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To examine the effect of the snow‐albedo feedback (SAF) on the current surface climate across terrestrial regions at mid–high latitudes, we perform a series of idealized sensitivity experiments using an atmospheric general circulation model (AGCM), in which the snow albedo is assumed to be considerably smaller than that in the control experiment. When the snow albedo is reduced, the fall and spring surface air temperatures (SATs) in northern Eurasia are considerably higher than those in the control experiment. Particularly, the spring SAT at terrestrial high latitudes rises by more than 10°C, due to low snow albedo. Despite the small surface snow albedo during both fall and spring, the fall temperature difference between the two experiments is smaller than that during spring. The feedback with the hydrological effect, which accelerates snowmelt, is either nonexistent or weak during periods of seasonally low air temperatures. This result indicates that the hydrological effect significantly influences the SAF, and different magnitudes of the hydrological effect including cloud differences are a possible source of SAF uncertainty between models. The radiative albedo effect also impacts the evolution of the snow area in central Asia and eastern Europe through changes in lateral water vapour transport. Furthermore, the experiments indicate that the cooling effect of snow on land is necessary for the strength of the Siberian High and the pattern of Arctic Oscillation, suggesting that snow cover may also significantly extend the duration of Arctic Oscillation effects. [ABSTRACT FROM AUTHOR]

In sharp contrast to rapid global warming, the surface air temperature (SAT) in Northeast Asia (NEA) has exhibited strong cooling in June since 2010. Our results show that this cooling is a possible response to declining Bering Sea sea ice concentrations (BSICs) in March. A physical process analysis shows that decreasing BSICs provoke a south‐eastward‐propagating Rossby wave train and induce a strong anomalous anticyclone over the midlatitude Northwest Atlantic, resulting in tripolar anomalous sea surface temperature (SST) pattern with warm anomalies in the midlatitude Northwest Atlantic. These persistent tripolar SST anomalies generate a new Rossby wave across Eurasia in June, which enhances the cyclonic atmosphere circulation anomaly over NEA and leads to the cold SAT anomalies observed in this area. Correspondingly, in response to the sharp decline in BSIC in March, the NEA has exhibited an unprecedented cooling trend in June over the most recent decade. Plain Language Summary: In contrast to rapid global warming, the surface air temperature (SAT) over Northeast Asia (NEA) in June has exhibited a strong cooling trend since 2010, which has had an important impact on local agriculture. Here we show that reduced Bering Sea sea ice concentrations (BSICs) in March promote cold SATs in the following June in NEA. Declining BSICs in March excite a Rossby wave train that propagates eastward, causing a strong anomalous anticyclone (cyclone) over the midlatitude North Atlantic (subpolar Atlantic) and a tripolar anomalous sea surface temperature (SST) pattern by modifying the surface heat flux. The tripolar SST pattern in the North Atlantic develops in April and May due to the downstream development of the wave train; it persists in June mainly due to the ocean memory effect and subsequently generates a new Rossby wave across Eurasia via eddy‐mediated processes, provoking a cyclonic atmospheric circulation anomaly over NEA and leading to the observed cold SAT anomalies. Accompanying the significant BSIC decline in March since 2010, the atmospheric regime and SST variations over the North Atlantic in association with the cold SAT anomalies observed in NEA in June have strengthened and thus induced strong cooling over NEA. Key Points: Unusual cooling has been observed in June over Northeast Asia (NEA) under the most recent global warmingThis June cooling in NEA is consistent with declining Bering Sea sea ice concentrations (BSICs) in MarchThe Rossby wave train and the sea surface temperature anomalies in Northwest Atlantic bridge the declining BSIC in March and the cooling over NEA in June [ABSTRACT FROM AUTHOR]

This study investigates the variability of summer surface air temperature (SAT) over northern Eurasia and its precursory signals in the tropical Atlantic and northern Asian land. The leading mode of summer SAT variations features a northern Eurasian SAT tripole (NEST) pattern, with two same‐sign SAT anomaly regions over eastern Europe–western Siberia and the Far East region and an opposite‐sign SAT anomaly region around the Baikal Lake. It is found that sea surface temperature (SST) or SAT anomalies in the tropical Atlantic and rainfall‐soil moisture anomalies around the Baikal Lake during May can modulate the NEST pattern. The SST anomalies in the tropical Atlantic persist from May to summer and induce a downstream zonal wave train across northern Eurasia, consequently causing the variation in the summer NEST pattern. May rainfall anomalies around the Baikal Lake affect the overlying atmospheric circulation during summer through the 'memory' effect of soil moisture and the soil moisture‐rainfall interaction, correspondingly modulating the downstream wave train and the associated NEST pattern. Based on the above results, a statistical prediction model is established using the two precursory signals, that is, SAT in the tropical Atlantic and rainfall around the Baikal Lake during May. The leave‐three‐out cross‐validation shows that the model has a high skill in predicting the summer NEST pattern, with a correlation coefficient of 0.51 (significant at the 99.8% confidence level) between observation and prediction during the period 1980–2016. [ABSTRACT FROM AUTHOR]

This study evaluates the possible influence of the winter surface conditions in Eurasia on the summer circulation over the Asian continent and Indo‐Pacific region. We have analysed multi‐seasonal ensemble reforecasts for 30 years (1979–2008) using the National Centers for Environmental Prediction Climate Forecast System version 2 initialized at the beginning of each month from January to May. It is found that the reforecasts initialized in winter (e.g., February) overestimate the snow cover fraction, depth and water equivalent, as well as surface albedo in the excessively snow‐covered portion of Eurasia from March to June. These biases are generated and perpetuated by a snow‐albedo feedback, leading to excessive upwards shortwave radiation reflected from the overly snow‐covered surface and an intense cold bias from the surface to mid‐troposphere. Originating over land, the cold bias is extended eastwards over the northwestern North Pacific by the advection of prevailing westerly winds. The cold air temperature in the broad mid‐latitude Asian‐Pacific region causes significantly lower geopotential heights at pressure levels in the middle and upper troposphere and thus increases the upper‐level westerly winds on its southern flank over the Asian continent and Indo‐Pacific. A slower than observed snow melting rate helps the winter cold bias persists well into the summer season in these runs. As a result, compared with the reforecasts initialized in spring (e.g., May), winter‐initialized reforecasts feature lower geopotential heights in the upper troposphere over Eurasia and a stronger subtropical jet over the Asian continent and the North Pacific from May to September, especially in early summer. The CFSv2 reforecasts in both sets of cases have too little total cloud fraction over Eurasia during June–August, leading to enhanced downwards shortwave radiation. [ABSTRACT FROM AUTHOR]

Eurasia is one of the most sensitive areas to climate change in the world. Its western and eastern coasts are very likely to exhibit different temperature and precipitation variations in response to the global climate change. By using precipitation (PRCP), maximum temperature (Tmax), minimum temperature (Tmin), and daily temperature range (DTR) data from 333 meteorological stations in Western (WE) and Eastern Eurasia (EE), we quantitatively compared spatio‐temporal changes on both the seasonal and annual scales from 1961 to 2012. Results showed that PRCP mainly exhibited increasing trends in northern WE and decreasing trends in southern WE, whereas PRCP in EE recorded an increase–decrease–increase trend from high to low latitudes. The increase of annual PRCP in WE was higher than that in EE. On the seasonal scale, the PRCP in WE recorded an opposite trend from EE. Tmax and Tmin significantly increased for almost all stations on the annual and seasonal scales, especially during the winter. Nevertheless, the increase of Tmin was higher than that of Tmax in EE, resulting in a decreased DTR on both the seasonal and annual scales. An reverse trend of DTR was detected in WE. Our results concluded that the Arctic Oscillation was the major large‐scale atmospheric circulation affecting the trends of PRCP (negative correlation) and temperature (positive correlation) over WE and EE, and it might play an important role in future climate change. [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]