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Persistent shifts in mean rainfall have wide-ranging impacts to hydrology and water availability, and a reliable set of climate projections of change to mean rainfall is a useful tool for future planning. Most climate models project a decrease in winter rainfall in southern Australia, however there is a wide model range and there is not yet a robust assessment of underlying physical processes that can inform and constrain projections. Here, a multiple linear regression model between indices of atmospheric circulation and gridded rainfall in observations and in CMIP5 climate models is developed for July, representing the peak of winter. The regression is used as an evaluation tool for models and a basis to select models. Spatial distributions of the coefficients from the regression illustrate the relative important of different circulation features for rainfall across the region, and illustrate where climate models have deficiencies. As an additional check of projections, historical years that are an analogue for the projected future mean state of the atmospheric circulation are identified and the rainfall anomaly during those years is examined. Both approaches broadly agree and support previous work in suggesting a constraint on rainfall change to a decrease only. The regression analysis also suggests that the median projection for southwest Western Australia should be revised lower than the median of all climate models. The results demonstrate value in applying statistical techniques to understand relationships of rainfall to circulation and to refine confidence in regional climate projections. [ABSTRACT FROM AUTHOR]

Change to precipitation in a warming climate holds many implications for water management into the future, and an enhancement of a precipitation decrease or increase on or around mountains would have numerous impacts. Here, an intermediate resolution regional climate model (RCM) ensemble projects enhanced precipitation decrease on the windward slopes of over many mid-latitude mountains in winter, consistent with theory and model studies of idealised mountain ranges. This ensemble projects that an increase in convective rainfall determines the sign of total rainfall change in many regions in summer, only some of which are on or near mountains such as the European Alps. These same projected changes are present in inland slopes of the Australian Alps compared to surrounding regions as simulated by three RCM ensembles (the intermediate resolution and two high resolution ensembles), which agree on an enhanced precipitation decrease on the windward slopes in winter and spring, as well as an enhanced precipitation increase in summer driven by an increase in convective rainfall. The ensembles disagree on an enhanced precipitation decrease in autumn. The results represent regional-scale added value in the climate change signal of projections from high resolution models in cooler seasons, but suggest that the specific model components such as convection schemes strongly influence projections of summer rainfall change. Confidence in the simulation of change in convective rainfall, or convection-permitting modelling may be needed to raise confidence in summer rainfall projections over mountains. [ABSTRACT FROM AUTHOR]

Abstract: Transient climate response (TCR), transient response at 140 years (T140), and equilibrium climate sensitivity (ECS) indices are intended as benchmarks for comparing the magnitude of climate response projected by climate models. It is generally assumed that TCR or T140 would explain more variability between models than ECS for temperature change over the 21st century, since this timescale is the realm of transient climate change. Here we find that TCR explains more variability across Coupled Model Intercomparison Project phase 5 than ECS for global temperature change since preindustrial, for 50 or 100 year global trends up to the present, and for projected change under representative concentration pathways in regions of delayed warming such as the Southern Ocean. However, unexpectedly, we find that ECS correlates higher than TCR for projected change from the present in the global mean and in most regions. This higher correlation does not relate to aerosol forcing, and the physical cause requires further investigation. [ABSTRACT FROM AUTHOR]

The article focuses on the circulation pattern that drives cold outbreaks as well as severe frost risk in southwest Western Australia in September 2016. Topics being presented include thermodynamic changes as well as the effect of human influence on cold extremes and rising temperatures of the climate mean state and forced changes to circulation is presented,

Atmospheric circulation change is likely to be the dominant driver of multidecadal rainfall trends in the midlatitudes with climate change this century. This study examines circulation features relevant to southern Australian rainfall in January and July and explores emergent constraints suggested by the intermodel spread and their impact on the resulting rainfall projection in the CMIP5 ensemble. The authors find relationships between models' bias and projected change for four features in July, each with suggestions for constraining forced change. The features are the strength of the subtropical jet over Australia, the frequency of blocked days in eastern Australia, the longitude of the peak blocking frequency east of Australia, and the latitude of the storm track within the polar front branch of the split jet. Rejecting models where the bias suggests either the direction or magnitude of change in the features is implausible produces a constraint on the projected rainfall reduction for southern Australia. For RCP8.5 by the end of the century the constrained projections are for a reduction of at least 5% in July (with models showing increase or little change being rejected). Rejecting these models in the January projections, with the assumption the bias affects the entire simulation, leads to a rejection of wet and dry outliers. [ABSTRACT FROM AUTHOR]

The article examines the possible causes of mean seal level pressure (MSLP) anomalies in south Australia in August 2014. Topics covered include analysis of weather@home global simulations, the impact of climate change on the monthly MSLP anomalies and the findings that human influence on climate variation increased the chances of extreme high pressure anomalies associated with reduced rainfall, lowland snowfall and frosts.

Climate warming has large implications for rainfall patterns, and identifying the most plausible pattern of rainfall change over the next century among various model projections would be valuable for future planning. The spatial pattern of projected sea surface temperature change has a key influence on rainfall changes in the tropical Pacific Ocean. Here it is shown that simple indices of the size of the equatorial peak in the spatial pattern of warming and to a lesser extent the hemispheric asymmetry in warming are useful for classifying the surface temperature change in different models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Models with a more pronounced equatorial warming show a fairly distinct rainfall response compared to those with more uniform warming, including a greater 'warmer-get-wetter' or dynamical response, whereby rainfall increases follow the surface warming anomaly. Models with a more uniform warming pattern project a smaller rainfall increase at the equator and a rainfall increase in the southern tropical Pacific, a pattern that is distinct from the multimodel mean of CMIP5. Thus, the magnitude of enhanced equatorial warming and to some extent the hemispheric asymmetry in warming provides a useful framework for constraining rainfall projections. While there is not a simple emergent constraint for enhanced equatorial warming in models in terms of past trends or bias in the current climate, further understanding of the various feedbacks involved in these features could lead to a useful constraint of rainfall for the Pacific region. [ABSTRACT FROM AUTHOR]

ABSTRACT A set of 27 global climate models from the Coupled Model Inter-comparison Project Phase 5 ( CMIP5) ensemble are assessed for their performance for the purpose of making future climate projection studies in the western tropical Pacific and differences to Coupled Model Inter-comparison Project Phase 3 ( CMIP3) are assessed. The CMIP5 models show some improvements upon CMIP3 in the simulation of the climate in the western tropical Pacific in the late 20th century. There are fewer CMIP5 models with very poor skill scores than in CMIP3 for some measures and a small group of the well-performing models in CMIP5 have lower biases than in an equivalent group from CMIP3. These best-performing models could be particularly informative for studying certain climate sensitivities and feedbacks in the region. There is evidence to reject one model as unsuitable for making regional climate projections in the region, and another two models unsuitable for analysis of the South Pacific Convergence Zone (SPCZ). However, while there have been improvements, many of the systematic model biases in the mean climate in CMIP3 are also present in the CMIP5 models. They are primarily related to the shape of the transition between the Indo-Pacific warm pool and equatorial cold tongue, and the associated biases in the position and orientation of the SPCZ and Inter-Tropical Convergence Zone, as well as in the spatial pattern, variability and teleconnections of the West Pacific monsoon, and the simulation of El Niño Southern Oscillation. Overall, the results show that careful interpretation and consideration of biases is required when using CMIP5 outputs for generating regional climate projections for the western tropical Pacific, particularly at the country scale, just as there was with CMIP3. [ABSTRACT FROM AUTHOR]

ABSTRACT We describe the method and performance of a bias-correction applied to high-resolution (˜10 km) simulations from a stretched-grid Regional Climate Model ( RCM) over Tasmania, Australia. The bias-correction is a quantile mapping of empirical cumulative frequency distributions. Corrections are applied at a daily time step to five variables: rainfall, potential evaporation (PE), solar radiation, maximum temperature and minimum temperature. Corrections are calculated independently for each season. We show that quantile mapping of empirical distributions can be highly effective in correcting biases in RCM outputs. Cross-validation shows biases are effectively reduced across the range of cumulative frequency distributions, with few exceptions. The bias-correction is not as effective at correcting biases for values at or near zero (e.g. in rainfall simulations), although even here the bias-correction improves biases evident in the uncorrected simulations. In addition, the bias-correction improves frequency characteristics of variables such as the number of rain days. We use a detrending technique to apply the bias-correction to 140-year time series of RCM variables. We show that the bias-correction effectively preserves long-term changes (e.g. to the mean and variance) to variables projected by the uncorrected RCM simulations. Correlations between key variables are also largely preserved, thus the bias-corrected outputs reflect the dynamics of the underlying RCM. However, the bias-corrected simulations still exhibit some of the deficiencies of the RCM simulations, e.g. the tendency to underestimate the magnitude and duration of large, multi-day rain events, and the tendency to underestimate the duration of dry spells. The bias-corrected simulations for six downscaled GCMs for the A2 and B1 emissions scenarios are available to researchers from . [ABSTRACT FROM AUTHOR]

The article presents a study which examined the roles of the 2015-2016 El Niño, anthropogenic climate change, and internal atmospheric variability on low rainfall recorded in October 2015 in Tasmania. It mentions that model simulations were used and fraction of attributable risk was calculated. It shows that El Niño and anthropogenic climate change made a significant contributions and the main contributor to the increasing likelihood of low rainfall was atmospheric variability.

• Nationwide streamflow projections for Australia informed by CMIP5 and CMIP6. • Vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. • Lower winter rainfall translates to a significant reduction in annual runoff. • Modelled median projection of runoff shows a 50% reduction in far southwest Australia. • Modelled median projection of runoff shows a 20% reduction in far southeast Australia. Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts. [ABSTRACT FROM AUTHOR]

Coarse resolution global climate models (GCMs) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, 'realised added value', that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development. [ABSTRACT FROM AUTHOR]

The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961–2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5- day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century. [ABSTRACT FROM AUTHOR]