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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]

We examine the impact of horizontal resolution and model time step on the climate of the OpenIFS version 43r3 atmospheric general circulation model. A series of simulations for the period 1979–2019 are conducted with various horizontal resolutions (i.e. ∼100 , ∼50 , and ∼25 km) while maintaining the same time step (i.e. 15 min) and using different time steps (i.e. 60, 30, and 15 min) at 100 km horizontal resolution. We find that the surface zonal wind bias is significantly reduced over certain regions such as the Southern Ocean and the Northern Hemisphere mid-latitudes and in tropical and subtropical regions at a high horizontal resolution (i.e. ∼25 km). Similar improvement is evident too when using a coarse-resolution model (∼100 km) with a smaller time step (i.e. 30 and 15 min). We also find improvements in Rossby wave amplitude and phase speed, as well as in weather regime patterns, when a smaller time step or higher horizontal resolution is used. The improvement in the wind bias when using the shorter time step is mostly due to an increase in shallow and mid-level convection that enhances vertical mixing in the lower troposphere. The enhanced mixing allows frictional effects to influence a deeper layer and reduces wind and wind speed throughout the troposphere. However, precipitation biases generally increase with higher horizontal resolutions or smaller time steps, whereas the surface air temperature bias exhibits a small improvement over North America and the eastern Eurasian continent. We argue that the bias improvement in the highest-horizontal-resolution (i.e. ∼25 km) configuration benefits from a combination of both the enhanced horizontal resolution and the shorter time step. In summary, we demonstrate that, by reducing the time step in the coarse-resolution (∼100 km) OpenIFS model, one can alleviate some climate biases at a lower cost than by increasing the horizontal resolution. [ABSTRACT FROM AUTHOR]

Snow anomalies over the Tibetan Plateau (TP) have been shown to contribute to the climate variability in the neighboring and remote regions. The present study provides a review of the research progress of studies on the impacts of the TP snow anomalies on the climate over East Asia and North America. This review covers long-term TP snow variations in different seasons and in different regions, interdecadal TP snow changes in different times and their contributions to the interdecadal rainfall changes over East Asia, impacts of TP snow anomalies in different parts and different seasons on East Asian and North America climate variability on interannual time scales, intraseasonal TP snow variations and their impacts on East Asian atmospheric circulation, and interdecadal changes in the relationship of the East Asian rainfall and North American air temperature to the TP snow. The review also includes the atmospheric circulation patterns that link the TP snow to East Asian and North American climate. Discussions are provided for relevant issues of the TP snow impacts. [ABSTRACT FROM AUTHOR]

The global mean surface temperature cooled slightly in the mid-twentieth century despite a continuous increase in greenhouse gas concentrations. The cooling was strongest in the Northern Hemisphere mid-latitudes, while the Southern Hemisphere mid-latitudes experienced moderate warming. This apparent contradiction is often attributed to internal multi-decadal variability originating from Pacific and Atlantic ocean-atmosphere interactions. Given the rapid increase of industrial activities in North America and Europe during that period, it is also plausible that anthropogenic aerosol (AA) emissions (as an external forcing) contributed to the stronger Northern Hemisphere cooling. This paper aims to quantify the contributions of AA and decadal variability to the 1948–1978 cooling. We analyzed the latitudinal temperature trend asymmetry in 60° S–60° N throughout the troposphere, using multiple reanalysis datasets and the Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble that bears significant similarity with the observed patterns. We show that both AA increase and the North Atlantic Variability Index (NAVI) transition into its negative phase are the major contributors to the latitudinal asymmetry of cooling. At the surface level, based on the horizontal pattern correlation method, AA and NAVI have similar contribution fractions (20 vs. 16%), but the contribution fraction of AA is much larger at 500 hPa (55 vs. 8%). Attributions based on vertical pattern correlation and latitudinal gradient show consistent results. Natural forcings (NAT) also contribute to the cooling asymmetry during mid-20C, but with a much smaller impact compared to AA and NAVI. Therefore, we argue that previous studies that mostly focused on surface variables may have underestimated the role of AA in the mid-twentieth-century climate change. The study suggests that the three-dimensional thermal structure and atmospheric circulation change should be closely examined in future climate attribution analysis. [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]