Response of Arctic Freshwater to the Arctic Oscillation in Coupled Climate Models

Abstract

The freshwater content (FWC) of the Arctic Ocean is intimately linked to the stratification—a physical characteristic of the Arctic Ocean with wide relevance for climate and biology. Here, we explore the relationship between atmospheric circulation and Arctic FWC across 12 different control-run simulations from phase 5 of the Coupled Model Intercomparison Project. Using multiple lagged regression, we seek to isolate the linear response of Arctic FWC to a step change in the strength of the Arctic Oscillation (AO) as well as the second and third orthogonal modes of SLP variability over the Arctic domain. There is broad agreement among models that a step change to a more anticyclonic AO leads to an increase in Arctic FWC, with an e-folding time scale of 5–10 yr. However, models differ widely in the degree to which a linear response to SLP variability can explain FWC changes. Although the mean states, time scales, and magnitudes of FWC variability may be broadly similar, the physical origins of variability are highly inconsistent among models. We perform a robustness test that incorporates a Monte Carlo approach to determine which response functions are most likely to represent causal, physical relationships within the models and which are artifacts of regression. Convolution with SLP reanalysis data shows that the four most robust response functions have some skill at reproducing observed accumulation of FWC during the late 1990s and 2000s, consistent with the idea that this change was largely wind driven.

Forced Changes in the Arctic Freshwater Budget Emerge in the Early 21st Century

“…So, while the results presented here have the caveat that they are derived from a single model, this study presents a first assessment of the changes in the Arctic FW budget in the context of internal variability, which is only possible when using an ensemble of simulations from one model. By enabling the separation of internal variability from the forced response, this study fills a clear gap in our understanding of the changing Arctic FW budget (as identified in Cornish et al, 2020;Lique et al, 2016).…”

“…Furthermore, Cornish et al. (2020) find that the strength of the relationship between sea level pressure and liquid FW storage variability varies greatly between different CMIP5 models and is weaker than in the model used in Johnson et al. (2018), leaving room for other contributions to the liquid FW content change beside those driven by changes in sea level pressure.…”

Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model

“…because the Green function has a singularity (in the form of a Dirac's δ contribution) for = t 0 29 . We remark that in previous works [33][34][35][36]38 , the linear prediction of the desired climate observable is instead obtained by convolving time pattern of another climatic observable -assumed to be the driver -rather than the actual external forcing -with an effective transfer function -rather than the true Green function. The conditions under which climate observables can be used as both predictands and predictors have been discussed by Lucarini 29 .…”

Arctic Ocean Freshening Linked to Anthropogenic Climate Change: All Hands on Deck

“…The Beaufort Gyre is thought to be driven by a balance between the stress from anticyclonic winds encircling the Beaufort High in sea level pressure and ocean eddies (see, for instance, Manucharyan et al, 2016). Changes in the Beaufort High are believed to contribute to the observed Beaufort Gyre freshwater increase (Cornish et al, 2020). But debates continue on the importance of sea ice, of ocean bathymetry, of the relationship to the Arctic Ocean general circulation, such as the Transpolar Drift, and of the transient dynamics of freshwater storage and release.…”