Professor Myles Allen CBE FRS

Abstract:

Augmenting previous papers about the exceptional 2011-15 California drought, we offer new perspectives on the ‘snow drought’ that extended into Oregon in 2014 and Washington in 2015. Over 80% of measurement sites west of 115°W experienced record low snowpack in 2015, and we estimate a return period of 400-1000 years for California’s snowpack under the questionable assumption of stationarity. Hydrologic modeling supports the conclusion that 2015 was the most severe on record by a wide margin. Using a crowd-sourced superensemble of regional climate model simulations, we show that both human influence and sea surface temperature anomalies contributed strongly to the risk of snow drought in Oregon and Washington: the contribution of SST anomalies was about twice that of human influence. By contrast, SSTs and humans appear to have played a smaller role in creating California’s snow drought. In all three states, the anthropogenic effect on temperature exacerbated the snow drought.

Abstract:

A new climate modelling project has been developed for regional climate simulation and the attribution of weather and climate extremes over Australia and New Zealand. The project, known as weather@home Australia-New Zealand, uses public volunteers' home computers to run a moderate-resolution global atmospheric model with a nested regional model over the Australasian region. By harnessing the aggregated computing power of home computers, weather@home is able to generate an unprecedented number of simulations of possible weather under various climate scenarios. This combination of large ensemble sizes with high spatial resolution allows extreme events to be examined with well-constrained estimates of sampling uncertainty. This paper provides an overview of the weather@home Australia-New Zealand project, including initial evaluation of the regional model performance. The model is seen to be capable of resolving many climate features that are important for the Australian and New Zealand regions, including the influence of El Niño-Southern Oscillation on driving natural climate variability. To date, 75 model simulations of the historical climate have been successfully integrated over the period 1985-2014 in a time-slice manner. In addition, multi-thousand member ensembles have also been generated for the years 2013, 2014 and 2015 under climate scenarios with and without the effect of human influences. All data generated by the project are freely available to the broader research community.

Abstract:

Whenever an extreme weather or climate-related event occurs the extent to which human-induced climate change has played a role is routinely asked. Increasingly scientists are able to give robust quantitative answers to this question. Understanding how the overall risks of extreme events are changing in a warming world requires both a thermodynamic perspective and an understanding of changes in the atmospheric circulation.

Abstract:

Atmospheric modes of variability relevant for extreme temperature and precipitation events are evaluated in models currently being used for extreme event attribution. A 100 member initial condition ensemble of the global circulation model HadAM3P is compared with both the multi-model ensemble from the Coupled Model Inter-comparison Project, Phase 5 (CMIP5) and the CMIP5 atmosphere-only counterparts (AMIP5). The use of HadAM3P allows for huge ensembles to be computed relatively fast, thereby providing unique insights into the dynamics of extremes. The analysis focuses on mid Northern Latitudes (primarily Europe) during winter, and is compared with ERA-Interim reanalysis. The tri-modal Atlantic eddy-driven jet distribution is remarkably well captured in HadAM3P, but not so in the CMIP5 or AMIP5 multi-model mean, although individual models fare better. The well known underestimation of blocking in the Atlantic region is apparent in CMIP5 and AMIP5, and also, to a lesser extent, in HadAM3P. Pacific blocking features are well produced in all modeling initiatives. Blocking duration is biased towards models reproducing too many short-lived events in all three modelling systems. Associated storm tracks are too zonal over the Atlantic in the CMIP5 and AMIP5 ensembles, but better simulated in HadAM3P with the exception of being too weak over Western Europe. In all cases, the CMIP5 and AMIP5 performances were almost identical, suggesting that the biases in atmospheric modes considered here are not strongly coupled to SSTs, and perhaps other model characteristics such as resolution are more important. For event attribution studies, it is recommended that rather than taking statistics over the entire CMIP5 or AMIP5 available models, only models capable of producing the relevant dynamical phenomena be employed.