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Clare Goodess
Climatic Research Unit, University of East Anglia, UK
Panel discussion: Enabling the transition to climate resilience – 19 June 2014, OECD, Paris
Global Framework for
Climate Services (GFCS)
Dynamical and
statistical downscaling
The impacts,
adaptation and
vulnerability
(IAV) community
Approaches to climate adaptation,
Dessai and Hulme, 2004
Source: Dessai and Hulme
(2007) and Ranger et al. (2010)
So – need to reframe some of the questions:
 What are the current priorities for successfully translating
adaptation planning into implementation?
 How well-suited are current policy approaches to addressing
the longer-term consequences of climate change?
 How to better engage the private sector in managing the
risks and maximising the opportunities of the adaptation?
How can professional bodies, trade associations and others
be used to assist this process?
Climate science can provide evidence and tools
• But easier to make the case for adaptation
• Than to input effectively into implementation of adaptation
Projected ‘All Europe’ changes in temperature and precipitation
extremes, including dryness. For 2071-2100 (wrt 1961-1990) or
2080-2100 (wrt 1980-2000) - GCMs/RCMs and A2/A1B emissions.
Tmax (warm days WD
& cold days CD) and
Tmin (warm nights
WN & cold nights CN)
Heat waves/warm
spells
Heavy precipitation
(HPD>95thP, %DP10, HPC,
RV20HP)
Dryness
High confidence
WD/WN very likely to
increase and CD/CN
very likely to decrease.
Largest WD increases
in summer & in C & S
Europe, smallest in N
Europe.
High confidence:
likely more frequent,
longer, &/or more
intense heat waves &
warm spells but little
change over
Scandinavia.
Low confidence to high
confidence depending on
region: likely overall increases
& decreases in return periods:
strong signals in N Europe
particularly in winter, but lower
confidence in C Europe & in
particular, Mediterranean.
Medium confidence:
European area affected
by stronger dryness
with largest and most
consistent changes in
Mediterranean.
See IPCC SREX Table 3.3 for all 3 European regions and full details.
Very likely = 90-100% probability. Likely = 66-100% probability.
A look at observed and modelled time series of
warm spell duration for 1950-2050 – produced
for stakeholders in the North Adriatic
• Black is the average of the five RCMS
• Grey is the individual models
• Red is gridded 25 km observations – which
are more directly comparable with RCMs
than single station series
• Moss green is observations for Bologna
• Bright green is the VenFVG 12-station series
• RCMs reproduce WSDI fairly well in the first few decades – but underestimate the
increased frequency of longer-lasting events over the most recent decade
• All RCMs show a continuing increase. For 2021-2050 minus 1971-2000, the ensemble mean
change is +10 days (model range is + 3 days to + 17 days)
• 2003 is a very extreme year in the observations and is not captured by the models,
although they do simulate some very large events towards the middle of this century
IPCC AR5
WGII
SPM1
SPM3

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Goodess clare univ east anglia

  • 1. Clare Goodess Climatic Research Unit, University of East Anglia, UK Panel discussion: Enabling the transition to climate resilience – 19 June 2014, OECD, Paris
  • 2. Global Framework for Climate Services (GFCS) Dynamical and statistical downscaling The impacts, adaptation and vulnerability (IAV) community
  • 3. Approaches to climate adaptation, Dessai and Hulme, 2004 Source: Dessai and Hulme (2007) and Ranger et al. (2010)
  • 4. So – need to reframe some of the questions:  What are the current priorities for successfully translating adaptation planning into implementation?  How well-suited are current policy approaches to addressing the longer-term consequences of climate change?  How to better engage the private sector in managing the risks and maximising the opportunities of the adaptation? How can professional bodies, trade associations and others be used to assist this process? Climate science can provide evidence and tools • But easier to make the case for adaptation • Than to input effectively into implementation of adaptation
  • 5. Projected ‘All Europe’ changes in temperature and precipitation extremes, including dryness. For 2071-2100 (wrt 1961-1990) or 2080-2100 (wrt 1980-2000) - GCMs/RCMs and A2/A1B emissions. Tmax (warm days WD & cold days CD) and Tmin (warm nights WN & cold nights CN) Heat waves/warm spells Heavy precipitation (HPD>95thP, %DP10, HPC, RV20HP) Dryness High confidence WD/WN very likely to increase and CD/CN very likely to decrease. Largest WD increases in summer & in C & S Europe, smallest in N Europe. High confidence: likely more frequent, longer, &/or more intense heat waves & warm spells but little change over Scandinavia. Low confidence to high confidence depending on region: likely overall increases & decreases in return periods: strong signals in N Europe particularly in winter, but lower confidence in C Europe & in particular, Mediterranean. Medium confidence: European area affected by stronger dryness with largest and most consistent changes in Mediterranean. See IPCC SREX Table 3.3 for all 3 European regions and full details. Very likely = 90-100% probability. Likely = 66-100% probability.
  • 6. A look at observed and modelled time series of warm spell duration for 1950-2050 – produced for stakeholders in the North Adriatic • Black is the average of the five RCMS • Grey is the individual models • Red is gridded 25 km observations – which are more directly comparable with RCMs than single station series • Moss green is observations for Bologna • Bright green is the VenFVG 12-station series • RCMs reproduce WSDI fairly well in the first few decades – but underestimate the increased frequency of longer-lasting events over the most recent decade • All RCMs show a continuing increase. For 2021-2050 minus 1971-2000, the ensemble mean change is +10 days (model range is + 3 days to + 17 days) • 2003 is a very extreme year in the observations and is not captured by the models, although they do simulate some very large events towards the middle of this century