Simulations of tropical cyclones and african easterly waves in high- and low-resolution climate models

Cette thèse se penche sur différents aspects des cyclones tropicaux tels que simulés par des modèles de circulation générale (MCG) et un modèle régional de climat (MRC), le modèle régional de climat canadien (MRCC5). D'abord, nous évaluons la capacité d'un ensemble de MCG, utilisé dans le cadre du 4e rapport du GIEC (Groupe d'experts Intergouvernemental sur l'Évolution du Climat), à capturer les principales zones de cyclogenèse au travers d'indices dérivés à partir des champs atmosphériques favorables à la formation des cyclones tropicaux. En comparant les événements de cyclogenèse observés avec les deux indices calculés à partir de réanalyses et d'un ensemble de MCG, nous vérifions que les indices arrivent à relativement bien représenter la distribution actuelle des cyclones tropicaux, autant dans les modèles que les réanalyses. En comparant des simulations couvrant la période 2080-2100 avec la période présente, l'indice jugé plus stable projette une légère augmentation du nombre des tempêtes dans le Pacifique Ouest. Le deuxième partie de la thèse est consacrée à évaluer la capacité du MRCC5 à reproduire la climatologie des cyclones tropicaux observée durant la période 1979-2006. Plus précisément, nous évaluons l'impact d'une augmentation de la résolution sur les caractéristiques physiques des cyclones ainsi que sur leur distribution géographique, de même que l'impact des conditions aux frontières, de la technique de « downscaling » dynamique utilisée et de la taille du domaine sur les cyclones simulés. Une telle évaluation est une étape cruciale à toute étude d'impact des changements climatiques sur les ouragans. La distribution des cyclones est consistante avec la distribution d'un indice de cyclogenèse, ce qui permet de mieux comprendre les changements observés dans les différentes simulations. Aussi, nous évaluons la capacité du modèle à reproduire la variabilité interannuelle observée durant cette période, et plus particulièrement l'impact de l'oscillation australe d'El Niño (El Niño Southern Oscillation ou ENSO) sur la cyclogenèse. Finalement, nous étudions les ondes d'Est africaines, systèmes précurseurs des ouragans dans l'Atlantique, tel que simulées par le MRCC5 de même que leur relation avec les cyclones tropicaux de l'Atlantique. Règle générale, le MRCC5 arrive à reproduire de façon réaliste l'activité observée durant la période 1979-2006. \ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : cyclones tropicaux, indices de cyclogenèse, ondes d'Est africaines, modèle régional de climat, modèle de circulation général

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Impact of reanalysis boundary conditions on downscaled Atlantic hurricane activity

Climate models are capable of producing features similar to tropical cyclones, but typically display strong biases for many of the storm physical characteristics due to their relatively coarse resolution compared to the size of the storms themselves. One strategy that has been adopted to circumvent this limitation is through the use of a hybrid downscaling technique, wherein a large set of synthetic tracks are created by seeding disturbances in the large-scale environment. Here, we evaluate the ability of this technique at reproducing many of the characteristics of the recent North Atlantic hurricane activity as well as its sensitivity to the choice of the reanalysis dataset used as boundary conditions. In particular, we show that the geographical and intensity distributions are well reproduced, but that the technique has difficulty capturing the large difference in activity observed between the most recent active and quiescent phase. Although the signal is somewhat reduced compared to observation, the technique also detects a significant decrease in the intensification rate of hurricanes near the coastal US during the active phase compared to the quiescent phase. Finally, the influence of the El Niño Southern Oscillation on hurricane activity is generally well captured as well, but the technique fails to reproduce the increase in activity over the western part of the basin during Modoki El Niños.We would like to thank NOAA’s National Centers for Environmental Information for making the IBTrACS data available. JPB and LPC would like to acknowledge the financial support from the Ministerio de Economa y Competitividad (MINECO; Project GL2014-55764-R). LPC’s contract is co-financed by the MINECO under Juan de la Cierva Incorporacin postdoctoral fellowship number IJCI-2015-23367. MB would like to acknowledge financial support from the Natural Sciences and Engineering Research Council (NSERC) of Canada. Finally, we are grateful to Kerry Emanuel for providing the data as well as some useful feedback, and two anonymous reviewers for their helpful comments.Peer ReviewedPostprint (published version

Effect of 5-azacytidine and galectin-1 on growth and differentiation of the human b lymphoma cell line bl36

BACKGROUND: 5-AzaCytidine (AzaC) is a DNA demethylating drugs that has been shown to inhibit cell growth and to induce apoptosis in certain cancer cells. Induced expression of the galectin1 (Gal1) protein, a galactoside-binding protein distributed widely in immune cells, has been described in cultured hepatoma-derived cells treated with AzaC and this event may have a role in the effect of the drug. According to this hypothesis, we investigated the effect of AzaC and Gal1 on human lymphoid B cells phenotype. METHODS: The effect of AzaC and Gal1 on cell growth and phenotype was determined on the Burkitt lymphoma cell line BL36. An immunocytochemical analysis for detection of Gal1 protein expression was performed in AzaC-treated cells. To investigate the direct effects of Gal1, recombinant Gal1 was added to cells. RESULTS: Treatment of lymphoid B cells with AzaC results in: i) a decrease in cell growth with an arrest of the cell cycle at G0/G1 phase, ii) phenotypic changes consistent with a differentiated phenotype, and iii) the expression of p16, a tumor-suppressor gene whose expression was dependent of its promoter demethylation, and of Gal1. A targeting of Gal 1 to the plasma membrane follows its cytosolic expression. To determine which of the effects of AzaC might be secondary to the induction of Gal1, recombinant Gal1 was added to BL36 cells. Treated cells displayed growth inhibition and phenotypic changes consistent with a commitment toward differentiation. CONCLUSIONS: Altered cell growth and expression of the cell surface plasma cell antigen, CD138 are detectable in BL36 cells treated by AzaC as well as by Gal1. It seems that AzaC-induced Gal1 expression and consequent binding of Gal1 on its cell membrane receptor may be, in part, involved in AzaC-induced plasmacytic differentiation

How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

The recent emergence of near-term climate prediction, wherein climate models are initialized with the contemporaneous state of the Earth system and integrated up to 10 years into the future, has prompted the development of three different multiannual forecasting techniques of North Atlantic hurricane frequency. Descriptions of these three different approaches, as well as their respective skill, are available in the peer-reviewed literature, but because these various studies are sufficiently different in their details (e.g., period covered, metric used to compute the skill, measure of hurricane activity), it is nearly impossible to compare them. Using the latest decadal reforecasts currently available, we present a direct comparison of these three multiannual forecasting techniques with a combination of simple statistical models, with the hope of offering a perspective on the current state-of-the-art research in this field and the skill level currently reached by these forecasts. Using both deterministic and probabilistic approaches, we show that these forecast systems have a significant level of skill and can improve on simple alternatives, such as climatological and persistence forecasts.The first author would like to thank Isadora Jimenez for providing the necessary material for Fig. 2. The first author would like to acknowledge the financial support from the Ministerio de Economía, Industria y Competitividad (MINECO; Project CGL2014- 55764-R), the Risk Prediction Initiative at BIOS (Grant RPI2.0-2013-CARON), and the EU [Seventh Framework Programme (FP7); Grant Agreement GA603521]. We additionally acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LPC's contract is cofinanced by the MINECO under the Juan de la Cierva Incorporacion postdoctoral fellowship number IJCI-2015-23367. Finally, we thank the National Hurricane Center for making the HURDAT2 data available. All climate model data are available at https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/.Peer ReviewedPostprint (published version