The Roles of External Forcings and Internal Variabilities in the Northern Hemisphere Atmospheric Circulation Change from the 1960s to the 1990s

Abstract The Northern Hemisphere atmospheric circulation change from the 1960s to the 1990s shows a strong positive North Atlantic Oscillation (NAO) and a deepening of the Aleutian low. The issue regarding the contributions of external forcings and internal atmospheric variability to this circulation change has not been resolved satisfactorily. Previous studies have found the importance of tropical SST forcing. Here, this hypothesis is examined again using relatively large ensembles of atmospheric general circulation model simulations of the twentieth-century climate forced only by historically varying SST. The resulting ensemble-mean amplitude underestimates the observed change by at least 70%, although the spatial pattern is reproduced well qualitatively. Furthermore, AGCM experiments are performed to investigate other driving factors, such as the greenhouse gases, sea ice, the stratospheric ozone, as well as the contribution from atmospheric internal variability. The increase in ensemble-mean trend amplitude induced by these additional drivers was not enough to substantially improve the agreement with the observed trend. However, the full distribution of simulated trends reveals that the ensemble members at the upper tail are much closer to the observed amplitude. In the "best" ensemble, the 95th percentile of the simulated NAO trend amplitude remains at about 80% of the observed trend amplitude, with nearly equal contributions from external forcings and internal variability. The results also indicate that a complete set of driving factors and a correct simulation of stratospheric trends are important in bridging the gap between observed and modeled interdecadal variability in the North Atlantic winter circulation

Circulation Regimes: Chaotic Variability versus SST-Forced Predictability

Abstract The circulation regimes in the Pacific–North American region are studied using the NCEP–NCAR reanalyses for the 18-winter period (1981/82–1998/99; NCEP18) and for the 54-winter period (1948/49–2001/02; NCEP54). The sampling properties of the regimes are estimated using very large ensembles (of size 55) of winter simulations made for the NCEP18 period with the atmospheric general circulation model of the Center for Ocean–Land–Atmosphere Studies, forced by observed SST and sea ice. The regimes are identified using a modified version of the k-means method. From the NCEP54 dataset a set of four clusters was found [i.e., the Alaskan ridge (AR), Arctic low (AL), Pacific trough (PT), and the Arctic high (AH)], which are significant (vis-à-vis a multinormal background), and more reproducible (within randomly chosen half-length samples) than would be expected from a multinormal process. The frequency of occurrence of the PT (AH) has increased (decreased) significantly during the past two decades. The PT cluster obtained from NCEP18 dataset more closely resembles the El Niño–forced seasonal mean pattern of recent decades than it does the traditional PNA. The GCM simulates the AR, AL, and PT clusters (but not the AH). The simulated AR and PT patterns have errors (cf. the NCEP18 results), which are outside the range of internal variability. The simulated frequency of occurrence agrees with the NCEP18 results within sampling variability. The differences in cluster properties of the PT and AR regimes between the NCEP18 and NCEP54 datasets are due to changes in SST forcing, not sampling error. Year-to-year changes in the frequency of occurrence of the PT, AL, and AR clusters in the simulations and the NCEP18 dataset are generally consistent with each other

Tropical Pacific–Driven Decadel Energy Transport Variability

Abstract The atmospheric energy transport variability associated with decadal sea surface temperature variability in the tropical Pacific is studied using an atmospheric primitive equation model coupled to a slab mixed layer. The decadal variability is prescribed as an anomalous surface heat flux that represents the reduced ocean heat transport in the tropical Pacific when it is anomalously warm. The atmospheric energy transport increases and compensates for the reduced ocean heat transport. Increased transport by the mean meridional overturning (i.e., the strengthening of the Hadley cells) causes increased poleward energy transport. The subtropical jets increase in strength and shift equatorward, and in the midlatitudes the transients are affected. NCEP–NCAR reanalysis data show that the warming of the tropical Pacific in the 1980s compared to the early 1970s seems to have caused very similar changes in atmospheric energy transport indicating that these atmospheric transport variations were driven from the tropical Pacific. To study the implication of these changes for the coupled climate system an ocean model is driven with winds obtained from the atmosphere model. The poleward ocean heat transport increased when simulated wind anomalies associated with decadal tropical Pacific variability were used, showing a negative feedback between decadal variations in the mean meridional circulation in the atmosphere and in the Pacific Ocean. The Hadley cells and subtropical cells act to stabilize each other on the decadal time scale

CMIP6 Models Trend Toward Less Persistent European Blocking Regimes in a Warming Climate

The response of the Euro-Atlantic wintertime circulation to climate change is deeply uncertain. The Atlantic jet is caught in a “tug-of-war” between rapid warming trends in both the tropics and the Arctic leading to debate over the changing “waviness” of the jet, which is subject to strong non-linearity and internal variability. From the complementary perspective of weather regimes, there is considerable uncertainty in how atmospheric blocking will alter under climate change. By applying the hybrid approach of geopotential-jet regimes to 6th phase of the coupled model inter-comparison project projections, we show that the centers of action of anticyclonic regimes hardly alter even under severe warming. Instead, regimes are expected to become less persistent, with zonal flow conditions becoming more prevalent, although models disagree on the details of regime changes. Finally, we show the regime response can be captured qualitatively in a simple Lorenz-like model, emphasizing the conceptual link between observed regimes and those in basic mathematical systems

On Pacific Subtropical Cell Variability over the Second Half of the Twentieth Century

Abstract The evolution of the Pacific subtropical cells (STC) is presented for the period 1948–2007. Using ocean models of different resolutions forced with interannually varying atmospheric forcing datasets, the mechanisms responsible for the observed STC weakening and late recovery during the period of study are analyzed. As a result of the STC weakening (strengthening), warming (cooling) trends are found in the equatorial Pacific sea surface temperatures (SSTs). Model results agree well with observed estimates of STC transport, STC convergence, and equatorial SST anomalies. It is shown that subtropical atmospheric variability is the primary driver of the STC and equatorial SST low-frequency evolution and is responsible for both the slowdown during the second half of the twentieth century and the rebound at the end of the century. Subtropically forced STC variability is identified as a major player in the generation of equatorial Pacific decadal SST anomalies, pacing tropical Pacific natural climate variability on interdecadal time scales, as observed in historical records. The natural mode of variability has implications for the evolution of equatorial SST in the coming decades under the concomitant effects of climate change

Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population

Stroke-related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non-affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce maladaptive plasticity. Ekso is a wearable powered exoskeleton robot able to support over-ground gait training. The user controls the exoskeleton by triggering each single step during the gait cycle. The fine-tuning of the exoskeleton control system is crucial-it is set according to the residual functional abilities of the patient, and it needs to ensure lower limbs powered gait to be the most physiological as possible. This work focuses on the definition of an automatic calibration procedure able to detect the best Ekso setting for each patient. EMG activity has been recorded from Tibialis Anterior, Soleus, Rectus Femoris, and Semitendinosus muscles in a group of 7 healthy controls and 13 neurological patients. EMG signals have been processed so to obtain muscles activation patterns. The mean muscular activation pattern derived from the controls cohort has been set as reference. The developed automatic calibration procedure requires the patient to perform overground walking trials supported by the exoskeleton while changing parameters setting. The Gait Metric index is calculated for each trial, where the closer the performance is to the normative muscular activation pattern, in terms of both relative amplitude and timing, the higher the Gait Metric index is. The trial with the best Gait Metric index corresponds to the best parameters set. It has to be noted that the automatic computational calibration procedure is based on the same number of overground walking trials, and the same experimental set-up as in the current manual calibration procedure. The proposed approach allows supporting the rehabilitation team in the setting procedure. It has been demonstrated to be robust, and to be in agreement with the current gold standard (i.e., manual calibration performed by an expert engineer). The use of a graphical user interface is a promising tool for the effective use of an automatic procedure in a clinical context

A biofeedback cycling training to improve locomotion: a case series study based on gait pattern classification of 153 chronic stroke patients

<p>Abstract</p> <p>Background</p> <p>The restoration of walking ability is the main goal of post-stroke lower limb rehabilitation and different studies suggest that pedaling may have a positive effect on locomotion. The aim of this study was to explore the feasibility of a biofeedback pedaling treatment and its effects on cycling and walking ability in chronic stroke patients. A case series study was designed and participants were recruited based on a gait pattern classification of a population of 153 chronic stroke patients.</p> <p>Methods</p> <p>In order to optimize participants selection, a k-means cluster analysis was performed to subgroup homogenous gait patterns in terms of gait speed and symmetry.</p> <p>The training consisted of a 2-week treatment of 6 sessions. A visual biofeedback helped the subjects in maintaining a symmetrical contribution of the two legs during pedaling. Participants were assessed before, after training and at follow-up visits (one week after treatment). Outcome measures were the unbalance during a pedaling test, and the temporal, spatial, and symmetry parameters during gait analysis.</p> <p>Results and discussion</p> <p>Three clusters, mainly differing in terms of gait speed, were identified and participants, representative of each cluster, were selected.</p> <p>An intra-subject statistical analysis (ANOVA) showed that all patients significantly decreased the pedaling unbalance after treatment and maintained significant improvements with respect to baseline at follow-up. The 2-week treatment induced some modifications in the gait pattern of two patients: one, the most impaired, significantly improved mean velocity and increased gait symmetry; the other one reduced significantly the over-compensation of the healthy limb. No benefits were produced in the gait of the last subject who maintained her slow but almost symmetrical pattern. Thus, this study might suggest that the treatment can be beneficial for patients having a very asymmetrical and inefficient gait and for those that overuse the healthy leg.</p> <p>Conclusion</p> <p>The results demonstrated that the treatment is feasible and it might be effective in translating progresses from pedaling to locomotion. If these results are confirmed on a larger and controlled scale, the intervention, thanks to its safety and low price, could have a significant impact as a home- rehabilitation treatment for chronic stroke patients.</p

On the Need of Intermediate Complexity General Circulation Models: A "SPEEDY" Example

processes that allows realistic and fast climate simula -tions that often involve large ensembles for the purpose of reducing uncertainty and estimation of the forced and internal variability of the system. The forced signal is typically estimated by an ensemble mean of many simulations, but ensembles of state-of-the-art models are often too small to reduce the remaining internal variability. The ensemble size needed to estimate the mean accurately depends on the signal-to-noise ratio for the variable and region under consideration. For example, the ensemble size to estimate midlatitude 500-hPa height accurately is about 20, which is larger than most ensembles used in seasonal hindcast data-sets or climate projections performed by individual centers. Intermediate complexity models can also be used efficiently to investigate the sensitivity of simu-lated climate to changes in parameters in the physical parameterizations. Another application is related to climate change. For example, Forest et al. (2002) and Sokolov at al. (2009) use the MIT Integrated Global System Model (MIT IGSM) to investigate topics such as climate sensitivity, aerosol forcing, ocean heat uptake rate, and probabilistic projections of climate change. There are many intermediate complexity system models of intermediate complexity (EMICs). A number of them are participating in the IPCC Fifth Assessment Report and can be found at http://climate .uvic.ca/EMICAR5 (one of which is based on a previous version of the model introduced here). This website also provides information about experiments that are performed with these models that range from en-sembles of 1,000-year-long historical simulations to the assessment of different C

Adjunctive treatment and BoNT-A for post-stroke spasticity: are we really focusing on the patient-centered goals?

[no abstract available