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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]

The Northern Hemisphere (NH) has experienced winter Arctic warming and continental cooling in recent decades, but the dominant patterns in winter surface air temperature (SAT) are not well understood. Here, a self-organizing map (SOM) analysis is performed to identify the leading patterns in winter daily SAT fields from 1979 to 2018, and their associated atmospheric and ocean conditions are also examined. Three distinct winter SAT patterns with two phases of nearly opposite signs and a time scale of 7–12 days are found: one pattern exhibits concurrent SAT anomalies of the same sign over North America (NA) and northern Eurasia, while the other two patterns show SAT anomalies of opposite signs between, respectively, NA and the Bering Sea, and the Kara Sea and East Asia (EA). Winter SAT variations may arise from changes in the SOM frequencies. Specifically, the observed increasing trends of winter cold extremes over NA, central Eurasia, and EA during 1998–2013 can be understood as a result of the increasing occurrences of some specific SAT patterns. These SOMs are closely related to poleward advection of midlatitude warm air and equatorward movements of polar cold airmass. These meridional displacements of cold and warm airmasses cause concurrent anomalies over different regions not only in SAT but also in water vapor and surface downward longwave radiation. Anomalous sea surface temperatures in the tropical Pacific, midlatitude North Pacific, and North Atlantic and anomalous Arctic sea ice concentrations also concur to support and maintain the anomalous atmospheric circulation that causes the SAT anomalies. [ABSTRACT FROM AUTHOR]

We analyze the temporal structure of the climatological seasonal cycle in surface air temperature across the globe. We find that, over large regions of Earth, the seasonal cycle of surface temperature departs from an annual harmonic: the duration of fall and spring differ by as much as 2 months. We characterize this asymmetry by the metric ASYM, defined as the phase lag of the seasonal maximum temperature relative to the summer solstice minus the phase lag of the seasonal minimum temperature relative to winter solstice. We present a global analysis of ASYM from weather station data and atmospheric reanalysis and find that ASYM is well represented in the reanalysis. ASYM generally features positive values over land and negative values over the ocean, indicating that spring has a longer duration over the land domain whereas fall has a longer duration over the ocean. However, ASYM also features more positive values over North America compared to Europe and negative values in the polar regions over ice sheets and sea ice. Understanding the root cause of the climatological ASYM will potentially further our understanding of controls on the seasonal cycle of temperature and its future/past changes. We explore several candidate mechanisms to explain the spatial structure of ASYM including 1) modification of the seasonal cycle of surface solar radiation by the seasonal evolution of cloud thickness, 2) differences in the seasonal cycle of the atmospheric boundary layer depth over ocean and over land, and 3) temperature advection by the seasonally evolving atmospheric circulation. [ABSTRACT FROM AUTHOR]

Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. The findings show that warm extremes at most locations are associated with positive 500-hPa geopotential height and sea level pressure anomalies just downstream with negative anomalies farther upstream. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. Circulation patterns aloft are more coherent across the continent than those at the surface where local surface features influence the occurrence of and patterns associated with extreme temperature days. Temperature extremes may be more sensitive to small shifts in circulation at locations where temperature is strongly influenced by mountains or large water bodies, or at the margins of important large-scale circulation patterns making such locations more susceptible to nonlinear responses to future climate change. The identification of these patterns and processes will allow for a thorough evaluation of the ability of climate models to realistically simulate extreme temperatures and their future trends. [ABSTRACT FROM AUTHOR]

Specifications of 1- and 3-month mean Pacific-North America region 700-hPa heights and U.S. surface temperatures and precipitation, from global sea surface temperatures (SSTs) and the ensemble average output of multiple runs of a general circulation model with the same SSTs prescribed, were explored with canonical correlation analysis. In addition to considerable specification skill, the authors found that 1) systematic errors in SST-forced model variability had substantial linear parts, 2) use of both predictor fields usually enhanced specification performance for the U.S. fields over that for just one of the predictor fields, and 3) skillful specification and model correction of the heights and temperatures were also possible for nonactive or transitional El Niño-Southern Oscillation situations. [ABSTRACT FROM AUTHOR]