A late medieval warm period in the Southern Ocean as a delayed response to external forcing?

International audienceOn the basis of long simulations performed with a three‐dimensional climate model, we propose an interhemispheric climate lag mechanism, involving the long‐term memory of deepwater masses. Warm anomalies, formed in the North Atlantic when warm conditions prevail at surface, are transported by the deep ocean circulation towards the Southern Ocean. There, the heat is released because of large scale upwelling, maintaining warm conditions and inducing a lagged response of about 150 years compared to the Northern Hemisphere. Model results and observations covering the first half of the second millenium suggest a delay between the temperature evolution in the Northern Hemisphere and in the Southern Ocean. The mechanism described here provides a reasonable hypothesis to explain such an interhemipsheric lag

Protein multi-scale organization through graph partitioning and robustness analysis: Application to the myosin-myosin light chain interaction

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding.Comment: 13 pages, 7 Postscript figure

An artificial neural network‐based model to predict chronic kidney disease in aged cats

Background Chronic kidney disease (CKD) frequently causes death in older cats; its early detection is challenging. Objectives To build a sensitive and specific model for early prediction of CKD in cats using artificial neural network (ANN) techniques applied to routine health screening data. Animals Data from 218 healthy cats ≥7 years of age screened at the Royal Veterinary College (RVC) were used for model building. Performance was tested using data from 3546 cats in the Banfield Pet Hospital records and an additional 60 RCV cats—all initially without a CKD diagnosis. Methods Artificial neural network (ANN) modeling used a multilayer feed‐forward neural network incorporating a back‐propagation algorithm. Clinical variables from single cat visits were selected using factorial discriminant analysis. Independent submodels were built for different prediction time frames. Two decision threshold strategies were investigated. Results Input variables retained were plasma creatinine and blood urea concentrations, and urine specific gravity. For prediction of CKD within 12 months, the model had accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 88%, 87%, 70%, 53%, and 92%, respectively. An alternative decision threshold increased specificity and PPV to 98% and 87%, but decreased sensitivity and NPV to 42% and 79%, respectively. Conclusions and Clinical Importance A model was generated that identified cats in the general population ≥7 years of age that are at risk of developing CKD within 12 months. These individuals can be recommended for further investigation and monitoring more frequently than annually. Predictions were based on single visits using common clinical variables

Bidecadal North Atlantic ocean circulation variability controlled by timing of volcanic eruptions

International audienceWhile bidecadal climate variability has been evidenced in several North Atlantic paleoclimaterecords, its drivers remain poorly understood. Here we show that the subset of CMIP5historical climate simulations that produce such bidecadal variability exhibits a robustsynchronization, with a maximum in Atlantic Meridional Overturning Circulation (AMOC) 15years after the 1963 Agung eruption. The mechanisms at play involve salinity advection fromthe Arctic and explain the timing of Great Salinity Anomalies observed in the 1970s and the1990s. Simulations, as well as Greenland and Iceland paleoclimate records, indicate thatcoherent bidecadal cycles were excited following five Agung-like volcanic eruptions of the lastmillennium. Climate simulations and a conceptual model reveal that destructive interferencecaused by the Pinatubo 1991 eruption may have damped the observed decreasing trend of theAMOC in the 2000s. Our results imply a long-lasting climatic impact and predictabilityfollowing the next Agung-like eruption

Diffusive limits on the Penrose tiling

In this paper random walks on the Penrose lattice are investigated. Heat kernel estimates and the invariance principle are shown

Developing a western Siberia reference site for tropospheric water vapour isotopologue observations obtained by different techniques (in situ and remote sensing)

Water stable isotopologues provide integrated tracers of the atmospheric water cycle, affected by changes in air mass origin, non-convective and convective processes and continental recycling. Novel remote sensing and in situ measuring techniques have recently offered opportunities for monitoring atmospheric water vapour isotopic composition. Recently developed infrared laser spectrometers allow for continuous in situ measurements of surface water vapour δD_v and δ¹⁸O_v. So far, very few intercomparisons of measurements conducted using different techniques have been achieved at a given location, due to difficulties intrinsic to the comparison of integrated with local measurements. Nudged simulations conducted with high-resolution isotopically enabled general circulation models (GCMs) provide a consistent framework for comparison with the different types of observations. Here, we compare simulations conducted with the ECHAM5-wiso model with two types of water vapour isotopic data obtained during summer 2012 at the forest site of Kourovka, western Siberia: hourly ground-based FTIR total atmospheric columnar δD_v amounts, and in situ hourly Picarro δD_v measurements. There is an excellent correlation between observed and predicted δD_v at surface while the comparison between water column values derived from the model compares well with FTIR estimates

Summer Temperature Trend Over the Past Two Millennia Using Air Content in Himalayan Ice

Two Himalayan ice cores display a factor-two decreasing trend of air content over the past two millennia, in contrast to the relatively stable values in Greenland and Antarctica ice cores over the same period. Because the air content can be related with the relative frequency and intensity of melt phenomena, its variations along the Himalayan ice cores provide an indication of summer temperature trend. Our reconstruction point toward an unprecedented warming trend in the 20th century but does not depict the usual trends associated with Medieval Warm Period (MWP), or Little Ice Age (LIA)

Target atmospheric CO2: Supporting material

Additional material supporting the article "Target atmospheric CO2: Where should humanity aim?"Comment: 27 pages, 21 figures; final version accepted by Open Science Atmospheric Journal; main article separately submitted to arXiv as "Target atmospheric CO2: Where should humanity aim?", arxiv:0804.112

Isotopic exchange on the diurnal scale between near-surface snow and lower atmospheric water vapor at Kohnen station, East Antarctica

Quantifying the magnitude of post-depositional processes affecting the isotopic composition of surface snow is essential for a more accurate interpretation of ice core data. To achieve this, high temporal resolution measurements of both lower atmospheric water vapor and surface snow iso- topic composition are required. This study presents contin- uous measurements of water vapor isotopes performed in East Antarctica (Kohnen station) from December 2013 to January 2014 using a laser spectrometer. Observations have been compared with the outputs of two atmospheric gen- eral circulation models (AGCMs) equipped with water va- por isotopes: ECHAM5-wiso and LMDZ5Aiso. During our monitoring period, the signals in the 2 m air temperature T , humidity mixing ratio q and both water vapor isotopes δD and δ18O are dominated by the presence of diurnal cycles. Both AGCMs simulate similar diurnal cycles with a mean amplitude 30 to 70 % lower than observed, possibly due to an incorrect simulation of the surface energy balance and the boundary layer dynamics. In parallel, snow surface samples were collected each hour over 35 h, with a sampling depth of 2–5 mm. A diurnal cycle in the isotopic composition of the snow surface is observed in phase with the water vapor, reaching a peak-to-peak amplitude of 3 ‰ for δD over 24 h (compared to 36 ‰ for δD in the water vapor). A simple box model treated as a closed system has been developed to study the exchange of water molecules between an air and a snow reservoir. In the vapor, the box model simulations show too much isotopic depletion compared to the observations. Mix- ing with other sources (advection, free troposphere) has to be included in order to fit the observations. At the snow surface, the simulated isotopic values are close to the observations with a snow reservoir of ∼ 5 mm depth (range of the snow sample depth). Our analysis suggests that fractionation oc- curs during sublimation and that vapor–snow exchanges can no longer be considered insignificant for the isotopic compo- sition of near-surface snow in polar regions