Stochastic ensemble climate forecast with an analogue model

This paper presents a system to perform large-ensemble climate stochastic forecasts. The system is based on random analogue sampling of sea-level pressure data from the NCEP reanalysis. It is tested to forecast a North Atlantic Oscillation (NAO) index and the daily average temperature in five European stations. We simulated 100-member ensembles of averages over lead times from 5 days to 80 days in a hindcast mode, i.e., from a meteorological to a seasonal forecast. We tested the hindcast simulations with the usual forecast skill scores (CRPS or correlation) against persistence and climatology. We find significantly positive skill scores for all timescales. Although this model cannot outperform numerical weather prediction, it presents an interesting benchmark that could complement climatology or persistence forecast.</p

Postural adaptations to unilateral knee joint hypomobility induced by orthosis wear during gait initiation

Abstract Balance control and whole-body progression during gait initiation (GI) involve knee-joint mobility. Single knee-joint hypomobility often occurs with aging, orthopedics or neurological conditions. The goal of the present study was to investigate the capacity of the CNS to adapt GI organization to single knee-joint hypomobility induced by the wear of an orthosis. Twenty-seven healthy adults performed a GI series on a force-plate in the following conditions: without orthosis ("control"), with knee orthosis over the swing leg ("orth-swing") and with the orthosis over the contralateral stance leg ("orth-stance"). In orth-swing, amplitude of mediolateral anticipatory postural adjustments (APAs) and step width were larger, execution phase duration longer, and anteroposterior APAs smaller than in control. In orth-stance, mediolateral APAs duration was longer, step width larger, and amplitude of anteroposterior APAs smaller than in control. Consequently, step length and progression velocity (which relate to the "motor performance") were reduced whereas stability was enhanced compared to control. Vertical force impact at foot-contact did not change across conditions, despite a smaller step length in orthosis conditions compared to control. These results show that the application of a local mechanical constraint induced profound changes in the global GI organization, altering motor performance but ensuring greater stability

Attribution of human-induced dynamical and thermodynamical contributions in extreme weather events

This is the final version. Available on open access from IOP Publishing via the DOI in this recordWe present a new method that allows a separation of the attribution of human influence in extreme events into changes in atmospheric flows and changes in other processes. Assuming two data sets of model simulations or observations representing a natural, or 'counter-factual' climate, and the actual, or 'factual' climate, we show how flow analogs used across data sets can provide quantitative estimates of each contribution to the changes in probabilities of extreme events. We apply this method to the extreme January precipitation amounts in Southern UK such as were observed in the winter of 2013/2014. Using large ensembles of an atmospheric model forced by factual and counterfactual sea surface temperatures, we demonstrate that about a third of the increase in January precipitation amounts can be attributed to changes in weather circulation patterns and two thirds of the increase to thermodynamic changes. This method can be generalized to many classes of events and regions and provides, in the above case study, similar results to those obtained in Schaller et al (2016 Nat. Clim. Change 6 627-34) who used a simple circulation index, describing only a local feature of the circulation, as in other methods using circulation indices (van Ulden and van Oldenborgh 2006 Atmos. Chem. Phys. 6 863-81).European Union FP7French Ministry of EcologyEuropean Research Council (ERC

Climate of the Past Open Access Using palaeo-climate comparisons to constrain future projections

www.clim-past.net/10/221/2014/ doi:10.5194/cp-10-221-2014 © Author(s) 2014. CC Attribution 3.0 License

Multivariate stochastic bias corrections with optimal transport

Bias correction methods are used to calibrate climate model outputs with respect to observational records. The goal is to ensure that statistical features (such as means and variances) of climate simulations are coherent with observations. In this article, a multivariate stochastic bias correction method is developed based on optimal transport. Bias correction methods are usually defined as transfer functions between random variables. We show that such transfer functions induce a joint probability distribution between the biased random variable and its correction. The optimal transport theory allows us to construct a joint distribution that minimizes an energy spent in bias correction. This extends the classical univariate quantile mapping techniques in the multivariate case. We also propose a definition of non-stationary bias correction as a transfer of the model to the observational world, and we extend our method in this context. Those methodologies are first tested on an idealized chaotic system with three variables. In those controlled experiments, the correlations between variables appear almost perfectly corrected by our method, as opposed to a univariate correction. Our methodology is also tested on daily precipitation and temperatures over 12 locations in southern France. The correction of the inter-variable and inter-site structures of temperatures and precipitation appears in agreement with the multi-dimensional evolution of the model, hence satisfying our suggested definition of non-stationarity.</p

Possibility between earthquake and explosion seismogram differentiation by discrete stochastic non-Markov processes and local Hurst exponent analysis

The basic purpose of the paper is to draw the attention of researchers to new possibilities of differentiation of similar signals having different nature. One of examples of such kind of signals is presented by seismograms containing recordings of earthquakes (EQ's) and technogenic explosions (TE's). We propose here a discrete stochastic model for possible solution of a problem of strong EQ's forecasting and differentiation of TE's from the weak EQ's. Theoretical analysis is performed by two independent methods: with the use of statistical theory of discrete non-Markov stochastic processes (Phys. Rev. E62,6178 (2000)) and the local Hurst exponent. Time recordings of seismic signals of the first four dynamic orthogonal collective variables, six various plane of phase portrait of four dimensional phase space of orthogonal variables and the local Hurst exponent have been calculated for the dynamic analysis of the earth states. The approaches, permitting to obtain an algorithm of strong EQ's forecasting and to differentiate TE's from weak EQ's, have been developed.Comment: REVTEX +12 ps and jpg figures. Accepted for publication in Phys. Rev. E, December 200

Multiple perspectives on the attribution of the extreme European summer of 2012 to climate change

Summer 2012 was very wet in northern Europe, and unusually dry and hot in southern Europe. We use multiple approaches to determine whether anthropogenic forcing made the extreme European summer of 2012 more likely. Using a number of observation- and model-based methods, we find that there was an anthropogenic contribution to the extremes in southern Europe, with a qualitative consensus across all methodologies. There was a consensus across the methodologies that there has been a significant increase in the risk of hot summers in southern Europe with climate change. Most approaches also suggested a slight drying, but none of the results were statistically significant. The unusually wet summer in northern Europe was made more likely by the observed atmospheric circulation pattern in 2012, but no evidence was found for a long-term trend in circulation

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies

Spectral quantification of nonlinear behaviour of the nearshore seabed and correlations with potential forcings at Duck, N.C., U.S.A

Local bathymetric quasi-periodic patterns of oscillation are identified from monthly profile surveys taken at two shore-perpendicular transects at the USACE field research facility in Duck, North Carolina, USA, spanning 24.5 years and covering the swash and surf zones. The chosen transects are the two furthest (north and south) from the pier located at the study site. Research at Duck has traditionally focused on one or more of these transects as the effects of the pier are least at these locations. The patterns are identified using singular spectrum analysis (SSA). Possible correlations with potential forcing mechanisms are discussed by 1) doing an SSA with same parameter settings to independently identify the quasi-periodic cycles embedded within three potentially linked sequences: monthly wave heights (MWH), monthly mean water levels (MWL) and the large scale atmospheric index known as the North Atlantic Oscillation (NAO) and 2) comparing the patterns within MWH, MWL and NAO to the local bathymetric patterns. The results agree well with previous patterns identified using wavelets and confirm the highly nonstationary behaviour of beach levels at Duck; the discussion of potential correlations with hydrodynamic and atmospheric phenomena is a new contribution. The study is then extended to all measured bathymetric profiles, covering an area of 1100m (alongshore) by 440m (cross-shore), to 1) analyse linear correlations between the bathymetry and the potential forcings using multivariate empirical orthogonal functions (MEOF) and linear correlation analysis and 2) identify which collective quasi-periodic bathymetric patterns are correlated with those within MWH, MWL or NAO, based on a (nonlinear) multichannel singular spectrum analysis (MSSA). (...continued in submitted paper)Comment: 50 pages, 3 tables, 8 figure