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This study identifies a significantly positive relationship between summer surface air temperature (SAT) anomalies over two remote regions in the Eurasian continent and North America during the period 1979–2021 on the interannual time scale. The former region includes the East European Plain and the West Siberian Plain, and the latter region includes central and eastern North America. The regionally averaged summer SAT anomalies show a correlation coefficient of 0.66 between these two regions, which is significant at the 99% confidence level. This intercontinental SAT relationship can be explained by a wavelike pattern of circulation anomalies, which is the leading mode of upper-tropospheric circulation anomalies over the middle and high latitudes of the Northern Hemisphere in summer. Further analysis suggests that the sea surface temperature (SST) anomalies over the Pacific and North Atlantic in the preceding spring, being coupled with the leading mode of atmospheric circulation anomalies over the Pacific–Atlantic sector, persist into summer and affect the SATs in the two remote regions, resulting in the intercontinental SAT connection. Significance Statement: Summer surface air temperature (SAT) has profound effects on public health and agricultural production. Here we find a significantly positive relationship between interannual variations of summer SATs over two remote regions, one in the Eurasian continent and the other in North America. This intercontinental relationship in SATs can be explained as a result of atmosphere–ocean coupling over the Pacific and North Atlantic in the preceding spring. The result is likely to be a critical implication for the seasonal forecast of SAT variations over the two regions. In addition, the concurrence of higher or lower temperatures in these two regions may have impacts on global grain production, since these two regions include many major grain-producing areas in the world. [ABSTRACT FROM AUTHOR]

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue "windows of forecast opportunity" in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated. [ABSTRACT FROM AUTHOR]