Temporal variation of temperature and related proxies from the penultimate glacial towards the Eemian in the Black Sea

The last glacial-interglacial transition or Termination I (T I) is well documented in the Black Sea, whereas little is known about climate and environmental dynamics during the penultimate Termination (T II). Here we present a multi-proxy study based on a sediment core from the SE Black Sea covering the penultimate glacial and almost the entire Eemian interglacial (133.5 ±0.7-122.5 ±1.7 ka BP). Proxies comprise ice-rafted debris (IRD), O and Sr isotopes as well as Sr/Ca, Mg/Ca, and U/Ca ratios of benthic ostracods, organic and inorganic sediment geochemistry, as well as TEX86 and UK'37derived water temperatures. The ending penultimate glacial (MIS 6, 133.5 to 129.9 ±0.7 ka BP) is characterised by mean annual lake surface temperatures of about 9°C as estimated from the TEX86 palaeothermometer. This period is impacted by two Black Sea melt water pulses (BSWP-II-1 and 2) as indicated by very low Sr/Ca ostracods but high sedimentary K/Al values. Anomalously high radiogenic 87Sr/86Sr ostracod values (max. 0.70945) during BSWP-II-2 suggest a potential Himalayan source communicated via the Caspian Sea. The T II warming started at 129.9 ±0.7 ka BP, witnessed by abrupt disappearance of IRD, increasing d18O ostracod values, and a first TEX86 derived temperature rise of about 2.5°C. A second, abrupt warming step to ca. 15.5°C as the prelude of the Eemian warm period is documented at 128.3 ka BP. The Mediterranean-Black Sea reconnection most likely occurred at 128.1 ±0.7 ka BP as demonstrated by increasing Sr/Ca ostracods and U/Ca ostracods values. The disappearance of ostracods and TOC contents >2% document the onset of Eemian sapropel formation at 127.6 ka BP. During sapropel formation, TEX86 temperatures dropped and stabilised at around 9°C, while UK'37 temperatures remain on average 17°C. This difference is possibly caused by a habitat shift of Thaumarchaeota communities from surface towards nutrient-rich deeper and colder waters located above the gradually establishing halo-and redoxcline.

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Spatio-temporal Variability of Atmospheric Ozone over Indian Subcontinent and its Relation to Meteorological Parameters

Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.

Spatio-temporal coverage optimization of sensor networks

Les réseaux de capteurs sont formés d’un ensemble de dispositifs capables de prendre individuellement des mesures d’un environnement particulier et d’échanger de l’information afin d’obtenir une représentation de haut niveau sur les activités en cours dans la zone d’intérêt. Une telle détection distribuée, avec de nombreux appareils situés à proximité des phénomènes d’intérêt, est pertinente dans des domaines tels que la surveillance, l’agriculture, l’observation environnementale, la surveillance industrielle, etc. Nous proposons dans cette thèse plusieurs approches pour effectuer l’optimisation des opérations spatio-temporelles de ces dispositifs, en déterminant où les placer dans l’environnement et comment les contrôler au fil du temps afin de détecter les cibles mobiles d’intérêt. La première nouveauté consiste en un modèle de détection réaliste représentant la couverture d’un réseau de capteurs dans son environnement. Nous proposons pour cela un modèle 3D probabiliste de la capacité de détection d’un capteur sur ses abords. Ce modèle inègre également de l’information sur l’environnement grâce à l’évaluation de la visibilité selon le champ de vision. À partir de ce modèle de détection, l’optimisation spatiale est effectuée par la recherche du meilleur emplacement et l’orientation de chaque capteur du réseau. Pour ce faire, nous proposons un nouvel algorithme basé sur la descente du gradient qui a été favorablement comparée avec d’autres méthodes génériques d’optimisation «boites noires» sous l’aspect de la couverture du terrain, tout en étant plus efficace en terme de calculs. Une fois que les capteurs placés dans l’environnement, l’optimisation temporelle consiste à bien couvrir un groupe de cibles mobiles dans l’environnement. D’abord, on effectue la prédiction de la position future des cibles mobiles détectées par les capteurs. La prédiction se fait soit à l’aide de l’historique des autres cibles qui ont traversé le même environnement (prédiction à long terme), ou seulement en utilisant les déplacements précédents de la même cible (prédiction à court terme). Nous proposons de nouveaux algorithmes dans chaque catégorie qui performent mieux ou produits des résultats comparables par rapport aux méthodes existantes. Une fois que les futurs emplacements de cibles sont prédits, les paramètres des capteurs sont optimisés afin que les cibles soient correctement couvertes pendant un certain temps, selon les prédictions. À cet effet, nous proposons une méthode heuristique pour faire un contrôle de capteurs, qui se base sur les prévisions probabilistes de trajectoire des cibles et également sur la couverture probabiliste des capteurs des cibles. Et pour terminer, les méthodes d’optimisation spatiales et temporelles proposées ont été intégrées et appliquées avec succès, ce qui démontre une approche complète et efficace pour l’optimisation spatio-temporelle des réseaux de capteurs.

Spatio-temporal filtering properties of a dendritic cable with active spines: a modeling study in the spike-diffuse-spike framework

The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whilst communication between spines is mediated by the cable equation. In this paper we develop a computational framework that allows the study of multiple spiking events in a network of such spines embedded on a simple one-dimensional cable. In the first instance this system is shown to support saltatory waves with the same qualitative features as those observed in a model with Hodgkin-Huxley kinetics in the spine-head. Moreover, there is excellent agreement with the analytically calculated speed for a solitary saltatory pulse. Upon driving the system with time varying external input we find that the distribution of spines can play a crucial role in determining spatio-temporal filtering properties. In particular, the SDS model in response to periodic pulse train shows a positive correlation between spine density and low-pass temporal filtering that is consistent with the experimental results of Rose and Fortune [1999, Mechanisms for generating temporal filters in the electrosensory system. The Journal of Experimental Biology 202, 1281-1289]. Further, we demonstrate the robustness of observed wave properties to natural sources of noise that arise both in the cable and the spine-head, and highlight the possibility of purely noise induced waves and coherent oscillations.

Temporal variation of delta C-13 in particulate organic matter and oyster Crassostrea gigas in Marennes-Oleron Bay (France): Effect of freshwater inflow

The temporal variability of delta(13)C in suspended particulate organic matter (POM) and oyster Crassostrea gigas along a salinity gradient was investigated from May 1992 to September 1993 within the estuarine bay of Marennes-Oleron (France). During this period the mean daily discharge of the Charente River exhibited large seasonal variation, with a high discharge from November 1992 to January 1993. Contrary to that at the river mouth and the marine littoral, delta(13)C in POM and in oysters at mid-estuary was affected by the high flood period. The delta(13)C values of POM decreased in mid-estuary and remained at low levels during the high discharge period, indicating an increasing contribution of terrestrial inputs to the estuarine POM pool. At the same site, a remarkable decrease of delta(13)C in oysters occurred between December 1992 and March 1993 (after a time lag compared to the ambient POM), indicating incorporation of terrestrial organic matter in oyster tissues during the high flood discharge. The lag between the delta(13)C decrease in POM and oysters is attributed to the time needed for oyster tissues to incorporate enough newly terrestrial light carbon to be recognized by the delta(13)C measure (about 1 to 2 mo). This time interval depends on tissue turnover time. The delta(13)C POM decrease (i.e. 1.3 parts per thousand) cannot explain entirely the decrease observed in oysters (i.e. 2.3 parts per thousand). In fact, the pattern exhibited by mid-estuarine oysters can be explained by the increasing contribution of terrestrial organic matter to their feeding, and the inability to preferentially utilize specific components of the estuarine POM that are C-13-enriched.

Spatio-temporal modeling of data imputation for daily rainfall series in homogeneous zones.

Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.

Spatio-temporal patterns of herbage availability and livestock movements: A cross-border analysis in the Chinese-Mongolian Altay

Due to increasing population and the recent implementation of policies to intensify the use of land and water resources, the transhumant pastoral systems in the Chinese-Mongolian Altay-Dzungarian region are rapidly changing, leading to modifications of herd size, herd composition and spatial distribution of livestock grazing. This may have major consequences for the supply and quality of rangeland biomass. Despite similar topographic settings, the socio-political framework for Chinese and Mongolian pastoralists differs significantly, leading to differences in rangeland utilization. To substantiate these claims, the long-distance transhumance routes, frequency of pasture changes, daily grazing itineraries and size of pastures were recorded by means of GPS tracking of cattle and goats on 1,535 (China) and 1,396 (Mongolia) observation days. The status quo of the main seasonal pastures was captured by measuring the herbage offer and its nutritive value in 869 sampling spots. In the Altay-Dzungarian region, small ruminant herds covered up to 412 km (Mongolia) and grazed on up to nine pastures per year (China). In Mongolia, the herds’ average duration of stay at an individual pasture was longer than in China, particularly in spring and autumn. Herbage allowance at the onset of a grazing period (kg dry matter per sheep unit and day) ranged from 34/17 to 91/95 (China/Mongolia). Comparing crude protein and phosphorous concentrations of herbage, in China, the highest concentrations were measured for spring and summer pastures, whereas in Mongolia, the highest concentrations were determined for autumn and winter pastures. Based on our data, we conclude that regulation of animal numbers and access to pastures seemingly maintained pasture productivity in China, especially at high altitudes. However, this policy may prohibit flexible adaptation to sudden environmental constraints. In contrast, high stocking densities and grazing of pastures before flowering of herbaceous plants negatively affected rangeland productivity in Mongolia, especially for spring and summer pastures.

Airborne particulate matter at a bus station : concentration levels and governing parameters

Traffic emissions are an important contributor to ambient air pollution, especially in large cities featuring extensive and high density traffic networks. Bus fleets represent a significant part of inner city traffic causing an increase in exposure to general public, passengers and drivers along bus routes and at bus stations. Limited information is available on quantification of the levels, and governing parameters affecting the air pollution exposure at bus stations. The presented study investigated the bus emissions-dominated ambient air in a large, inner city bus station, with a specific focus on submicrometer particles. The study’s objectives were (i) quantification of the concentration levels; (ii) characterisation of the spatio-temporal variation; (iii) identification of the parameters governing the emissions levels at the bus station and (iv) assessment of the relationship between particle concentrations measured at the street level (background) and within the bus station. The results show that up to 90% of the emissions at the station are ultrafine particles (smaller than 100 nm), with the concentration levels up to 10 times the value of urban ambient air background (annual) and up to 4 times the local ambient air background. The governing parameters affecting particle concentration at the station were bus flow rate and meteorological conditions (wind velocity). Particle concentration followed a diurnal trend, with an increase in the morning and evening, associated with traffic rush hours. Passengers’ exposure could be significant compared to the average outdoor and indoor exposure levels.

Estimate of Lagrangian integral scales in shallow tidal water using high resolution GPS-tracked drifters

In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

内蒙古锡林河流域草原群落土壤呼吸的时空变异及其影响因子研究

　　土壤呼吸是全球碳循环中的一个重要环节，其对全球碳平衡的影响是近年来人们关注的焦点之一。探讨碳素的失汇(missing sink)问题，对陆地生态系统土壤呼吸的研究是必不可少的。环境因子与土壤呼吸之间的关系可以用于将土壤呼吸从“chamber”水平的测量放大到整个生态系统或更大尺度。而温度、水分和植被状况都是对土壤呼吸有重要影响的因子，随着全球气候的变化，这些因子也会发生相应的改变，在这种情况下，它们极有可能与土壤CO2排放之间形成正反馈。温带草原是主要的陆地生态系统类型之一，目前非常缺乏有关土壤呼吸的研究资料。因此，在2001年生长季，我们在内蒙古锡林河流域南部集水区设定了一条东西长约160km、南北宽约30km的样带，从中选择了11个不同的植物群落，采用碱液吸收法周期性地对这些群落的土壤呼吸速率进行同步测定，并对土壤呼吸的时空动态及其与温度、土壤水分和植被状况之间的关系进行了研究。现将主要研究结果概述如下： 　　①锡林河流域南部集水区的土壤呼吸表现出明显的季节变化和空间变异。温度是影响土壤呼吸季节变化的主要因子之一，指数模型能够较好地揭示各群落土壤呼吸对温度变化的响应，但低温时模型的拟合效果更好。各群落土壤呼吸的季节动态与温度变化不完全同步，表明温度并不是影响土壤呼吸的唯一因子 。 　　②土壤呼吸的温度敏感性在各群落之间存在着一定的差异。春小麦群落的Q10值高于草原群落，说明不同的土地利用方式会影响到土壤呼吸对温度变化的敏感程度。水分对土壤呼吸的温度敏感性有重要影响，秩相关分析的结果表明，土壤水分与Q10值之间存在着显著的正相关关系。此外，依据不同土壤层次的温度得出的Q10值各不相同，基于变化幅度大的浅层土壤温度和气温得出的Q10值较小，而根据变化幅度小的深层土壤温度得出的Q10值较大。 　　③水分对各群落的土壤呼吸也有较大影响，但其影响程度有一定的季节差异，生长旺季水分对土壤呼吸的影响显著高于其它季节。从各群落的具体情况来看，水分对土壤呼吸的影响明显受制于群落的水分供应状况。水分供应状况比较好的和水分变化幅度小的群落中，土壤呼吸与水分之间没有显著的函数关系，而水分相对欠缺的群落则存有显著的线性关系。消除温度的影响后，这种线性关系显著增强。土壤水分含量较低的芨芨草群落中，土壤呼吸与表层水分之间的关系也不明显，这与芨芨草根系分布较深，能够利用土壤中较深层次的水分有关。 　　④土壤呼吸季节变化与植被之间的关系与各群落内水分状况以及植被对水分的利用机制有关。所有群落土壤呼吸速率随着绿色活体生物量的增长有上升趋势，且在水分供应充足的群落和植被较为耐旱或能够利用深层土壤水的群落中，这二者之间呈显著或极显著的指数关系，其它群落中相关关系不够显著。由于植被立枯量大小反映了水热的综合状况，所以群落的土壤呼吸速率随立枯量的增长呈下降趋势，二者之间的关系也可以用指数方程来表示。 　　⑤土壤呼吸在锡林河流域南部的空间变异主要受水分和植被状况的影响。总体来看，土壤水分含量高、地上生物量（包括绿色活体生物量）大或地上净第一性生产力高的草地群落，其土壤呼吸速率也较高。基础呼吸速率对于改进土壤呼吸模型在时间和空间上的预测精度有重要意义。我们的研究结果表明，在平均温度低、水分状况好、地上和地下生物量大、地上净第一性生产力高的地方，基础土壤呼吸速率也相应较高。