The Westerly Index as complementary indicator of the North Atlantic oscillation in explaining drought variability across Europe

This paper analyses the influence of different atmospheric circulation indices on the multi-scalar drought variability across Europe by using the Standardized Precipitation Evapotranspiration Index (SPEI). The monthly circulation indices used in this study include the North Atlantic oscillation (NAO), the East Atlantic (EA), the Scandinavian (SCAN) and the East Atlantic-Western Russia (EA-WR) patterns, as well as the recently published Westerly Index (WI), defined as the persistence of westerly winds over the eastern north Atlantic region. The results indicate that European drought variability is better explained by the station-based NAO index and the WI than by any other combination of circulation indices. In northern and central Europe the variability of drought severity for different seasons and time-scales is strongly associated with the WI. On the contrary, the influence of the NAO on southern Europe droughts is stronger than that exerted by the WI. The correlation patterns of the NAO and WI with the SPEI show a spatial complementarity in shaping drought variability across Europe. Lagged correlations of the NAO and WI with the SPEI also indicate enough skill of both indices to anticipate drought severity several months in advance. As long as instrumental series of the NAO and WI are available, their combined use would allow inferring European drought variability for the last two centuries and improve the calibration and interpretation of paleoclimatic proxies associated with drought.

Test-Retest Reliability of Resting-State Magnetoencephalography Power in Sensor and Source Space

Several studies have reported changes in spontaneous brain rhythms that could be used asclinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), low beta (13–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted inhigh within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials.