Dear Cryosphere community,
The Model Evaluation and Diagnostics team (@pboubel) and the ISM team (@mtetley) at ACCESS-NRI are currently working on a set of recipes to evaluate ISMIP (Ice Sheet Model Intercomparison Project) outputs. Our goal is to create a robust framework that leverages both existing tools and data to assess the performance of ice sheet models. Additionally, we are working on making this collection available on NCI’s Gadi, ensuring accessibility for researchers within the community.
As part of this effort, we are looking for input on the observational datasets that would be most useful for evaluating ISMIP outputs. Below is a list of datasets we’ve identified, but we’d love to hear your thoughts on whether these are sufficient or if there are other key datasets we should consider incorporating:
- Surface Ice Velocity (e.g., MEaSUREs): High-resolution ice velocity measurements to evaluate ice sheet flow.
- Ice Sheet Elevation (e.g., ICESat, ICESat-2, CryoSat-2): Data on ice sheet elevation changes over time, crucial for assessing model simulations of ice thinning/thickening.
- Ice Sheet Mass Balance (e.g., GRACE, GRACE-FO): Observations of ice sheet mass changes from gravity measurements?
- Surface Melt and Accumulation (e.g., MAR, RACMO): ??
- Bedrock Topography and Ice Thickness (e.g., BedMachine, BEDMAP2): High-resolution bedrock and ice thickness data, vital for assessing model initialization and basal conditions.
- Sea-Level Rise Observations (e.g., altimetry from Jason satellites): Sea-level rise data to compare against model projections of ice sheet contributions to global sea levels.
- Calving Front Locations (e.g., Landsat, Sentinel-1/2 imagery): Satellite images tracking glacier calving front positions?
We welcome any suggestions on additional datasets or considerations that could improve the evaluation of ISMIP model outputs. Your feedback will help us ensure we are using the best available observations.
Thanks in advance for your input!
Romain