Coastal and Marine Projections for the Natural Resource Management Regions of Australia The Australian Coastal Councils Association Conference, May 4, 2016, Rockingham, WA Kathleen McInnes John Church, Andrew Lenton, Didier Monselesan, Julian O Grady, Xuebin Zhang CSIRO Oceans and Atmosphere
The NRM (Natural Resource Management) Project Projections: Atmosphere and Land Projections (and recent trends): Marine and Coasts Sea Level Rise Sea Level Allowances Sea Surface Temperatures Sea Surface Salinity Ocean Acidification Aragonite Saturation Marine Explorer http://www.climatechangeinaustralia.gov.au/en/climate-projections/coastalmarine/marine-explorer/
Coastal Systems are particularly sensitive to: o Sea Level Rise Sea levels have risen about 20 cm since 1900 Relative rates may be higher due to land subsidence Impacts will be most profound during extreme events o Other factors include: o Ocean Storms, Temperature winds and waves Over Freshwater 90% of input the increase in energy in the climate system has warmed the oceans over recent decades o Ocean Acidification IPCC WG2 Ch5, Wong et al, 2014 Coastal sea surface temperatures have been increasing at a faster About rate 30% than of the ocean anthropogenic temperatures CO 2 emitted over the last Climate 200 years zones has have been moved absorbed polewards by the oceans Ocean ph has fallen 0.1 units representing a 26% increase in the hydrogen ion concentration in seawater Acidification impedes the ability of calcifying organisms to form their skeletons
Marine Projections 1. Regional projections of mean sea level rise 2. Allowances for extreme sea levels 3. Projections of changes in SSTs, aragonite and ph
Marine Projections 1. Regional projections of mean sea level rise 2. Allowances for extreme sea levels 3. Projections of changes in SSTs, aragonite and ph
Plausible Futures (RCPs) Taylor et al, 2010 RCP8.5 High emissions RCP6.0 RCP4.5 Intermediate emissions Intermediate emissions RCP2.6 Low emissions
Global sea level reflects the state of the Earth s climate system Figure 13.1 Warming/cooling of the ocean (thermal expansion/contraction) Change in mass of glaciers and ice sheets Changes in terrestrial storage Relative sea level is also affected by ocean density, circulation, land movement, and distribution of mass on the Earth
Projections of Global mean sea level rise (GMSLR) Sea level rise by 2100 compared with 1986 2005 RCP2.6 0.44 [0.28 0.61] m RCP8.5 0.74 [0.53 0.98] m Scenario Likely range for sea level rise 2081-2100 relative to 1986-2005 RCP2.6 RCP4.5 RCP6.0 RCP8.5 0.26-0.55 m 0.32-0.63 m 0.33-0.63 m 0.45-0.82 m Collapse of marine-based sectors of the Antarctic Ice Sheet, if initiated, would add no more than several tenths of a meter by 2100. Figure 13.27
Trends around Australia Altimeter 1993-2012 and tide gauges (dots) Spatial patterns show large regional departures from global mean sea level rise because of other influences such as El Nino/Southern Oscillation SOI included SOI removed Source: White et al, Earth-Science Reviews, 2014
Contributing processes lead to non-uniform SLR Glacial Isostatic Adjustment Ocean dynamical response Glacier mass loss Ice sheet mass loss SLR Sum For RCP 8.5 in 2080 2099 relative to 1986-2005 About 70% of the global coastlines are projected to experience a sea level change within 20% of the global mean sea level change.
Sea level rise projections for Australia Method similar to IPCC: Warming/cooling of the ocean (thermal expansion/contraction) Ocean density, circulation Change in mass of glaciers and ice sheets and distribution of mass on the Earth Changes in terrestrial storage Land movement (Glacial Isostatic Adjustment) 0.37-0.50 m 0.45-0.67 m 0.43-0.59 m 0.58-0.86 m Source: McInnes et al, AMOJ (2015) Australian region rates of SLR are similar in magnitude to GMSLR
Sea level projections for Australia relative to 1986-2005 Tide gauge measurements Altimeter measurements + 95% Tide gauge (reconstruction) Range of model projected change RCP 8.5 and RCP 2.5 Source: McInnes et al, AMOJ (2015)
Marine Projections 1. Regional projections of mean sea level rise 2. Allowances for extreme sea levels 3. Projections of changes in SSTs, aragonite and ph
Highest Astronomical Tide 1-in-100 year storm tide height (Source: McInnes et al, 2016) Estimated from modelled sea levels over 66 year period Includes tides and surge but not wave effects (source: Haigh et al, 2014)
Sea level allowances - based on Hunter (2012) 1. Consider raising an asset (or its protection) by an amount that ensures future level of protection is unchanged from today s 2. Takes into account (1) mean sea level rise - Δz (2) sea level rise uncertainty - σ 2 derived from 5-95% uncertainty (3) extreme sea level characteristics the slope of the extreme sea level return period curve λ 3. Allowance: A=Δz+σ 2 /2λ (Assuming normal distribution for SLR range) σ Δz λ
Sea level rise will increase the frequency of extreme sea levels Allowance: A=Δz+σ 2 /2λ Allowance Planning Benchmark Allowance Planning Benchmark SLR Source: McInnes et al, AMOJ (2015)
Sea level and expected number of exceedances Allowance: A=Δz+σ 2 /2λ
Sea level allowances 1. At 2030, allowances are close to midrange SLR scenario 2. At 2090, allowances are close to high end SLR scenarios (* assumes storminess doesn t change)
Caveats: Storms (frequency, intensity and locations of occurrence) may change in the future Waves and their future changes are not taken into consideration. Source: Hemer et al, 2013
Projected Impacts on the Coastal Environment Increased sea level will increase the frequency of extreme sea level events and will increase the frequency of coastal inundation and erosion. Sea Level Allowances provide guidance on how to adapt to rising sea levels.
Marine Projections 1. Regional projections of mean sea level rise 2. Allowances for extreme sea levels 3. Projections of changes in SSTs, aragonite and ph
Mean State 1986-2005 SST (C) Observed = CSIRO Atlas of Regional Seas (CARS)
Mean State 1986-2005 ph Aragonite Saturation State (Ω AR ) Observed = spatial reconstruction of ph and Ω AR Source: Lenton et al, 2015
SST projections Projected change in SST by 2090 Measurements are from IMOS reference stations
Aragonite projections Projected change in Aragonite by 2090 Measurements are from IMOS reference stations
ph projections Projected change in ph by 2090 Measurements are from IMOS reference stations
Projected Impacts on the Marine Environment Increased temperature and acidification are expected to have significant impacts on the long-term health, diversity and viability of many marine species, with consequences for fin and shellfish fisheries, aquaculture, tourism and coastal protection. Hoegh-Guldberg et al, 2007
Summary New climate projections for the NRM regions of Australia show that in response to rising atmospheric CO 2 levels : sea levels will be higher, marine environment will be warmer and more acidic under all emissions scenarios Projected values vary around the coast The magnitude of the change will be proportional to the level of emissions References Special Issue of AMOJ: McInnes, K.L., Church, J.A., Monselesan, D. Hunter, J.R. O Grady, J.G., Haigh, I.D. and Zhang, X., 2015: Sea-level Rise Projections for Australia: Information for Impact and Adaptation Planning. Australian Meteorology and Oceanography Journal. 65: 127 149. Lenton, A., McInnes, K.L., and O Grady J.G. 2016: Marine Projections of Warming and Ocean Acidification in the Australasian Region. Australian Meteorology and Oceanography Journal. 65(1) S2-S28.
Thank you For more information kathleen.mcinnes@csiro.au http://www.cmar.csiro.au/sealevel/
But, how the SLR uncertainty is used has large effect on the allowances A=Δz+σ 2 /2λ Allowances are larger for large SLR uncertainty and small extreme sea level return slopes. σ is the standard deviation of the SLR projection uncertainty The 5 to 95% model range is assumed to represent the 5-95% uncertainty range But the 5-95% model range is assumed to be likely i.e. represent the 17-83% of the total range For RCP 8.5 in 2090 assuming WGI range to be 17-83% means the allowances would become around 0.4 m larger. (~50% higher) Source: McInnes et al (2015)