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This paper uses monthly surface air temperature (SAT) data from the Climatic Research Unit dataset and the Coupled Model Intercomparison Project phase 6 multimodel ensemble simulations to investigate the variations in the annual‐mean and four seasons SAT across the Eurasian and North Africa landmasses and the possible causes. The SAT over multiple timescales has significant seasonal and regional differences. The trend, variance of decadal variation (DV), and variance of interannual variability (IV) show that the differences between Siberia and mid‐low latitudes are much larger in winter and spring than in summer and autumn. The SAT exhibits a robust warming trend over Siberia in winter (0.21–0.42°C·decade−1) than over mid–low latitudes in summer (<0.07°C·decade−1). The cause is the combined diversity effects of greenhouse gases (GHG) and anthropogenic aerosols (AA) in four seasons over different regions. The warming trend of Siberia in winter is affected by the combination of strong warming effect by GHG and the weak cooling effect by AA, and the trend of mid–low latitudes in summer is opposite. The leading modes of the DV show a consistent spatial pattern over the whole Eurasia in four seasons while the IV show a meridional dipole pattern across 40°N except in summer. The internal climate variability is the main driver of the SAT IV and DV, but the effect of anthropogenic activity and natural forcing may reinforce the IV and DV in some regions. The combined role of GHG and AA forcings can significantly enlarge the DV in many parts of Eurasia, and the AA and natural forcing have significant effect on the IV in the high latitudes. [ABSTRACT FROM AUTHOR]

This study investigates the role of internal climate variability on the wintertime surface air temperature (SAT) trend over Eurasia during 1970–2004 based on outputs from the Community Earth System Model Large Ensemble Project. The SAT trends vary significantly in both spatial pattern and magnitude among ensemble members, indicating the essential role of internal climate variability on SAT trends. The leading modes of the spread of SAT trends are extracted via inter‐member empirical orthogonal function (EOF) analysis of the SAT trend patterns among 40 ensemble members. The first EOF mode shows widespread warming over northern Eurasia and slight cooling southward of 40°N during its positive phase. The second EOF mode displays a zonal dipole, with one center located in Europe and the other of the opposite sign over Siberia. The Arctic Oscillation and Scandinavian patterns are key dynamical factors associated with the two dominant modes, respectively. A dynamical adjustment method is further employed to decompose the internal climate variability into those related to large‐scale atmospheric circulation and residuals. The spread of SAT trends among ensemble members is primarily associated with the various large‐scale atmospheric circulation and second by the residual component that is closely tied to diverse snow cover trends over Eurasia, especially over northern Eurasia. These results may help understand the relationship between internal climate variability and winter SAT trends over Eurasia via dynamical and thermodynamical processes. Key Points: Internal climate variability plays a crucial role in the Eurasian winter surface air temperature trends of the past decadesArctic Oscillation and Scandinavian patterns are two essential internal dynamical factors associated with the temperature trendsSnow cover is the key internal thermodynamical factor associated with the temperature trends [ABSTRACT FROM AUTHOR]

In this study, the single value decomposition method was used to analyze the covariation between the winter (December, January, and February) North Atlantic sea surface temperature (SST) and spring (April and May) normalized difference vegetation index (NDVI) over mid‐high‐latitude Eurasia for the period 1982–2015. The results show that the first paired mode explains 32.8% of the total squared covariance, and the correlation of time coefficients is +0.67 (p < 0.01), suggesting that the meridional tripole structure of the winter North Atlantic SST is significantly associated with the three zonally anomalous centers of the spring mid‐high‐latitude Eurasian NDVI. Surface air temperature (T2m) is the most important factor related to spring NDVI changes. The tripole pattern of the winter North Atlantic SST can persist until the following spring, triggering an eastward anomalous Rossby wave train in the middle troposphere, which features two negative geopotential height anomalies centers near northwestern Europe and eastern Siberia and one positive center over central Eurasia. Surface temperature anomalies are well consistent with these anomalous pressure centers. This implies that the winter North Atlantic SST could be a robust driver and potential precursor for spring vegetation prediction over the mid‐high latitudes of Eurasia. Key Points: There is a significant covarying mode between the tripole pattern of the winter North Atlantic sea surface temperature (SST) and spring normalized difference vegetation index (NDVI) anomaly over EurasiaT2m is the main intermediate factor linking SST and large‐scale NDVIThe tripole pattern can persist until the following spring, which modulates T2m over Eurasia through a Rossby wave train [ABSTRACT FROM AUTHOR]

In recent decades, the winter surface air temperature (SAT) anomaly in the Northern Hemisphere has exhibited a warm Arctic‐cold Eurasia (WACE) dipole pattern and this has undergone significant decadal variation. In this paper, the physical cause of the decadal variability of the WACE pattern is explored, and it is shown to be mediated by the phases of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Although the negative PDO (PDO−) or positive AMO (AMO+) favors the WACE pattern, the meridional structure of the pattern is significantly influenced by whether PDO− or AMO+ dominates. During PDO− (AMO+) phase, the winter‐mean WACE pattern shows an asymmetric dipole with weak (strong) warm anomaly over the Barents‐Kara Seas or BKS and strong (weak) cold anomaly over central Eurasia or Siberia, which corresponds to Ural blocking (UB) concurring with the negative (positive) phase of North Atlantic Oscillation in a winter‐mean field. The winter asymmetric WACE pattern is more strongly related to PDO− than AMO+. It is further found that an asymmetric sub‐seasonal WACE dipole pattern with strong (weak) warm anomaly over BKS and weak (strong) cold anomaly over Siberia is usually formed during the UB episode due to favored (suppressed) sub‐seasonal downward infrared radiation and turbulent heat flux over BKS during AMO+ (PDO−), which leads to a strong asymmetric dipole of the winter WACE pattern. Plain Language Summary: The most prominent climate change in the Northern Hemispheric mid‐high latitudes in recent decades is that the winter surface air temperature anomaly has exhibited a warm Arctic‐cold Eurasia (WACE) dipole pattern. However, it is still unknown what causes the decadal variability of the winter WACE pattern and its meridional asymmetry. In this paper, we address this issue by examining the different effects of Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on the winter WACE pattern. It is shown that PDO− (AMO+) plays an important role in the occurrence of the asymmetric WACE dipole with weak (strong) warm anomaly over the Barents‐Kara Seas and strong (weak) cold anomaly over central Eurasia or Siberia through modulating Ural blocking and associated sub‐seasonal cold anomaly. It is also found that the asymmetric WACE dipole is more strongly dependent on PDO− than AMO+. Our findings are of great significance for understanding the physical cause of the decadal variability of the WACE dipole pattern in spatial structure. Key Points: Ural Blocking plays an important role in the occurrence of the sub‐seasonal warm Arctic‐cold Eurasia (WACE) dipole pattern in winterUral blocking can amplify the winter‐mean Warm Arctic‐cold Eurasia (WACE) patternWarm Arctic‐cold Eurasia (WACE) is linked to the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) [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]

Siberia is a region where despite global warming a winter cooling trend has been observed over last decades. This cooling trend and its potential linkage to Arctic sea ice loss are controversially discussed. However, recent winters have not been taken into account so far. Here, we analyse ERA‐Interim reanalysis data until 2017 and ERA20C reanalysis to investigate the robustness of the winter surface air temperature trends to updated and extended time periods. Our results show that winter temperatures in Siberia were above normal after 2013 leading to strongly reduced cooling trends since 1980. The trend before 2014 was dominated by four cold winters between 2010 and 2013. These cold winters were mainly caused by strong negative phases of the North Atlantic Oscillation (NAO), except for the winter 2011/2012, where the NAO was positive and a strongly negative phase of the Pacific Decadal Oscillation (PDO) in combination with low sea ice in the Barents Sea caused the cold winter. Both NAO and PDO shift from more negative to positive phases in 2014 and contribute to a return to warmer Siberian temperatures. Furthermore, the NAO shows no trend between 1980 and 2017 indicating that the suggested linkage between Arctic sea ice loss and a negative trend in this mode is not robust. However, continuously low Arctic sea ice in recent years and a slightly negative trend in the PDO since 1980 contribute to the remaining observed cold trends over parts of Eurasia between 1980 and 2017. [ABSTRACT FROM AUTHOR]