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Assessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2
The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen modeling groups from Europe and five from North America have run regional air quality models to simulate the year 2010 over one European and one North American domain. The MACC re-analysis has been used as chemical initial (IC) and boundary conditions (BC) by all participating regional models in AQMEII-2. The aim of the present work is to evaluate the MACC re-analysis along with the participating regional models against a set of ground-based measurements (O3, CO, NO, NO2, SO2, SO42−) and vertical profiles (O3 and CO). Results indicate different degrees of agreement between the measurements and the MACC re-analysis, with an overall better performance over the North American domain. The influence of BC on regional air quality simulations is analyzed in a qualitative way by contrasting model performance for the MACC re-analysis with that for the regional models. This approach complements more quantitative approaches documented in the literature that often have involved sensitivity simulations but typically were limited to only one or only a few regional scale models. Results suggest an important influence of the BC on ozone for which the underestimation in winter in the MACC re-analysis is mimicked by the regional models. For CO, it is found that background concentrations near the domain boundaries are rather close to observations while those over the interior of the two continents are underpredicted by both MACC and the regional models over Europe but only by MACC over North America. This indicates that emission differences between the MACC re-analysis and the regional models can have a profound impact on model performance and points to the need for harmonization of inputs in future linked global/regional modeling studies
Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data
© 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio
Disruption of Saccadic Adaptation with Repetitive Transcranial Magnetic Stimulation of the Posterior Cerebellum in Humans
Saccadic eye movements are driven by motor commands that are continuously modified so that errors created by eye muscle fatigue, injury, or—in humans—wearing spectacles can be corrected. It is possible to rapidly adapt saccades in the laboratory by introducing a discrepancy between the intended and actual saccadic target. Neurophysiological and lesion studies in the non-human primate as well as neuroimaging and patient studies in humans have demonstrated that the oculomotor vermis (lobules VI and VII of the posterior cerebellum) is critical for saccadic adaptation. We studied the effect of transiently disrupting the function of posterior cerebellum with repetitive transcranial magnetic stimulation (rTMS) on the ability of healthy human subjects to adapt saccadic eye movements. rTMS significantly impaired the adaptation of the amplitude of saccades, without modulating saccadic amplitude or variability in baseline conditions. Moreover, increasing the intensity of rTMS produced a larger impairment in the ability to adapt saccadic size. These results provide direct evidence for the role of the posterior cerebellum in man and further evidence that TMS can modulate cerebellar function
Fingertip force control during bimanual object lifting in hemiplegic cerebral palsy
In the present study we examined unimanual and bimanual fingertip force control during grasping in children with hemiplegic cerebral palsy (CP). Participants lifted, transported and released an object with one hand or both hands together in order to examine the effect on fingertip force control for each hand separately and to determine whether any benefit exists for the affected hand when it performed the task concurrently with the less-affected hand. Seven children with hemiplegic CP performed the task while their movement and fingertip force control were measured. In the bimanual conditions, the weight of the instrumented objects was equal or unequal. The durations of the all temporal phases for the less-affected hand were prolonged during bimanual control compared to unimanual control. We observed close synchrony of both hands when the task was performed with both hands, despite large differences in duration between both hands when they performed separately. There was a marginal benefit for two of the five force related variables for the affected hand (grip force at onset of load force, and peak grip force) when it transported the object simultaneously with the less-affected hand. Collectively, these results corroborate earlier findings of reaching studies that showed slowing down of the less-affected hand when it moved together with the affected hand. A new finding that extends these studies is that bimanual tasks may have the potential to facilitate force control of the affected hand. The implications of these findings for recent rehabilitative therapies in children with CP that make use of bimanual training are discussed
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