Impact of brine-inducted stratification on the glacial carbon cycle

During the cold period of the Last Glacial Maximum (LGM, about 21 000 years ago) atmospheric CO2 was around 190 ppm, much lower than the pre-industrial concentration of 280 ppm. The causes of this substantial drop remain partially unresolved, despite intense research. Understanding the origin of reduced atmospheric CO2 during glacial times is crucial to comprehend the evolution of the different carbon reservoirs within the Earth system (atmosphere, terrestrial biosphere and ocean). In this context, the ocean is believed to play a major role as it can store large amounts of carbon, especially in the abyss, which is a carbon reservoir that is thought to have expanded during glacial times. To create this larger reservoir, one possible mechanism is to produce very dense glacial waters, thereby stratifying the deep ocean and reducing the carbon exchange between the deep and upper ocean. The existence of such very dense waters has been inferred in the LGM deep Atlantic from sediment pore water salinity and δ18O inferred temperature. Based on these observations, we study the impact of a brine mechanism on the glacial carbon cycle. This mechanism relies on the formation and rapid sinking of brines, very salty water released during sea ice formation, which brings salty dense water down to the bottom of the ocean. It provides two major features: a direct link from the surface to the deep ocean along with an efficient way of setting a strong stratification. We show with the CLIMBER-2 carbon-climate model that such a brine mechanism can account for a significant decrease in atmospheric CO2 and contribute to the glacial-interglacial change. This mechanism can be amplified by low vertical diffusion resulting from the brine-induced stratification. The modeled glacial distribution of oceanic δ13C as well as the deep ocean salinity are substantially improved and better agree with reconstructions from sediment cores, suggesting that such a mechanism could have played an important role during glacial times

Systematic study of the impact of fresh water fluxes on the glacial carbon cycle

During glacial periods, atmospheric CO2 concentration increases and decreases by around 15 ppm. At the same time, the climate changes gradually in Antarctica. Such climate changes can be simulated in models when the AMOC (Atlantic Meridional Oceanic Circulation) is weakened by adding fresh water to the North Atlantic. The impact on the carbon cycle is less straightforward, and previous studies give opposite results. Because the models and the fresh water fluxes were different in these studies, it prevents any direct comparison and hinders finding whether the discrepancies arise from using different models or different fresh water fluxes. In this study we use the CLIMBER-2 coupled climate carbon model to explore the impact of different fresh water fluxes. In both preindustrial and glacial states, the addition of fresh water and the resulting slow-down of the AMOC lead to an uptake of carbon by the ocean and a release by the terrestrial biosphere. The duration, shape and amplitude of the fresh water flux all have an impact on the change of atmospheric CO2 because they modulate the change of the AMOC. The maximum CO2 change linearly depends on the time integral of the AMOC change. The different duration, amplitude, and shape of the fresh water flux cannot explain the opposite evolution of ocean and vegetation carbon inventory in different models. The different CO2 evolution thus depends on the AMOC response to the addition of fresh water and the resulting climatic change, which are both model dependent. In CLIMBER-2, the rise of CO2 recorded in ice cores during abrupt events can be simulated under glacial conditions, especially when the sinking of brines in the Southern Ocean is taken into account. The addition of fresh water in the Southern Hemisphere leads to a decline of CO2, contrary to the addition of fresh water in the Northern Hemisphere

Russian approaches to energy security and climate change: Russian gas exports to the EU

The proposition that EU climate policy represents a threat to Russia’s gas exports to the EU, and therefore to Russia’s energy security, is critically examined. It is concluded that whilst the greater significance of climate-change action for Russian energy security currently lies not in Russia’s own emissions reduction commitments but in those of the EU, an even greater threat to Russia’s energy security is posed by the development of the EU internal gas market and challenges to Russia’s participation in that market. However, the coming decades could see Russia’s energy security increasingly influenced by climate-change action policies undertaken by current importers of Russian gas such as the EU, and potential importers such as China and India. The challenge for Russia will be to adapt to developments in energy security and climate-change action at the European and global levels

Proprioceptive perception of phase variability

Previous work has established that judgments of relative phase variability of 2 visually presented oscillators covary with mean relative phase. Ninety degrees is judged to be more variable than 0° or 180°, independently of the actual level of phase variability. Judged levels of variability also increase at 180°. This pattern of judgments matches the pattern of movement coordination results. Here, participants judged the phase variability of their own finger movements, which they generated by actively tracking a manipulandum moving at 0°, 90°, or 180°, and with 1 of 4 levels of Phase Variability. Judgments covaried as an inverted U-shaped function of mean relative phase. With an increase in frequency, 180° was judged more variable whereas 0° was not. Higher frequency also reduced discrimination of the levels of Phase Variability. This matching of the proprioceptive and visual results, and of both to movement results, supports the hypothesized role of online perception in the coupling of limb movements. Differences in the 2 cases are discussed as due primarily to the different sensitivities of the systems to the information

Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe

International audienceLocal-scale climate information is increasingly needed for the study of past, present and future climate changes. In this study we develop a non-linear statistical downscaling method to generate local temperatures and precipitation values from large-scale variables of a Earth System Model of Intermediate Complexity (here CLIMBER). Our statistical downscaling scheme is based on the concept of Generalized Additive Models (GAMs), capturing non-linearities via non-parametric techniques. Our GAMs are calibrated on the present Western Europe climate. For this region, annual GAMs (i.e. models based on 12 monthly values per location) are fitted by combining two types of large-scale explanatory variables: geographical (e.g. topographical information) and physical (i.e. entirely simulated by the CLIMBER model). To evaluate the adequacy of the non-linear transfer functions fitted on the present Western European climate, they are applied to different spatial and temporal large-scale conditions. Local projections for present North America and Northern Europe climates are obtained and compared to local observations. This partially addresses the issue of spatial robustness of our transfer functions by answering the question "does our statistical model remain valid when applied to large-scale climate conditions from a region different from the one used for calibration?". To asses their temporal performances, local projections for the Last Glacial Maximum period are derived and compared to local reconstructions and General Circulation Model outputs. Our downscaling methodology performs adequately for the Western Europe climate. Concerning the spatial and temporal evaluations, it does not behave as well for Northern America and Northern Europe climates because the calibration domain may be too different from the targeted regions. The physical explanatory variables alone are not capable of downscaling realistic values. However, the inclusion of geographical-type variables – such as altitude, advective continentality and moutains effect on wind (W–slope) – as GAM explanatory variables clearly improves our local projections

Levels of Cadmium, Lead, Mercury and 137caesium in Caribou (Rangifer tarandus) Tissues from Northern Québec

Levels of cadmium (Cd), lead (Pb) and total mercury (Hg) were assessed in samples of muscle, kidney, and liver from caribou (Rangifer tarandus; n = 317) harvested in two regions of northern Québec between 1994 and 1996. Levels of 137caesium (137Cs) were also examined in muscle samples. Log concentration of the three metals varied significantly among tissues and was lowest in diaphragm muscle and highest in kidneys and liver. Mean Cd (wet weight, w.w.) concentration was 0.01 µg/g in muscle, 7.69 µg/g in kidneys and 1.13 µg/g in liver. Levels of Cd exceeded tolerance thresholds for human consumption in nearly all kidney samples and in nearly half the liver samples. Mean Pb concentration (w.w.) was 0.05 µg/g in muscle, 0.26 µg/g in kidneys and 0.95 µg/g in liver, with few samples exceeding consumption thresholds. Mean total Hg concentration (w.w.) in muscle was 0.03 µg/g, 1.26 µg/g in kidneys and 0.67 µg/g in liver, with concentrations exceeding consumption thresholds in most kidney samples and nearly half the liver samples. Regional differences occurred in log concentration of the three metals for most tissues, with the western region consistently showing higher values. Mean log Cd and Pb concentrations increased with age in kidneys, but log Pb decreased with age in muscle samples. Interactions between month of collection and sex and region also occurred for some metals in some tissues. Mean level of 137Cs in muscle samples was 94.7 Bq/kg, never exceeding the acceptable limit for human consumption.On a mesuré les niveaux de cadmium (Cd), de plomb (Pb) et de mercure total (Hg) dans des échantillons de muscle, de rein et de foie de caribous (Rangifer tarandus; n = 317) prélevés dans deux régions du Québec nordique entre 1994 et 1996. On a en outre étudié les niveaux de césium 137 (137Cs) dans des échantillons musculaires. Les concentrations enregistrées des trois métaux montraient d'importantes variations parmi les divers tissus et étaient les plus faibles dans le muscle du diaphragme et les plus élevées dans le rein et le foie. La concentration moyenne de Cd (poids frais, p.f.) était de 0,01 µg/g dans le muscle, de 7,69 µg/g dans le rein et de 1,13 µg/g dans le foie. Les niveaux de Cd dépassaient les seuils de tolérance pour la consommation humaine dans presque tous les échantillons de rein et dans près de la moitié des échantillons de foie. La concentration moyenne (p.f.) de Pb était de 0,05 µg/g dans le muscle, de 0,26 µg/g dans le rein et de 0,95 µg/g dans le foie, avec peu d'échantillons dépassant les seuils de consommation. La concentration moyenne de Hg total (p.f.) dans le muscle était de 0,03 µg/g, de 1,26 µg/g dans le rein et de 0,67 µg/g dans le foie, avec des concentrations qui dépassaient les seuils de consommation dans la plupart des échantillons de rein et presque la moitié des échantillons de foie. Des différences régionales sont apparues dans les concentrations enregistrées des trois métaux pour la plupart des tissus, la zone occidentale montrant constamment des valeurs plus élevées. Avec l'âge, les concentrations moyennes enregistrées pour le Cd et le Pb augmentaient dans le rein, alors que celles de Pb diminuaient dans le muscle. Des interactions entre le mois des prélèvements, le sexe et la région se produisaient aussi avec certains métaux et certains tissus. Le niveau moyen de 137Cs dans les échantillons musculaires était de 94,7 Bq/kg, ne dépassant jamais la limite acceptable pour la consommation humaine

Simulated last glacial maximum D14Catm and the deep glacial ocean carbon reservoir

∆14Catm has been estimated as 420 ± 80‰ (IntCal09) during the Last Glacial Maximum (LGM) compared to preindustrial times (0‰), but mechanisms explaining this difference are not yet resolved. ∆14Catm is a function of both cosmogenic production in the high atmosphere and of carbon cycling and partitioning in the Earth system. 10Be-based reconstructions show a contribution of the cosmogenic production term of only 200 ± 200‰ in the LGM. The remaining 220‰ have thus to be explained by changes in the carbon cycle. Recently, Bouttes et al. (2010, 2011) proposed to explain most of the difference in pCO2atm and δ13C between glacial and interglacial times as a result of brine-induced ocean stratification in the Southern Ocean. This mechanism involves the formation of very saline water masses that contribute to high carbon storage in the deep ocean. During glacial times, the sinking of brines is enhanced and more carbon is stored in the deep ocean, lowering pCO2atm. Moreover, the sinking of brines induces increased stratification in the Southern Ocean, which keeps the deep ocean well isolated from the surface. Such an isolated ocean reservoir would be characterized by a low ∆14C signature. Evidence of such 14C-depleted deep waters during the LGM has recently been found in the Southern Ocean (Skinner et al. 2010). The degassing of this carbon with low ∆14C would then reduce ∆14Catm throughout the deglaciation. We have further developed the CLIMBER-2 model to include a cosmogenic production of 14C as well as an interactive atmospheric 14C reservoir. We investigate the role of both the sinking of brine and cosmogenic production, alongside iron fertilization mechanisms, to explain changes in ∆14Catm during the last deglaciation. In our simulations, not only is the sinking of brine mechanism consistent with past ∆14C data, but it also explains most of the differences in pCO2atm and ∆14Catm between the LGM and preindustrial times. Finally, this study represents the first time to our knowledge that a model experiment explains glacial-interglacial differences in pCO2atm, δ13C, and ∆14C together with a coherent LGM climate

Modeling the dynamics of glacial cycles

This article is concerned with the dynamics of glacial cycles observed in the geological record of the Pleistocene Epoch. It focuses on a conceptual model proposed by Maasch and Saltzman [J. Geophys. Res.,95, D2 (1990), pp. 1955-1963], which is based on physical arguments and emphasizes the role of atmospheric CO2 in the generation and persistence of periodic orbits (limit cycles). The model consists of three ordinary differential equations with four parameters for the anomalies of the total global ice mass, the atmospheric CO2 concentration, and the volume of the North Atlantic Deep Water (NADW). In this article, it is shown that a simplified two-dimensional symmetric version displays many of the essential features of the full model, including equilibrium states, limit cycles, their basic bifurcations, and a Bogdanov-Takens point that serves as an organizing center for the local and global dynamics. Also, symmetry breaking splits the Bogdanov-Takens point into two, with different local dynamics in their neighborhoods

Lithium bis­(2-methyl­lactato)borate monohydrate

The title compound {systematic name: poly[[aqua­lithium]-μ-3,3,8,8-tetra­methyl-1,4,6,9-tetra­oxa-5λ4-borataspiro­[4.4]nonane-2,7-dione]}, [Li(C8H12BO6)(H2O)]n (LiBMLB), forms a 12-membered macrocycle, which lies across a crystallographic inversion center. The lithium cations are pseudo-tetra­hedrally coordinated by three methyl­lactate ligands and a water mol­ecule. The asymmetric units couple across crystallographic inversion centers, forming the 12-membered macrocycles. These macrocycles, in turn, cross-link through the Li+ cations, forming an infinite polymeric structure in two dimensions parallel to (101)

Present and LGM permafrost from climate simulations : contribution of statistical downscaling

We quantify the agreement between permafrost distributions from PMIP2 (Paleoclimate Modeling Intercomparison Project) climate models and permafrost data. We evaluate the ability of several climate models to represent permafrost and assess the variability between their results. <br><br> Studying a heterogeneous variable such as permafrost implies conducting analysis at a smaller spatial scale compared with climate models resolution. Our approach consists of applying statistical downscaling methods (SDMs) on large- or regional-scale atmospheric variables provided by climate models, leading to local-scale permafrost modelling. Among the SDMs, we first choose a transfer function approach based on Generalized Additive Models (GAMs) to produce high-resolution climatology of air temperature at the surface. Then we define permafrost distribution over Eurasia by air temperature conditions. In a first validation step on present climate (CTRL period), this method shows some limitations with non-systematic improvements in comparison with the large-scale fields. <br><br> So, we develop an alternative method of statistical downscaling based on a Multinomial Logistic GAM (ML-GAM), which directly predicts the occurrence probabilities of local-scale permafrost. The obtained permafrost distributions appear in a better agreement with CTRL data. In average for the nine PMIP2 models, we measure a global agreement with CTRL permafrost data that is better when using ML-GAM than when applying the GAM method with air temperature conditions. In both cases, the provided local information reduces the variability between climate models results. This also confirms that a simple relationship between permafrost and the air temperature only is not always sufficient to represent local-scale permafrost. <br><br> Finally, we apply each method on a very different climate, the Last Glacial Maximum (LGM) time period, in order to quantify the ability of climate models to represent LGM permafrost. The prediction of the SDMs (GAM and ML-GAM) is not significantly in better agreement with LGM permafrost data than large-scale fields. At the LGM, both methods do not reduce the variability between climate models results. We show that LGM permafrost distribution from climate models strongly depends on large-scale air temperature at the surface. LGM simulations from climate models lead to larger differences with LGM data than in the CTRL period. These differences reduce the contribution of downscaling