Wide disagreement among individual modeling studies has contributed to a debate on the role of recent sea ice loss in the Arctic amplification of global warming and the Siberian wintertime cooling trend. We perform coordinated experiments with six atmospheric general circulation models forced by the observed and climatological daily sea ice concentration and sea surface temperature. The results indicate that the impact of the recent sea ice decline is rather limited to the high‐latitude lower troposphere in winter, and the sea ice changes do not significantly lead to colder winters over Siberia. The observed wintertime Siberian temperature and corresponding circulation trends are reproduced in a small number of ensemble members but not by the multimodel ensemble mean, suggesting that atmospheric internal dynamics could have played a major role in the observed trends.

Observation shows that eastern China experienced an interdecadal shift in the summer precipitation during the second half of the 20th century. The summer precipitation increased in the middle and lower reaches of the Yangtze River valley, whereas it decreased in northern China. Here we use a coupled ocean–atmosphere general circulation model and multi-ensemble simulations to show that the interdecadal shift is mainly caused by the anthropogenic forcing. The rapidly increasing greenhouse gases induce a notable Indian Ocean warming, causing a westward shift of the western Pacific subtropical high (WPSH) and a southward displacement of the East Asia westerly jet (EAJ) on an interdecadal timescale, leading to more precipitation in Yangtze River valley. At the same time the surface cooling effects from the stronger convection, higher precipitation and rapidly increasing anthropogenic aerosols contribute to a reduced summer land–sea thermal contrast. Due to the changes in the WPSH, the EAJ and the land–sea thermal contrast, the East Asian summer monsoon weakened resulting in drought in northern China. Consequently, an anomalous precipitation pattern started to emerge over eastern China in the late 1970s. According to the model, the natural forcing played an opposite role in regulating the changes in WPSH and EAJ, and postponed the anthropogenically forced climate changes in eastern China. The Indian Ocean sea surface temperature is crucial to the response, and acts as a bridge to link the external forcings and East Asian summer climate together on a decadal and longer timescales. Our results further highlight the dominant roles of anthropogenic forcing agents in shaping interdecadal changes of the East Asian climate during the second half of the 20th century.

It is now well established that the Arctic is warming at a faster rate than the global average. This warming, which has been accompanied by a dramatic decline in sea ice, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998–2012. This is a counter-intuitive impact under global warming given that land regions should warm more than ocean (and the global average). Some studies have proposed a causal teleconnection from Arctic sea-ice retreat to Eurasian wintertime cooling; other studies argue that Eurasian cooling is mainly driven by internal variability. Overall, there is an impression of strong disagreement between those holding the “ice-driven” versus “internal variability” viewpoints. Here, we offer an alternative framing showing that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the lens of dynamics (linked primarily to internal variability with some potential contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea-ice retreat; warms Eurasia). This approach, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allows both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that Eurasian cooling of this magnitude is consistent with internal variability, with some periods exhibiting stronger cooling than others, either by chance or by forced changes. Rather than posit a “yes-or-no” causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea-ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming.

We have used an Atmospheric General Circulation Model with a large ensemble (300) to explore the atmospheric responses during the autumn–winter (September to February) to the projected sea-ice free Arctic in autumn (September to November). The detectability of the responses against the internal variability has also been studied. Three ensemble experiments have been performed, the control (CONT) forced by the simulated present-day Arctic sea-ice concentration (SIC) and sea surface temperature (SST), the second forced by the projected autumn Arctic SIC free and present-day SSTs (SENSICE) and the third forced by the projected autumn Arctic SIC free and projected SSTs (SENS). The results show that the disappearance of autumn Arctic sea-ice can cause significant synchronous near-surface warming and increased precipitation over the regions where the sea-ice is removed. The changes in autumn surface heat flux (sensible plus latent), surface air temperature (SAT) and precipitation averaged over the sea-ice reduction region between the SENS and the CONT are about 46, 43 and 50 % more respectively than the changes between the SENSICE and the CONT, which is consistent with the prescribed boundary setting: the surface temperature warming averaged over the sea-ice reduction region in the SENS relative to the CONT is 48 % higher than that in the SENSICE relative to the CONT. The response shows a significant negative Arctic Oscillation (AO) in the troposphere during autumn and December. However, the negative AO does not persist into January–February (JF). Instead, 500 hPa geopotential height (GH) response presents a wave train like pattern in JF which is related to the downstream propagation of the planetary wave perturbations during November–December. The SAT increases over northern Eurasia in JF in accordance with the atmosphere circulation changes. The comparison of the atmosphere response with the atmosphere internal variability (AIV) shows that the responses of SAT and precipitation in the Arctic far exceed the AIV in autumn and the response of the 500 hPa GH is comparable to the AIV in autumn, but none of the responses during JF exceeds the AIV.

Projected global warming is not spatially uniform and one of the minima in warming occurs in the North Atlantic (NA). Several models from the Coupled Model Intercomparison Project Phase 5 even projected a slight NA cooling in 2081–2100 relative to 1986–2005. Here we show that, by our simulations performed with the Bergen Climate Model (BCM), an autumn (September to November) sea-ice free Arctic (SIF) contributes to the NA warming minimum by weakening the Atlantic meridional overturning circulation (AMOC). The role of the air–sea interaction in the response to the SIF, which has not been widely discussed in the literature, has been highlighted by the results presented in this study.

During the past decades, the Arctic has experienced significant tropospheric warming, with varying decadal warming rates. However, the relative contributions from potential drivers and modulators of the warming are yet to be further quantified. Here, we utilize a unique set of multi‐model large‐ensemble atmospheric simulations to isolate the respective contributions from the combined external radiative forcing (ERF‐AL), interdecadal Pacific variability (IPV), Atlantic multidecadal variability (AMV), and Arctic sea‐ice concentration changes (ASIC) to the warming during 1979–2013. In this study, the ERF‐AL impacts are the ERF impacts directly on the atmosphere and land surface, excluding the indirect effects through SST and SIC feedback. The ERF‐AL is the primary driver of the April–September tropospheric warming during 1979–2013, and its warming effects vary at decadal time scales. The IPV and AMV intensify the warming during their transitioning periods to positive phases and dampen the warming during their transitioning periods to negative phases. The IPV impacts are prominent in winter and spring and are stronger than AMV impacts on 1979–2013 temperature trends. The warming impacts of ASIC are generally restricted to below 700 hPa and are strongest in autumn and winter. The combined effects of these factors reproduce the observed accelerated and step‐down Arctic warming in different decades, but the intensities of the reproduced decadal variations are generally weaker than in the observed.