Data-Adaptive Wavelets and Multi-Scale Singular Spectrum Analysis

Using multi-scale ideas from wavelet analysis, we extend singular-spectrum analysis (SSA) to the study of nonstationary time series of length $N$ whose intermittency can give rise to the divergence of their variance. SSA relies on the construction of the lag-covariance matrix C on M lagged copies of the time series over a fixed window width W to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components; here W = M Dt, with Dt the time step. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M <= W <= N. Multi-scale SSA varies W, while keeping a fixed W/M ratio, and uses the eigenvectors of the corresponding lag-covariance matrix C_M as a data-adaptive wavelets; successive eigenvectors of C_M correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's covariance matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic and geophysical time series. A real application is to the Southern Oscillation index (SOI) monthly values for 1933-1996. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 4 and 3 years supports the Devil's staircase scenario for the El Nino/Southern Oscillation phenomenon.Comment: 24 pages, 19 figure

Klima. 30 pitanja za razumijevanje Konferencije u Parizu (Pascal Canfin i Peter Staime)

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21–9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part

PMIP4-CMIP6: the contribution of the Paleoclimate Modelling Intercomparison Project to CMIP6

The goal of the Palaeoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to changes in different climate forcings and to feedbacks. Through comparison with observations of the environmental impacts of these climate changes, or with climate reconstructions based on physical, chemical or biological records, PMIP also addresses the issue of how well state-of-the-art models simulate climate changes. Palaeoclimate states are radically different from those of the recent past documented by the instrumental record and thus provide an out-of-sample test of the models used for future climate projections and a way to assess whether they have the correct sensitivity to forcings and feedbacks. Five distinctly different periods have been selected as focus for the core palaeoclimate experiments that are designed to contribute to the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This manuscript describes the motivation for the choice of these periods and the design of the numerical experiments, with a focus upon their novel features compared to the experiments performed in previous phases of PMIP and CMIP as well as the benefits of common analyses of the models across multiple climate states. It also describes the information needed to document each experiment and the model outputs required for analysis and benchmarking

The PMIP4 contribution to CMIP6 – Part 4: scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments

The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM

Differential Selection on Carotenoid Biosynthesis Genes as a Function of Gene Position in the Metabolic Pathway: A Study on the Carrot and Dicots

Background: Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics. Methodology/Principal Findings: Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway

Utilisation de fragments d'ADN polymorphes amplifies au hasard (RAPD) pour la realisation d'une cartographie genetique de Petunia hybrida hort. et d'une phylogenie du genre Petunia

* INRA Laboratoire de Phytopharmacie, BV 1540, 21034 Dijon cedex (FRA) Diffusion du document : INRA Laboratoire de Phytopharmacie, BV 1540, 21034 Dijon cedex (FRA) Diplôme : Dr. d'Universit

Analyse de la variabilité génétique mitochondriale et chloroplastique de deux espèces du genre Lupinus (L.Albus et L. Mutabilis)

Notice présente dans BelInra (https://belinra.inra.fr/gestion/catalog.php?categ=isbd&id=90015)il s'agit d'un type de produit dont les métadonnées ne correspondent pas aux métadonnées attendues dans les autres types de produit : DISSERTATIONAnalyse de la variabilité génétique mitochondriale et chloroplastique de deux espèces du genre Lupinus (L.Albus et L. Mutabilis

Utilisation de fragments d'ADN polymorphes amplifies au hasard (RAPD) pour la realisation d'une cartographie genetique de Petunia hybrida hort. et d'une phylogenie du genre Petunia

* INRA Laboratoire de Phytopharmacie, BV 1540, 21034 Dijon cedex (FRA) Diffusion du document : INRA Laboratoire de Phytopharmacie, BV 1540, 21034 Dijon cedex (FRA) Diplôme : Dr. d'Universit

Genetic neighbourhood and effective population size in the endangered European mink Mustela lutreola

Genetic neighbourhood and effective population size (Ne) are critical factors when determining the potential survival of threatened species. Carnivores have intrinsically small effective numbers, because, as top predators, they show low densities. The European mink, Mustela lutreola, is one of the most endangered carnivores in the world and has suffered continual decline and local extinctions. The genetic neighbourhood, area within which adults could randomly mate, averaged Na = 31.7 km diameter, allowing that population size within the neighbourhood area only ranged from Nb = 6.1 to 22.8 animals. Although the population size was assessed in one of the main mink populations in the world, this neighbourhood size is far below the values regarded as critical in literature. However, in contrast with recent propositions, the ratio Ne/N only ranged between 0.09 and 0.19, estimates close to the average recognised by Frankham [(1995) Genetic Research 66: 95–107] for wildlife populations. In the context of the challenge to conserve this endangered carnivore, the studied neighbourhood provided crucial information suggesting both a low neighbourhood size and severe disturbance of breeding exchanges, emphasising the dramatically threatened status of the European mink