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Beach modelling I: Beach Beach modelling I: Beach erosion occurrence and erosion occurrence and causes causes Adonis F. Velegrakis Adonis F. Velegrakis Dept Marine Sciences Dept Marine Sciences University of the Aegean University of the Aegean

Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

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Page 1: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Beach modelling I: Beach Beach modelling I: Beach erosion occurrence and causes erosion occurrence and causes

Adonis F. VelegrakisAdonis F. VelegrakisDept Marine SciencesDept Marine Sciences

University of the AegeanUniversity of the Aegean

Page 2: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

SynopsisSynopsis

1 Significance of beaches to other ecosystems and economic activity

2 Coastal erosion

3 Causes of beach erosion

4 Climate change: a short review 4.1 Trends4.2 The mechanism 4.3 The future 4.4 What scenario

5. Erosion costs and adaptation

Page 3: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

1 Significance of beaches to other ecosystems and economic activity

Beaches, i.e. the low lying coasts built on unconsolidated sediments, are valuable ecosystems by themselves; they also, front/protect various other important back-barrier environments/ecosystems

Beaches protect very important coastal economic assets/infrastructure and activities from marine inundation

Beaches are very important assets by themselves, being the focus of the very large and lucrative ‘sun and beach’ tourist industry; islands, in particular, depend on their beaches for most of their income.

Beaches are considered as particularly vulnerable to climate change, likely to bear the brunt of the adverse impacts of climate change, particularly through coastal retreat/erosion

Page 4: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

2 Beach erosion

Coastal (beach) erosion, i.e. the retreat of the coastline (which may or may not be accompanied by reduction in the beach sediment volume), is a global phenomenon

It can be differentiated into:

• Long term erosion, i.e. non-reversible coastline retreat, occurring in long (in engineering terms) temporal scales and

• Short term erosion, i.e. reversible on non-reversible retreat, occurring in short (in engineering terms) temporal scales

Both can be devastating

Page 5: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

3. Causes of beach erosion

Major causes of beach erosion include:

• Climatic changes (e.g. sea level rise (ASLR), changes (reduction) in precipitation and, thus, in river sediment discharges, changes in the frequency/intensity and destructiveness of storms/storm surges

• Reduction in coastal sediment supply-negative sediment budgets due to e.g. river management schemes, destruction of coastal seagrass prairies that provide marine biogenic sediments to beaches and badly designed coastal works

• Isostatic and tectonic movements

• Natural or human –induced subsidence of coastal deltaic/estuarine sediments on which most of the large coastal cities are built (Erikson et al., 2005)

Page 6: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Climate change impacts on beaches

One the most potent drivers of beach erosion are the climatic changes, i.e.

• the sea level rise • changes (reduction) in precipitation and, thus, in river sediment

discharges• changes in the frequency/intensity/destructiveness of storms/storm

surges• increases in coastal water temperatures that may negatively affect

natural beach defences e.g. coral reefs and seagrasses

Note: Beach response to climatic changes is a non-linear process; it (mainly) depends on the magnitude/rate of sea level rise, beach slope and morphology, the impinging (and generated-infragravity) wave energy and the intensity, duration and frequency of storm surges and the nature of coastal sediments

Our knowledge on these processes is still incomplete and, thus, predictions are characterised by a large uncertainty

Page 7: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

4. Climate change: a short review

Page 8: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

4.1 Trends

Climate Change (CC): defined as the change of climatic conditions relative to a reference period, i.e.:

• Period with first accurate records (1850s-1860s) or • Average climate of periods with accurate climatic information and associated

with infrastructure used today (e.g. 1961-1990 1980-1999)

• Temperature, sea level and precipitation trends • Polar Ice loss • Extreme climate events

• There are also feedbacks/tipping points. Trends can be changed by reinforcing (or negative) feedbacks and if thresholds are crossed changes will not be linear and potentially reversible, but abrupt, large and (potentially) irreversible in human temporal scales (Lenton et al., 2009).

Page 9: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

4.2 Mechanism: what are the processes involved?

• Climate is controlled by solar heat inflows/outflows

• A major cause of the observed increase in the planet’s heat content is the increasing atmospheric concentrations of greenhouse gases (GHGs) that absorb heat reflected back from the Earth’s surface

• Variability is both natural and human- induced

Page 10: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

4.3 The Future

Predictions of future changes are characterised by uncertainty and, thus, there is a large range of predictions,

Predictions depend on: • Simulations based on complex coupled atmospheric-oceanographic models

• Different scenarios regarding drivers which, in turn, are controlled by different scenarios of anthropogenic factors/socio-economic behaviour

• The predicted changes are region-dependent

• It must be stressed that there is a lot to learn on both the ‘slow’ processes and the feedback mechanisms and the abrupt (‘catastrophic’) changes

• It must be noted that (IPCC) predictions are conservative, due to (a) politics and (b) scientists’ attitude.

Page 11: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

4.4 What scenario?4.4 What scenario?

• Impacts are scenario-dependent and, thus, GHG emission-dependent

• These scenarios do not include ‘run-away’ climatic changes due to feedbacks/tipping points (e.g. permafrost melting, conveyor belt grinding halts and the melting of the Greenland and Antarctic ice sheets).

• Major scenarios appear to be optimistic if current attitudes are taken into account (e.g. the commissioning of new coal plants)

• If the BAU scenario will be the case, in 2050, global annual GDP is predicted (Stern Review 2006) to be significantly (negatively) affected (̴ 5 %) annually.

.

Page 12: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

5. Erosion costs and adaptation

Few integrated, comprehensive studies on the ecological and socio-economic impacts of climate-change driven beach erosion

The best studies undertaken in the US, UK and the Netherlands

These studies highlight the huge socioeconomic and environmental costs of the ‘do nothing’ attitude and the large costs of the inevitable adaptation For example, it is predicted that in 2050 (at least) 124 million people and assets of 28 trillion US $ will be at risk of coastal inundation at the 136 coastal megacities

The evidence suggests that we have no other choice but to get prepared for a huge adaptation effort that will be based on sound science and engineering.

Page 13: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Thank you for your patienceand see you after coffee!

Page 14: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 1. If beaches (and/or coastal defences) are breached, then large tracts of back-barrier ecosystems (e.g. wetlands and saltmarshes) are under a deadly threat

The Netherlands disaster case (Mollema, 2009).

Page 15: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Coastal housing destruction, following short-term (catastrophic) beach erosion

Fig. 2 S. Carolina (US) beach (c) before and (d) after a storm event in September 1996 (USGS, 1996)

Page 16: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 3 The main railway line to Sochi in Black Sea will be in jeopardy, if the fronting beach would be eroded – which, will be (red line) under 1 m storm surge and offshore waves with height (H) = 4 m and period (T) = 7.9 sec.

Sochi, S. RussiaSochi, S. Russia

Coastal transport infrastructure

Page 17: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Storm surge 1 mStorm surge 1 m

Leont’ yev Model Leont’ yev Model

Present normal conditions

Page 18: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig.4 (a) Flood risk at US Gulf

coast under sea level rise of 0-

6-1.2 m (MSL+ storm surge);

such rise could inundate > 2400

miles of roads, > 70% of the

existing port facilities, 9% of the

rail lines and 3 airports.

(b) In the case of a ~5.4-7 m

rise (MSL+ storm surge), >

50% of interstate and arterial

roads, 98% of port facilities,

33% of railways and 22 airports

could be affected (CCSP,

2008).

US Gulf Coast inundation risk

Page 19: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 5. Super Paradise (Mykonos). A pocket beach with very large economic potential. Economic value of Greek beaches min €1400/m/yr. This beach, €60000/m/yr.

Page 20: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Erosion Causes Reference

Long-term Short-term

% rate % rate

St.Lawrence,Canada

up to 1.5m/y

Storm waves/surgesForbes et al,

2004

S. Carolina (US) 70% 1.4 m/yr 59% 1.8 m/y Storm waves and surges, SLRMorton & Miller,

2005

Louisiana 91%8.2±4.4

m/yr88% 12.0 m/y

Subsidence,storm waves and surges, SLR, sediment supply reduction, coastal

works

Morton et al, 2004

Texas (US) 64%1.8±1.3

m/yr48% 2.6 m/y

Subsidence,storm waves and surges, SLR, sediment supply reduction, coastal

works

Morton et al, 2004

C. California (US)

53%0.3±0.1

m/yr79%

0.8±0.4 m/y

El Niño, storm waves and surges, SLR, sediment supply reduction, coastal works

Hapke et al, 2006

E. China 44%420 m/y (delta)

Subsidence, storms, SLR, sediment supply reduction, coastal works, sand

abstraction Cai et al, 2009

Provence, France

40%0.1±0.03

m/yr60% of erosion due to SLR

Brunel and Sabatier, 2009

Cies Ιslands (Spain)

0.44 m/yr

1.7 - 3.2 m/y

ΝΑΟ Storm waves and surges, SLR, sand abstraction

Costas & Alejo, 2007

E. UK 67% Storm waves and surges, SLR, Taylor et al.,

2004

Romania,Black Sea

> 50% 5- 25 m/yr

Storm waves and surges, SLR, sediment supply reduction, coastal works

Stanica & Panin, 2009

Nigeria 3 m/yStorm waves and surges, SLR sediment

supply reductionOkude &

Ademiluyi, 2006

Negril (Jamaica) >

80%Up to 1.4

m/yrStorm waves and surges, SLR, sediment

supply and seagrass reduction, RiVAMP, 2010

Examples of beach erosion

Page 21: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Country Coastline

(km)

Coastline erosion 2001

(km)

Protected coastline 2001

(km)

Eroded protected coastline

(km)

Total eroded coastline

(km)

Belgium 98 25 46 18 53

Cyprus 66 25 0 0 25

Denmark 4605 607 201 92 716

Estonia 2548 51 9 0 60

Finland 14018 5 7 0 12

France 8245 2055 1360 612 2803

Germany 3524 452 772 147 1077

Greece 15780 3945 579 156 4368

Italy 7468 1704 1083 438 2349

Malta 173 7 0 0 7

Poland 634 349 138 134 353

Portugal 1187 338 72 61 349

Spain 6584 757 214 147 824

Sweden 13567 327 85 80 332

UK 17381 3009 2373 677 4705

Total 100925 15111 7546 2925 19732

Coastal erosion in Europe

Source: Eurosion, 2004

Page 22: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

0 10 20 30 40 50 60 70 80 90 100

ProjectConcept

Construction Potential length of service

Engineering Design

AdoptedLong-term Plan

Years

Development Development Planning ProcessPlanning Process

Climate Impacts

Coastal development planning/engineering time scales must take into consideration future climate

Adapted from Savonis (2011)

Page 23: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Long-term beach erosion

Fig. 7 Beach erosion since the 1945 in Morris Island, S. Carolina, US (SEPM, 1996)

Page 24: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Germanbunkers built in

1942 on the foredune

GIRONDE

Estuary

ROYAN

LACANAU-OCEAN

CARCANS-PLAGE

HOURTIN-PLAGE

Sémaphore

LE GRAND CROHOT

LE PORGE-OCEAN

Pointe de GraveSt Nicolas

Les HuttesLes Arros

SOULACL’AMELIEPointe de la Négade

LE GURP

MONTALIVET

PK 0

PK 20

PK 40

PK 60

CAP-FERRET

ARCACHONPK 100

PK 80

Pointe de la Négade

- 40-30-20-10010

Retreat

(m/year)

Advance

(m/year)

20

40

60

80

100

km

L’AMELIE

3

Source J-P. Tastet

Page 25: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 9 Nearshore bed cover and shoreline changes along Negril’s beaches (at the location of the 74 used beach profiles (RiVAMP, 2010)

Page 26: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig.10 Long-term and short-term (catastrophic beach erosion, Eressos beach E. Mediterranean

Page 27: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 11 Trends in total annual stream flow into Perth dams 1911–2008. (Steffen, 2009)

Page 28: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 12 Coastal sediment supply in the Med has been reduced from 1012 x 106 σε 355 x106 tons/yr during the second half of the 20th century due to the presence of about 3500 dams, 84% of which have been constructed during this period (Poulos et al., 2002).

Page 29: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 13 (a) The dam and the Eressos drainage basin/beach, (c) monthly time series (2004) of (potential) sediment load (in tons) of the Eresos basin (black) and the sub-basin of the dam (white), for steady and high intensity (simulated) rainfall for 2 soil cases (i) sand soil (K=0.03) and (ii) silt soil (K=0.52). The dam witholds 52-55% of the sediments produced in the drainage basin

Page 30: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 14 Eressos, Lesbos, E. Med 27-2-2004. The beach, the river and the dam, which

Page 31: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 15 Sea level rise at Pensacola (FL) 2.14 mm/yr, Grand Isle (LA)- 9.85 mm/yr, and Galveston (TX)- 6.5 mm/yr. These trends show the high rates of local subsidence in Louisiana and Texas relative to the more stable geology of Florida (Savonis et al., 2008)

Page 32: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 16 Schema showing the beach response to sea level rise. For a sea level increase α, sediments from the shoreface are eroded and transported to the submarine section of the beach, resulting to a coastal retreat s.

Page 33: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig.?? Global sea level changes 1860-2010 (Rahmstorf, 2011).

Projections for 2100: - 0.20 - 0.59 m (IPCC, 2007) - > 1 m if the melt of Ice sheets is included (Rahmstorf, 2007)above the mean sea level of 1980-1999

Fig. 17 Mean temperature rise 1880-2010. NASA Data (Rahmstorf, 2011).

Projections for 2100: - Increase 0.5 - 4.0 oC, depending on the scenario (IPCC, 2007)

Page 34: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig 18. Long term climate-induced increase in sea level (accelerated sea level rise-ASLR) is caused by the thermal expansion of the oceans and the melting of continental ice sheets (IPCC, 2007). The relationship, however is complex, particularly at a regional level

Page 35: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Figure 3.9

Fig. 19

(a)Linear trend of annual temperatures in °C per decade for 1979-2005. Areas in grey denote insufficient data. Data sets from Smith and Reynolds (2005). After IPCC (2007)

(b) Geographic distribution of 1993-2003 trends in mean sea level (mm yr–1) based on TOPEX/ Poseidon satellite altimetry (after Cazenave and Nerem, 2004)

Figure 5.15

Figure 5.15

Page 36: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Figure 3.14Fig. 20 Annual mean trends (% per century) for 1901-2005 (Grey areas- insufficient data). Time

series of annual precipitation (% of mean for 1961-1990) for the different Green bars (annual), black bars (decadal variations). After IPCC (2007).

Page 37: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 21 (a) The decrease of Arctic sea ice: minimum extent in September 1982 and September 2007 and projections for the future late summers (2010-2030, 2040-2060 and 2070-2090) (http://maps.grida.no/go/graphic/the-decrease-of-arctic-sea-ice-minimum-extent-in-1982-and-2007-and-climate-projections-norwegian). (b) Model results/observations of sea ice loss (Rahmstorf, 2011).

Page 38: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 22 Increases in the annual mean, winter averages, mean of the highest annual waves and annual maxima significant wave heights at the NDBC #46005 platform (NE Pacific). The annual maximum significant wave height has increased 2.4 m! in the last 25 years. (Ruggiero et al., 2010).

Current trends: More energetic extreme waves

Page 39: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 23 Predictions (estimates) showing an increase in the number of large storms (hurricanes) in the US coast (from M. Beniston, 2009).

Page 40: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 24 Observed and projected increase in hurricane intensity. If the increase is due to the relatively higher increase in the Atlantic SSTs relative to other oceans, then the intensity might relax to earlier levels as inter-ocean basin SSTs equilibrate. Conversely, if the intensity is related to absolute SSTs, then even more intense cyclones are expected (Steffen, 2009).

Page 41: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Heat = solar radiation - Heat = solar radiation - back radiationback radiation

Global temperature a result Global temperature a result of energy balanceof energy balance

Page 42: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 26 Atmospheric CO2 concentration (in parts per million) during the last 11000 years (Rahmstorf, 2011) and the last 50 years. The concentrations of the CH4 and N2O (in ppb-parts ber billion) since 1978 are also shown (Richardson et al., 2009).

Trends in GHG atmospheric concentration

Page 43: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Climate change: Natural causes

Fig. 27. Astronomical (Milankovich) cycles that force periodic increases and decreases of incoming heat to the Earth system (Zachos and Berger, 2004).

Page 44: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Climate change: Natural causes

Fig. 28. Relationship between temperature and CO2 concentration (from ice cores in the Antarctic, Petit et al., 1999) with the astronomical cycles

Page 45: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 29 Tempearture/CO2 concentration increase in the northern hemisphere in the last 1000 years. Note the large and accelerating increase since the industrial revolution (e.g. Mann and Jones, 2003; Zachos and Berger, 2004).

Climate change: Anthropogenic causes

Page 46: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 30

Diagnosis/prognosis from

climatic models (Hadley Centre

for Climate Prediction, UK)

which show the combined

natural/anthropogenic control

on temperature; only combined

forcing results in aggreemnt

between moels and

observations ((Mann and Jones,

2003).

Climate change: Natural and anthropogenic

Page 47: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Figure 11.22

Fig. 27 Temperature anomalies with respect to 1901-1950 for 6 oceanic regions for (a) 1906-2005 (black line) and as simulated by known forcings; and (b) as projected for 2001-2100 for the A1B scenario (orange envelope). The bars at the end of the orange envelope represent the range of projected changes for 2091-2100 for the B1 scenario (blue), the A1B scenario (orange) and the A2 scenario (red). Black line is dashed where observations are present for less than 50% of the area in the decade concerned.

Page 48: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

FAQ 5.1, Figure 1Fig. 28 Global mean sea level (relative to the 1980-1999 mean) in the past and future (grey

shading shows past uncertainty). The red line from tide gauges (red shading shows variation range). The green line shows global mean sea level observations from satellite altimetry. Blue shading represents the range of model projections for the 21st century, relative to the 1980-1999 mean. Emissions scenario?. More recent research (2008-2011) shows that we may have underestimated the trends by a factor of 2.5-3.

Page 49: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Table 1. IPCC 2007 socioeconomic scenarios (IPCC 2007)

Page 50: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 29 Scenario-dependent global warming (IPCC 2007)

Page 51: Beach modelling I: Beach erosion occurrence and causes Adonis F. Velegrakis Dept Marine Sciences University of the Aegean

Fig. 30 Stabilisation levels/probability ranges for temperature increases

Types of impacts as the world comes into equilibrium with greenhouse gases. •The top panel shows the range of temperatures projected at stabilisation levels 400ppm-750ppm CO2 at equilibrium.•The solid horizontal lines indicate the 5 - 95% range based on climate sensitivity tests from IPCC 2001 and a recent Hadley Centre ensemble study. •The vertical line indicates the mean of the 50th percentile point. •The dashed lines show the 5 - 95% range based on 11 recent studies. •The bottom panel illustrates the range of•impacts expected at different levels of warming. The relationship between global average temperature changes and regional climate changes is uncertain. (Stern Review, 2006).