Must view guide on how to prepare a climate adaptation and preparedness strategy for Internet networks

1. NREN Climate Change Preparedness
– Adapting under uncertainty
Dr. Conor Murphy
Irish Climate Analysis and Research Units (ICARUS),
Dept. Of Geography, NUI Maynooth
NUI MAYNOOTH
Ollscoil na Éireann Má Nuad

2. Observations
of Global
Temperature

3. Loading the Dice
Source: Hansen et al 2012 PNAS

4. Ireland Winter 2013-14

5. 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

6. 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

7. 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

8. 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

9. Multi-sector Mega Floods

10. 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

11. Conventional Scenario Led
Adaptation

12. 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.

13. 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.

14. Scenario Neutral Adaptation Planning

16. 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

19. Scenario Neutral Adaptation Planning

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

21. Role of surprises and cascade failures
Source Scheffer 2009

22. 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