Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought

An important and under-quantified facet of the risks associated with human-induced climate change emerges through extreme weather. In this paper, we present an initial attempt to quantify recent costs related to extreme weather due to human interference in the climate system, focusing on economic costs arising from droughts and floods in New Zealand during the decade 2007–2017. We calculate these using previously collected information about the damages and losses associated with past floods and droughts, and estimates of the “fraction of attributable risk” that characterizes each event. The estimates we obtain are not comprehensive, and almost certainly represent an underestimate of the full economic costs of climate change, notably chronic costs associated with long-term trends. However, the paper shows the potential for developing a new stream of information that is relevant to a range of stakeholders and research communities, especially those with an interest in the aggregation of the costs of climate change or the identification of specific costs associated with potential liability.

[1]  Myles R. Allen,et al.  Reconciling two approaches to attribution of the 2010 Russian heat wave , 2012 .

[2]  Myles Allen,et al.  Liability for climate change , 2003, Nature.

[3]  Ilan Noy,et al.  The Long-Term Consequences of Disasters: What Do We Know, and What We Still Don't , 2018, International Review of Environmental and Resource Economics.

[4]  A. Islam,et al.  Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives , 2019, Hydrology and Earth System Sciences.

[5]  C. Brooks.  Climatic Change , 1913, Nature.

[6]  R. Lamb,et al.  Flood event attribution and damage estimation using national‐scale grid‐based modelling: Winter 2013/2014 in Great Britain , 2018, International Journal of Climatology.

[7]  R. Vautard,et al.  Attribution of Extreme Weather Events in the Context of Climate Change , 2016 .

[8]  Ilan Noy.  Tropical storms: The socio-economics of cyclones , 2016 .

[9]  William D. Nordhaus,et al.  Rolling the ‘DICE’: an optimal transition path for controlling greenhouse gases , 1993 .

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

[11]  G. Hegerl,et al.  Detection and attribution of climate change: from global to regional , 2013 .

[12]  E. Fischer,et al.  Understanding the regional pattern of projected future changes in extreme precipitation , 2017 .

[13]  D. Wallom,et al.  The weather@home regional climate modelling project for Australia and New Zealand , 2016 .

[14]  V. Pope,et al.  The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3 , 2000 .

[15]  Daniel M. Mitchell,et al.  Attributing human mortality during extreme heat waves to anthropogenic climate change , 2015 .

[16]  Bo Christiansen,et al.  The Role of the Selection Problem and Non-Gaussianity in Attribution of Single Events to Climate Change , 2015 .

[17]  Marjolijn Haasnoot,et al.  Dynamic Adaptive Policy Pathways (DAPP): From Theory to Practice , 2019, Decision Making under Deep Uncertainty.

[18]  Alison L. Kay,et al.  Attribution of Autumn/Winter 2000 flood risk in England to anthropogenic climate change: A catchment-based study , 2011 .

[19]  Vincent Marchau,et al.  Decision Making under Deep Uncertainty: From Theory to Practice , 2019 .

[20]  Mark D. Risser,et al.  Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events , 2017, Journal of the American Statistical Association.

[21]  Arthur A. Mirin,et al.  Detection and Attribution of Streamflow Timing Changes to Climate Change in the Western United States , 2009 .

[22]  J. Gardiner.  Ministry of Agriculture and Fisheries , 1924, Nature.

[23]  C. Mcdonald,et al.  Drying out: Investigating the economic effects of drought in New Zealand , 2013 .

[24]  M. Hulme.  Attributing weather extremes to ‘climate change’ , 2014 .

[25]  Bashir Ahmad,et al.  The need for bottom-up assessments of climate risks and adaptation in climate-sensitive regions , 2019, Nature Climate Change.

[26]  C. Donlon,et al.  The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system , 2012 .

[27]  David J. Frame,et al.  Investigating event‐specific drought attribution using self‐organizing maps , 2016 .

[28]  Michael F. Wehner,et al.  Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence , 2017, Climate Dynamics.

[29]  R. Pindyck.  Climate Change Policy: What Do the Models Tell Us? , 2013 .

[30]  John F. B. Mitchell,et al.  Workbook on generating high resolution climate change scenarios using PRECIS , 2003 .

[31]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[32]  W. Nordhaus,et al.  Roll the DICE Again: Economic Models of Global Warming , 1999 .

[33]  M. Mcphaden,et al.  Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization , 2017 .

[34]  Richard G. Jones,et al.  Human influence on climate in the 2014 southern England winter floods and their impacts , 2016 .

[35]  Rachel James,et al.  Stakeholder perceptions of event attribution in the loss and damage debate , 2017 .

[36]  Martin Weitzman,et al.  GHG Targets as Insurance Against Catastrophic Climate Damages , 2010 .

[37]  Investigating differences between event-as-class and probability density-based attribution statements with emerging climate change , 2017, Climatic Change.

[38]  Ying Sun,et al.  Attribution of extreme weather and climate‐related events , 2015, Wiley interdisciplinary reviews. Climate change.

[39]  A. Challinor,et al.  Transmission of climate risks across sectors and borders , 2018, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[40]  M. Wehner,et al.  The economic costs of Hurricane Harvey attributable to climate change , 2020, Climatic Change.

[41]  Michael F. Wehner,et al.  Attribution of floods in the Okavango basin, Southern Africa , 2014 .

[42]  T. Berntsen,et al.  Assigning historic responsibility for extreme weather events , 2017 .

[43]  Simon Wilson,et al.  weather@home—development and validation of a very large ensemble modelling system for probabilistic event attribution , 2015 .

[44]  Chris Hope,et al.  The marginal impact of CO2 from PAGE2002: An integrated assessment model incorporating the IPCC's five reasons for concern , 2006 .

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

[46]  P. Stott,et al.  Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000 , 2011, Nature.