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In the North West Shelf region of Australia is a surface current (Holloway Current), which flows southwestward along the shelf break. This paper describes a seasonal undercurrent below the Holloway Current. A 5-day climatology is constructed from the output of an eddy-resolving oceanic general circulation model (OGCM). A seasonal northeastward-flowing undercurrent is found on the upper continental slope during the climatological April-May. This undercurrent reverses during February-March. During its annual cycle, the phase of the undercurrent tends to propagate southwestward and upward. The annual frequency dominates, but the positive and negative phases of the undercurrent are not symmetric in the yearly cycle because of the contributions from the semi-annual and 1/3-annual components. We propose a hypothesis that this undercurrent is a beam of coastal trapped wave (CTW). As an initial attempt to assess the plausibility of this hypothesis, we construct an idealized linear coastal-trapped wave (CTW) solution driven by an idealized harmonic meridional winds at the annual frequency. The solution takes the form of a beam originating from the forcing region on the continental shelf and propagating offshore and southward. When it emerges on to the continental slope, it takes the form of an undercurrent. This idealized solution shares several properties with the undercurrent in the OGCM despite several discrepancies. [ABSTRACT FROM AUTHOR]

When record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of reoccurrence or are reflective of an altered frequency or intensity as a result of climate change. This paper describes a method to attribute extreme weather and climate events to observed increases in atmospheric CO2 using an initialized subseasonal to seasonal coupled global climate prediction system. Application of this method provides quantitative estimates of the contribution arising from increases in the level of atmospheric CO2 to individual weather and climate extreme events. Using a coupled subseasonal to seasonal forecast system differs from other methods because it has the merit of being initialized with the observed conditions and subsequently reproducing the observed events and their mechanisms. This can aid understanding when the reforecasts with and without enhanced CO2 are compared and communicated to a general audience. Atmosphere–ocean interactions are accounted for. To illustrate the method, we attribute the record Australian heat event of October 2015. We find that about half of the October 2015 Australia-wide temperature anomaly is due to the increase in atmospheric CO2 since 1960. This method has the potential to provide attribution statements for forecast events within an outlook period (i.e., before they occur). This will allow for informed messaging to be available as required when an extreme event occurs, which is of particular use to weather and climate services. [ABSTRACT FROM AUTHOR]

Current methods for climate change assessment ignore the significant differences in uncertainty in model projections of the two key constituents of drought, precipitation, and evapotranspiration. We present here a new basis for assessing future drought using climate model simulations that addresses this limitation. The new method estimates the Standardized Precipitation Evapotranspiration Index (SPEI) in a two‐stage process. The first stage of our proposed approach is to derive the Standardized Precipitation Index (SPI) using reliable atmospheric variables, which are filtered with a wavelet‐based spectral transformation. This derived SPI is then converted to an equivalent SPEI by combining it with climate model evapotranspiration simulations. We assess the performance of our proposed approach across Australia. The consistency of general circulation model (GCM) drought projections, in terms of both frequency and severity, is improved using the derived SPI. Incorporating evapotranspiration further improves the consistency of the multiple GCMs and drought time scales. The proposed framework can also be generalized to other water resources applications, where the differences in GCM uncertainty for precipitation and evapotranspiration affect climate change impact assessments. Plain Language Summary: Drought is affected by both rainfall and evapotranspiration. Drought indices represent drought severity compared to normal conditions as a function of time. Some drought indices are based on rainfall alone and some use both rainfall and evapotranspiration in the calculations. To understand future drought risk, simulations from climate models are needed. Unfortunately, different climate models often disagree on amounts and patterns of rainfall in the future, the disagreement being considerably more on rainfall than for evapotranspiration. In this study, we attempt to reduce the impact of these differences by developing a new method to estimate future drought. We used a mathematical method known as wavelets to estimate drought indices based on rainfall. Evapotranspiration is then used directly from the climate model and combined with the rainfall based drought index to create one overall drought index. We used projections from multiple climate models to understand if our new method led to a greater agreement in how often and severe future droughts may be. Our results confirm that the new method offers greater consistency in drought projections for the future. Key Points: Current methods for projecting drought ignore differences in uncertainty between P and ET simulationsA new basis for projecting drought is proposed that explicitly accounts for relative uncertainty between P and ETOur results show that the new method offers greater consistency in drought projections for the future [ABSTRACT FROM AUTHOR]

• Quantile-quantile rainfall mapping methods are extended to improve streamflow simulations. • Extensions correct rainfall bias at multiple time scales and model rainfall autocorrelation. • Methods reduce bias in rainfall sequencing metrics for downscaled GCM simulations. • Methods reduce bias in streamflow simulations forced by downscaled GCM simulations. Global circulation models (GCMs) provide important insights into future climate change. Bias-correction of downscaled GCM output is integral to any hydrological investigations of climate change due to discrepancies between the statistics of downscaled GCM simulations and observations. Many bias-correction techniques have been developed to support hydrological applications. However, there have been few comparisons of the sensitivity of hydrological simulations to different bias-correction assumptions. This paper investigates the importance of two common assumptions: (i) simultaneously correcting bias at multiple time scales, and (ii) explicitly handling rainfall autocorrelation; in quantile mapping of downscaled GCM rainfall data for hydrological simulation. Four quantile mapping methods are applied to correct bias in dynamically downscaled reanalysis and historical GCM simulations of rainfall for 11 catchments in south-eastern Australia and the performance of bias-corrected rainfall and streamflow simulations is evaluated. All quantile mapping methods investigated can effectively eliminate bias in monthly and annual rainfall totals. Quantile mapping methods that consider differences in the temporal dependence (autocorrelation) structure of downscaled GCM and observed rainfall are most effective in reducing bias in rainfall sequencing statistics, such as probability of consecutive wet or dry days. Streamflow simulations of mean and high streamflow percentiles are underestimated when generated using rainfall that is corrected using quantile mapping methods that do not consider differences in the temporal dependence structure of downscaled GCM and observed rainfall. Future hydrological investigations of climate change should therefore adopt methods that explicitly consider the temporal dependence structures of downscaled GCM and observed rainfall. [ABSTRACT FROM AUTHOR]

The effects of climate change have been observed in the Murrumbidgee River basin, which is one of the main river basins in the southeast region of Australia. The study area is the largest and most important agricultural production area within the Murray Darling Basin (MDB). It produces more than AUD 1.9 billion of agricultural products annually and accounts for about 46% of Australia's total agricultural production. Since Australia's economy largely depends on its natural resources, climate change adversely impacts the economy in various ways. According to the Intergovernmental Panel on Climate Change's fifth assessment report (IPCC, AR5), the adaptive capacity and adaptation processes have increased in Australia. The country has implemented policies and management changes in both rural and urban water systems to adapt to future drought, unexpected floods, and other climatic changes. In this study, future catchment runoff has been estimated using the hydrological model, Simplified Hydrolog (SIMHYD), which is integrated with data from three different General Circulation Models (GCMs) and future emission scenarios. Two different representative concentration pathway (RCP) emission scenarios, RCP 4.5 and RCP 8.5, have been used to obtain downscaled future precipitation and evapotranspiration data for the period of 2016 to 2100. Modeling results from the two emission scenarios showed an anticipated warmer and drier climate for the Murrumbidgee River catchment. Runoff in the Murrumbidgee catchment is affected by various dams and weirs, which yields positive results in runoff even when the monthly rainfall trend decreases. The overall runoff simulation result indicated that the impact of climate change is short and intense. The result of the Simplified Hydrolog (SIMHYD) modeling tool used in this study under the RCP 4.5 scenario for the period 2016 to 2045 indicates a significant future impact from climate change on the volumes of runoff in the Murrumbidgee River catchment. For the same period, the climate change prediction showed a decrease in total annual rainfall within the range of 2% to 62%. This reduction in rainfall is projected to decrease river runoff in the upper catchments (e.g., Tharwa, and Yass) by 17% to 58% over the projected periods. However, the runoff trends in the lower sub-catchments (e.g., Borambola) have increased by 137% to 87% under RCP 4.5 and RCP 8.5, respectively. This increasing potential runoff trend in the lower Murrumbidgee catchments gives an indication to build irrigation dams for dry season irrigation management. [ABSTRACT FROM AUTHOR]

Over the last few years, decadal prediction has been paid much attention for its potential applications in agriculture, hydrology and for assessing the climate impact on the various aspects of human life. Though the fidelity of decadal prediction specifically the hindcasts experiments through Coupled Model Inter-comparison Project Phase 5 (CMIP5) has been examined for many climate variables and at different temporal and spatial scales, the drift in CMIP5 decadal precipitation at a local scale remains unknown. Drift is the long-term time varying systematic bias generated by GCMs while they revert to their equilibrium state from the forced initialized state. This study used seven general circulation models (GCMs) from five different modelling groups to examine the drift in monthly and seasonal mean precipitation from the CMIP5 decadal hindcasts for Brisbane river catchment, Australia. Drifts of individual model's ensemble mean and multi-model ensembles' mean (MMEM) at monthly and seasonal time scales were quantified and examined using four different skill tests. Results revealed that the magnitude of drifts are higher in monthly precipitation than the seasonal mean precipitation. Next, the drift in hindcast precipitation was corrected using mean drift correction method and found that the mean drift correction method is not sufficient to alleviate the drift in CMIP5 decadal precipitation. This suggests further research for an appropriate drift correction method for decadal precipitation. Comparing the drift and skill test results over the entire catchment, this study finds, MMEM showing the lowest drifts and outperformed in all models in skill tests. [ABSTRACT FROM AUTHOR]

The International Panel on Climate Change (IPCC) projects a global temperature rise of 4.3 ± 0.7 °C by 2100 and an extinction of 8.5% in one out of every six species. Australia's aquatic ecosystem is no exception; habitat loss, fragmentation, and loss of biodiversity are being experienced. As the center for Nymphaea species distribution, it presents the culturally, ecologically, and scientifically important genus as the best candidate for habitat suitability assessment in climate change, whose habitat suitability is presumed to decline. The models were run according to the maximum entropy (MaxEnt) method, using one general circulation model (GCM). Projections were made for the current, past, and future in medium (4.5) and high (8.5) representative concentration pathways. Significantly, bio2 and bio15 were highly preferred among the species. Less distribution was noted in West Australia compared to the north, east, and south of the continent, while north of the continent in Western Australia, Northern Territory, and Queensland indicate more habitat contractions compared to the east and southeast of Queensland and New South Wales, although it receives high precipitation. Generally, the species respond variably to both temperature and precipitation variables which is a key species response factor for planners and decision makers in species habitat and biodiversity conservation. [ABSTRACT FROM AUTHOR]

Evapotranspiration plays an important role in the terrestrial water cycle. Reference crop evapotranspiration (ET o) has been widely used to estimate water transfer from vegetation surface to the atmosphere. Seasonal ET o forecasting provides valuable information for effective water resource management and planning. Climate forecasts from general circulation models (GCMs) have been increasingly used to produce seasonal ET o forecasts. Statistical calibration plays a critical role in correcting bias and dispersion errors in GCM-based ET o forecasts. However, time-dependent errors resulting from GCM misrepresentations of climate trends have not been explicitly corrected in ET o forecast calibrations. We hypothesize that reconstructing climate trends through statistical calibration will add extra skills to seasonal ET o forecasts. To test this hypothesis, we calibrate raw seasonal ET o forecasts constructed with climate forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) SEAS5 model across Australia, using the recently developed Bayesian joint probability trend-aware (BJP-ti) model. Raw ET o forecasts demonstrate significant inconsistencies with observations in both magnitudes and spatial patterns of temporal trends, particularly at long lead times. The BJP-ti model effectively corrects misrepresented trends and reconstructs the observed trends in calibrated forecasts. Improving trends through statistical calibration increases the correlation coefficient between calibrated forecasts and observations (r) by up to 0.25 and improves the continuous ranked probability score (CRPS) skill score by up to 15 (%) in regions where climate trends are misrepresented by raw forecasts. Skillful ET o forecasts produced in this study could be used for streamflow forecasting, modeling of soil moisture dynamics, and irrigation water management. This investigation confirms the necessity of reconstructing climate trends in GCM-based seasonal ET o forecasting and provides an effective tool for addressing this need. We anticipate that future GCM-based seasonal ET o forecasting will benefit from correcting time-dependent errors through trend reconstruction. [ABSTRACT FROM AUTHOR]

Sea surface height (SSH) along the west coast of Australia is key to local climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. This study provides a method to predict interannual variability in SSH along the west coast of Australia using a simple 1.5‐layer dynamical ocean model forced by a statistical atmospheric model for ENSO‐related winds. The model has realistic coastlines and is driven by reanalysis surface winds regressed onto an ENSO index. The model when run in hindcast mode to predict past variability can simulate tide gauge observations at Fremantle along the west coast of Australia up to 13 months in advance, which outperforms persistence. We conclude that this methodology can be useful as a baseline for gauging the performance of more sophisticated forecast models for predicting SSH variations along the west coast of Australia. Plain Language Summary: Sea surface height (SSH) along the west coast of Australia is key to regional climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. Previous studies predicted interannual variability in SSH in this region using sophisticated ocean‐atmosphere coupled general circulation models, but their ocean models had coarse horizontal resolution, required to reduce computational burden. This study provides a much simpler method to predict SSH variability along the west coast of Australia using a simple ocean dynamical model with realistic coastlines forced by ENSO‐related atmospheric winds. Our model, run in hindcast mode to predict past SSH variability, is able to simulate SSH anomalies along the west coast of Australia up to 13 months in advance. A true forecast system to predict future variations would also require prediction of ENSO. However, this methodology can be useful as a baseline for gauging the performance of more sophisticated model forecast systems. Key Points: Interannual variability in sea level along the west Australian coast can be predicted up to 13 months in advance using a simple ocean modelTo illustrate, the model is run in hindcast mode forced remotely by Pacific surface winds related to El Niño Southern OscillationModel hindcasts generally outperform persistence forecasts in terms of anomaly correlation and root‐mean‐squared differences [ABSTRACT FROM AUTHOR]

For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision-making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast postprocessing methods that are needed to remedy biases and uncertainties in model forecasts. The inability of the forecasts to reproduce the trends severely undermines user confidence in the forecasts. In our previous work, we proposed a new statistical postprocessing model that counteracted departures in trends of model forecasts from observations. Here, we further extend this trend-aware forecast postprocessing methodology to carefully treat the trend uncertainty associated with the sampling variability due to limited data records. This new methodology is validated on forecasting seasonal averages of daily maximum and minimum temperatures for Australia based on the SEAS5 climate model of the European Centre for Medium-Range Weather Forecasts. The resulting postprocessed forecasts are shown to have proper trends embedded, leading to greater accuracy in regions with significant trends. The application of this new forecast postprocessing is expected to boost user confidence in seasonal climate forecasts. [ABSTRACT FROM AUTHOR]

Ensembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble. [ABSTRACT FROM AUTHOR]

Climate change has the potential to impact the generation of renewable energy significantly subject to location and equipment specifications. As the penetration of renewable energy in the energy systems keeps increasing, this impact needs be systematically assessed so that investment and reliability information is accurate. Australia represents an ideal study case characterized by its frequency of extreme weather events and the recent and planned growth in the renewable energy sector. In this study, we model and quantify the long-term temperature de-rating impact of utility-scale solar photovoltaic and wind power generation over Australia. Using climate projections simulated by six Global Circulation Models and the CSIRO's Cubic Conformal Atmospheric Model, we analyze half-hourly time series of key weather variables such as temperature, surface solar irradiance, and wind speed for 1980–2060 at two sites where variable renewable generators are located, or are likely to be located in the future based on the current Integrated System Plan by the Australian Energy Market Operator. We also built power conversion models for the temperature de-rating of solar and wind power with added focus on high temperature scenarios. We found that the general temporal trends in annual solar and wind power generation due to climate change are small, being at the order of 0.1% of their average production per decade. However, for peak temperature events, which coincide with the peak power demand and, generally, high prices, the temperature de-rating impact can be much more substantial and disruptive. [ABSTRACT FROM AUTHOR]

Rainfall in southeastern Australia (SEA) decreased substantially in the austral autumn (March–May) of the 1990s and 2000s. The observed autumn rainfall reduction has been linked to the climate change–induced poleward shift of the subtropical dry zone across SEA and natural multidecadal variations. However, the underlying physical processes responsible for the SEA drought are still not fully understood. This study highlights the role of sea surface temperature (SST) warming in the subtropical South Pacific (SSP) in the autumn rainfall reduction in SEA since the early 1990s. The warmer SSP SST enhances rainfall to the northwest in the southern South Pacific convergence zone (SPCZ); the latter triggers a divergent overturning circulation with the subsidence branch over the eastern coast of Australia. As such, the subsidence increases the surface pressure over Australia, intensifies the subtropical ridge, and reduces the rainfall in SEA. This mechanism is further confirmed by the result of a sensitivity experiment using an atmospheric general circulation model. Moreover, this study further indicates that global warming and natural multidecadal variability contribute approximately 44% and 56%, respectively, of the SST warming in the SSP since the early 1990s. [ABSTRACT FROM AUTHOR]

The southeast Indian Ocean (SEIO) exhibits decadal variability in sea surface temperature (SST) with amplitudes of ~0.2–0.3 K and covaries with the central Pacific (r = −0.63 with Niño-4 index for 1975–2010). In this study, the generation mechanisms of decadal SST variability are explored using an ocean general circulation model (OGCM), and its impact on atmosphere is evaluated using an atmospheric general circulation model (AGCM). OGCM experiments reveal that Pacific forcing through the Indonesian Throughflow explains <20% of the total SST variability, and the contribution of local wind stress is also small. These wind-forced anomalies mainly occur near the Western Australian coast. The majority of SST variability is attributed to surface heat fluxes. The reduced upward turbulent heat flux (QT; latent plus sensible heat flux), owing to decreased wind speed and anomalous warm, moist air advection, is essential for the growth of warm SST anomalies (SSTAs). The warming causes reduction of low cloud cover that increases surface shortwave radiation (SWR) and further promotes the warming. However, the resultant high SST, along with the increased wind speed in the offshore area, enhances the upward QT and begins to cool the ocean. Warm SSTAs co-occur with cyclonic low-level wind anomalies in the SEIO and enhanced rainfall over Indonesia and northwest Australia. AGCM experiments suggest that although the tropical Pacific SST has strong effects on the SEIO region through atmospheric teleconnection, the cyclonic winds and increased rainfall are mainly caused by the SEIO warming through local air–sea interactions. [ABSTRACT FROM AUTHOR]

The koala's Phascolarctos cinereus distribution is currently restricted to eastern and south‐eastern Australia. However, fossil records dating from 70 ± 4 ka (ka = 103 yr) from south‐western Australia and the Nullarbor Plain are evidence of subpopulation extinctions in the southwest at least after the Last Interglacial (~128–116 ka). We hypothesize that koala sub‐population extinctions resulted from the eastward retraction of the koala's main browse species in response to unsuitable climatic conditions. We further posit a general reduction in the distribution of main koala‐browse trees in the near future in response climate change. We modelled 60 koala‐browse species and constructed a set of correlative species distribution models for five time periods: Last Interglacial (~128–116 ka), Last Glacial Maximum (~23–19 ka), Mid‐Holocene (~7–5 ka), present (interpolations of observed data, representative of 1960–1990), and 2070. We based our projections on five hindcasts and one forecast of climatic variables extracted from WorldClim based on two general circulation models (considering the most pessimistic scenario of high greenhouse‐gas emissions) and topsoil clay fraction. We used 17 dates of koala fossil specimens identified as reliable from 70 (± 4) to 535 (± 49) ka, with the last appearance of koalas at 70 ka in the southwest. The main simulated koala‐browse species were at their greatest modelled extent of suitability during the Last Glacial Maximum, with the greatest loss of koala habitat occurring between the Mid‐Holocene and the present. We predict a similar habitat loss between the present and 2070. The spatial patterns of habitat change support our hypothesis that koala extinctions in the southwest, Nullarbor Plain and central South Australia resulted from the eastward retraction of the dominant koala‐browse species in response to long‐term climate changes. Future climate patterns will likely increase the extinction risk of koalas in their remaining eastern ranges. [ABSTRACT FROM AUTHOR]

Many general circulation models fail to capture the observed frequency of atmospheric blocking events in the Northern Hemisphere; however, few studies have examined models in the Southern Hemisphere and those studies that have, have often been based on only a few models. To provide a comprehensive view of how the current generation of coupled general circulation models performs in the Southern Hemisphere and how blocking frequency changes under enhanced greenhouse gas forcing, we examine the output of 23 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that models have differing biases during winter, when blocking occurrence is highest, though models underestimate blocking frequency south of Australia during summer. We show that models generally have a reduction in blocking frequency with future anthropogenic forcing, particularly in the Australia‐New Zealand sector with the number of winter blocked days reduced by about one third by the end of the 21st century. Plain Language Summary: Atmospheric blocking is a process in which an atmospheric wave breaks, diverting the jet stream and any incoming storms to the north or south. A blocking event is characterized by high pressure on the poleward side and low pressure on the equatorward side and persists for upward of 4 days. A key feature of blocks is their persistence, which can lead to events, which have significant impacts on society including heat waves in summer and periods of extreme cold in winter. Climate models often do not simulate enough blocking events, though most research on this problem has focused on the Northern Hemisphere and less is known about the Southern Hemisphere. We survey 23 climate models and show that during winter some models simulate too many blocking events, while others simulate too few, whereas during summer, almost all models simulate too few events to the south of Australia. We also show that with higher concentrations of greenhouse gases we expect there to be less blocking, particularly to the south of Australia and over New Zealand during winter. Key Points: We provide a comprehensive survey of Southern Hemisphere blocking using a large number of coupled modelsFuture projections generally suggest an overall decrease in Southern Hemisphere blocking frequencyThere is strong model agreement on blocking frequency decreases to the south of Australia during austral winter [ABSTRACT FROM AUTHOR]

Monsoon and arid regions in the Asia-Africa-Australia (A-A-A) realm occupy more than 60% of the total area of these continents. Geological evidence showed that significant changes occurred to the A-A-A environments of the monsoon and arid regions, the land-ocean configuration in the Eastern Hemisphere, and the topography of the Tibetan Plateau (TP) in the Cenozoic. Motivated by this background, numerical experiments for 5 typical geological periods during the Cenozoic were conducted using a coupled ocean-atmosphere general circulation model to systemically explore the formations and evolutionary histories of the Cenozoic A-A-A monsoon and arid regions under the influences of continental drift and plateau uplift. Results of the numerical experiments indicate that the timings and causes of the formations of monsoon and arid regions in the A-A-A realm were very different. The northern and southern African monsoons existed during the mid-Paleocene, while the South Asian monsoon appeared in the Eocene after the Indian Subcontinent moved into the tropical Northern Hemisphere. In contrast, the East Asian monsoon and northern Australian monsoon were established much later in the Miocene. The establishment of the tropical monsoons in northern and southern Africa, South Asia, and Australia were determined by both the continental drift and seasonal migration of the Inter-Tropical Convergence Zone (ITCZ), while the position and height of the TP were the key factor for the establishment of the East Asian monsoon. The presence of the subtropical arid regions in northern and southern Africa, Asia, and Australia depended on the positions of the continents and the control of the planetary scale subtropical high pressure zones, while the arid regions in the Arabian Peninsula and West Asia were closely related to the retreat of the Paratethys Sea. The formation of the mid-latitude arid region in the Asian interior, on the other hand, was the consequence of the uplift of the TP. These results from this study provide insight to the important roles played by the earth's tectonic boundary conditions in the formations and evolutions of regional climates during geological times. [ABSTRACT FROM AUTHOR]

The representation of rainfall, and in particular its diurnal cycle, is generally poor in general circulation models (GCMs). Nonetheless, studies make use of GCMs in future climate projections in regions where precipitation has a strong diurnal cycle. In this study we evaluate whether one GCM (ACCESS1.3) can represent the rainfall in such a region (Australia) where the diurnal cycle of rainfall is produced as a result of both the destabilisation of the boundary layer (convection) and a larger-scale reorganisation of the low-level flow, the latter of which may be resolved by a GCM. In northern and eastern Australia, where the diurnal cycle of rainfall is controlled by convective processes, the GCM produces rain 3 to 6 h too early in the day. Nevertheless, the model represents the continental-scale reorganisation of the low-level circulation that results from the diurnal cycle of surface heating and cooling. A nocturnal low-level jet forms over the western half of the continent with strong convergence at the jet exit, which initiates rain overnight in the continental northwest, in agreement with previous work. The model also captures the change in the air-flow direction, from a southeasterly to a northeasterly, responsible for bringing the necessary moisture for precipitation to occur. Thus, while the model may have a tendency to initiate convection too early, it is able to represent the larger-scale nocturnal reorganisation of the flow and the associated rainfall. [ABSTRACT FROM AUTHOR]

A rigorous evaluation of future hydro-climatic changes is necessary for developing climate adaptation strategies for a catchment. The integration of future climate projections from general circulation models (GCMs) in the simulations of a hydrologic model, such as the Soil and Water Assessment Tool (SWAT), is widely considered as one of the most dependable approaches to assess the impacts of climate alteration on hydrology. The main objective of this study was to assess the potential impacts of climate alteration on the hydrology of the Yarra River catchment in Victoria, Australia, using the SWAT model. The climate projections from five GCMs under two Representative Concentration Pathway (RCP) scenarios—RCP 4.5 and 8.5 for 2030 and 2050, respectively—were incorporated into the calibrated SWAT model for the analysis of future hydrologic behaviour against a baseline period of 1990–2008. The SWAT model performed well in its simulation of total streamflow, baseflow, and runoff, with Nash–Sutcliffe efficiency values of more than 0.75 for monthly calibration and validation. Based on the projections from the GCMs, the future rainfall and temperature are expected to decrease and increase, respectively, with the highest changes projected by the GFDL-ESM2M model under the RCP 8.5 scenario in 2050. These changes correspond to significant increases in annual evapotranspiration (8% to 46%) and decreases in other annual water cycle components, especially surface runoff (79% to 93%). Overall, the future climate projections indicate that the study area will become hotter, with less winter–spring (June to November) rainfall and with more water shortages within the catchment. [ABSTRACT FROM AUTHOR]

Soil salinization is a major environmental issue in arid and semi-arid regions, and has been accelerated in some areas by removal of native vegetation cover. Partial afforestation can be a practical mitigation strategy if efficiently integrated with farms and pastures. Using an integrated surface-subsurface hydrological model, this study evaluates the water and salt dynamics and soil salinization conditions of a rural intermittent catchment in the semi-arid climate of southeast Australia subjected to four different partial afforestation configurations under different climate change scenarios, as predicted by several general circulation models. The results show that the locations of afforested areas can induce a retarding effect in the outflow of groundwater salt, with tree planting at lower elevations showing the steadier salt depletion rates. Moreover, except for the configuration with trees planted near the outlet of the catchment, the streamflow is maintained under all other configurations. It appears that under both Representative Concentration Pathways considered (RCP 4.5 and RCP 8.5), the Hadley Centre Global Environmental Model represents the fastest salt export scheme, whereas the Canadian Earth System Model and the Model for Interdisciplinary Research on Climate represent the slowest salt export scheme. Overall, it is found that the location of partial afforestation generally plays a more significant role than the climate change scenarios. [ABSTRACT FROM AUTHOR]