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Year‐to‐year forecasts of the Arctic climate conditions have drawn much interest in recent decades. This study investigates the primary drivers responsible for interannual variations (without multi‐decadal trends) of air temperature at 2 m (T2m) and sea ice concentration (SIC) over the Barents‐Kara Seas (BKS) during September from 1950 to 2021. The Arctic Dipole (AD), a leading factor in the BKS variability, plays an important role via influencing large‐scale atmospheric circulations and local thermodynamical feedbacks (i.e., vapor and albedo feedbacks). During a negative AD phase, the positive surface air temperature advection anomalies warm up the BKS region and promote sea ice melting, which in turn maintains the below‐normal sea ice and warmer‐than‐normal conditions via positive vapor and albedo feedbacks. Moreover, our results suggest that the sea surface temperature (SST) variability in the midlatitudes of the North Atlantic in the preceding month could also be an important driver of the SIC variability over the BKS area. The anomalous temperature advections from the surface to the upper troposphere are accompanied by a Rossby wave‐type atmospheric response, which intensifies the energy exchanges between the ocean and the atmosphere. Local SST anomalies associated with the surface heat flux anomalies further persist in the following month and influence sea ice variations due to their long‐lasting memory. A better understanding of the mechanisms of interannual climate variabilities over the BKS region in boreal early autumn is helpful to improving the Arctic regional climate predictions. Key Points: Understanding primary drivers of the interannual climate variabilities over the Arctic is essential to improve the regional prediction skillsThe Arctic Dipole is mainly responsible for driving the Barents‐Kara Seas (BKS) surface air temperature interannual variability in SeptemberThe North Atlantic sea surface temperature variability at 1‐month lead is associated with the early autumn sea ice cover variability in the BKS region [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis. [ABSTRACT FROM AUTHOR]

A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic. Plain Language Summary: Changing Arctic sea ice conditions since the late 1970s have exerted profound impacts on environment and ecosystem at the high latitudes and have been suggested to affect midlatitude weather and climate, although this topic has been controversial. In order to improve our understanding on how Arctic sea ice changes influence local and remote weather and climate, a coordinated set of experiments has been performed using various state‐of‐the‐art atmosphere‐only models to study the linkages between the Arctic climate change and lower latitudes. This study uses seven models following a common experimental protocol to investigate the atmospheric circulation changes forced by Arctic sea ice variability. The protocol allows the Arctic sea ice‐driven variability (SIDV) to be singled out. In boreal winter, the Arctic SIDV is ~0.18 hPa2 and accounts for only ~1.5% of the total variance for sea level pressure, while it is ~0.35 K2 and accounts for ~21% for surface air temperature. The results also suggest that using insufficient ensembles always leads to an overestimation of SIDV, and more than 100 and 40 ensemble members are needed for sea level pressure and surface air temperature within the Arctic, respectively, to separate the SIDV from the variability due to other factors, primarily the atmospheric internal variability. Key Points: Arctic sea ice variations drive ~1.5% of boreal winter Arctic SLP variance during 1979–2014 in coordinated 130‐member AGCM experimentsAn accurate quantification of the impacts of Arctic sea ice‐driven SLP variability requires an ensemble size greater than 100 membersInsufficient ensemble size always leads to an overestimation of the Arctic sea ice‐driven variance within and outside Arctic [ABSTRACT FROM AUTHOR]