Distribution of metals exposure and associations with cardiometabolic risk factors in the "Modeling the Epidemiologic Transition Study".

BACKGROUND: Metals are known endocrine disruptors and have been linked to cardiometabolic diseases via multiple potential mechanisms, yet few human studies have both the exposure variability and biologically-relevant phenotype data available. We sought to examine the distribution of metals exposure and potential associations with cardiometabolic risk factors in the "Modeling the Epidemiologic Transition Study" (METS), a prospective cohort study designed to assess energy balance and change in body weight, diabetes and cardiovascular disease risk in five countries at different stages of social and economic development. METHODS: Young adults (25-45 years) of African descent were enrolled (N = 500 from each site) in: Ghana, South Africa, Seychelles, Jamaica and the U.S.A. We randomly selected 150 blood samples (N = 30 from each site) to determine concentrations of selected metals (arsenic, cadmium, lead, mercury) in a subset of participants at baseline and to examine associations with cardiometabolic risk factors. RESULTS: Median (interquartile range) metal concentrations (μg/L) were: arsenic 8.5 (7.7); cadmium 0.01 (0.8); lead 16.6 (16.1); and mercury 1.5 (5.0). There were significant differences in metals concentrations by: site location, paid employment status, education, marital status, smoking, alcohol use, and fish intake. After adjusting for these covariates plus age and sex, arsenic (OR 4.1, 95% C.I. 1.2, 14.6) and lead (OR 4.0, 95% C.I. 1.6, 9.6) above the median values were significantly associated with elevated fasting glucose. These associations increased when models were further adjusted for percent body fat: arsenic (OR 5.6, 95% C.I. 1.5, 21.2) and lead (OR 5.0, 95% C.I. 2.0, 12.7). Cadmium and mercury were also related with increased odds of elevated fasting glucose, but the associations were not statistically significant. Arsenic was significantly associated with increased odds of low HDL cholesterol both with (OR 8.0, 95% C.I. 1.8, 35.0) and without (OR 5.9, 95% C.I. 1.5, 23.1) adjustment for percent body fat. CONCLUSIONS: While not consistent for all cardiometabolic disease markers, these results are suggestive of potentially important associations between metals exposure and cardiometabolic risk. Future studies will examine these associations in the larger cohort over time.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Imatinib plasma concentrations variability in hemato-oncologic patients

Abstract Imatinib (Glivec~ has transformed the treatment and prognosis of chronic myeloid leukaemia (CML) and of gastrointestinal stromal tumor (GIST). However, the treatment must be taken indefinitely and is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs. Considering the large interindividual differences in the function of the enzymatic and transport systems involved in imatinib disposition, exposure to this drug can be expected to vary widely among patients. Among those known systems is a cytochrome P450 (CYI'3A4) that metabolizes imatinib, the multidrug transporter P-glycoprotein (P-gp; product of the MDR1 gene) that expels imatinib out of cells, and al-acid glycoprotein (AGP), a circulating protein binding imatinib in the plasma. The aim of this observational study was to explore the influence of these covariates on imatinib pharmacokinetics (PK), to assess the interindividual variability of the PK parameters of the drug, and to evaluate whether imatinib use would benefit from a therapeutic drug monitoring (TDM) program. A total of 321 plasma concentrations were measured in 59 patients receiving imatinib, using a validated chromatographic method developed for this study (HPLC-LTV). The results were analyzed by non-linear mixed effect modeling (NONMEM). A one-compartment pharmacokinetic model with first-order absorption appropriately described the data, and a large interindividual variability was observed. The MDK> polymorphism 3435C>T and the CYP3A4 activity appeared to modulate the disposition of imatinib, albeit not significantly. A hyperbolic relationship between plasma AGP levels and oral clearance, as well as volume of distribution, was observed. A mechanistic approach was built up, postulating that only the unbound imatinib concentration was able to undergo first-order elimination. This approach allowed determining an average free clearance (CL,~ of 13101/h and a volume of distribution (Vd) of 301 1. By comparison, the total clearance determined was 141/h (i.e. 233 ml/min). Free clearance was affected by body weight and pathology diagnosis. The estimated variability of imatinib disposition (17% for CLu and 66% for Vd) decreased globally about one half with the model incorporating the AGP impact. Moreover, some associations were observed between PK parameters of the free imatinib concentration and its efficacy and toxicity. Finally, the functional influence of P-gp activity has been demonstrated in vitro in cell cultures. These elements are arguments to further investigate the possible usefulness of a TDM program for imatinib. It may help in individualizing the dosing regimen before overt disease progression or development of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug. Résumé L'imatinib (Glivec ®) a révolutionné le traitement et le pronostic de la leucémie myéloïde chronique (LMC) et des tumeurs stromales d'origine digestive (GIST). Il s'agit toutefois d'un traitement non dénué d'inconvénients et de toxicité, et qui doit être pris indéfiniment. Par ailleurs, une résistance, ou des échappements au traitement, sont également rencontrés. Le devenir de ce médicament dans l'organisme dépend de systèmes enzymatiques et de transport connus pour présenter de grandes différences interindividuelles, et l'on peut s'attendre à ce que l'exposition à ce médicament varie largement d'un patient à l'autre. Parmi ces systèmes, on note un cytochrome P450 (le CYP3A4) métabolisant l'imatinib, la P-glycoprotéine (P-gp ;codée par le gène MDR1), un transporteur d'efflux expulsant le médicament hors des cellules, et l'atglycoprotéine acide (AAG), une protéine circulante sur laquelle se fixe l'imatinib dans le plasma. L'objectif de la présente étude clinique a été de déterminer l'influence de ces covariats sur la pharmacocinétique (PK) de l'imatinib, d'établir la variabilité interindividuelle des paramètres PK du médicament, et d'évaluer dans quelle mesure l'imatinib pouvait bénéficier d'un programme de suivi thérapeutique (TDM). En utilisant une méthode chromatographique développée et validée à cet effet (HPLC-UV), un total de 321 concentrations plasmatiques a été dosé chez 59 patients recevant de l'imatinib. Les résultats ont été analysés par modélisation non linéaire à effets mixtes (NONMEM). Un modèle pharmacocinétique à un compartiment avec absorption de premier ordre a permis de décrire les données, et une grande variabilité interindividuelle a été observée. Le polymorphisme du gène MDK1 3435C>T et l'activité du CYP3A4 ont montré une influence, toutefois non significative, sur le devenir de l'imatinib. Une relation hyperbolique entre les taux plasmatiques d'AAG et la clairance, comme le volume de distribution, a été observée. Une approche mécanistique a donc été élaborée, postulant que seule la concentration libre subissait une élimination du premier ordre. Cette approche a permis de déterminer une clairance libre moyenne (CLlibre) de 13101/h et un volume de distribution (Vd) de 301 l. Par comparaison, la clairance totale était de 141/h (c.à.d. 233 ml/min). La CLlibre est affectée par le poids corporel et le type de pathologie. La variabilité interindividuelle estimée pour le devenir de l'imatinib (17% sur CLlibre et 66% sur Vd) diminuait globalement de moitié avec le modèle incorporant l'impact de l'AAG. De plus, une certaine association entre les paramètres PK de la concentration d'imatinib libre et l'efficacité et la toxicité a été observée. Finalement, l'influence fonctionnelle de l'activité de la P-gp a été démontrée in nitro dans des cultures cellulaires. Ces divers éléments constituent des arguments pour étudier davantage l'utilité potentielle d'un programme de TDM appliqué à l'imatinib. Un tel suivi pourrait aider à l'individualisation des régimes posologiques avant la progression manifeste de la maladie ou l'apparition de toxicité, améliorant tant l'efficacité que la tolérabilité de ce médicament. Résumé large public L'imatinib (un médicament commercialisé sous le nom de Glivec ®) a révolutionné le traitement et le pronostic de deux types de cancers, l'un d'origine sanguine (leucémie) et l'autre d'origine digestive. Il s'agit toutefois d'un traitement non dénué d'inconvénients et de toxicité, et qui doit être pris indéfiniment. De plus, des résistances ou des échappements au traitement sont également rencontrés. Le devenir de ce médicament dans le corps humain (dont l'étude relève de la discipline appelée pharmacocinétique) dépend de systèmes connus pour présenter de grandes différences entre les individus, et l'on peut s'attendre à ce que l'exposition à ce médicament varie largement d'un patient à l'autre. Parmi ces systèmes, l'un est responsable de la dégradation du médicament dans le foie (métabolisme), l'autre de l'expulsion du médicament hors des cellules cibles, alors que le dernier consiste en une protéine (dénommée AAG) qui transporte l'imatinib dans le sang. L'objectif de notre étude a été de déterminer l'influence de ces différents systèmes sur le comportement pharmacocinétique de l'imatinib chez les patients, et d'étudier dans quelle mesure le devenir de ce médicament dans l'organisme variait d'un patient à l'autre. Enfin, cette étude avait pour but d'évaluer à quel point la surveillance des concentrations d'imatinib présentes dans le sang pourrait améliorer le traitement des patients cancéreux. Une telle surveillance permet en fait de connaître l'exposition effective de l'organisme au médicament (concept abrégé par le terme anglais TDM, pour Therapeutic Drag Monitoring. Ce projet de recherche a d'abord nécessité la mise au point d'une méthode d'analyse pour la mesure des quantités (ou concentrations) d'imatinib présentes dans le sang. Cela nous a permis d'effectuer régulièrement des mesures chez 59 patients. Il nous a ainsi été possible de décrire le devenir du médicament dans le corps à l'aide de modèles mathématiques. Nous avons notamment pu déterminer chez ces patients la vitesse à laquelle l'imatinib est éliminé du sang et l'étendue de sa distribution dans l'organisme. Nous avons également observé chez les patients que les concentrations sanguines d'imatinib étaient très variables d'un individu à l'autre pour une même dose de médicament ingérée. Nous avons pu aussi mettre en évidence que les concentrations de la protéine AAG, sur laquelle l'imatinib se lie dans le sang, avait une grande influence sur la vitesse à laquelle le médicament est éliminé de l'organisme. Ensuite, en tenant compte des concentrations sanguines d'imatinib et de cette protéine, nous avons également pu calculer les quantités de médicament non liées à cette protéine (= libres), qui sont seules susceptibles d'avoir une activité anticancéreuse. Enfin, il a été possible d'établir qu'il existait une certaine relation entre ces concentrations, l'effet thérapeutique et la toxicité du traitement. Tous ces éléments constituent des arguments pour approfondir encore l'étude de l'utilité d'un programme de TDM appliqué à l'imatinib. Comme chaque patient est différent, un tel suivi pourrait aider à l'ajustement des doses du médicament avant la progression manifeste de la maladie ou l'apparition de toxicité, améliorant ainsi tant son efficacité que son innocuité.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

Terrain forms and spatial variability of soil properties in an area cultivatedwith citrus

The technique of precision agriculture and soil-landscape allows delimiting areas for localized management, allowing a localized application of agricultural inputs and thereby may contribute to preservation of natural resources. Therefore, the objective of this work was to characterize the spatial variability of chemical properties and clay content in the context of soil-landscape relationship in a Latosol (Oxisol) under cultivation of citrus. Soil samples were collected at a depth of 0.0-0.2 m in an area of 83.5 ha planted with citrus, as a 50-m intervals grid, with 129 points in concave terrain and 206 points in flat terrain, totaling 335 points. Values for the variables that express the chemical characteristics and clay content of soil properties were analyzed with descriptive statistics and geostatistical modeling of semivariograms for making maps of kriging. The values of range and kriging maps indicated higher variability in the shape of concave topography (top segment) compared with the shape of flat topography (slope and hillside segments below). The identification of different forms of terrain proved to be efficient in understanding the spatial variability of chemical properties and clay content of soil under cultivation of citrus.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Low Level Jet stream of Asian Summer Monsoon and its Variability

The main objective of the of present study are to study the intraseasonal variability of LLJ and its relation with convective heating of the atmosphere, to establish whether LLJ splits into two branches over the Arabian sea as widely believed, the role of horizonatal wind shear of LLJ in the episodes of intense rainfall events observed over the west coast of India, to perform atmospheric modeling work to test whether small (meso) scale vortices form during intense rainfall events along the west coast; and to study the relation between LLJ and monsoon depression genesis. The results of a study on the evolution of Low Level Jetstream (LLJ) prior to the formation of monsoon depressions are presented. A synoptic model of the temporal evolution of monsoon depression has been produced. There is a systematic temporal evolution of the field of deep convection strength and position of the LLJ axis leading to the genesis of monsoon depression. One of the significant outcomes of the present thesis is that the LLJ plays an important role in the intraseasonal and the interannual variability of Indian monsoon activity. Convection and rainfall are dependent mainly on the cyclonic vorticity in the boundary layer associated with LLJ. Monsoon depression genesis and the episodes of very heavy rainfall along the west coast of India are closely related to the cyclonic shear of the LLJ in the boundary layer and the associated deep convection. Case studies by a mesoscale numerical model (MM5) have shown that the heavy rainfall episodes along the west coast of India are associated with generation of mesoscale cyclonic vortices in the boundary layer.

Sea Surface Temperature-Convection Relationship in Tropical Oceans with Special Emphasis to Intraseasonal Variability of Indian Summer Monsoon

The SST convection relation over tropical ocean and its impact on the South Asian monsoon is the first part of this thesis. Understanding the complicated relation between SST and convection is important for better prediction of the variability of the Indian monsoon in subseasonal, seasonal, interannual, and longer time scales. Improved global data sets from satellite scatterometer observations of SST, precipitation and refined reanalysis of global wind fields have made it possible to do a comprehensive study of the SST convection relation. Interaction of the monsoon and Indian ocean has been discussed. A coupled feedback process between SST and the Active-Break cycle of the Asian summer monsoon is a central theme of the thesis. The relation between SST and convection is very important in the field of numerical modeling of tropical rainfall. It is well known that models generally do very well simulating rainfall in areas of tropical convergence zones but are found unable to do satisfactory simulation in the monsoon areas. Thus in this study we critically examined the different mechanisms of generation of deep convection over these two distinct regions.The study reported in chapter 3 has shown that SST - convection relation over the warm pool regions of Indian and west Pacific oceans (monsoon areas) is in such a way that convection increases with SST in the SST range 26-29 C and for SST higher than 29-30 C convection decreases with increase of SST (it is called Waliser type). It is found that convection is induced in areas with SST gradients in the warm pool areas of Indian and west Pacific oceans. Once deep convection is initiated in the south of the warmest region of warm pool, the deep tropospheric heating by the latent heat released in the convective clouds produces strong low level wind fields (Low level Jet - LLJ) on the equatorward side of the warm pool and both the convection and wind are found to grow through a positive feedback process. Thus SST through its gradient acts only as an initiator of convection. The central region of the warm pool has very small SST gradients and large values of convection are associated with the cyclonic vorticity of the LLJ in the atmospheric boundary layer. The conditionally unstable atmosphere in the tropics is favorable for the production of deep convective clouds.

Impact of Climatic Variability and Drought on Crop Yields in Kerala

In the present investigation, the impacts of the variability of the climatic parameters on the yields of major crops grown in the State are analyzed. In particular, the effects of rainfall variability on the water balances of the different regions in the State have been studied. Through this analysis the drought climatology of the region has been studied along with an overview of the climatic shifts involved in individual years. The relationship between weather parameters and crop yields over the State has been analyzed with case studies of two crops- coconut and paddy. Crop-weather models for forecasting coconut and paddy yields have been developed, which could be used for planning purposes

Interannual and interdecadal oscillations in hydrological variables: Sources and modeling of the persistence in the Elbe River Basin

Wenn man die Existenz von physikalischen Mechanismen ignoriert, die für die Struktur hydrologischer Zeitreihen verantwortlich sind, kann das zu falschen Schlussfolgerungen bzgl. des Vorhandenseins möglicher Gedächtnis (memory) -Effekte, d.h. von Persistenz, führen. Die hier vorgelegte Doktorarbeit spürt der niedrigfrequenten klimatischen Variabilität innerhalb den hydrologischen Zyklus nach und bietet auf dieser "Reise" neue Einsichten in die Transformation der charakteristischen Eigenschaften von Zeitreihen mit einem Langzeitgedächtnis. Diese Studie vereint statistische Methoden der Zeitreihenanalyse mit empirisch-basierten Modelltechniken, um operative Modelle zu entwickeln, die in der Lage sind (1) die Dynamik des Abflusses zu modellieren, (2) sein zukünftiges Verhalten zu prognostizieren und (3) die Abflusszeitreihen an unbeobachteten Stellen abzuschätzen. Als solches präsentiert die hier vorgelegte Dissertation eine ausführliche Untersuchung zu den Ursachen der niedrigfrequenten Variabilität von hydrologischen Zeitreihen im deutschen Teil des Elbe-Einzugsgebietes, den Folgen dieser Variabilität und den physikalisch basierten Reaktionen von Oberflächen- und Grundwassermodellen auf die niedrigfrequenten Niederschlags-Eingangsganglinien. Die Doktorarbeit gliedert sich wie folgt: In Kapitel 1 wird als Hintergrundinformation das Hurst Phänomen beschrieben und ein kurzer Rückblick auf diesbezügliche Studien gegeben. Das Kapitel 2 diskutiert den Einfluss der Präsenz von niedrigfrequenten periodischen Zeitreihen auf die Zuverlässigkeit verschiedener Hurst-Parameter-Schätztechniken. Kapitel 3 korreliert die niedrigfrequente Niederschlagsvariabilität mit dem Index der Nord-Atlantischen Ozillations (NAO). Kapitel 4-6 sind auf den deutschen Teil des Elbe-Einzugsgebietes fokussiert. So werden in Kapitel 4 die niedrigfrequenten Variabilitäten der unterschiedlichen hydro-meteorologischen Parameter untersucht und es werden Modelle beschrieben, die die Dynamik dieser Niedrigfrequenzen und deren zukünftiges Verhalten simulieren. Kapitel 5 diskutiert die mögliche Anwendung der Ergebnisse für die charakteristische Skalen und die Verfahren der Analyse der zeitlichen Variabilität auf praktische Fragestellungen im Wasserbau sowie auf die zeitliche Bestimmung des Gebiets-Abflusses an unbeobachteten Stellen. Kapitel 6 verfolgt die Spur der Niedrigfrequenzzyklen im Niederschlag durch die einzelnen Komponenten des hydrologischen Zyklus, nämlich dem Direktabfluss, dem Basisabfluss, der Grundwasserströmung und dem Gebiets-Abfluss durch empirische Modellierung. Die Schlussfolgerungen werden im Kapitel 7 präsentiert. In einem Anhang werden technische Einzelheiten zu den verwendeten statistischen Methoden und die entwickelten Software-Tools beschrieben.

Statistical modeling on (α, +∞)

Observations in daily practice are sometimes registered as positive values larger then a given threshold α. The sample space is in this case the interval (α,+∞), α > 0, which can be structured as a real Euclidean space in different ways. This fact opens the door to alternative statistical models depending not only on the assumed distribution function, but also on the metric which is considered as appropriate, i.e. the way differences are measured, and thus variability

Aerosol optical depths over North Africa: 2. Modeling and model validation

An operational dust forecasting model is developed by including the Met Office Hadley Centre climate model dust parameterization scheme, within a Met Office regional numerical weather prediction (NWP) model. The model includes parameterizations for dust uplift, dust transport, and dust deposition in six discrete size bins and provides diagnostics such as the aerosol optical depth. The results are compared against surface and satellite remote sensing measurements and against in situ measurements from the Facility for Atmospheric Airborne Measurements for a case study when a strong dust event was forecast. Comparisons are also performed against satellite and surface instrumentation for the entire month of August. The case study shows that this Saharan dust NWP model can provide very good guidance of dust events, as much as 42 h ahead. The analysis of monthly data suggests that the mean and variability in the dust model is also well represented.

Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

[1] We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.

Atlantic climate variability and predictability: A CLIVAR perspective

Three interrelated climate phenomena are at the center of the Climate Variability and Predictability (CLIVAR) Atlantic research: tropical Atlantic variability (TAV), the North Atlantic Oscillation (NAO), and the Atlantic meridional overturning circulation (MOC). These phenomena produce a myriad of impacts on society and the environment on seasonal, interannual, and longer time scales through variability manifest as coherent fluctuations in ocean and land temperature, rainfall, and extreme events. Improved understanding of this variability is essential for assessing the likely range of future climate fluctuations and the extent to which they may be predictable, as well as understanding the potential impact of human-induced climate change. CLIVAR is addressing these issues through prioritized and integrated plans for short-term and sustained observations, basin-scale reanalysis, and modeling and theoretical investigations of the coupled Atlantic climate system and its links to remote regions. In this paper, a brief review of the state of understanding of Atlantic climate variability and achievements to date is provided. Considerable discussion is given to future challenges related to building and sustaining observing systems, developing synthesis strategies to support understanding and attribution of observed change, understanding sources of predictability, and developing prediction systems in order to meet the scientific objectives of the CLIVAR Atlantic program.