The model uncertainty, one of the major sources of projection uncertainty, is still a challenge in the climate simulation. In this study, we investigated the inter‐model spread of the simulated winter surface air temperature (SAT) over the Eurasian continent and the physical link to the upper‐level jet streams from the Coupled Model Inter‐comparison Project Phase 6 models. Extracted by the inter‐model empirical orthogonal function analysis, the leading inter‐model spread of SAT over the Eurasian continent is characterized by a cold pattern, particularly over high latitudes, which is closely associated with the out‐of‐phase variation in the intensity of the East Asian polar front jet (EAPJ) and East Asian subtropical jet (EASJ). The weakened‐EAPJ‐enhanced‐EASJ pattern is linked to the intensified Siberian high, the strengthened Aleutian low, and the deepened East Asian trough. All the variations would benefit the cold air invasion, resulting in the leading inter‐model spread of the SAT. The possible mechanism for the inter‐model uncertainty in the out‐of‐phase variation in the intensity of the two jets would be traced to the cooling over the Northwest Pacific oceans, which has reduced (enhanced) the meridional temperature gradient over high (low) latitudes and thereby contributed to the out of phase variation in the two jets. Our findings would help provide a potential metric for understanding the winter SAT change over the Eurasian continent.
Migraine is a chronic and idiopathic disorder leading to cognitive and affective problems. However, the neural basis of migraine without aura is still unclear. In this study, dynamic amplitude of low-frequency fluctuations (dALFF) analyses were performed in 21 patients with migraine without aura and 21 gender- and age-matched healthy controls to identify the voxel-level abnormal functional dynamics. Significantly decreased dALFF in the bilateral anterior insula, bilateral lateral orbitofrontal cortex, bilateral medial prefrontal cortex, bilateral anterior cingulate cortex, and left middle frontal cortex were found in patients with migraine without aura. The dALFF values in the anterior cingulate cortex were negatively correlated with pain intensity, i.e., visual analog scale. Finally, support vector machine was used to classify patients with migraine without aura from healthy controls and achieved an accuracy of 83.33%, sensitivity of 90.48%, and specificity of 76.19%. Our findings provide the evidence that migraine influences the brain functional activity dynamics and reveal the neural basis for migraine, which could facilitate understanding the neuropathology of migraine and future treatment.
Abstract. Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system; consequently, a long-term SM product with high quality is urgently needed. In this study, five SM products, including one microwave remote sensing product – the European Space Agency's Climate Change Initiative (ESA CCI) – and four reanalysis data sets – European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis – Interim (ERA-Interim), National Centers for Environmental Prediction (NCEP), the 20th Century Reanalysis Project from National Oceanic and Atmospheric Administration (NOAA), and the ECMWF Reanalysis 5 (ERA5) – are systematically evaluated using in situ measurements during 1981–2013 in four climate regions at different timescales over the Chinese mainland. The results show that ESA CCI is closest to the observations in terms of both the spatial distributions and magnitude of the monthly SM. All reanalysis products tend to overestimate soil moisture in all regions but have higher correlations than the remote sensing product except in Northwest China. The largest inconsistency is found in southern Northeast China region, with an unbiased root mean square error (ubRMSE) value larger than 0.04. However, all products exhibit certain weaknesses in representing the interannual variation in SM. The largest relative bias of 144.4 % is found for the ERA-Interim SM product under extreme and severe wet conditions in northeastern China, and the lowest relative bias is found for the ESA CCI SM product, with the minimum of 0.48 % under extreme and severe wet conditions in northwestern China. Decomposing mean square errors suggests that the bias terms are the dominant contribution for all products, and the correlation term is large for ESA CCI. As a result, the ESA CCI SM product is a good option for long-term hydrometeorological applications on the Chinese mainland. ERA5 is also a promising product, especially in northern and northwestern China in terms of low bias and high correlation coefficient. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
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