In this article the concept of weather regimes is used to assess the flow‐dependent skill of the European Centre for Medium‐range Weather Forecast (ECMWF) ensemble predictions at the late ...medium‐range. The flow patterns leading to more or less accurate predictions are identified and the variations of skill in these situations are quantified. The focus is on the Euro‐Atlantic sector during the extended winter period when the atmospheric regime structure is most pronounced. Verification results show that, in the medium range, forecasts initiated in the negative phase of North Atlantic Oscillation (NAO−) are the most skillful. For these forecasts the ensemble spread over Europe is lower than average, showing that the ensemble spread provides useful information about the error of the ensemble‐mean forecast. The performance of the ensemble is further assessed by stratifying the cases according to their initial conditions, as well as by their accuracy at forecast day 10. Results indicate that the least skillful predictions are mainly associated with missing the transitions to a blocking regime circulation. Forecasts also underestimate the blocking persistence, whereas they overestimate the persistence of zonal flows. Transitions to a positive phase of the NAO are also overrepresented.
The potential of early warning for severe cold conditions is explored using the Subseasonal to Seasonal (S2S) Prediction research project data archive. We explore the use of a two‐dimensional phase ...space based on the leading empirical orthogonal functions (EOFs) of mid‐tropospheric flow computed over the Euro‐Atlantic region in order to study the time evolution of flow patterns associated with high‐impact temperature anomalies. We find that the phase space is an effective tool for monitoring predictions of regime transitions at medium and extended ranges. We show that a number of S2S systems have some skill in the prediction of cold spells over Europe, even beyond the medium range. In particular, the ECMWF (European Centre for Medium‐Range Weather Forecasts) model represents well the observed preferential transition paths. We reveal that the impact of the Madden–Julian Oscillation (MJO) on the predictive skill of large‐scale flow over Europe is asymmetric. The impact of the MJO on the Brier skill scores and reliability is significantly positive for predictions of the negative phase of the North Atlantic Oscillation (NAO): beyond week one, forecasts with the MJO in their initial state are significantly more reliable than forecasts with no MJO in their initial conditions. In contrast, the predictive skill for positive NAO shows little sensitivity to the MJO.
Subseasonal predictions provide enormous potential for early warnings of severe cold events over Europe. As the image shows, several forecasting systems can provide skillful predictions of large‐scale patterns, typically associated with severe cold events over Europe, more than 10 days in advance. However, the success of forecasting weeks ahead changes in large‐scale flow that lead to cold conditions depends on the type of transitions.
The Arctic Oscillation (AO) is the leading mode of variation in the northern hemisphere winter circulation. Despite its importance for winter temperatures, seasonal forecast models typically suggest ...that its predictability is low. Nonetheless, we show that an operational forecast model has high skill in predicting the AO, with a correlation of 0.61 for the period of 1981–2010. Experimentation covering a recent 8 year high‐skill period demonstrates the predictability of the model AO to be dominated by atmospheric initial conditions, although surface forcing does have increasing influence later in the winter. Results suggest that the stratosphere is an important carrier of model predictability during the early winter. These results challenge the conventional paradigm of surface forcing being the dominant source of predictability on seasonal time scales but are compatible with the results showing stratospheric influence on winter circulation. They also suggest that model representation of stratospheric to tropospheric coupling needs urgent improvement.
Key Points
High skill in predicting the Arctic Oscillation over a 30 year period
Model predictability is dominated by atmospheric initial conditions
Results suggest that stratosphere‐troposphere coupling needs improvement
Stratosphere–troposphere coupling is often viewed from the perspective of the annular modes and their dynamics. Despite the obvious benefits of this approach, recent work has emphasised the greater ...tropospheric sensitivity to stratospheric variability in the Atlantic basin than in the Pacific basin. In this study, a new approach to understanding stratosphere–troposphere coupling is proposed, with a focus on the influence of the stratospheric state on North Atlantic weather regimes (during extended winter, November to March). The influence of the strength of the lower‐stratospheric vortex on four commonly used tropospheric weather regimes is quantified. The negative phase of the North Atlantic Oscillation is most sensitive to the stratospheric state, occurring on 33% of days following weak vortex conditions but on only 5% of days following strong vortex conditions. An opposite and slightly weaker sensitivity is found for the positive phase of the North Atlantic Oscillation and the Atlantic Ridge regime. For the North Atlantic Oscillation regimes, stratospheric conditions change both the probability of remaining in each regime and the probability of transitioning to that regime from others. A logistic regression model is developed to further quantify the sensitivity of tropospheric weather regimes to the lower stratospheric state. The logistic regression model predicts an increase of 40–60% in the probability of transition to the negative phase of the North Atlantic Oscillation for a one standard deviation reduction in the strength of the stratospheric vortex. Similarly it predicts a 10–30% increase in the probability of transition to the positive phase of the North Atlantic Oscillation for a one standard deviation increase in the strength of the stratospheric vortex. The stratosphere–troposphere coupling in the European Centre for Medium‐range Weather Forecasts Integrated Forecasting System model is found to be consistent with the re‐analysis data by fitting the same logistic regression model.
Stratosphere–troposphere coupling is often viewed from the perspective of the annular modes. In this study, a new approach is proposed, focussing on the influence of the stratospheric state on North Atlantic weather regimes. The influence of the strength of the lower‐stratospheric vortex on four commonly used tropospheric weather regimes is quantified. The figure shows how the probability of one of the regimes (the negative phase of the NAO) changes with the strength of the lower‐stratospheric jet.
This letter presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based ...receding-horizon approach computes a local trajectory that minimizes the tracking error while avoiding obstacles. We build on nonlinear model-predictive contouring control (MPCC) and extend it to incorporate a static map by computing, online, a set of convex regions in free space. We model moving obstacles as ellipsoids and provide a correct bound to approximate the collision region, given by the Minkowsky sum of an ellipse and a circle. Our framework is agnostic to the robot model. We present experimental results with a mobile robot navigating in indoor environments populated with humans. Our method is executed fully onboard without the need of external support and can be applied to other robot morphologies such as autonomous cars.
Weather regime forecasts are a prominent use case of sub‐seasonal prediction in the midlatitudes. A systematic evaluation and understanding of year‐round sub‐seasonal regime forecast performance is ...still missing, however. Here we evaluate the representation of and forecast skill for seven year‐round Atlantic–European weather regimes in sub‐seasonal reforecasts from the European Centre for Medium‐Range Weather Forecasts. Forecast calibration improves regime frequency biases and forecast skill most strongly in summer, but scarcely in winter, due to considerable large‐scale flow biases in summer. The average regime skill horizon in winter is about 5 days longer than in summer and spring, and 3 days longer than in autumn. The Zonal Regime and Greenland Blocking tend to have the longest year‐round skill horizon, which is driven by their high persistence in winter. The year‐round skill is lowest for the European Blocking, which is common for all seasons but most pronounced in winter and spring. For the related, more northern Scandinavian Blocking, the skill is similarly low in winter and spring but higher in summer and autumn. We further show that the winter average regime skill horizon tends to be enhanced following a strong stratospheric polar vortex (SPV), but reduced following a weak SPV. Likewise, the year‐round average regime skill horizon tends to be enhanced following phases 4 and 7 of the Madden–Julian Oscillation (MJO) but reduced following phase 2, driven by winter but also autumn and spring. Our study thus reveals promising potential for year‐round sub‐seasonal regime predictions. Further model improvements can be achieved by reduction of the considerable large‐scale flow biases in summer, better understanding and modeling of blocking in the European region, and better exploitation of the potential predictability provided by weak SPV states and specific MJO phases in winter and the transition seasons.
The overall sub‐seasonal forecast performance (biases and skill) for predicting seven year‐round Atlantic–European weather regimes is highest in winter and lowest in summer. The year‐round skill horizon is shortest for the European Blocking and longest for the Zonal Regime and Greenland Blocking (see figure). Furthermore, the winter skill horizon tends to be enhanced following a strong stratospheric polar vortex but reduced following a weak one. Madden–Julian Oscillation phases 4 and 7 tend to increase and phase 2 to decrease the year‐round skill horizon.
The European Summer of 2003 Ferranti, Laura; Viterbo, Pedro
Journal of climate,
08/2006, Letnik:
19, Številka:
15
Journal Article
Recenzirano
The European summer of 2003 is used as a case study to analyze the land surface role in augmenting the local temperature anomalies. Using the European Centre for Medium-Range Weather Forecasts ...(ECMWF) analysis and the 40-yr ECMWF Re-Analysis (ERA-40) climate, it is shown that in the months preceding the extreme summer events, positive anomalies in the surface shortwave radiation and a large precipitation deficit indicated an impending dry summer in early June. The use of soil water analysis values as possible predictors for drought is currently limited by the systematic attenuation of its seasonal cycle. Several numerical simulations with the ECMWF atmospheric model have been used to explore the atmospheric model sensitivity to the initial soil water conditions. The atmospheric response to large initial perturbations in the root zone extends up to month 2 and is nonlinear, and larger for drier regimes. Perturbations to the whole soil depth increase the amplitude of the atmospheric anomaly and extend its duration up to 3 months. The response of large initial dry soil anomalies greatly exceeds the impact of the ocean boundary forcing. Results from numerical simulations indicate the possible benefit of using perturbations in the initial soil water conditions, commensurate with soil moisture uncertainties, in the generation of the seasonal forecast ensembles.
There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is ...driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.
Convergent evidence indicates that apathy affects cognitive behavior in different neurological and psychiatric conditions. Studies of clinical populations have also suggested the primary involvement ...of the prefrontal cortex and the basal ganglia in apathy. These brain regions are interconnected at both the structural and functional levels and are deeply involved in cognitive processes, such as working memory and attention. However, it is unclear how apathy modulates brain processing during cognition and whether such a modulation occurs in healthy young subjects. To address this issue, we investigated the link between apathy and prefrontal and basal ganglia function in healthy young individuals. We hypothesized that apathy may be related to sub-optimal activity and connectivity in these brain regions.
Three hundred eleven healthy subjects completed an apathy assessment using the Starkstein's Apathy Scale and underwent fMRI during working memory and attentional performance tasks. Using an ROI approach, we investigated the association of apathy with activity and connectivity in the DLPFC and the basal ganglia.
Apathy scores correlated positively with prefrontal activity and negatively with prefrontal-basal ganglia connectivity during both working memory and attention tasks. Furthermore, prefrontal activity was inversely related to attentional behavior.
These results suggest that in healthy young subjects, apathy is a trait associated with inefficient cognitive-related prefrontal activity, i.e., it increases the need for prefrontal resources to process cognitive stimuli. Furthermore, apathy may alter the functional relationship between the prefrontal cortex and the basal ganglia during cognition.
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