The possibility that Arctic sea ice loss weakens mid-latitude westerlies, promoting more severe cold winters, has sparked more than a decade of scientific debate, with apparent support from ...observations but inconclusive modelling evidence. Here we show that sixteen models contributing to the Polar Amplification Model Intercomparison Project simulate a weakening of mid-latitude westerlies in response to projected Arctic sea ice loss. We develop an emergent constraint based on eddy feedback, which is 1.2 to 3 times too weak in the models, suggesting that the real-world weakening lies towards the higher end of the model simulations. Still, the modelled response to Arctic sea ice loss is weak: the North Atlantic Oscillation response is similar in magnitude and offsets the projected response to increased greenhouse gases, but would only account for around 10% of variations in individual years. We further find that relationships between Arctic sea ice and atmospheric circulation have weakened recently in observations and are no longer inconsistent with those in models.
Since the 1970s sea ice extent has decreased dramatically in the Northern Hemisphere and increased slightly in the Southern Hemisphere, a difference that is potentially explained by ozone depletion ...in the Southern Hemisphere stratosphere. In this study we consider the impact of stratospheric ozone depletion on Antarctic sea ice extent using a climate model forced with observed stratospheric ozone depletion from 1979 to 2005. Contrary to expectations, our model simulates a year‐round decrease in Antarctic sea ice due to stratospheric ozone depletion. The largest percentage sea ice decrease in our model occurs in the austral summer near the coast of Antarctica, due to a mechanism involving offshore Ekman sea ice transport. The largest absolute decrease is simulated in the austral winter away from the coast of Antarctica, in response to an ocean warming that is consistent with a poleward shift of the large‐scale pattern of sea surface temperature. Our model results strongly suggest that processes not linked to stratospheric ozone depletion must be invoked to explain the observed increase in Antarctic sea ice extent.
Over the past half-century, the ozone hole has caused a poleward shift of the extratropical westerly jet in the Southern Hemisphere. Here, we argue that these extratropical circulation changes, ...resulting from ozone depletion, have substantially contributed to subtropical precipitation changes. Specifically, we show that precipitation in the southern subtropics in austral summer increases significantly when climate models are integrated with reduced polar ozone concentrations. Furthermore, the observed patterns of subtropical precipitation change, from 1979 to 2000, are very similar to those in our model integrations, where ozone depletion alone is prescribed. In both climate models and observations, the subtropical moistening is linked to a poleward shift of the extratropical westerly jet. Our results highlight the importance of polar regions for the subtropical hydrological cycle.
Arctic sea ice loss may influence midlatitude climate by changing large‐scale circulation. The extent to which climate change can be understood as greenhouse gas‐induced changes that are modulated by ...this loss depends on how additive the responses to the separate influences are. A novel sea ice nudging methodology in a fully coupled climate model reveals that the separate effects of doubled atmospheric carbon dioxide (CO2) concentrations and associated Arctic sea ice loss are remarkably additive and insensitive to the mean climate state. This separability is evident in several fields throughout most of the year, from hemispheric to synoptic scales. The extent to which the regional response to sea ice loss sometimes agrees with and sometimes cancels the response to CO2 is quantified. The separability of the responses might provide a means to better interpret the diverse array of modeling and observational studies of Arctic change and influence.
Plain Language Summary
The decrease in Arctic sea ice area may influence midlatitude climate and weather by changing hemispheric‐scale winds. Whether the change in winds due to this Arctic sea ice loss can be cleanly separated from the wind changes due to human‐induced greenhouse gas increase remains a question. Here using a global climate computer model, we explicitly separate the climate response to Arctic sea ice loss from the climate response to a doubling of atmospheric carbon dioxide (CO2) concentration with fixed Arctic sea ice. We show that the two separate responses add up to the full climate response to a doubling of CO2 concentration. We also show that it is not important whether CO2 is doubled with a large amount of Arctic sea ice or a small amount or whether Arctic sea ice decreases in a warm climate or in a cold climate. These results imply that some features of human‐induced climate change may be explained by Arctic sea ice melting and may help to explain the many different greenhouse gas‐induced wind changes found in modeling and observational studies.
Key Points
New framework to isolate response to Arctic sea ice loss and greenhouse gas forcing in a coupled system
Response to Arctic sea ice loss and CO2 doubling is very additive, even at small spatial scales
Areas where sea ice loss amplifies or cancels response to doubled CO2 can be quantified
The need for skillful seasonal forecasts of Arctic sea ice is rapidly increasing. Technology to perform such forecasts with coupled atmosphere‐ocean‐sea ice systems has only recently become ...available, with previous skill evaluations mainly limited to area‐integrated quantities. Here we show, based on a large set of retrospective ensemble model forecasts, that a dynamical forecast system produces skillful seasonal forecasts of local sea ice retreat and advance dates—variables that are of great interest to a wide range of end users. Advance dates can generally be skillfully predicted at longer lead times (~5 months on average) than retreat dates (~3 months). The skill of retreat date forecasts mainly stems from persistence of initial sea ice anomalies, whereas advance date forecasts benefit from longer time scale and more predictable variability in ocean temperatures. These results suggest that further investments in the development of dynamical seasonal forecast systems may result in significant socioeconomic benefits.
Plain Language Summary
As Arctic waters have become increasingly accessible in recent years, there is an urgent need to improve forecasts of Arctic sea ice on seasonal (1–12 month) timescales. Statistical models, traditionally employed to perform such forecasts, may suffer from large errors due to the rapid changes in the Arctic environment. Consequently, creating seasonal forecasts may increasingly depend on the use of dynamical forecast models. Technology to obtain sea ice forecasts with such systems have only recently become available, with previous skill evaluations focused on area‐integrated quantities such as total Arctic sea ice. It is currently not known if skillful seasonal predictions of more user‐relevant local sea ice information can be obtained. Here we show, for the first time, that a dynamical forecast system is able to produce skillful seasonal forecasts of local retreat and advance dates ‐ quantities that are of obvious interest to a large group of end‐users. In addition, we identify physical mechanisms responsible for the obtained skill.
Key Points
A dynamical forecast system produces skillful seasonal forecasts of socioeconomically relevant sea ice events
Advance dates can generally be skillfully predicted at longer lead times (~5 months on average) than retreat dates (~3 months)
Skill of retreat date forecasts mainly stems from persistence, whereas advance date forecasts benefit from predictable ocean temperatures
We assess the seasonal forecast skill of pan‐Arctic sea ice area in a dynamical forecast system that includes interactive atmosphere, ocean, and sea ice components. Forecast skill is quantified by ...the correlation skill score computed from 12 month ensemble forecasts initialized in each month between January 1979 to December 2009. We find that forecast skill is substantial for all lead times and predicted seasons except spring but is mainly due to the strong downward trend in observations for lead times of about 4 months and longer. Skill is higher when evaluated against an observation‐based dataset with larger trends. The forecast skill when linear trends are removed from the forecasts and verifying observations is small and generally not statistically significant at lead times greater than 2 to 3 months, except for January/February when forecast skill is moderately high up to an 11 month lead time. For short lead times, high trend‐independent forecast skill is found for October, while low skill is found for November/December. This is consistent with the seasonal variation of observed lag correlations. For most predicted months and lead times, trend‐independent forecast skill exceeds that of an anomaly persistence forecast, highlighting the potential for dynamical forecast systems to provide valuable seasonal predictions of Arctic sea ice.
Key Points
We present and explain forecast skill of sea ice area in a dynamical model
Forecast skill is very sensitive to the magnitude of the trend
Achieved forecast skill generally exceeds that of persistence forecasts
Abstract There is great uncertainty in the atmospheric circulation response to future Arctic sea ice loss, with some models predicting a shift towards the negative phase of the North Atlantic ...Oscillation (NAO), while others predicting a more neutral NAO response. We investigate the potential role of systematic model biases in the spread of these responses by modifying the unperturbed (or ‘control’) climate (hereafter referred to as the ‘basic state’) of the Canadian Earth system model version 5 (CanESM5) in sea ice loss experiments based on the protocol of the Polar Amplification Model Intercomparison Project. We show that the presence or absence of the stratospheric pathway in response to sea ice loss depends on the basic state, and that only the CanESM5 version that shows a weakening of the stratospheric polar vortex features a strong negative NAO response. We propose a mechanism that explains this dependency, with a key role played by the vertical structure of the winds in the region between the subtropical jet and the stratospheric polar vortex (‘the neck region winds’), which determines the extent to which anomalous planetary wave activity in response to sea ice loss propagates away from the polar vortex. Our results suggest that differences in the models’ basic states could significantly contribute to model spread in the simulated atmospheric circulation response to sea ice loss, which may inform efforts to narrow the uncertainties regarding the impact of diminishing sea ice on mid-latitude climate.
Operational seasonal to interannual forecasting systems are in continued development around the world. Various studies have applied models to the dynamical forecasting of sea ice, particularly in the ...Arctic. The Antarctic, however, has received relatively little attention, with few previous endeavours to quantify operational forecast skill of sea ice. This study assesses sea ice extent prediction skill of the Canadian Seasonal to Interannual Prediction System version 2 (CanSIPSv2) in the Pan-Antarctic domain as well as in various sectors of the Southern Ocean. The forecast skill of GEM-NEMO, one of two constituent models that together comprise CanSIPSv2, is found to generally exceed that of the other, CanCM4i. This difference is potentially due to substantial model drift of sea ice extent away from observations in CanCM4i, in addition to their different initializations of sea ice thickness. Both models show significant forecast skill exceeding that of an anomaly persistence forecast. Prediction skill was found to vary substantially across different sectors of the Southern Ocean. Moreover, our analysis also finds that CanSIPSv2 forecast skill in the Antarctic shows a dependence on time period, demonstrating generally lower skill than seen in the Arctic over the years 1980-2010, in contrast to generally higher skill than in the Arctic over the years 1980-2019.
PDF
