Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed Sea Surface Temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution

Natural hazards in Australia: heatwaves

As part of a special issue on natural hazards, this paper reviews the current state of scientific knowledge of Australian heatwaves. Over recent years, progress has been made in understanding both the causes of and changes to heatwaves. Relationships between atmospheric heatwaves and large-scale and synoptic variability have been identified, with increasing trends in heatwave intensity, frequency and duration projected to continue throughout the 21st century. However, more research is required to further our understanding of the dynamical interactions of atmospheric heatwaves, particularly with the land surface. Research into marine heatwaves is still in its infancy, with little known about driving mechanisms, and observed and future changes. In order to address these knowledge gaps, recommendations include: focusing on a comprehensive assessment of atmospheric heatwave dynamics; understanding links with droughts; working towards a unified measurement framework; and investigating observed and future trends in marine heatwaves. Such work requires comprehensive and long-term collaboration activities. However, benefits will extend to the international community, thus addressing global grand challenges surrounding these extreme events

Erratum: On the use of composite analyses to form physical hypotheses: An example from heat wave - SST associations.

Scientific Reports 6: Article number: 29599; published online: 14 July 2016; updated: 24 August 2016 This Article contains an error in the legend of Table 1. “Results are computed for the entire 3150 days in DJF (black values) and for the 25 HW days selected in DJF (bold italic) during 1979–2014,” should read:</jats:p

A new 'bio-comfort' perspective for Melbourne based on heat stress, air pollution and pollen

Humans are at risk from exposure to extremes in their environment, yet there is no consistent way to fully quantify and understand the risk when considering more than just meteorological variables. An outdoor 'bio-comfort' threshold is defined for Melbourne, Australia using a combination of heat stress, air particulate concentration and grass pollen count, where comfortable conditions imply an ideal range of temperature, humidity and wind speed, acceptable levels of air particulates and a low pollen count. This is a new approach to defining the comfort of human populations. While other works have looked into the separate impacts of different variables, this is the first time that a unified bio-comfort threshold is suggested. Composite maps of surface pressure are used to illustrate the genesis and evolution of the atmospheric structures conducive to an uncomfortable day. When there is an uncomfortable day due to heat stress conditions in Melbourne, there is a high pressure anomaly to the east bringing warm air from the northern interior of Australia. This anomaly is part of a slow moving blocking high originating over the Indian Ocean. Uncomfortable days due to high particulate levels have an approaching cold front. However, for air particulate cases during the cold season there are stable atmospheric conditions enhanced by a blocking high emanating from Australia and linking with the Antarctic continent. Finally, when grass pollen levels are high, there are northerly winds carrying the pollen from rural grass lands to Melbourne, due to a stationary trough of low pressure inland. Analysis into days with multiple types of stress revealed that the atmospheric signals associated with each type of discomfort are present regardless of whether the day is uncomfortable due to one or multiple variables. Therefore, these bio-comfort results are significant because they offer a degree of predictability for future uncomfortable days in Melbourne

On the use of composite analyses to form physical hypotheses: An example from heat wave - SST associations

This paper highlights some caveats in using composite analyses to form physical hypotheses on the associations between environmental variables. This is illustrated using a specific example, namely the apparent links between heat waves (HWs) and sea surface temperatures (SSTs). In this case study, a composite analysis is performed to show the large-scale and regional SST conditions observed during summer HWs in Perth, southwest Australia. Composite results initially point to the importance of the subtropical South Indian Ocean, where physically coherent SST dipole anomalies appear to form a necessary condition for HWs to develop across southwest Australia. However, sensitivity tests based on pattern correlation analyses indicate that the vast majority of days when the identified SST pattern appears are overwhelmingly not associated with observed HWs, which suggests that this is definitely not a sufficient condition for HW development. Very similar findings are obtained from the analyses of 15 coupled climate model simulations. The results presented here have pertinent implications and applications for other climate case studies, and highlight the importance of applying comprehensive statistical approaches before making physical inferences on apparent climate associations

Relationships between Antarctic cyclones and surface conditions as derived from high-resolution numerical weather prediction data

© 2012 American Geophysical Unio