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B. Timbal and R. Fawcett

Abstract

The instrumental record for rainfall across Australia is regarded as being sufficiently reliable to produce national monthly gridded rainfall analyses from 1900 onward. Prior to 1900, the rainfall gauge network is much sparser. The possibility of using those nineteenth-century observations that do exist to construct an estimate of rainfall across the southeastern part of Australia (SEA) is explored by constructing a network based on 11 locations comprising either single observing sites or composites of nearby observing sites with long continuous records. It is shown that, during the period 1900–2010, the monthly rainfall reconstruction based on this network captures 98% of the variability of SEA monthly average rainfall. This network, which extends back to 1865, provides a useful view of the Federation Drought, making a comparison possible with other long-term droughts observed in SEA, around the time of the Second World War and the Millennium Drought from 1997 to 2009. A comparison of these three historical low-rainfall periods was conducted using the drought–depth–duration criteria: the ongoing decline in southeastern Australia is seen as being notably worse than the previous two historical droughts. The network also provides an insight into the decadal variability of SEA rainfall in the later part of the nineteenth century; it includes a high peak in the 1870s comparable to similar wet decadal peaks in the 1950s and 1970s. The implications of this longer perspective on the decadal variability in southeastern Australia in light of the current understanding of the ongoing rainfall deficit are discussed.

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B. Timbal, R. Kounkou, and G. A. Mills

Abstract

Anthropogenic climate change is likely to be felt most acutely through changes in the frequency of extreme meteorological events. However, quantifying the impact of climate change on these events is a challenge because the core of the climate change science relies on general circulation models to detail future climate projections, and many of these extreme events occur on small scales that are not resolved by climate models. This note describes an attempt to infer the impact of climate change on one particular type of extreme meteorological event—the cool-season tornadoes of southern Australia. The Australian Bureau of Meteorology predicts threat areas for cool-season tornadoes using fine-resolution numerical weather prediction model output to define areas where the buoyancy of a near-surface air parcel and the vertical wind shear each exceed specified thresholds. The diagnostic has been successfully adapted to coarser-resolution climate models and applied to simulations of the current climate, as well as future projections of the climate over southern Australia. Simulations of the late twentieth century are used to validate the models’ ability to reproduce the climatology of the risk of cool-season tornado formation by comparing these with similar computations based on historical reanalyses. Model biases are overcome by setting model specific thresholds to define the cool-season tornado risk. The diagnostic, applied to simulations of the twenty-first century, is then used to quantify the impact of the projected climate change on cool-season tornado risk. The sign of the response is consistent across all models: a decrease of the risk of formation during the twenty-first century is projected, driven by the thermodynamical response. The thermal response is modulated by the dynamical response, which varies between models. The projected decrease in tornadoes risk during the cool season is consistent with the projection of positive southern annular mode trends and the known influence of this mode of variability on interannual to intraseasonal time-scale variations in cool-season tornado occurrence.

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B. Timbal, P. Hope, and S. Charles

Abstract

The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

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A. Pepler, B. Timbal, C. Rakich, and A. Coutts-Smith

Abstract

The strong relationship between eastern Australian winter–spring rainfall and tropical modes of variability such as the El Niño–Southern Oscillation (ENSO) does not extend to the heavily populated coastal strip east of the Great Dividing Range in southeast Australia, where correlations between rainfall and Niño-3.4 are insignificant during June–October. The Indian Ocean dipole (IOD) is found to have a strong influence on zonal wind flow during the winter and spring months, with positive IOD increasing both onshore winds and rainfall over the coastal strip, while decreasing rainfall elsewhere in southeast Australia. The IOD thus opposes the influence of ENSO over the coastal strip, and this is shown to be the primary cause of the breakdown of the ENSO–rainfall relationship in this region.

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H. Nguyen, A. Evans, C. Lucas, I. Smith, and B. Timbal

Abstract

Analysis of the annual cycle of intensity, extent, and width of the Hadley circulation across a 31-yr period (1979–2009) from all existent reanalyses reveals a good agreement among the datasets. All datasets show that intensity is at a maximum in the winter hemisphere and at a minimum in the summer hemisphere. Maximum and minimum values of meridional extent are reached in the respective autumn and spring hemispheres. While considering the horizontal momentum balance, where a weakening of the Hadley cell (HC) is expected in association with a widening, it is shown here that there is no direct relationship between intensity and extent on a monthly time scale.

All reanalyses show an expansion in both hemispheres, most pronounced and statistically significant during summer and autumn at an average rate of expansion of 0.55° decade−1 in each hemisphere. In contrast, intensity trends are inconsistent among the datasets, although there is a tendency toward intensification, particularly in winter and spring.

Correlations between the HC and tropical and extratropical large-scale modes of variability suggest interactions where the extent of the HC is influenced by El Niño–Southern Oscillation (ENSO) and the annular modes. The cells tend to shrink (expand) during the warm (cold) phase of ENSO and during the low (high) phase of the annular modes. Intensity appears to be influenced only by ENSO and only during spring for the southern cell and during winter for the northern cell.

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B. Timbal, S. Power, R. Colman, J. Viviand, and S. Lirola

Abstract

Interannual variations of Australian climate are strongly linked to the El Niño–Southern Oscillation (ENSO) phenomenon. However, the impact of other mechanisms on prediction, such as atmosphere–land surface interactions, has been less frequently investigated. Here, the impact of soil moisture variability on interannual climate variability and predictability is examined using the Bureau of Meteorology Research Centre atmospheric general circulation model. Two sets of experiments are run, each with five different initial conditions. In the first set of experiments, soil moisture is free to vary in response to atmospheric forcing in each experiment according to a set of simple prognostic equations. A potential predictability index is computed as the ratio of the model's internal variability to its external forced variability. This estimates the level of predictability obtained assuming perfect knowledge of future ocean surface temperatures. A second set of five experiments with prescribed soil moisture is performed. A comparison between these two sets of experiments reveals that fluctuations of soil moisture increase the persistence, the variance, and the potential predictability of surface temperature and rainfall. The interrelationship between these two variables is also strongly dependent upon the soil water content. Results are particularly marked over Australia in this model. A novel feature of this study is the focus on the effectiveness of ENSO-based statistical seasonal forecasting over Australia. Forecasting skill is shown to be crucially dependent upon soil moisture variability over the continent. In fact, surface temperature forecasts in this manner are not possible without soil moisture variability. This result suggests that a better representation of land–surface interaction has the potential to increase the skill of seasonal prediction schemes.

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H. Nguyen, C. Lucas, A. Evans, B. Timbal, and L. Hanson

Abstract

Changes of the Southern Hemisphere Hadley cell over the twentieth century are investigated using the Twentieth Century Reanalysis (20CR) and coupled model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Trends computed on a 30-yr sliding window on the 20CR dataset reveal a statistically significant expansion of the Hadley cell from 1968 forced by an increasing surface global warming. This expansion is strongly associated with the intensification and poleward shift of the subtropical dry zone, which potentially explain the increasing trends of droughts in the subtropical regions such as southern Australia, South America, and Africa. Coupled models from the CMIP5 do not adequately simulate the observed amount of the Hadley expansion, only showing an average of one-fourth of the expansion as determined from the 20CR and only when simulations include greenhouse gas forcing as opposed to simulations including natural forcing only.

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B. Timbal, J-F. Mahfouf, J-F. Royer, U. Cubasch, and J. M. Murphy

Abstract

The production of climate simulations using global coupled ocean–atmosphere models at high resolution is currently limited by computational expense and the long periods of integration that are necessary. A method of increasing the number of experiments that can be performed is the so-called time-slice technique. Using the Arpège-climat atmospheric model three 5-yr integrations of this type were run: a control and two integrations forced with sea surface temperatures derived from coupled model simulations of the transient response to increasing carbon dioxide. These coupled models are the ECHAM1 model of the Max-Planck Institute (Hamburg, Germany) and the U.K. Meteorological Office model of the Hadley Centre. The sensitivity of the response to the oceanic forcing is studied. The results are compared with the 10-yr mean atmospheric response of the coupled models at the time of the doubling of CO2. Global warmings ranging from 1.3 K to 1.9 K are obtained. Special attention is given to the modifications that occur in the hydrological cycle and their sensitivity to the SSTs. Climatic signals related to oceanic forcing, such as the modification of the ITCZ maximum of precipitation, are separated from signals due to the internal feedbacks and physical parameterizations of the models.

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