2019-20 Honours project - Sea level fingerprints associated with future land ice melting

• Other Authors: Zhang, Shujing (hasPrincipalInvestigator), Zhang, Shujing (pointOfContact), King, Matt (hasPrincipalInvestigator), King, Matt (pointOfContact), Zhang, Xuebin (hasPrincipalInvestigator), Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS) (hasAssociationWith), School of Technology, Environments and Design, University of Tasmania (UTAS) (hasAssociationWith), CSIRO Oceans and Atmosphere (hasAssociationWith)
• Format: Dataset
• Language: unknown
• Published: University of Tasmania, Australia
• Subjects: oceans; SEA LEVEL RISE; EARTH SCIENCE; CLIMATE INDICATORS; ATMOSPHERIC/OCEAN INDICATORS; GLACIER/ICE SHEET THICKNESS; CRYOSPHERIC INDICATORS; GLACIAL MEASUREMENTS; SEA LEVEL CHANGE; SOLID EARTH; GEOMORPHIC LANDFORMS/PROCESSES; COASTAL PROCESSES; Glaciology; EARTH SCIENCES; PHYSICAL GEOGRAPHY AND ENVIRONMENTAL GEOSCIENCE; Physical Oceanography; OCEANOGRAPHY; Caron; Gomez; Keller; Ice Sheet
• Online Access: https://researchdata.edu.au/2019-20-honours-ice-melting/1601385; https://metadata.imas.utas.edu.au:443/geonetwork/srv/en/metadata.show?uuid=5a2a7cd8-f91a-4a05-9e1d-290873d22279; https://data.imas.utas.edu.au/attachments/5a2a7cd8-f91a-4a05-9e1d-290873d22279/Shujing_Zhang_-_Thesis.pdf

We utilize the sea level fingerprint module - ISSM’s Solid Earth and Sea level Adjustment Workbench (ISSM-SESAW), developed by NASA/Jet Propulsion Laboratory (JPL), to provide high-resolution sea level fingerprints in response to future polar ice sheet mass changes in the 21st century under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. We also explore the sensitivity of sea level fingerprints to different 1-D elastic Earth models and the spatial resolution at which mass change of polar ice sheets is resolved. Furthermore, sea level contributions by individual polar ice sheet basins in the 21st century are also estimated for some coastal cities of interest (e.g., Perth) in this research. 1. Validation of ISSM-SESAW computation A) Using monthly land water storage change for the period April 2002 to August 2016 from GRACE data (Adhikari et al., 2019), we derived associated monthly relative sea level change by ISSM. Then we derived a linear trend over the period. B) Under the assumption that ice over the GrIS and AIS melts uniformly, we computed the associated relative sea level chages using ISSM. We normalized them by the barystatic sea level change and denoted them as normalized sea level fingerprints. 2. Resolution test We prepared five unstructured meshes which have incremental spatial resolutions (i.e., 100 km, 50 km, 25 km ,10 km, 5 km) for each of the GrIS and AIS domains, respectively. We then computed sea level fingerprints using each of them in turn, forced by high-resolution ice sheet mass changes. Here we chose the high-resolution projections of ice thickness change over the GrIS (2.5 km) and AIS (5 km) in 2100 compared to 2000 under the RCP8.5 scenario (Golledge et al., 2019). Finally, we scaled the sea level fingerprints by the barystatic sea level change (i.e., normalized sea level fingerprints). 3. Sensitivity test to 1-D elastic Earth models We computed sea level fingerprints in response to uniform thinning of the GrIS and AIS with three 1-D elastic Earth models: PREM, ak135 and iasp91 (Wang et al., 2012) respectively. 4. Future sea level fingerprints associated with polar ice sheets melting We adopted PREM 1-D elastic Earth model and the optimal ISSM mesh (i.e., 10 km resolution for the GrIS and AIS domains) to compute high resolution sea level fingerprints in response to every 5-year ice thickness change over individual polar ice sheets in the 21st century under the RCP4.5 and RCP8.5 scenarios (Golledge et al., 2019). Then we derived a linear trend over the period. 5. Kernel-based sea level projections We used kernel-based sea level projection to provide sea level contributions in the 21st century from each basin over GrIS and AIS for ten selected coastal cities globally under the RCP4.5 and RCP8.5 scenarios. In kernel-based sea level projections, we combined future ice thickness changes (Golledge et al., 2019) and site-specific sea level sensitivity kernels (Mitrovica et al., 2018) to derive local sea level contributions from each drainage basin. References: Adhikari, S., Ivins, E. R., Frederikse, T., Landerer, F. W. and Caron, L. (2019) 'Sea-level fingerprints emergent from GRACE mission data', Earth Syst. Sci. Data, 11(2), pp. 629-646. Golledge, N. R., Keller, E. D., Gomez, N., Naughten, K. A., Bernales, J., Trusel, L. D. and Edwards, T. L. (2019) 'Global environmental consequences of twenty-first-century icesheet melt', Nature, 566(7742), pp. 65-72. Mitrovica, J. X., Hay, C. C., Kopp, R. E., Harig, C. and Latychev, K. (2018) 'Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice MassFlux', Journal of Climate, 31(9), pp. 3701-3709 Wang, H., Xiang, L., Jia, L., Jiang, L., Wang, Z., Hu, B. and Gao, P. (2012) 'Load Love numbers and Green's functions for elastic Earth models PREM, iasp91, ak135, and modifiedmodels with refined crustal structure from Crust 2.0', Computers & Geosciences, 49, pp. 190-199.