The Role of Circulation and Land Surface Conditions in Current and Future Australian Heat Waves

AbstractUnderstanding the physical drivers of heat waves is essential for improving short-term forecasts of individual events and long-term projections of heat waves under climate change. This study provides the first analysis of the influence of the large-scale circulation on Australian heat waves, conditional on the land surface conditions. Circulation types, sourced from reanalysis, are used to characterize the different large-scale circulation patterns that drive heat wave events across Australia. The importance of horizontal temperature advection is illustrated in these circulation patterns, and the pattern occurrence frequency is shown to reorganize through different modes of climate variability. It is further shown that the relative likelihood of a particular synoptic situation being associated with a heat wave is strongly modulated by the localized partitioning of available energy between surface sensible and latent heat fluxes (as measured through evaporative fraction) in many regions in reanalys...

[1]  S. Perkins‐Kirkpatrick,et al.  Understanding the spatio‐temporal influence of climate variability on Australian heatwaves , 2017 .

[2]  Acacia S. Pepler,et al.  On the use of self‐organizing maps for studying climate extremes , 2017 .

[3]  E. Fischer,et al.  Comparing Australian heat waves in the CMIP5 models through cluster analysis , 2017 .

[4]  Byron A. Steinman,et al.  Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events , 2017, Scientific Reports.

[5]  Jianping Huang,et al.  Uncertainties of soil moisture in historical simulations and future projections , 2017 .

[6]  R. Koster,et al.  Land Surface Precipitation in MERRA-2 , 2017 .

[7]  D. S. Wilks,et al.  “The Stippling Shows Statistically Significant Grid Points”: How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It , 2016 .

[8]  O. Martius,et al.  Regional‐scale jet waviness modulates the occurrence of midlatitude weather extremes , 2016 .

[9]  S. Seneviratne,et al.  Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics , 2016 .

[10]  R. Horton,et al.  A Review of Recent Advances in Research on Extreme Heat Events , 2016, Current Climate Change Reports.

[11]  O. Martius,et al.  A global quantification of compound precipitation and wind extremes , 2016 .

[12]  L. Alexander,et al.  The influence of soil moisture deficits on Australian heatwaves , 2016 .

[13]  A. Phatak,et al.  Natural hazards in Australia: heatwaves , 2016, Climatic Change.

[14]  C. Deser,et al.  Forced and Internal Components of Winter Air Temperature Trends over North America during the past 50 Years: Mechanisms and Implications* , 2016 .

[15]  G. Meehl,et al.  Projected intensification of subseasonal temperature variability and heat waves in the Great Plains , 2016 .

[16]  S. Seneviratne,et al.  Influence of land‐atmosphere feedbacks on temperature and precipitation extremes in the GLACE‐CMIP5 ensemble , 2016 .

[17]  S. Seneviratne,et al.  Allowable CO2 emissions based on regional and impact-related climate targets , 2016, Nature.

[18]  A. Pitman,et al.  Evaluating synoptic systems in the CMIP5 climate models over the Australian region , 2016, Climate Dynamics.

[19]  M. Burke,et al.  Global non-linear effect of temperature on economic production , 2015, Nature.

[20]  A. Pitman,et al.  Influence of antecedent soil moisture conditions on the synoptic meteorology of the Black Saturday bushfire event in southeast Australia , 2015 .

[21]  O. Martius,et al.  Flood triggering in Switzerland: the role of daily to monthly preceding precipitation , 2015 .

[22]  C. White,et al.  Relationships between climate variability, soil moisture, and Australian heatwaves , 2015 .

[23]  Bala Rajaratnam,et al.  Contribution of changes in atmospheric circulation patterns to extreme temperature trends , 2015, Nature.

[24]  J. Nairn,et al.  The Excess Heat Factor: A Metric for Heatwave Intensity and Its Use in Classifying Heatwave Severity , 2014, International journal of environmental research and public health.

[25]  Gail M. Williams,et al.  Global Variation in the Effects of Ambient Temperature on Mortality: A Systematic Evaluation , 2014, Epidemiology.

[26]  N. Nicholls,et al.  Modes of climate variability and heat waves in Victoria, southeastern Australia , 2014 .

[27]  P. Uotila,et al.  Atmospheric and Oceanic Conditions Associated with Southern Australian Heat Waves: A CMIP5 Analysis , 2014 .

[28]  T. Shepherd Atmospheric circulation as a source of uncertainty in climate change projections , 2014 .

[29]  Dominic A. Hudson,et al.  Intra-seasonal drivers of extreme heat over Australia in observations and POAMA-2 , 2014, Climate Dynamics.

[30]  A. Pezza,et al.  More Frequent, Longer, and Hotter Heat Waves for Australia in the Twenty-First Century , 2014 .

[31]  Diego G. Miralles,et al.  Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation , 2014 .

[32]  G. Berry,et al.  The influence of tropical cyclones on heat waves in Southeastern Australia , 2013 .

[33]  E. Fischer,et al.  Robust spatially aggregated projections of climate extremes , 2013 .

[34]  Lisa V. Alexander,et al.  On the Measurement of Heat Waves , 2013 .

[35]  S. Hardiman,et al.  Multi‐model analysis of Northern Hemisphere winter blocking: Model biases and the role of resolution , 2013 .

[36]  A. Lorrey,et al.  Influence of large‐scale climate modes on daily synoptic weather types over New Zealand , 2013 .

[37]  D. Ginsbourger,et al.  Changes in the odds of extreme events in the Atlantic basin depending on the position of the extratropical jet , 2012 .

[38]  Pascal Yiou,et al.  Asymmetric European summer heat predictability from wet and dry southern winters and springs , 2012 .

[39]  J. Wallace,et al.  Simulated versus observed patterns of warming over the extratropical Northern Hemisphere continents during the cold season , 2012, Proceedings of the National Academy of Sciences.

[40]  L. Alexander,et al.  The shifting probability distribution of global daytime and night‐time temperatures , 2012 .

[41]  M. Casado,et al.  Use of circulation types classifications to evaluate AR4 climate models over the Euro-Atlantic region , 2012, Climate Dynamics.

[42]  Heini Wernli,et al.  Quantifying the relevance of atmospheric blocking for co‐located temperature extremes in the Northern Hemisphere on (sub‐)daily time scales , 2012 .

[43]  N. Nicholls,et al.  Impact of drought on temperature extremes in Melbourne, Australia , 2011 .

[44]  Adam A. Scaife,et al.  Atmospheric Blocking and Mean Biases in Climate Models , 2010 .

[45]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[46]  John J. Chen Communicating complex information: the interpretation of statistical interaction in multiple logistic regression analysis. , 2003, American journal of public health.

[47]  B. Hewitson,et al.  Self-organizing maps: applications to synoptic climatology , 2002 .

[48]  A. Wald Tests of statistical hypotheses concerning several parameters when the number of observations is large , 1943 .

[49]  W. Cai,et al.  Severe heat waves in Southern Australia: synoptic climatology and large scale connections , 2011, Climate Dynamics.