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

• Other Authors: CSIRO Oceans and Atmosphere (hasAssociationWith), IMAS Data Manager (pointOfContact), Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS) (hasAssociationWith), King, Matt (pointOfContact), King, Matt (hasPrincipalInvestigator), Matt King (pointOfContact), Matt King (hasPrincipalInvestigator), School of Technology, Environments and Design, University of Tasmania (UTAS) (hasAssociationWith), Zhang, Shujing (pointOfContact), Zhang, Shujing (hasPrincipalInvestigator), Zhang, Xuebin (hasPrincipalInvestigator)
• Format: Dataset
• Language: unknown
• Published: Australian Ocean Data Network
• Subjects: oceans; EARTH SCIENCE | CLIMATE INDICATORS | ATMOSPHERIC/OCEAN INDICATORS | SEA LEVEL RISE; EARTH SCIENCE | CLIMATE INDICATORS | CRYOSPHERIC INDICATORS | GLACIAL MEASUREMENTS | GLACIER/ICE SHEET THICKNESS; EARTH SCIENCE | SOLID EARTH | GEOMORPHIC LANDFORMS/PROCESSES | COASTAL PROCESSES | SEA LEVEL CHANGE; EARTH SCIENCE | SOLID EARTH; Glaciology; EARTH SCIENCES; PHYSICAL GEOGRAPHY AND ENVIRONMENTAL GEOSCIENCE; Physical Oceanography; OCEANOGRAPHY; Ice Sheet
• Online Access: https://researchdata.edu.au/2019-20-honours-ice-melting/1591161

Maintenance and Update Frequency: notPlanned Statement: 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 ...