOD to this skewness and how they respond to increasing greenhouse gases are not well understood. The nonlinearity of four feedbacks (the Bjerknes feedback, sea surface temperature (SST)-cloud-radiation feedback, wind-evaporation-SST feedback, and nonlinear dynamic heating) was investigated and their responses to a warmer climate examined using CMIP5 models. A single model was first used to examine the nonlinearity of the four feedbacks, allowing the cause and effect of each feedback process to be determined. Following this, the analysis was applied to a multi-model ensemble to determine the cause of positive IOD skewness. The role of nonlinear dynamic heating in increasing the frequency of extreme events was then examined. This provides a better understanding of IOD dynamics and future behaviour. The positive Bjerknes feedback controls IOD skewness through the thermocline feedback. In a warmer climate, models show that the skewness of the IOD weakens and the asymmetry of the thermocline feedback displays a significant relationship with this reduced skewness. This decreased asymmetry occurs due to the mean state change of the tropical Indian Ocean where the Walker circulation exhibits weakening. The weaker mean westerly winds allow the climatological thermocline to shoal in the east, reducing the asymmetry of the thermocline feedback and thereby IOD skewness. The other feedbacks do not show as strong a relationship with IOD skewness. The negative SST-cloud-radiation feedback shows stronger damping of positive IODs and this is detrimental for IOD skewness. Under greenhouse warming there appears to be a shift amongst most models, with weaker damping of positive IODs and stronger damping of negative IODs. This is unfavourable for the reduction in skewness that occurs under increasing greenhouse gases. The positive wind-evaporation-SST feedback is not well simulated in coupled models. Therefore the relationship between IOD skewness and the wind-evaporation-SST feedback is uncertain and there does not appear to be a significant change in the asymmetry of this feedback in a warmer climate. Nonlinear dynamic heating involves advection of heat by oceanic currents, reinforcing positive IODs but damping negative IOD events. Amongst the models analysed, this process does not appear to contribute significantly to IOD skewness; however it does play an important role in the generation of extreme events and the projected increase. Nonlinear zonal and vertical advection during moderate events becomes more extreme-like due to the mean state change of the tropical Indian Ocean. This means that conditions during future moderate positive IOD events are similar to present-day extreme events, facilitating the projected increase of extreme positive IODs in a warmer climate.
ItemHydrological extremes and consequences of climate changeJakob, Dörte ( 2013)In the design of infrastructure, risk has been – and often still is – assessed on the basis of long-term averages. Information on variation in hydrological extremes is required as the basis for informed decision-making, preparedness and possible adaptation. Long-term trends are fairly well understood for temperature but less well for precipitation. While climate models have become sophisticated tools for projecting future changes in our climate, their ability to replicate observed variations in precipitation is limited and it is therefore prudent to complement climate models through analysis of historical observations. Design rainfall is used as one of the required inputs for hydrological models in the design of structures such as dams and bridges. Design rainfall estimates are supplied in form of intensity-frequency-duration curves. Rainfall frequency analysis is almost invariably based on the assumption of a stationary climate. Sub-daily durations are of particular interest for urban applications. This thesis was strongly driven by the motivation to provide guidance to decision makers who have to account for non-stationarity in rainfall extremes. Non-stationarity in rainfall extremes comes about as a conflation of climate change and climate variability. Unlike for temperature extremes, rainfall extremes for Australia as a whole exhibit no clear increase or decrease in intensity over time but strong association with the El Niño-Southern Oscillation (ENSO). This has implications for the choice of suitable analysis techniques, e.g. sophisticated non-parametric techniques. Depending on the planning horizons both climate change and climate variability may have to be accounted for. The association of rainfall extremes with ENSO leads to an opportunity to develop statistical models to support decision-making on shorter time scales. Analysis of seasonality in frequency and magnitude of rainfall extremes revealed considerable variation across a set of sites in the southeast of Australia, implying different dominating rainfall-producing mechanisms and/or interactions with local topography. The strongest signal for an increase in extreme precipitation is found for short durations. Changes in rainfall extremes come about through a combination of changes in thermodynamical and dynamical variables. To assess large-scale changes in circulation, a classification technique (self-organising maps, SOM) was applied and synoptic types were identified. Rainfall extremes were then related to the synoptic type under which they occurred, to assess observed changes in the frequency of rainfall extremes. Rainfall extremes are typically preceded by conditions that are much wetter (both in absolute and relative terms) and warmer than the climatological average. These anomalies tend to be larger for shorter durations, and for rarer events. Given that increase in humidity exhibits strong regional variability and that it may be counteracted by changes in dynamics, it appears simplistic to state categorically that climate change will lead to an increase in extreme rainfall events and observed trends in rainfall extremes show a picture that is more complex. In summary, the combination of changes in thermodynamic and dynamic variables will define the change in frequency and intensity of rainfall extremes. The factors that are most relevant for the effect of climate change on rainfall extremes depend on geographical location.
ItemDrivers of Southern Hemisphere climate changeArblaster, Julie Michelle ( 2013)The climate of the Southern Hemisphere (SH) has undergone significant changes over recent decades, with additional warming expected under future emission scenarios. However, while temperature increases are robust across models there is more uncertainty around changes in rainfall, atmospheric circulation and extremes, all of which have a large impact on human society and ecosystems. The objective of this thesis was to increase our confidence in future projections by considering the relative importance of various drivers of past and future climate change, with a focus on the Southern Hemisphere. These drivers include sea surface temperatures (SSTs; which may or may not be anthropogenically forced), greenhouse gases and stratospheric ozone. To achieve this objective a hierarchy of model experiments were utilised, from idealised experiments to multimodel datasets. Insights were gained by exploring both the consistencies and the spread across the model results. The main results were: 1) The internal variability of the climate system, such as the El Niño-Southern Oscillation (ENSO), impacts the emerging signals of anthropogenic climate change and characterisations of this noise were explored. Opposite phases of ENSO were found to drive marked contrasts in maximum temperature extremes, with ENSO fidelity crucial in simulating the observed relationships. These patterns are unlikely to change substantially under future climate change. Over the Australian continent, future warming leads to increases in warm temperature extremes and a propensity for longer dry spells interspersed with heavy rainfall events. In general, the magnitude of changes in both temperature and precipitation extremes indices scaled with the strength of emissions. 2) Coupled model simulations were able to reproduce the large-scale features of SH climate trends since 1950, if observed changes in anthropogenic forcings were included. However, atmospheric models driven by observed SSTs and anthropogenic forcings were unable to capture wintertime trends, suggesting either deficiencies in the modelling framework, SSTs or models themselves or that internal variability has been largely responsible for these trends. The improvement of the simulated trends in experiments with partial coupling suggests the modelling framework plays some role in this deficiency. 3) Future changes in the SH atmospheric circulation will be driven by the competing effects of greenhouse gases and stratospheric ozone recovery. Climate sensitivity was found to largely explain the difference in Southern Annular Mode (SAM) projections between two coupled climate models under identical greenhouse gas and stratospheric ozone forcing. This result extended to multimodel simulations under transient carbon dioxide (CO2) conditions in all seasons, with the stronger the warming the larger the trend in the SAM. Tropical upper tropospheric warming was found to be more relevant than polar stratospheric cooling to the model spread in SAM responses to CO2. 4) Idealised SST experiments in two models showed a consistent poleward shift of the SH wintertime westerly jet under Southern Ocean cooling. However, the austral winter response to increased tropical SSTs was found to be model dependent, with opposite latitudinal shifts in the SH westerly jet in the two models. This finding was linked to different tropical rainfall and convective atmospheric heating responses in the models to identical SST increases. These results highlight the reliability of current climate model simulations as well as some of their limitations. Potential deficiencies in forcing datasets, modelling frameworks and the simulation of internal variability were identified. Understanding and improving these deficiencies is crucial for interpreting recent observed change and understanding future projections, particularly at the regional scale.
ItemThe impacts of climate variability and change on severe thunderstorm environments in AustraliaAllen, John Terrence ( 2012)Severe thunderstorms present a relatively infrequent but significant threat to property and life in Australia during the spring and summer. These thunderstorms can produce hailstones over 2cm in diameter, winds in excess of 90kmh-1 and less frequently tornadoes. Any of these phenomena can result in localised high impact severe events. Recent examples of this potential are illustrated by damage caused by the 1999 Sydney Hailstorm, 2008 Gap Microburst and the 2010 and 2011 Melbourne Hailstorms. This risk makes the implications of a changing and variable climate on severe thunderstorms important to understand. Recent studies into the impacts of anthropogenic climate change on severe weather events, including thunderstorms, suggest a potential increasing trend in both frequency and intensity for Australia. While current convective parameterisations in both global and regional climate models limit direct assessments of future convection, the use of environmental parameters to estimate changes in severe thunderstorm environments has been successful in other geographical regions. This study seeks an answer to the question “Is the frequency and distribution of severe thunderstorm environments in Australia likely to change in the future?” A database of 1550 independent severe thunderstorm reports in Australia has been developed for the period March 2003 to April 2010. Severe thunderstorm reports are then used to identify relationships with their associated environments estimated using proximal soundings from a mesoscale numerical weather assimilation and prediction model (MesoLAPS). This proximity climatology of known severe thunderstorm environments has been successfully used to derive covariate discriminants that identify the potential of an environment to produce severe thunderstorms. These covariates use variables describing the potential for organised convection (deep-layer wind shear), and the potential for instability over the depth of the atmosphere (convective available potential energy). Applying these discriminants to a reanalysis dataset (ERA-Interim), a climatology of the frequency and spatial distribution of environments favourable to the development of severe and significant severe thunderstorms for Australia has been developed for warm seasons during the period 1979-2011. This climatology demonstrates that inter-annual variability in terms of both the frequency and spatial distribution of environments is influenced by El Niño- Southern Oscillation. La Niña conditions are typically associated with an increased frequency and an inland shift of favourable environments over eastern Australia, while El Niño typically results in fewer environments, particularly along the coastal fringe. Applying this climatology, the environments simulated by two climate models (CSIRO Mk3.6 and CCAM) for the 20-season period 1980-2000 are examined over Australia and tested against the reanalysis climatology. In particular, the ability of the models to resolve the intra-annual variability and both quantify and simulate the spatial distribution of convective variables are analysed, and are found to perform reasonably well, especially in the case of the higher resolution CCAM. Finally, future simulations of severe thunderstorm environments from high emissions projections for the period 2079-2099 are presented for both models. Comparing these simulations to the 20th century, a potential small increase in the frequency of severe thunderstorm environments appears likely for southeast and eastern Australia under a warming climate.