Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit

Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.

Corticomuscular coherence modulation with the pattern of finger force coordination

We assess the corticomuscular coherence (CMC) of the contralateral primary motor cortex and the hand muscles during a finger force-tracking task and explore whether the pattern of finger coordination has an impact on the CMC level. Six healthy subjects (three men and three women) were recruited to conduct the force-tracking tasks comprising two finger patterns, i.e., natural combination of index and middle fingers and unnatural combination of index and middle fingers (i.e., simultaneously producing equal force strength in index and middle finger). During the conducting of the tasks with right index and middle finger, MEG and sEMG signals were recorded from left primary motor cortex (M1) and right flexor digitorum superficialis (FDS), respectively; the contralateral CMC was calculated to assess the neuromuscular interaction. Finger force-tracking tasks of Common-IM only induce beta-band CMC, whereas Uncommon-IM tasks produce CMC in both beta and low-gamma band. Compared to the force-tracking tasks of Common-IM, the Uncommon-IM task is associated with the most intensive contralateral CMC. Our study demonstrated that the pattern of finger coordination had significant impact on the CMC between the contralateral M1 and hand muscles, and more corticomuscular interaction was necessary for unnaturally coordinated finger activities to regulate the fixed neural drive of hand muscles.