Global sea level projections by 2100 - CLIVAR · 2018. 9. 4. · Sea Level Expansion Glaciers...

Svetlana JevrejevaNational Oceanography Centre, Liverpool, UK

sveta@noc.ac.uk

Global sea level projections by 2100

Outline

• Cause of sea level rise/Sea level budget

• Global sea level projections by 2100:

1. Process based approach

2. Probabilistic approach

3. Semi-empirical approach

• Uncertainties in sea level projections

• Short conclusion

Figure 13.27, AR5 IPCC ( 2013)

Sea Level Expansion Glaciers Land Water AntarcticaGreenland

Global sea level rise since 1700

Sea level budget

S- sea level

T- thermal expansion of the ocean

Mg- mass loss from glaciers

Gis – Greenland ice sheet

Ais- Antartcica ice sheet

Snc- None climatic component

Sea level budget since 1993

From A. Cazenave, http://www.psmsl.org/about_us/news/2013/workshop_2013/talks/02_PSMSL_Liverpool_28Oct2013_WEB.pdf

Figure 13.27, AR5 IPCC ( 2013)

Sea Level Expansion Glaciers Land Water AntarcticaGreenland

Global sea level rise by 2100

Processes contributing to sea level changes

Slangen et al., 2017

Process based approach

• AR5 IPCC, https://www.ipcc.ch/report/ar5/

• Climate forcing

• Climate /emission scenarios

• Coupled Model Intercomparison Project (CMIP5), World Climate Research

Programme (WCRP),

https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip5

• Modelling of individual components of sea level (excluding land water storage,

scenario independent)

• Challenges

Figure 8.18, AR5 IPCC

Radiative forcingRadiative forcing (W/m2) is “the rate of energy change per unit area of the globe as measured at the top of the atmosphere”

Where does the heat go?

➔

Net Heat Input to Earth System

(Levitus et al., GRL, 2004)

84% -- Saved by the oceans!

Amount of Heat Absorbed by Parts of Earth Climate System Over Past 40 Years

Scenarios: Representative Concentration Pathways (RCPs)

RCP8.5 (Representative Concentration Pathways )

GHG emissions continue to grow at current level

RCP2.6

Substantial reductions in emissions

3.7 °C

(2081-2100)

[2.6 4.8]

(2081-2100)

1 °C

[0.3 1.7]AR5 IPCC, 2013

Thermal expansion: modelling vs observations (0-700m)

Melet and Meyssignac, 2015

Thermosteric sea level (mm) referenced in 2005 for the 0–700-m layer

Thermosteric sea level (mm) referenced in 2005 for the full ocean depth

Melet and Meyssignac, 2015

Thermal expansion the full ocean depth: modelling vs observations

Thermal expansion: modelling vs observations

Slangen et al., 2017

Projections: Thermal expansion (CMIP5)

Global mean steric sea level change (zossga) over 21st century relative to 2006 for CMIP5 models for experiments (left) RCP 4.5, (middle) RCP 8.5 and (right) multi-model ensemble mean and 2σ

Modelling of individual components: Glaciers

Reviews of GeophysicsVolume 51, Issue 3, pages 484-522, 24 SEP 2013 DOI: 10.1002/rog.20015http://onlinelibrary.wiley.com/doi/10.1002/rog.20015/full#rog20015-fig-0010

Fig 4.12, AR5 IPCC

Glaciers

Glaciers

Slangen et al., 2016

Contribution from glaciers (mass balance)

Ice loss in Greenland

The rate of mass loss, in cm/yr water equivalent thickness, determined from monthly GRACE gravity field solutions, from Khan et al, 2010.

2003-2007 2003-2009

Straneo et al. 2012

Modelling contribution from Greenland ice sheet

Reviews of GeophysicsVolume 51, Issue 3, pages 484-522, 24 SEP 2013 DOI: 10.1002/rog.20015http://onlinelibrary.wiley.com/doi/10.1002/rog.20015/full#rog20015-fig-0004

Modelling of the 20th century contribution from Greenland

KK Kjeldsen et al. 2015

Slangen et al. 2017

Future Greenland ice sheet contribution

Slangen et al., 2016 [reproduced from Furst et al. (2015)].

Reviews of GeophysicsVolume 51, Issue 3, pages 484-522, 24 SEP 2013 DOI: 10.1002/rog.20015http://onlinelibrary.wiley.com/doi/10.1002/rog.20015/full#rog20015-fig-0006

Contribution from Antarctica ice sheet

Large Ensemble model analyses of future Antarctic contributions to GMSL

R M DeConto et al. Nature 531, 591–597 (2016) doi:10.1038/nature17145

Historical and projected terrestrial water contributions to sea level rise

Land water storage

Slangen et al., 2017 (based on Wada et al., 2012)

Slangen et al., 2017

Modelled total sea level changes since 1900s

Global sea level projections by 2100 in AR5 IPCC

AR5 IPCC, 2013

Median values and likely ranges for projections of global mean sea level (GMSL) rise and its contributions in metres in 2081–2100 relative to 1986–2005 for the four RCP scenarios and SRES A1B, GMSL rise in 2046–2065 and 2100, and rates of GMSL rise in mm/yr in 2081–2100 (AR5 IPCC, 2013).

Uncertainties in global sea level projections

Credits: Finnish Meteorological Institute

Likely range (66% probability)

AR5 IPCC, 2013

1879

1928

1890

1953

Photo from Environment Agency, UK

Photo from Environment Agency, UK

Probabilistic approach

AR5 IPCC, 2013

Likely range (66% probability)

Jevrejeva et al, 2014

Probabilistic approach in global sea level projections

Probabilistic approach in global sea level projections

Expansion

Glacier

Greenland

Antarctica

0 0.2 0.4 0.6 0.8 1

Landwater

Projected sea level contribution by 2100 (m)

Likely range (IPCC)

Our study

Jevrejeva et al, 2014

Semi-empirical approach

Reviews of GeophysicsVolume 51, Issue 3, pages 484-522, 24 SEP 2013 DOI: 10.1002/rog.20015http://onlinelibrary.wiley.com/doi/10.1002/rog.20015/full#rog20015-fig-0001

2007 2013

Approach:• Smooth GSL record (1880-2000)

• Calculate dH/dt

• Linear regression against observed T.

• Use projected temperatures to project GSL

Semi-empirical model by Rafmstorf, 2007

Model including a response time (Grinsted et al, 2010)

S=f(T)

Parameters:

(τ, a, b, S0)

baTSeq += (eq. 1)

Inverse problem

• We know T(Temperature, 2000 yrs)

• We know S(Tide gauges, 300 yrs)

• We do not know the model parameters that allow us to calculate S from T: a, b, τ, S0

model:

S=f(T)

Tem

pe

ratu

re

Likelihood of the model

How well does S match observations taking into account the uncertainties in observed sea level

C is the uncertainty covariance matrix. This takes into account that the observations are not independent

PDFs for model parameters

Sea level projections (Using A1B temperatures)

AR4 IPCC A1B

AR4 IPCC A1B

Grinsted et al., 2010

Global mean sea level rise (metres) in 2081–2100 relative to 1986–2005 by semi-empirical models (bars) and process basedmodels (grey colour) for (a) RCP2.6, (b)RCP4.5, (c) RCP6.0 and (d) RCP8.5.

Figure 13.12 , AR5 IPCC

Grey colour (process based) is 17-83% Blue and red (SE) are 5-95%

NOTE:

Projections from process based and semi-empirical approaches

Limitations/Uncertainties

1. The largest uncertainties are associated with contribution from Greenland and Antarctica ice sheets: • Ocean-ice sheet interaction• Ice dynamics• Limited number of models/observations

2. Glaciers: • No ice dynamics, • Limited number of models • Limited number of observations to calibrate models

3. Thermal expansion• Deep ocean • Heat update by the ocean• Lack of observations below 2000m• Lack of observations prior 1955

Svetlana JevrejevaNational Oceanography Centre, Liverpool, UK

sveta@noc.ac.uk

Regional and local sea level projections by 2100

Outline

1. Background (global –regional- local)

2. Physical mechanisms for the regional changes:

• Ocean dynamics

• Gravitational forcing (fingerprints)

• Vertical land movement

3. Uncertainties in regional and local sea level projections

4. Conclusion

1993-2008

Cazenave and Llovel, 2010AR5 IPCC, 2013

Global Regional Local

Processes contributing to sea level changes

Slangen et al., 2017

Fingerprints

Global Regional Local

Tamisiea and Mitrovica, 2011

Sea level in each grid point

(SAL) - the impact of self-attraction and loading of the ocean upon itself; due to the long term alteration of ocean density changes;(STR)- globally averaged steric sea-level rise;(DSL)- dynamic sea-level change; (GLA)- glaciers ;(GRE)- Greenland ice sheet; (ANT)- Antarctic ice sheet;(LAN)- land-water storage;(GIA)- Glacial Isostatic Adjustment;(TECT)- tectonics; (NCLIM)- non-climatic land-motion

Jackson and Jevrejeva, 2016

Normalised pattern due to gravitational and Earth rotational effects

Jackson and Jevrejeva, 2016

a) Glaciers (Bamber & Riva, 2010), b) Greenland (Bamber & Riva,

2010), c) Antarctica (Bamber & Riva, 2010) d) Land-water (Wada et al. 2012).

Future contribution from cryosphere

Jevrejeva et al., 2016

2040 2080 2100

Ocean component (CMIP5)

Jevrejeva et al., 2016

2040 2080 2100

ModelNumber of realisations for RCP8.5

Reference

bcc-csm1-1 1 Wu et al. (2010)

bcc-csm1-1-m 1 Wu et al. (2010)

CanESM2 5 Arora et al. (2011)

CMCC-CESM 1

CMCC-CM 1 Scoccimarro et al. (2011)

CMCC-CMS 1

CNRM-CM5 5 Voldoire et al. (2013)

ACCESS1-0 1 BOM (2010)

ACCESS1-3 1 BOM (2010)

CSIRO-MK3-6-0 10 Rotstayn et al. (2010)

EC-EARTH 12 Hazeleger et al. (2010)

inmcm4 1 Volodin et al. (2010)

IPSL-CM5A-LR 4 Dufresne et al. (2013)

IPSL-CM5A-MR 1 Dufresne et al. (2013)

IPSL-CM5B-LR 1 Dufresne et al. (2013)

FGOALS-g2 1 Yongqiang et al. (2004)

MIROC5* 3 Watanabe et al. (2010)

MIROC-ESM 1 Watanabe et al. (2011)

MIROC-ESM-CHEM 1 Watanabe et al. (2011)

HadGEM2-CC 3 Martin et al. (2011)

HadGEM2-ES 4 Collins et al. (2011)

MPI-ESM-LR 3 Raddatz et al. (2007)

MPI-ESM-MR 1 Raddatz et al. (2007)

MRI-CGCM3 1 Yukimoto et al. (2001)

GISS-E2-R* 3 Schmidt et al. (2006)

CCSM4 6 Gent et al. (2011)

NorESM1-M 1 Iversen et al. (2013)

NorESM1-ME 1 Iversen et al. (2013)

GFDL-ESM2G 1 Donner et al. (2011)

GFDL-ESM2M 1 Donner et al. (2011)

CESM1-BGC 1 Vertenstein et al. (2012)

CESM1-CAM5 2 Vertenstein et al. (2012)

CESM1-WACCM 3 Vertenstein et al. (2012)

Total models 33

Total realisations 83

AOGSMs from CMIP5

Median

95%

Jevrejeva et al, 2016

Global Regional Local

Regional sea level projections with RCP8.5 by 2100

95%

Median

Ratio of projected local (1°grid cells close to coastline) median and upper limit (50%/95%) sea level rise to global median sea level rise

2040

2080

2100

Jevrejeva et al, 2016

Sea level rise with RCP8.5 along the coastlines

Coastal sea level: RCP4.5

Carson et al., 2016

Grinsted et al, 2015

5% 50% 95% 99%

Belfast0.27 0.64 1.57 2.22

Newlyn0.45 0.82 1.81 2.49

Cardiff0.40 0.77 1.73 2.40

Edinburgh0.26 0.64 1.56 2.20

Liverpool0.35 0.71 1.66 2.31

Aberdeen0.27 0.66 1.58 2.21

London0.43 0.81 1.76 2.43

RCP8.5

Sea level projections by 2100 for the UK locations

Sea level projections for Individual locations

95%

50%

Guangzhou Miami Maldives

Jevrejeva et al, 2016

Sea level rise for individual cities by 2100 (RCP8.5)

Uncertainties at individual locations (New York)

Earth's FutureVolume 2, Issue 8, pages 383-406, 21 AUG 2014 DOI: 10.1002/2014EF000239http://onlinelibrary.wiley.com/doi/10.1002/2014EF000239/full#eft237-fig-0004

Kopp et al, 2014

Thermal expansion

Greenland ice sheet

Antarctica ice sheet

Earth's FutureVolume 2, Issue 8, pages 383-406, 21 AUG 2014 DOI: 10.1002/2014EF000239http://onlinelibrary.wiley.com/doi/10.1002/2014EF000239/full#eft237-fig-0004

global

New York

Kopp et al., 2014

Kopp et al., 2014

Jevrejeva et al., 2016

Jevrejeva et al., 2016

Uncertainties in sea level projections

ICE 5G- ICE 1

ICE 5G- ICE 4G

ICE 5G- KL05

ICE 5G- ICE 3G

Jevrejeva et al, 2014

Uncertainties due to GIA (Glacial Isostatic Adjustment) corrections

Credits to Deltares

King et al, 2012

Top ten cities of each scenario listed in each panel are coloured whilst all other cities are plotted in grey

Sea level projections (median, 50%) without local vertical land movement

Sea level projections (median, 50%) with local vertical land movement

Probabilistic projections of extreme sea levels (sea level rise +waves+storm surges)

Vousdoukas et al., 2018

Return period of the present day 100-year ESL under RCP4.5 and RCP8.5 in 2050 and 2100

Probabilistic projections of extreme sea levels (sea level rise + waves + storm surges)

Vousdoukas et al., 2018

1. Sea level community is making a substantial progress in understanding of global and regional sea level rise and variability

1. The key uncertainties (global/regional/local) area) emission scenariosb) contribution from ice sheets

3. The largest uncertainties in regional and local sea level projections associated with ocean dynamics and the vertical land movement

4. The main challenges for coast projections:

• AOGSMs do not have resolution, physical mechanisms, topography to resolve coastal processes on the shelf

• Semi-enclosed seas (e.g. Mediterranean) are not resolved in AOGSMs• Decadal variability in ocean dynamics• Local vertical land movement

Conclusion (regional and local sea level projections)

5. Probabilistic sea level projections in coastal areas is a valuable solution for the risk assessment and decision making about the adaptation. However, probabilistic approach (or conventional approach) do not consider interaction between the components.

6. Challenges: interaction between physical mechanisms (e.g. river runoff with waves, tides, rainfall, storm surges, sediment transport, erosion) is available for specific events or short term simulations. Combined effect on the coast is not quantified.

7. Impact of sea level rise in the coastal areas is already seen and every 10 cm by 2100 could result in additional global annual flood damages of US$ 1.5 trillion per year (0.25% of global GDP) without adaptation. For many countries (e.g. China, EU countries) >1% GDP for every 10 cm sea level rise.

8. The large part of the coast is not covered with observations (tide gauges, waves, vertical land movement), we urgently need a novel instruments.

The main challenges for coast projections (continue):

Sea flood damage costs with the sea level rise by 2100

Global sea floods cost,Million US$ per year

Global sea floods cost, % of GDP (global)

Sea flood cost for China, % of GDP (China)

China, flood cost in 2100US$ 3.4 trillion per year (5.8 % GDP) with warming of 1.5 degree (0. 5 m sea level rise) US$ 4.6 trillion per year (7.8% GDP) with RCP8.5 (0. 8 m sea level rise)US$ 8.5 trillion per year (14 % GDP) with RCP8.5J14 (1.8 m sea level rise)

Jevrejeva et al., 2018

1.5 degree

RCP8.5

RCP8.5J14

Sea flood damage costs with the sea level rise by 2100

Global sea flood cost,Million US$ per year

Global sea flood cost, % of GDP (global)

UK sea flood cost,% of UK GDP

UK flood cost in 2100US$ 241 billion per year (2.5 % UK GDP) with warming of 1.5 degree (0. 5 m sea level rise) US$ 619 billion per year (6.5% UK GDP) with RCP8.5 (0. 8 m sea level rise)

US$ 1.1. trillion per year (11.1 % UK GDP) with RCP8.5J14 (1.8 m sea level rise) Jevrejeva et al., 2018