The impact of anthropogenic forcing and natural processes on past, present, and future rainfall over Victoria, Australia

Ó 2020 American Meteorological Society.Cool-season (April to October) rainfall dominates the annual average rainfall over Victoria, Australia, and is important for agriculture and replenishing reservoirs. Rainfall during the cool season has been unusually low since the beginning of the Millennium Drought in 1997 (;12% below the twentieth-century average). In this study, 24 CMIP5 climate models are used to estimate 1) the extent to which this drying is driven by external forcing and 2) future rainfall, taking both external forcing and internal natural climate variability into account. All models have preindustrial, historical, and twenty-first-century (RCP2.6, RCP4.5, and RCP8.5) simulations. It is found that rainfall in the past two decades is below the preindustrial average in two-thirds or more of model simulations. However, the magnitude of the multimodel median externally forced drying is equivalent to only 20% of the observed drying (interquartile range of 40% to 24%), suggesting that the drying is dominated by internally generated rainfall variability. Underestimation of internal variability of rainfall by the models, however, increases the uncertainties in these estimates. According to models the anthropogenically forced drying becomes dominant from 2010 to 2029, when drying is evident in over 90% of the model simulations. For the 2018–37 period, it is found that there is only a;12% chance that internal rainfall variability could completely offset the anthropogenically forced drying. By the late twenty-first century, the anthropogenically forced drying under RCP8.5 is so large that internal variability appears too small to be able to offset it. Confidence in the projections is lowered because models have difficulty in simulating the magnitude of the observed decline in rainfall

Subseasonal to Seasonal Climate Forecasts Provide the Backbone of a Near-Real-Time Event Explainer Service

The Bureau of Meteorology serves the Australian community to reduce its climate risk and is developing a suite of tools to explain the drivers of extreme events. Dynamical sub-seasonal to seasonal forecasts form the backbone of the service, potentially enabling it to be run in near real time

A CMIP6-based multi-model downscaling ensemble to underpin climate change services in Australia

A multi-scenario, multi-model ensemble of simulations from regional climate models is outlined to provide the core data source for a set of climate projections and a climate change service. A subset of realisations from CMIP6 Global Climate Models (GCMs) are selected for downscaling by Regional Climate Models (RCMs) under a ‘sparse matrix’ framework using the CORDEX guidelines for Shared Socio-economic Pathways that feature low emissions (SSP1-2.6) and high emissions (SSP3-7.0). The subset excludes poor performing models, with performance assessed by the climatology over a large Indo-Pacific domain and an Australian-specific domain, the simulation of atmospheric circulation and teleconnections to major drivers, then incorporating other evaluation from the literature. The models are selected to be relatively independent by simply choosing one model from each ‘family’ where possible. The projected change in temperature and rainfall in climatic regions of Australia in the selected models are broadly representative of that from the whole CMIP6 ensemble, after deliberately treating models with very high climate sensitivity separately. A limited but carefully constructed ensemble will not represent statistically balanced estimates but can be used effectively under a ‘storylines’ style approach and can maximise representativeness within limits. The resulting ensemble can be used as a key data source for the future climate component of climate services in Australia. The ensemble will be used in conjunction with CMIP6 and large ensembles of GCM simulations as important context, and targeted ‘convective permitting resolution’ modelling, deep learning models and emulators for added insights to inform climate change planning in Australia

Catalytic Enantioselective Cyclization and C3-Fluorination of Polyenes

(xylyl-phanephos)Pt(2+) in combination with XeF(2) mediates the consecutive diastereoselective cation-olefin cyclization/fluorination of polyene substrates. Isolated yields were typically in the 60s while enantioselectivies reached as high as 87%. The data are consistent with a stereoretentive fluorination of a P(2)Pt-alkyl cation intermediate