The global economic implications

of the melting of the Greenland ice

sheet

Jimena Alvarez1, Dmitry Yumashev1, Gail Whiteman1, Chris Hope2, Peter Wadhams2 and Jeremy Wilkinson3

1Erasmus Universiteit Rotterdam 2University of Cambridge 3British Antarctic Survey

Image: Melting ice in Greenland's Disko Bay; Hakan Ludwigson for TIME (http://science.time.com/2010/09/09/climate-change-a-slowdown-on-polar-melt/)

Outline

• Background: Benefits and costs of Arctic change

• Integrated Assessment models

• A quick introduction to PAGE09

• The melting of the Greenland ice sheet (GIS)

• Assessing GIS change with PAGE09

Arctic change

• The Arctic has been

warming at unpreceden-

ted rates over the past

two decades (IPCC AR5)

• The rapid warming has

resulted in declining sea

ice, thawing permafrost

and acceleration of the

Greenland ice sheet

melting

Source: Hezel et al. (2014). Colours: model results; black line: historic data

Arctic change: benefits & costs

Figure 1 summarizes existing literature (Petoukhov et al 2013, Walsh 2014, Wadhams 2012; Maslowski et al 2012, Gautier

2009, Smith and Stephenson 2013, Emmerson and Lahn, 2012)

Indirect Global Impacts via Polar amplification Repercussions of the destabilising Arctic

climate system across the globe

Extreme weather events, sea level rise, changes to global precipitation patterns

Costs to various economic sectors: insurance, agriculture, energy

Increasing threats to the highly- populated regions

(such as Western Europe, North- East US, China and India)

Arctic physical change retreating sea ice, receding glaciers, thawing permafrost

Direct Regional impacts on Arctic climate, ecosystems and local

communities

Economic opportunities in the region oil and gas extraction, mining, commercial

shipping, tourism and agriculture

Substantial investments new infrastructure in the Arctic

Potential to generate multi-billion dollar annual revenues regionally

over the coming years and decades

Integrated Assessment Models (IAM)

Source: Parson and Fisher-Vanden, 1997

Integrated Assessment Models (IAM)

• “IAMs are not predictive models; they cannot provide "the answer" about how to respond to the climate change problem” but “can provide a framework for understanding the climate change problem and for informing judgments about the relative value of different options for dealing with climate change.” (CIESIN, 1995)

• Main classification:

• Policy optimisation models

• Policy evaluation (simulation) models

• Different IAMs serve different purposes:

• DICE, FUND, PAGE

• IMAGE, MiniCAM, AIM, MESSAGE

• MERGE, MAGICC, etc.

PAGE09- Integrated Assessment Model

• Excel 2010 workbook with @RISK6 add-in

• Explicit treatment of CO2, CH4, N2O, sulphates

• 8 regions

o Including EU, US, China

• 10 analysis years

o up to 2200

• 4 impact sectors

o Sea level, economic, non-economic, discontinuity

• 112 uncertain inputs

• 100000 runs to calculate distributions of outputs

The social cost of CO2, BAU scenario

Source: 100000 PAGE09 runs, A1B scenario, 2010

From PAGE09 to PAGE-ICE

• While integrated assessment models (IAMs) have been previously used to

estimate the net present value of economic impacts of climate change

(Stern, 2007; Nordhaus, 2008; Hope, 2011; Hope, 2013), explicitly

considering the potential global economic impacts of Arctic change is a new

area for research (Whiteman et al., 2013).

• However, most IAMs, including PAGE09, do not directly incorporate physical

changes in the Arctic into model configurations, but rather rely on climate

sensitivity parameters for global temperature that include the Arctic implicitly.

• The climate sensitivity parameters are obtained from Earth System models

that currently underrepresent the ice sheets and permafrost (Vizcaino, 2014;

IPCC AR5). The attempts to couple ice sheet models with climate models are

ongoing (Perego et al., 2014; Vizcaino et al., 2014).

• Thus, large irreversibilities like potential accelerated GIS melt and extensive

greenhouse gas emissions from Arctic permafrost do not directly feed into

the IAM structures. Our new model PAGE-ICE will aim to rectify this.

The melting of the Greenland ice sheet

• Accelerated rate of ice loss since 1992: “the average rate has very

likely increased from 34 [–6 to 74] Gt yr–1 over the period 1992–2001

(sea level equivalent, 0.09 [–0.02 to 0.20] mm yr–1), to 215 [157 to

274] Gt yr–1 over the period 2002–2011 (0.59 [0.43 to 0.76] mm yr–1)”

(IPCC, 2013, page 353)

• In July 2012, satellite observations revealed that 98.6% of the extent of

the GIS melted at or near the surface whilst previous rare extreme melt

events occurred in 1889 and the next previous one about seven

centuries earlier (Nghiem, 2012)

• Even though the GIS represents slightly over 1% of global land

surface, if it were to melt completely, its sea level equivalent rise would

be 7.36 mts (IPCC, 2013).

The melting of the Greenland ice sheet

Figure 4.15 | Cumulative ice mass loss (and sea level equivalent, SLE) from Greenland derived as annual

averages from 18 recent studies (see main text and Appendix 4.A for details). Source: IPCC, AR5, WGI, Chapter 4

The melting of the Greenland ice sheet

• According to the IPCC, all modelling studies agree that in a warmer

climate the GIS will experience a significant decrease both in area

and volume which, asides from an increase in sea level rise, could

potentially weaken the Atlantic Meridional Overtuning (AMOC)

(IPCC, 2013).

• The long- term stability of the GIS depends on the threshold in the

global mean temperature rise (above pre- industrial levels) which

would lead to the complete melting of the ice sheet.

• Previous studies estimated the threshold to be 3.1°C (1.9–5.1 °C,

95% confidence interval) but recent estimates have set it at 1.6 °C

(range of 0.8- 3.2 °C) (Gregory & Huybrechts, 2006; Robinson et al.,

2012).

Objectives

To assess potential economic impacts caused by the

melting of the Greenland ice sheet using the PAGE09

model, the following two steps are required:

1. Developing add-ins to integrate the physical

changes in the GIS explicitly into the PAGE IAM

2. Adjusting the relevant damage functions in

PAGE, for example by introducing the rate of

sea level rise explicitly in order to represent the

likely lags in coastal adaptation

Methodology- Objective I

Developing add-ins to integrate the physical changes

in the GIS explicitly into the PAGE IAM involves:

• Separating various global contributors to the sea

level rise, most notably GIS and West Antarctic ice

sheet, within the existing module in PAGE

• Specifying potential drivers of the GIS melt – such

as overall Arctic warming and black carbon

pollution from the increasing wildfires (Benning et

al., 2014; Doherty et al., 2013, Colgan et al., 2014)

Methodology- Objective II

Adjusting the damage functions in PAGE involves:

• Looking into the main mechanisms by which the GIS melting will

cause economic impacts globally. These include: (i) sea level rise,

and (ii) changing atmospheric and ocean circulation and its effect

on weather patterns in Europe, North America and further afield

• Identifying distinct scenarios for the GIS melt under a given RCP

(global emissions scenario) and investigating the relevant sea level

rise impacts based on recent results from the DIVA model (Hinkel

et al., 2014)

• The new damage functions may include the rate of sea level rise

explicitly in order to represent the likely lags in coastal adaptation

Next steps

• Work with natural scientists in the ICE-ARC team in

order to:

• Develop functional forms that separate the

Greenland ice sheet from other drivers of sea level

rise in the relevant module of PAGE09

• Identify the long-term scenarios for the melting of

the Greenland ice sheet (based on the Dark Snow

project, for example, http://darksnow.org/)

• Use the results from Hinkel et al. (2014) in order to

derive a new sea level impact function in PAGE09

References

• Benning, L.G. A.M. Anesio, S. Lutz & M. Tranter (2014), Biological impact on Greenland’s albedo, Nature Geoscience 7, 691 doi:10.1038/ngeo2260

• Consortium for International Earth Science Information Network (CIESIN). 1995. Thematic Guide to Integrated Assessment Modeling of Climate Change [online]. University Center, Mich.

• CIESIN URL: http://sedac.ciesin.org/mva/iamcc.tg/TGHP.html

• Colgan, W., Box, J. E., Fausto, R. S., van As, D., Barletta, V. R., & Forsberg, R. (2014). Surface albedo as a proxy for the mass balance of Greenland’s terrestrial ice. Geological Survey of Denmark and Greenland Bulletin, 31, 91-94.

• Doherty, S. J., T. C. Grenfell, S. Forsström, D. L. Hegg, R. E. Brandt, and S. G. Warren (2013), Observed vertical redistribution of black carbon and other insoluble light-absorbing particles in melting snow, J. Geophys. Res. Atmos., 118, 5553–5569, doi:10.1002/jgrd.50235

• Emmerson, C. & Lahn, G. (Chatham House–Lloyd’s, 2012). Arctic Opening: Opportunity and Risk in the High North. Available at http://go.nature.com/ruby4b

• Gautier, D. L. et al. (2009), Science 324, 1175–1179.

• Gregory, J. M. & Huybrechts, P. (2006), Ice-sheet contributions to future sea-level change, Phil. Tran. R. Soc.,A 364, 1709-1731, doi:10.1098/rsta.2006.1796.

• Hope (2011), “The PAGE09 Integrated Assessment Model: A Technical Description”, Working Paper Series, Judge Business School.

• Hope (2011), “The Social Cost of CO2 from the PAGE09 Model”, Working Paper Series, Judge Business School.

• Hope, C. (2013), Critical issues for the calculation of the social cost of CO2: why the estimates from PAGE09 are higher than those from PAGE2002, Climatic Change, 117, Issue 3, Page 531-543, DOI: 10.1007/s10584-012-0633-z

• IPCC (2013). Climate change 2013: the physical science basis. Contribution of WG1 to the 5th Assessment Report of the IPCC. Cambridge University Press

• Maslowski, W., Kinney, J.C., Higgins, M., and Roberts, A. (2012). The future of Arctic sea ice. The Annual Review of Earth and Planetary Sciences, 40: 625-54. Doi: 10.1146/annurev-earth-042711-105345

• Nghiem, S. V., Hall, D. K., Mote, T. L., Tedesco, M., Albert, M. R., Keegan, K., Shuman, C. A., DiGirolamo, N. E., and Neumann, G. (2012), The extreme melt across the Greenland ice sheet in 2012, Geophys. Res. Lett., Vol. 39, L20502, doi:10.1029/2012GL053611.

• Nordhaus, W. D. (2008), A question of balance- weighing the options on global warming policies, Yale University Press.

• Parson, E., Fisher-Vanden. K (1997), “Integrated assessment models of global climate change”, Annual Review of Energy and the Environment.

• Perego, M., Price, S., & Stadler, G. (2014). Optimal initial conditions for coupling ice sheet models to Earth system models. Journal of Geophysical Research: Earth Surface, 119(9), 1894-1917.

• Petoukhov, V., Rahmstorf, S., Petri, S., & Schellnhuber, H. J. (2013). Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes. Proceedings of the National Academy of Sciences, 110(14), 5336-5341

• Robinson, A., Calov, R., Ganopolski, A. (2012), Multistability and critical thresholds of the Greenland ice sheet, Nature climate change, 2,429–432, doi:10.1038/nclimate1449

• Smith, L. C. & Stephenson, S. R. (2013) Proc. Natl Acad.Sci. USA 110, E1191–E1195.

• Stern, N. (2007) The economics of Climate Change. The Stern Review. Cambridge: Cambridge University Press.

• Vizcaino, M. (2014). Ice sheets as interactive components of Earth System Models: progress and challenges. Wiley Interdisciplinary Reviews: Climate Change, 5(4), 557-568.

• Vizcaíno, M., Lipscomb, W. H., Sacks, W. J., & van den Broeke, M. (2014). Greenland Surface Mass Balance as Simulated by the Community Earth System Model. Part II: Twenty-First-Century Changes. Journal of climate,27(1), 215-226.

• Wadhams, P. (2012), Arctic Ice Cover, Ice Thickness and Tipping Points, AMBIO (2012) 41:23–33 DOI 10.1007/s13280-011-0222-9.

• Walsh, J. E. (2014). Intensified warming of the Arctic: Causes and impacts on middle latitudes. Global and Planetary Change

• Whiteman, G., Hope C., and Wadhams, P. (2013) Vast costs of Arctic change. Nature Comment, 499: 401–403.

Q & A

Thank you!

Appendix

Changes in the GIS

• “Greenland observational records show large recent changes. Section 13.3

concludes that regional models for Greenland can reproduce trends in the

surface mass balance loss quite well if they are forced with the observed

meteorological record, but not with forcings from a Global Climate Model.

Regional model simulations (Fettweis et al., 2013) show that Greenland surface

melt increases nonlinearly with rising temperatures due to the positive feedback

between surface albedo and melt.” (IPCC, AR5, WGI, Chapter 10, page 909)

• “There have been exceptional changes in Greenland since 2007 marked by

record-setting high air temperatures, ice loss by melting and marine-terminating

glacier area loss (Hanna et al., 2013; Section 4.4.4).” (IPCC, AR5, WGI,

Chapter 10, page 909)

• “Hanna et al. (2013) show a weak relation of Greenland temperatures and ice

sheet runoff with the AMO; they more strongly correlate with a Greenland

atmospheric blocking index. Overland et al. (2012) and Francis and Vavrus

(2012) suggest that the increased frequency of the Greenland blocking pattern

is related to broader scale Arctic changes.” (IPCC, AR5, WGI, Chapter 10, page

909)

A case for looking into the GIS

• “The available evidence indicates that sustained global warming greater than a certain

threshold above pre-industrial would lead to the near-complete loss of the Greenland ice

sheet over a millennium or more, causing a global mean sea level rise of about 7 m.

Studies with fixed ice-sheet topography indicate the threshold is greater than 2°C but

less than 4°C (medium confidence) of global mean surface temperature rise with

respect to pre-industrial. The one study with a dynamical ice sheet suggests the

threshold is greater than about 1°C (low confidence) global mean warming with respect

to pre-industrial. We are unable to quantify a likely range. Whether or not a decrease in

the Greenland ice sheet mass loss is irreversible depends on the duration and degree of

exceedance of the threshold.” (IPCC, AR5, WGI, Chapter 13, page 1140)

• “We have high confidence in projections of future warming in Greenland because of the

agreement of models in predicting amplified warming at high northern latitudes (Sections

12.4.3.1, 14.8.2) for well-understood physical reasons, although there remains

uncertainty in the size of the amplification, and we have high confidence in projections of

increasing surface melting (Section 13.4.3.1) because of the sensitivity to warming

demonstrated by SMB models of the past.” (IPCC, AR5, WGI, Chapter 13, page 1154)

A case for looking into other cities

“It is commonly assumed that melting ice from glaciers or the Greenland

and Antarctic ice sheets would cause globally uniform sea level rise,

much like filling a bath tub with water. In fact, such melting results in

regional variations in sea level due to a variety of processes, including

changes in ocean currents, winds, the Earth’s gravity field and land

height. For example, computer models that simulate these latter two

processes predict a regional fall in relative sea level around the melting

ice sheets, because the gravitational attraction between ice and ocean

water is reduced, and the land tends to rise as the ice melts (FAQ 13.1,

Figure 2). However, further away from the ice sheet melting, sea level

rise is enhanced, compared to the global average value.” (IPCC, AR5,

WGI, Chapter 13, page 1149)

A case for looking into countries

• AR4 “estimates that global average sea level rose about 17 cm during the 20th century and projects

that within the 21st century it will continue to rise by an additional 18 cm to 59 cm (IPCC 2007a).

However, as stated in the IPCC Synthesis Report (IPCC 2007b), no reasonable upper bound of sea-

level rise can be determined as we are unsure how rapidly the major ice sheets (Greenland and

Antarctica) could collapse in a warming world. Several post-AR4 papers support the view that a 1

m+rise in sea level over the next century cannot be discounted at present (e.g., Grinsted et al. 2009;

Vermeer and Rahmstorf 2009). ” (Hinkel et al., 2010, page 704)

• “The impacts of sea-level rise on the coastal areas of Europe are expected to be overwhelmingly

negative based on earlier studies and reviews, such as Rotmans et al. (1994), Nicholls (2000), de la

Vega-Leinert et al. (2000), Nicholls and Klein (2005), Rochelle-Newall et al. (2005) and Nicholls and de

la Vega-Leinert (2008). The major impacts are expected to be increased flooding and permanent

inundation of low-lying coastal areas, increased erosion of beaches and cliffs, and degradation of

coastal ecosystems. Locally, salinisation effects may be important. Coastal morphology and human

utilisation will condition the nature of these impacts and their implications: in general, coastal lowlands

with microtidal conditions are most susceptible.” (Hinkel et al., 2010, page 704)

• “These existing studies are limited due to the broad treatment of impacts, or being based on

inconsistent data. The European-funded project DINAS-COAST (Dynamic and Interactive Assessment

of National, Regional and Global Vulnerability of Coastal Zones to Sea-Level Rise… addressed some

of these limitations by developing a new global coastal database, a set of consistent climatic and

socio-economic scenarios and an integrated simulation model called DIVA …. The model consists of a

number of modules that represent coastal subsystems developed by experts from various engineering,

natural and social science disciplines (Hinkel 2005; Hinkel & Klein 2009).” (Hinkel et al., 2010, page

704)

Cumulative ice mass loss (and sea level equivalent, SLE) from Greenland

Appendix 4.A: Details of Available and Selected Ice Sheet Mass

Balance Estimates from 1992 to 2012

All comprehensive mass balance estimates available for Greenland,

and the subset of those selected for this assessment (Section 4.4.2)

are listed in Tables 4.A.1 and 4.A.2. Those available for Antarctica

are shown in Tables 4.A.3 and 4.A.4. These studies include estimates

made from satellite gravimetry (GRACE), satellite altimetry (radar

and laser) and the mass balance (flux) method. The studies selected

for this assessment are the latest made by different research groups,

for each of Greenland and Antarctica. The tables indicate whether

smaller glaciers peripheral to the ice sheet are included, or excluded,

in the estimate, and explain why some studies were not selected

(e.g., earlier estimates from the same researchers have been

updated by more recent analyses using extended data).

Table 4.A.1 | Sources used for calculation of ice loss from Greenland

Table 4.A.2 | Sources NOT used for calculation of ice loss from Greenland

Table 13.1 | Global mean sea level budget (mm yr–1) over different time intervals from observations and

from model-based contributions. Uncertainties are 5 to 95%. The Atmosphere– Ocean General Circulation Model

(AOGCM) historical integrations end in 2005; projections for RCP4.5 are used for 2006–2010. The modelled thermal expansion

and glacier contributions are computed from the CMIP5 results, using the model of Marzeion et al. (2012a) for glaciers. The land

water contribution is due to anthropogenic intervention only, not including climate-related fluctuations.

Table 13.2 | Surface mass balance (SMB) and rates of change of SMB of the Greenland ice sheet,

calculated from ice-sheet SMB models using meteorological observations and reanalyses as input,

expressed as sea level equivalent (SLE). A negative SLE number for SMB indicates that accumulation exceeds runoff.

A positive SLE for SMB anomaly indicates that accumulation has decreased, or runoff has increased, or both. Uncertainties are

one standard deviation. Uncertainty in individual model results reflects temporal variability (1 standard deviations of annual mean

values indicated); the uncertainty in the model average is 1 standard deviation of variation across models.

Increase in SCCO2 from a 1 SD

increase in each input

Source: 100,000 PAGE09 runs RCP 4.5 scenario in 2010