Simulation of the Global Coupled Climate/Ice Sheet System over Millennial Timescales
Bibliographic record
Abstract
Ice sheets are important components of the Earth system that are expected to respond strongly to anthropogenic forcing of climate. The aim of this work is to use numerical climate and ice sheet modelling to identify and understand the millennial-scale interaction between the Antarctic and Greenland Ice Sheets (AIS and GIS) and global climate. An initial modelling effort evaluated the response of ice shelves and ice sheets to future CO2 emission scenarios by quantifying the duration and magnitude of summer melt periods. A temperature threshold based on positive degree days was applied to bias-corrected University of Victoria Earth System Climate Model (UVic ESCM) output spanning 1000 years into the future. The simulations indicated that an increase in summer melting over most of the GIS, the Ross and Ronne-Filchner ice shelves, and large sections of the West Antarctic Ice Sheet (where little present-day ablation occurs) could occur if future emissions are not curtailed. This initial work highlighted the need to assess the dynamic response of ice sheets to climate change. I therefore developed an ice sheet/climate model comprised of the UVic ESCM and the Pennsylvania State University Ice Sheet Model. Coupling these models required development of new techniques, including subgrid-scale energy balance calculations that incorporate a surface air temperature (SAT) model bias correction procedure. In testing the model, I found that climate model SAT bias, meltwater refreezing and albedo variations play an important role in simulated ice sheet evolution, particularly as more of the ice surface experiences melting conditions. The model realistically reproduced the AIS and GIS, and captured the surface mass balance (SMB) distributions for both ice sheets well for the present day, including narrow GIS ablation zones. The newly developed model was used to carry out a suite of experiments designed to assess the behavior of the GIS under elevated-CO2 conditions. A deglacial SMB-based GIS stability threshold was identified between 3-4x preindustrial atmospheric levels (PAL) of CO2. Below the threshold, GIS retreat still occurred but the ice ultimately stabilized in a ‘reduced ice sheet’ configuration, while at CO2 >= 4x PAL CO2, ice retreated to mountain ice caps. Ice sheet inception simulations indicated that above 4x PAL CO2, ice growth was limited, while at 4x PAL CO2 ice was able to reach the eastern Greenland coastline. Between 2-3x PAL CO2, separate ice caps in the southern and eastern mountains coalesced and exported ice onto the lowland plains. Large-scale ice sheet growth was limited until 1-2x PAL CO2. GIS ice loss increased with greater cumulative CO2 emissions in transient simulations. However, the ice sheet was able to briefly overshoot the CO2 stability threshold without experiencing drastic ice retreat due to the long response time of the simulated GIS relative to the rate of deep ocean carbon uptake. Finally, several model experiments were carried out using the coupled model to examine the impact of ocean melt-driven AIS retreat on the oceanic circulation and structure. This retreat produced freshwater fluxes to the Southern Ocean that were of the same magnitude (and initially greater) than the background continental flux, and continued for 3000 years after the initial shift to high-melt conditions. The Ross and Weddell Seas became productive sea ice export regions, which resulted in higher salinities in these seas and very low ocean temperatures. Enhanced sea ice export and melt in the open Southern Ocean contributed to a slight shallowing and weakening of the North Atlantic Deepwater circulation cell, that would reinforce predicted trends expected as a result of future anthropogenic CO2 emissions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".