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Northern midlatitudes, over central Eurasia in particular, have experienced frequent severe winters in recent decades1–3. A remote influence of Arctic sea-ice loss has been suggested4–14; however, the importance of this connection remains controversial because of discrepancies among modelling and between modelling and observational studies15–17. Here, using a hybrid analysis of observations and multi-model large ensembles from seven atmospheric general circulation models, we examine the cause of these differences. While all models capture the observed structure of the forced surface temperature response to sea-ice loss in the Barents–Kara Seas—including Eurasian cooling—we show that its magnitude is systematically underestimated. Owing to the varying degrees of this underestimation of sea-ice-forced signal, the signal-to-noise ratio differs markedly. Correcting this underestimation reconciles the discrepancy between models and observations, leading to the conclusion that ~44% of the central Eurasian cooling trend for 1995–2014 is attributable to sea-ice loss in the Barents–Kara Seas. Our results strongly suggest that anthropogenic forcing has significantly amplified the probability of severe winter occurrence in central Eurasia via enhanced melting of the Barents–Kara sea ice. The difference in underestimation of signal-to-noise ratio between models therefore calls for careful experimental design and interpretation for regional climate change attribution.The connections between Arctic sea-ice loss and severe Eurasian winters are complicated by differences among studies. Correcting model underestimates reveals that 44% of the central Eurasian cooling trend is attributable to sea-ice loss in the Barents–Kara Seas.

Severe winters have occurred frequently in mid-latitude Eurasia during the past decade. Simulations with a 100-member ensemble of an atmospheric model detect an influence of declining Arctic sea-ice cover. Over the past decade, severe winters occurred frequently in mid-latitude Eurasia 1 , 2 , despite increasing global- and annual-mean surface air temperatures 3 . Observations suggest that these cold Eurasian winters could have been instigated by Arctic sea-ice decline 2 , 4 , through excitation of circulation anomalies similar to the Arctic Oscillation 5 . In climate simulations, however, a robust atmospheric response to sea-ice decline has not been found, perhaps owing to energetic internal fluctuations in the atmospheric circulation 6 . Here we use a 100-member ensemble of simulations with an atmospheric general circulation model driven by observation-based sea-ice concentration anomalies to show that as a result of sea-ice reduction in the Barents–Kara Sea, the probability of severe winters has more than doubled in central Eurasia. In our simulations, the atmospheric response to sea-ice decline is approximately independent of the Arctic Oscillation. Both reanalysis data and our simulations suggest that sea-ice decline leads to more frequent Eurasian blocking situations, which in turn favour cold-air advection to Eurasia and hence severe winters. Based on a further analysis of simulations from 22 climate models we conclude that the sea-ice-driven cold winters are unlikely to dominate in a warming future climate, although uncertainty remains, due in part to an insufficient ensemble size.

With the progression of an aging society, the importance of walking assistance technology has been increasing. The research and development of robotic walkers for individuals requiring walking support are advancing. However, there was a problem that the conventional constant support amount did not satisfy the propulsion force required for the walking speed that users wanted. In this study, in order to solve this problem, we propose an algorithm for determining the support amount to maintain the walking speed when the average walking speed of each user is set as the target speed. A robotic walker was developed by attaching BLDC motors to an actual walker, along with a control algorithm for assistance based on sampling-type PID control. The effectiveness of the assistance determination algorithm and the usefulness of the parameters were demonstrated through experiments using weights loaded on the forearm support and target speeds. Subsequently, subject experiments were conducted to verify the ability to maintain target speeds, and a questionnaire survey confirmed that the assistance did not interfere with actual walking. The proposed algorithm for determining the assistance levels demonstrated the ability to maintain target speeds and allowed for adjustments in the necessary level of assistance.

Decline in winter sea-ice concentration (SIC) in the Barents-Kara Sea significantly impacts climate through increased heat release to the atmosphere. However, the past Barents-Kara SIC decrease rate is underestimated in the majority of Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models. Here we show that climate model simulations can reproduce the Barents-Kara SIC trend for 1970–2017 when sea surface temperature (SST) variability in the Gulf Stream region is constrained by observations. The constrained warming of the Gulf Stream strengthens ocean heat transport to the Barents-Kara Sea that enhances the SIC decline. The linear trends between the SIC and SST are highly correlated in the CMIP6 ensemble, suggesting that the externally forced component of the Gulf Stream SST increase explains up to 56% of the forced Barents-Kara SIC trend. Therefore, future warming of the Gulf Stream can be an essential pacemaker of the SIC decline. Climate model simulations show that for 1970-2017 externally-forced sea surface temperature increases in the Gulf Stream explain up to 56% of the sea-ice decline in the Barents-Kara Sea during winter via poleward oceanic heat transport.

An unprecedentedly large ensemble of climate simulations with a 60-km atmospheric general circulation model and dynamical downscaling with a 20-km regional climate model has been performed to obtain probabilistic future projections of low-frequency local-scale events. The climate of the latter half of the twentieth century, the climate 4 K warmer than the preindustrial climate, and the climate of the latter half of the twentieth century without historical trends associated with the anthropogenic effect are each simulated for more than 5,000 years. From large ensemble simulations, probabilistic future changes in extreme events are available directly without using any statistical models. The atmospheric models are highly skillful in representing localized extreme events, such as heavy precipitation and tropical cyclones. Moreover, mean climate changes in the models are consistent with those in phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensembles. Therefore, the results enable the assessment of probabilistic change in localized severe events that have large uncertainty from internal variability. The simulation outputs are open to the public as a database called “Database for Policy Decision Making for Future Climate Change” (d4PDF), which is intended to be utilized for impact assessment studies and adaptation planning for global warming.

Mitochondrial disorders have the highest incidence among congenital metabolic disorders characterized by biochemical respiratory chain complex deficiencies. It occurs at a rate of 1 in 5,000 births, and has phenotypic and genetic heterogeneity. Mutations in about 1,500 nuclear encoded mitochondrial proteins may cause mitochondrial dysfunction of energy production and mitochondrial disorders. More than 250 genes that cause mitochondrial disorders have been reported to date. However exact genetic diagnosis for patients still remained largely unknown. To reveal this heterogeneity, we performed comprehensive genomic analyses for 142 patients with childhood-onset mitochondrial respiratory chain complex deficiencies. The approach includes whole mtDNA and exome analyses using high-throughput sequencing, and chromosomal aberration analyses using high-density oligonucleotide arrays. We identified 37 novel mutations in known mitochondrial disease genes and 3 mitochondria-related genes (MRPS23, QRSL1, and PNPLA4) as novel causative genes. We also identified 2 genes known to cause monogenic diseases (MECP2 and TNNI3) and 3 chromosomal aberrations (6q24.3-q25.1, 17p12, and 22q11.21) as causes in this cohort. Our approaches enhance the ability to identify pathogenic gene mutations in patients with biochemically defined mitochondrial respiratory chain complex deficiencies in clinical settings. They also underscore clinical and genetic heterogeneity and will improve patient care of this complex disorder.

The dominant mode of wintertime interdecadal covariability between subseasonal surface air temperature (SAT) variability and midtropospheric circulation over the North Atlantic sector is identified through maximum covariance analysis applied to century-long reanalysis data. This mode highlights a tendency for subseasonal temperature variability over Europe and eastern North America to be enhanced during decades when the negative phase of the North Atlantic Oscillation (NAO) prevails. This interdecadal NAO is characterized by a stationary Rossby wave train that originates from the subtropical Atlantic, propagates northward into the subpolar Atlantic, and finally refracts toward Europe and the Middle East. A decadal increase in precipitation in the subtropics under the enhanced supply of heat and moisture from the Gulf Stream and its surroundings appears to act as a source for this wave train. The influence of the interdecadal NAO on subseasonal SAT variability is explained primarily by the modulated efficiency of baroclinic conversion of available potential energy from the background atmospheric flow to subseasonal eddies. The combination of enhanced subseasonal variability and low winter-mean temperature anomalies associated with the negative phase of the interdecadal NAO increases the frequency of cold extremes affecting Europe and the eastern United States.

Rheumatoid arthritis (RA) causes chronic polyarthritis and joint dysfunction, reducing work productivity. This reduction is mainly due to presenteeism, characterized by impaired work performance despite being present at work. This study aims to investigate the impact of specific joint involvement, particularly in the upper extremities, on work disability in RA patients. Annual surveys assessing work disability were conducted among RA outpatients enrolled in the Nagahama Riumachi Cohort at Nagahama City Hospital, using the Work Productivity and Activity Impairment Questionnaire (WPAI). A multivariate regression analysis was performed to examine the cross-sectional and longitudinal associations between self-reported presenteeism and the tender joint count (TJC) in the extremities across two WPAI surveys. The analysis included 201 patients, 52% of whom reported presenteeism. Cross-sectional analysis revealed a significant positive correlation between three or more TJCs of the upper extremity and presenteeism, with a regression coefficient (β) = 17.9 (95% confidence interval [CI]: 9.85-25.9). Among the joints evaluated, the sum of TJCs in the shoulder area (β = 9.55, CI: 5.39-13.7) and the fingers (β = 1.60, CI: 0.35-2.85) were significantly correlated with presenteeism. Additionally, change in presenteeism was significantly correlated with change in upper extremity TJCs (β = 1.41, CI: 0.05-2.77). No significant correlation was observed between lower extremity TJCs and presenteeism in these multivariate regression analyses. The upper extremity TJC is strongly associated with presenteeism in RA patients. Minimizing TJC in the upper extremities, particularly in the shoulders and fingers, could be important treatment goal to reduce work disability in RA patients.

The Pacific/North American (PNA) pattern is a major low‐frequency variability in boreal winter. A recent modeling study suggested that PNA variability increases through extratropical atmosphere‐ocean coupling, but the effect was not fully extracted due to a particular experimental design. By comparing coupled and two sets of uncoupled large‐ensemble global model simulations, here we show that the PNA‐induced horseshoe‐shaped sea‐surface temperature (SST) anomaly in the North Pacific returns a non‐negligible influence on the PNA itself. Its magnitude depends on the presence or absence of atmosphere‐ocean coupling. The coupling accounts for ∼16% of the PNA variance, while the horseshoe‐shaped SST anomaly explains only 5% under the uncoupled condition. The coupling reduces the damping of available potential energy by modulating turbulent heat fluxes and precipitation, magnifying the PNA variance. Precipitation processes in the extratropics as well as tropics are therefore important for realistically representing PNA variability and thereby regional weather and climate. Plain Language Summary Atmospheric flow is not entirely random; patterns of circulation variability appear recurrently in the same regions, known as teleconnection patterns. A major wintertime teleconnection pattern over the North Pacific‐North American sector is called the Pacific/North American (PNA) pattern. It causes strong fluctuations in precipitation, air temperature, and pressure over North America through persistent strengthening or meandering of the jet stream. While the influence of tropical ocean variability, such as El Niño/La Niña, on the formation and persistence of the PNA has been known, the role of the extratropical ocean remains unclear. Here we perform a vast number of numerical model simulations to detect the influence of the extratropical ocean on PNA. We show that the atmosphere‐ocean coupling (two‐way interaction between the ocean and atmosphere) enhances the PNA variability (i.e., the magnitude of meandering and strengthening of the westerlies) compared to the uncoupled condition. Furthermore, we propose possible mechanisms behind this enhancement. The findings of this study are expected to contribute to improving the accuracy of long‐term forecasts, such as one‐month predictions, and reducing uncertainty in future climate change projections through the improvement of numerical models. Key Points Extratropical air‐sea coupling enhances the variance of the Pacific/North American (PNA) pattern, which explains 16% of the total variance The enhancement is due to the reduced damping of available potential energy through modulations of turbulent heat fluxes and precipitation Atmosphere‐only simulation is likely to underestimate the impact of extratropical sea surface temperature anomalies on the PNA variability