NREN Climate Change Preparedness – Adapting under uncertainty

Dr. Conor MurphyIrish Climate Analysis and Research Units (ICARUS),

Dept. Of Geography, NUI Maynooth

NUI MAYNOOTHOllscoil na Éireann Má Nuad

Observations of Global Temperature

Loading the Dice

Source: Hansen et al 2012 PNAS

Ireland Winter 2013-14

Figure 1|Domains Analysed and NCEP1 Cyclone Metrics.

a, Domains analysed: I-UK (Ireland and UK), HLNA (High-Latitude North Atlantic) and the MLNA (Mid-Latitude North Atlantic). NA domain comprises both HLNA and MLNA.

b, Winter (December - February) cyclonicity metrics for the same regions derived from NCEP1 with associated rank for W2013/14.

Units for cyclone counts are ‘cyclone days’, defined as the number of cyclones detected in 6-hourly sea-level pressure fields, divided by four. Mean cyclone intensity is given as the local Laplacian of sea level pressure; ‘storminess’ is the summed intensities, in the same units.

Source: Matthews, T, Murphy, C. Wilby, R.L., Harrigan, S. Submitted Nature Climate Change April 2014

Supplementary Figure 1| Storm track position and trends in extreme wind speeds. a, Mean DJF (1948/49 to 2013/2014) storm-track position shown by the standard deviation of the 500-hPa geopotential height (m) calculated from 6-hourly NCEP1 data and bandpass filtered on time scales of 2–8 days. b, trends in DJF 95th percentiles of NCEP1 10-metre wind speeds, given as the slope of a least-squares linear regression of wind speed (‘y’) on year (‘x’) over the same period

Source: Matthews, T, Murphy, C. Wilby, R.L., Harrigan, S. Submitted Nature Climate Change April 2014

Figure 2|Extended Cyclone Metrics from 20CR. a, I-UK storminess for the 141-year RA-20CR (blue) and 66-year NCEP1 (red) series. The shaded region is the 95% prediction bound of the transfer function used to bridge 20CR to NCEP1 (see supplementary information). The red horizontal line shows the unprecedented nature of NCEP1 storminess for W2013/14. b, Correlation between CRUTS3.21 precipitation and cyclone metrics derived from RA-20CR.

Source: Matthews, T, Murphy, C. Wilby, R.L., Harrigan, S. Submitted Nature Climate Change April 2014

Atmospheric Rivers

• Atmospheric Rivers (ARs) are the key synoptic features which deliver the majority of pole-ward water vapour transport.

• Associated with episodes of heavy and prolonged rainfall.

• ARs are responsible for many of the largest winter floods in the mid-latitudes resulting in major socioeconomic losses;

Source Lavers et al 2013 Environmental Research Letters

Multi-sector Mega Floods

ARs More Common in Future!

• North Atlantic ARs are projected to become stronger and more numerous in the future scenarios of multiple simulations from global climate models

• Greater risk of higher rainfall totals and therefore larger winter floods with increased AR frequency leading to more flood episodes.

• In the high emissions scenario (RCP8.5) for 2074–2099 there is an approximate doubling of AR frequency in the five GCMs

Source: Lavers et al. (2013) Environmental Research Letters

Conventional Scenario Led Adaptation

Figure 1 A ‘cascade of uncertainty’ in precipitation changes projected by the CMIP5 ensemble for the River Naryn basin, Central Asia (70-80°E, 40-45°N). The three levels of each pyramid illustrate uncertainty due to the choice of Representative Concentration Pathway (RCP), GCM and realisation of climate variability. Not all simulations have multiple realisations, resulting in a vertical line in the lowest layer. The intersection on the top row for each time period is the multi-scenario, multi-model, multi-realisation mean.

Mired in Uncertainty......

Source - New, M. et al., 2007. Challenges in using probabilistic climate change information for impact assessments: an example from the water sector. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1857), pp.2117–2131.

Scenario Neutral Adaptation Planning

Framework for Preparedness

• Broad review of sectoral and cross-sectoral climate related risks.

• Understand current vulnerabilities and exposures through stakeholder engagement.

• Assess ranges of change for key risks – don't need to rely on just climate models!

• Develop adaptation inventory with stakeholders• Assess robustness and performance of measures

Scenario Neutral Adaptation Planning

Decision Appraisal

Source: Wilby, R.L., Dawson, C., Murphy, C., O’Connor, P Decision-Centric Adaptation. Climate Research (In review)

Role of surprises and cascade failures

Source Scheffer 2009

Conclusions

• Framework for climate change preparedness:– Improved understanding of climate change risks

and uncertainties– Brings best available evidence together in a

coherent and consistent framework to describe the sensitivity, vulnerability and potential risks of climate change

– Practical methods that meet the needs of decision makers