Global sea level projections by Svetlana Jevrejeva National Oceanography Centre, Liverpool, UK

Transcription

1 Global sea level projections by 2100 Svetlana Jevrejeva National Oceanography Centre, Liverpool, UK

2 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

3 Global sea level rise since 1700 Figure 13.27, AR5 IPCC ( 2013) Sea Level Expansion Glaciers Greenland Antarctica Land Water

4 S- sea level T- thermal expansion of the ocean Mg- mass loss from glaciers Gis Greenland ice sheet Ais- Antartcica ice sheet S nc- None climatic component Sea level budget

5 Sea level budget since 1993 From A. Cazenave,

6 Global sea level rise by 2100 Figure 13.27, AR5 IPCC ( 2013) Sea Level Expansion Glaciers Greenland Antarctica Land Water

7 Slangen et al., 2017 Processes contributing to sea level changes

8 Process based approach AR5 IPCC, Climate forcing Climate /emission scenarios Coupled Model Intercomparison Project (CMIP5), World Climate Research Programme (WCRP), Modelling of individual components of sea level (excluding land water storage, scenario independent) Challenges

9 Radiative forcing Radiative forcing (W/m 2 ) is the rate of energy change per unit area of the globe as measured at the top of the atmosphere Figure 8.18, AR5 IPCC

10 Where does the heat go? Amount of Heat Absorbed by Parts of Earth Climate System Over Past 40 Years Net Heat Input to Earth System 84% -- Saved by the oceans! (Levitus et al., GRL, 2004)

11 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 [ ] ( ) 1 C AR5 IPCC, 2013 [ ]

12 Thermal expansion: modelling vs observations (0-700m) Thermosteric sea level (mm) referenced in 2005 for the m layer Melet and Meyssignac, 2015

13 Thermal expansion the full ocean depth: modelling vs observations Thermosteric sea level (mm) referenced in 2005 for the full ocean depth Melet and Meyssignac, 2015

14 Thermal expansion: modelling vs observations Slangen et al., 2017

15 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

16 Modelling of individual components: Glaciers Fig 4.12, AR5 IPCC Reviews of Geophysics Volume 51, Issue 3, pages , 24 SEP 2013 DOI: /rog

17 Contribution from glaciers (mass balance) Glaciers Slangen et al., 2016 Glaciers

18 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, Straneo et al. 2012

19 Modelling contribution from Greenland ice sheet Reviews of Geophysics Volume 51, Issue 3, pages , 24 SEP 2013 DOI: /rog

20 Modelling of the 20 th century contribution from Greenland Slangen et al KK Kjeldsen et al. 2015

21 Future Greenland ice sheet contribution Slangen et al., 2016 [reproduced from Furst et al. (2015)].

22 Contribution from Antarctica ice sheet Reviews of Geophysics Volume 51, Issue 3, pages , 24 SEP 2013 DOI: /rog

23 Large Ensemble model analyses of future Antarctic contributions to GMSL R M DeConto et al. Nature 531, (2016) doi: /nature17145

24 Land water storage Historical and projected terrestrial water contributions to sea level rise Slangen et al., 2017 (based on Wada et al., 2012)

25 Modelled total sea level changes since 1900s Slangen et al., 2017

26 Global sea level projections by 2100 in AR5 IPCC AR5 IPCC, 2013

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

28 Uncertainties in global sea level projections Likely range (66% probability) AR5 IPCC, 2013 Credits: Finnish Meteorological Institute

29 Probabilistic approach Photo from Environment Agency, UK Photo from Environment Agency, UK

30 Probabilistic approach in global sea level projections Likely range (66% probability) AR5 IPCC, 2013 Jevrejeva et al, 2014

31 Probabilistic approach in global sea level projections Likely range (IPCC) Expansion Glacier Our study Greenland Antarctica Landwater Projected sea level contribution by 2100 (m) Jevrejeva et al, 2014

32 Semi-empirical approach Reviews of Geophysics Volume 51, Issue 3, pages , 24 SEP 2013 DOI: /rog

33 Semi-empirical model by Rafmstorf, 2007 Approach: Smooth GSL record ( ) Calculate dh/dt Linear regression against observed T. Use projected temperatures to project GSL

34 Model including a response time (Grinsted et al, 2010) S = at + b eq (eq. 1) S=f(T) Parameters: (τ, a, b, S 0 )

35 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, S 0

36 Temperature model: S=f(T)

37 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

38 PDFs for model parameters

39 Sea level projections (Using A1B temperatures) AR4 IPCC A1B AR4 IPCC A1B Grinsted et al., 2010

40 Projections from process based and semi-empirical approaches NOTE: Grey colour (process based) is 17-83% Blue and red (SE) are 5-95% Global mean sea level rise (metres) in relative to by semiempirical models (bars) and process based models (grey colour) for (a) RCP2.6, (b) RCP4.5, (c) RCP6.0 and (d) RCP8.5. Figure 13.12, AR5 IPCC

41 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

42 Regional and local sea level projections by 2100 Svetlana Jevrejeva National Oceanography Centre, Liverpool, UK

43 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

44 Global Regional Local AR5 IPCC, 2013 Cazenave and Llovel, 2010

45 Slangen et al., 2017 Processes contributing to sea level changes

46 Global Regional Local Fingerprints Tamisiea and Mitrovica, 2011

47 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

48 Normalised pattern due to gravitational and Earth rotational effects a) Glaciers (Bamber & Riva, 2010), b) Greenland (Bamber & Riva, 2010), c) Antarctica (Bamber & Riva, 2010) d) Land-water (Wada et al. 2012). Jackson and Jevrejeva, 2016

49 Future contribution from cryosphere Jevrejeva et al., 2016

50 Ocean component (CMIP5) Jevrejeva et al., 2016

51 Model Number 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-MK 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

52 Regional sea level projections with RCP8.5 by 2100 Global Regional Local Median Median 95% 95% Jevrejeva et al, 2016

53 Sea level rise with RCP8.5 along the coastlines Jevrejeva et al, 2016 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

54 Carson et al., 2016 Coastal sea level: RCP4.5

55 Sea level projections for Individual locations RCP8.5 Sea level projections by 2100 for the UK locations 5% 50% 95% 99% Grinsted et al, 2015 Belfast Newlyn Cardiff Edinburgh Liverpool Aberdeen London

56 Sea level rise for individual cities by 2100 (RCP8.5) 95% 50% Guangzhou Miami Maldives Jevrejeva et al, 2016

57 Uncertainties at individual locations (New York) Thermal expansion Greenland ice sheet Antarctica ice sheet Kopp et al, 2014 Earth's Future Volume 2, Issue 8, pages , 21 AUG 2014 DOI: /2014EF

58 Uncertainties in sea level projections Jevrejeva et al., 2016 global Kopp et al., 2014 Kopp et al., 2014 New York Jevrejeva et al., 2016 Earth's Future Volume 2, Issue 8, pages , 21 AUG 2014 DOI: /2014EF

59 Uncertainties due to GIA (Glacial Isostatic Adjustment) corrections ICE 5G- ICE 4G ICE 5G- ICE 3G ICE 5G- ICE 1 ICE 5G- KL05 Jevrejeva et al, 2014

60 King et al, 2012 Credits to Deltares

61 Sea level projections (median, 50%) without local vertical land movement Sea level projections (median, 50%) with local vertical land movement Top ten cities of each scenario listed in each panel are coloured whilst all other cities are plotted in grey

62 Probabilistic projections of extreme sea levels (sea level rise +waves+storm surges) Return period of the present day 100-year ESL under RCP4.5 and RCP8.5 in 2050 and 2100 Vousdoukas et al., 2018

63 Probabilistic projections of extreme sea levels (sea level rise + waves + storm surges) Vousdoukas et al., 2018

64 Conclusion (regional and local sea level projections) 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) are a) emission scenarios b) 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

65 The main challenges for coast projections (continue): 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.

66 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) 1.5 degree RCP8.5 RCP8.5J14 China, flood cost in 2100 US$ 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

67 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 2100 US$ 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