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Sea Level: Current knowledge, gaps, and challenges UFORIC

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Sea Level: Current knowledge, gaps, and challenges UFORIC Understanding Flooding on Reef-lined Island Coasts Workshop

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Sea Level: Current knowledge, gaps, and challenges UFORIC

  1. 1. UFORIC Workshop | Monday, 05 February, 2018 Understanding Flooding on Reef-lined Island Coasts Sea Level: Current knowledge, gaps, and challenges Phil Thompson University of Hawaii
  2. 2. Workshop goals: Discuss the state-of-the-art and identify knowledge gaps preventing us from answering the following two questions … 1. Can we estimate changes in habitability over the next 10 to 50 years? 2. Can we operationally predict flooding conditions? Sea Level: Current knowledge, gaps, and challenges
  3. 3. 1) Global a) How fast is global mean sea level rising? b) What are the contributions to global mean sea level rise? c) Is the rate accelerating? d) How much will global sea level rise by 2030? 2050? 2070? 2) Regional and local a) How much and why do regional/local rates differ from the global rate? b) How do regional and local processes factor into sea level projections? c) How will future sea level change affect the frequency of tidal flooding? Changes in habitability over the next 10 to 50 years
  4. 4. 20th Century rate (tide gauges) • Essential for historical context and sensitivity of GMSL to global temperature • Estimates range from 1.3-1.7 mm/yr depending on reconstruction technique • Newest estimates tend to be on lower end • Given the realities of the TG dataset, uncertainty is not likely to improve. Budget • Difficult to close due to lack observations • Roughly 1/2 thermal expansion, 1/2 melting of ice on land (IPCC AR5) Global mean sea level rise: Observations Natarov et al. (2017), doi:10.1002/2016GL071523
  5. 5. Natarov et al. (2017), doi:10.1002/2016GL071523Gregory et al. (2013), doi:10.1175/JCLI-D-12-00319.1 20th Century acceleration • Difficult to ascertain with certainty due to decadal variability in reconstructions • Potential reasons for lack of acceleration: • Sub-optimal sampling (Natarov et al., 2017) • Volcanic activity (e.g., Gregory et al., 2013) Global mean sea level rise: Observations
  6. 6. Last 60 years (tide gauges) Global mean sea level rise: Observations Frederikse et al. (2018), doi:10.1175/JCLI-D-17-0502.1
  7. 7. Global mean sea level rise: Observations Courtesy of E. Leuliette, 2017 Satellite altimetry era (1993- present) • Global rate: 3.4 ± 0.4 mm/year Budget • Closed since 2005 with Argo and GRACE • Roughly 1/3 thermal expansion, 2/3 melting of ice on land (IPCC AR5) Acceleration • Positive acceleration in budget terms (2005-present) • Negative acceleration in altimetry record (1993-present), -0.057 mm/yr2
  8. 8. Global mean sea level rise: Observations Beckley et al. (2017), doi:10.1002/2017JC013090 Reevaluation of altimetry acceleration • Flawed Topex Cal-1 calibration mode (Beckley et al., 2017) • Removing this correction improves agreement with in situ TG observations • Also changes early part of the record • Isolating the secular change (Nerem et al., 2018) • Subtract effects of Pinatubo and ENSO: acceleration = 0.091 ± 0.026 mm/yr2 • Similar to acceleration in sum of components: 0.084 ± 0.008 mm/yr2 Nerem et al. (2018), In review
  9. 9. Challenges and knowledge gaps • Maintain unprecedented sampling of the global ocean by the combination of satellite altimetry, Argo, and GRACE. • GRACE: accelerometer in one satellite is down → poor data during 2017. • GRACE-FO to be launched in 2018. • Increase the number of cGPS stations • Improves altimetry-TG comparisons → improved drift detection → improved acceleration estimates Global mean sea level rise: Observations
  10. 10. IPCC AR5 projections: RCP8.5 • CMIP5-based • 0.74 [0.52 to 0.98] m by end of century • 0.30 [0.22 to 0.38] m by mid-century Are these projections too low? Global mean sea level rise: 21st century projections Church et al. (2013)
  11. 11. Uncertain ice sheet contributions • (Relatively) recent realization: Most ice sheet mass loss is due to oceanic change (not atmospheric warming). • Modelling is difficult because • Lack of observations to support simulations of polar oceans • Key ice-sheet processes operate on km scales. This … • is computationally expensive and • requires detailed knowledge of bedrock and rheology. Global mean sea level rise: 21st century projections Church et al. (2013)
  12. 12. Updated projections • Kopp et al. (2017) • Replaces CMIP5 estimates of Antarctic melt with new estimates from updated models (DeConto and Pollard, 2016) • Includes improved ocean-ice interactions, as well as basal lubrication, hydrofracturing, and mechanical collapse of ice shelves • Joint probability with non-Antarctic contributions from CMIP5 • Result is an approximate doubling of the likely range for global sea level rise by 2100 (no change for 2050, though). Global mean sea level rise: 21st century projections Kopp et al. (2017), doi:10.1002/2017EF000663
  13. 13. Challenges and knowledge gaps • Improve observations and modeling of the ocean-ice interaction • e.g., Oceans Melting Greenland (OMG) project (Willis et al.): NASA-led 5-year effort including in situ ocean observations and flyovers by aircraft altimeters. • Include updated scenarios in planning • CMIP6 • More models; more complex, higher resolution models • https://www.wcrp-climate.org/wgcm-cmip/wgcm- cmip6 Global mean sea level rise: 21st century projections https://omg.jpl.nasa.gov/portal/
  14. 14. How much and why do regional/local rates deviate from the global average? • Ocean-atmosphere dynamics and decadal climate variability • Ice melt fingerprints • Tectonic and anthropogenic vertical land motion (GPS) • Glacial isostatic adjustment (GIA) Contributions to regional and local sea level rise
  15. 15. Ocean-atmosphere dynamics and decadal climate variability • Satellite altimetry → first complete global maps of sea level change • Observational and modelling studies have vastly improved our dynamical understanding of spatial structure in sea level change in all ocean basins. Contributions to regional and local sea level rise Merrifield (2011), doi:10.1175/2011JCLI3932.1
  16. 16. Predicting decadal sea level change • Essential for planning horizons of 10-30 years. • Regional decadal trends reach 5x current global rate. • Will remain leading order throughout 21st century. • Difficult in practice • Meehl et al. (2014), BAMS, doi:10.1175/BAMS-D-12-00241.1 • CMIP6: The Decadal Climate Prediction Project (DCPP) • Boer et al. (2016), doi:10.5194/gmd-9-3751- 2016 Contributions to regional and local sea level rise
  17. 17. In the absence of accurate decadal predictions … • Scenario-based additions to GMSL rise can be a useful exercise. • e.g., a climate model projects 25 cm of SLR for San Diego by 2050, however … • … if we also experience an El Niño event during a positive phase of the PDO around that time, then SD would experience an additional sea level anomaly of 5-10 cm. Contributions to regional and local sea level rise
  18. 18. Ice melt fingerprints • Spatial structure in absolute sea level change due to the effect of melting ice • Redistribution of mass → changes in the rotation and gravitational field of Earth • GRACE → improved understanding and ability to model • Local SLR due to any given melt source can be up to 50% larger than effect on GMSL. Contributions to regional and local sea level rise Adapted from Adhikari et al. (2016), doi:10.5194/gmd-9-1087-2016 Greenland fingerprint (1 mm/yr GMSLR)
  19. 19. Contributions to regional and local sea level rise Adapted from Adhikari et al. (2016), doi:10.5194/gmd-9-1087-2016
  20. 20. Future impact of melt fingerprints • Accuracy depends on climate models’ ability to capture ocean-ice interactions • W. Antarctic collapse → unequal consequences • Median GMSLR by 2100 from Kopp et al. (2017): 1.46 m • Hawaii and N. America: 2.0-2.2 m • Asia and Europe: < 1.25 m Contributions to regional and local sea level rise Adapted from Adhikari et al. (2016), doi:10.5194/gmd-9-1087-2016 Antarctic fingerprint (1 mm/yr GMSLR)
  21. 21. Challenges and knowledge gaps • Continue to improve dynamical understanding of ocean-atmosphere interactions and decadal climate variability • Improve performance of decadal predictions in initialized climate models • Higher resolution; improved representation of processes and feedbacks • Improve observations and modeling of the ocean-ice interaction for accurate fingerprint projections Contributions to regional and local sea level rise Antarctic fingerprint (1 mm/yr GMSLR)
  22. 22. Example from 4th U.S. NCA • Sea level rise is contributing to increased “minor” flooding. • Many locations experiencing >40 days during recent years. • Increasing to 100-200 days/year by mid century. • 5 year event → 0.2 year event in the next 10-30 years for a majority of the U.S. coastline. Challenges and gaps • Incorporate updated mean sea level projections • Determine locally-relevant thresholds Increasing frequency of nuisance tidal flooding Sweet et al. (2017), doi: 10.7930/J0VM49F2
  23. 23. Monthly to seasonal forecasts • These time scales generally require a global or basin-scale model. • e.g., POAMA • Skill is generally confined to planetary wave guides (McIntosh et al., 2015). • Multiple models make up the UHSLC operational forecast product • Widlansky et al. (2017) • Provides both dynamical and statistical forecasts • Incorporates classical tide predictions to give users a sense of future observed water levels Operational sea level forecasts McIntosh et al. (2015), doi:10.1002/2015GL065091 3 mo 6 mo POAMA forecast skill relative to altimetry Widlansky et al. (2017), doi:10.1175/JAMC-D-16-0284.1
  24. 24. Challenges and knowledge gaps • Seasonal forecasting outside the tropics • Identify sources of skill and/or processes not captured • Subject of NOAA MAPP project (NOAA, UH, SIO, USF, international partners) • Forecasting sub-monthly variability • Mesoscale variability can be important for island locations; amplitudes of same order as monthly anomalies • Leverage existing regional operational ocean models Operational sea level forecasts Widlansky et al. (2017), doi:10.1175/JAMC-D-16-0284.1
  25. 25. Observations • Maintain global observing system • Increase number of cGPS stations • Empirical, locally-relevant flooding thresholds Projections • Improve climate models • Improve understanding/modelling of ocean-ice interactions • Improve understanding/modelling of decadal climate variability • Incorporate updated projections into existing products and initiatives Summary: Challenges and gaps Operational forecasts • Seasonal forecasting outside the tropics • Sub-monthly forecasts of mesoscale variability

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