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This paper compares surface signatures of the zonally symmetric and asymmetric modes of stratospheric variability, which describe the strength of the polar vortex and a planetary wave‐1 pattern, respectively. Unlike a weak polar vortex followed by negative Arctic Oscillation–like anomalies, strong stratospheric wave activity features a polar vortex displacement with a deep planetary wave‐1 structure, resulting in positive North Atlantic Oscillation–like North American cooling in about 10 days. Moreover, the linkage between the stratosphere and surface is examined in two reanalyzes and four models of different configurations, which show more robust North American cooling following the displacement of the polar vortex due to strong stratospheric wave activity than the zonally symmetric weakening of the polar vortex. This suggests strong stratospheric wave activity acts as a better predictor for cold spells in the northern U.S. and Canada compared with a weak polar vortex. Plain Language Summary: A weak polar vortex in the winter stratosphere is likely associated with cold spells at the surface, yet there are large uncertainties in predicting surface cold events based on stratospheric signals. This study introduces a new method to separate stratospheric variability into the leading modes of zonally symmetric and asymmetric circulations. The zonally symmetric mode describes the strength of the polar vortex. A weak polar vortex is followed by cooling over northern Eurasia and midlatitude North America. In contrast, the zonally asymmetric mode characterizes a displacement of the polar vortex or a planetary wave‐1 pattern, with the positive phase featuring a high anomaly over North America and a low anomaly over Eurasia. This stratospheric wave pattern extends down to the surface, resulting in North American cooling and Eurasian warming in about 10 days. While both stratospheric modes are associated with surface cooling over North America, the linkage is more robust for the displacement than the zonally symmetric weakening of the polar vortex, based on analyses of several reanalyzes and models. This indicates that strong stratospheric wave activity serves as a better predictor for cold air outbreaks in the northern U.S. and Canada than the commonly used weak polar vortex events. Key Points: Distinct North American cooling signatures follow zonally symmetric and asymmetric modes of the stratosphereStrong stratospheric wave activity precedes positive North Atlantic Oscillation like North American coolingThe linkage between the stratospheric wave activity and the surface is robust in reanalyzes and models [ABSTRACT FROM AUTHOR]

The present work investigates different responses of Arctic surface air temperature (SAT) to two ENSO types based on reanalysis datasets and model experiments. We find that eastern Pacific (EP) ENSO events are accompanied by statistically significant SAT responses over the Barents–Kara Seas in February, while central Pacific (CP) events coincide with statistically significant SAT responses over northeastern Canada and Greenland. These impacts are largely of opposite sign for ENSO warm and cold phases. During EP El Niño in February, the enhanced tropospheric polar vortex over Eurasia and associated local low-level northeasterly anomalies over the Barents–Kara Seas lead to anomalously cold SAT in this region. Simultaneously, the enhanced tropospheric polar vortex leads to enhanced sinking air motion and consequently reduced cloud cover. This in turn reduces downward infrared radiation (IR), which further reduces SAT in the Barents–Kara Seas region. Such a robust response cannot be detected during other winter months for EP ENSO events. During CP El Niño, the February SATs over northeastern Canada and Greenland are anomalously warm and coincide with a weakened tropospheric polar vortex and related local low-level southwesterly anomalies originating from the Atlantic Ocean. The anomalous warmth can be enhanced by the local positive feedback. Similar SAT signals as in February during CP ENSO events can also be seen in January, but they are less statistically robust. We demonstrate that these contrasting Arctic February SAT responses are consistent with responses to the two ENSO types with a series of atmospheric general circulation model experiments. These results have implications for the seasonal predictability of regional Arctic SAT anomalies. [ABSTRACT FROM AUTHOR]

Background and Objectives: It is commonly assumed that allometric biomass models are species-specific and site-specific. However, the magnitude of species and site dependency in these models is not well-known. This study aims to investigate the variation in allometric models (i.e., aboveground biomass predicted by diameter at breast height and tree height) that has originated from the differences between tree species and between sites, thereby contributing to a better understanding of species and site-specificity issue in these models. Materials and Methods: The study is based on two large biomass datasets of 4921 and 5199 trees, from Eurasia and Canada. Using a nested ANOVA model on relative aboveground biomass residuals (with species and site as random effects), the proportion of variance explained by species or site was assessed by means of Variance Partition Coefficient (VPC). Results: The proportion of variance explained by species (VPCspecies = 42.56%, SE = 6.10% for Dataset 1 and VPCspecies = 47.54%, SE = 6.07% for Dataset 2) was larger than that explained by site (VPCsite = 20.08%, SE = 3.35% for Dataset 1 and VPCsite = 8.27%, SE = 1.38% for Dataset 2). The proportion of variance explained by site decreased by 24%–44% and the proportion of variance explained by species changed only slightly, when height is included in the allometric biomass models (i.e., models based on diameter at breast height alone, compared to models based on diameter at breast height and tree height). Conclusions: Allometric biomass models were more species-specific than they were site-specific. Therefore, the species (i.e., differences between species) seems to be a more important driver of variability in allometric models compared to site (i.e., differences between sites). Including height in allometric biomass models helped reduce the dependency of these models, on sites only. [ABSTRACT FROM AUTHOR]