Assortment and the analysis of natural selection on social traits.

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McDonald, Grant C; Farine, Damien R; Foster, Kevin R; Biernaskie, Jay M

2017-11-01

A central problem in evolutionary biology is to determine whether and how social interactions contribute to natural selection. A key method for phenotypic data is social selection analysis, in which fitness effects from social partners contribute to selection only when there is a correlation between the traits of individuals and their social partners (nonrandom phenotypic assortment). However, there are inconsistencies in the use of social selection that center around the measurement of phenotypic assortment. Here, we use data analysis and simulations to resolve these inconsistencies, showing that: (i) not all measures of assortment are suitable for social selection analysis; and (ii) the interpretation of assortment, and how to detect nonrandom assortment, will depend on the scale at which it is measured. We discuss links to kin selection theory and provide a practical guide for the social selection approach. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Enhancing neural-network performance via assortativity

International Nuclear Information System (INIS)

Franciscis, Sebastiano de; Johnson, Samuel; Torres, Joaquin J.

2011-01-01

The performance of attractor neural networks has been shown to depend crucially on the heterogeneity of the underlying topology. We take this analysis a step further by examining the effect of degree-degree correlations - assortativity - on neural-network behavior. We make use of a method recently put forward for studying correlated networks and dynamics thereon, both analytically and computationally, which is independent of how the topology may have evolved. We show how the robustness to noise is greatly enhanced in assortative (positively correlated) neural networks, especially if it is the hub neurons that store the information.

Genetic and educational assortative mating among US adults.

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Domingue, Benjamin W; Fletcher, Jason; Conley, Dalton; Boardman, Jason D

2014-06-03

Understanding the social and biological mechanisms that lead to homogamy (similar individuals marrying one another) has been a long-standing issue across many fields of scientific inquiry. Using a nationally representative sample of non-Hispanic white US adults from the Health and Retirement Study and information from 1.7 million single-nucleotide polymorphisms, we compare genetic similarity among married couples to noncoupled pairs in the population. We provide evidence for genetic assortative mating in this population but the strength of this association is substantially smaller than the strength of educational assortative mating in the same sample. Furthermore, genetic similarity explains at most 10% of the assortative mating by education levels. Results are replicated using comparable data from the Framingham Heart Study.

The Variety of An Assortment : An Extension to the Attribute-Based Approach

NARCIS (Netherlands)

Herpen, van H.W.I.; Pieters, F.G.M.

2002-01-01

In recent years, interest in category management has surged, and as a consequence, large retailers now systematically review their product assortments. Variety is a key property of assortments. Assortment variety can determine consumers' store choice and is only gaining in importance with today's

The relationship between intraspecific assortative mating and reproductive isolation between divergent populations

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Daniel I. BOLNICK, Mark KIRKPATRICK

2012-06-01

Full Text Available The term 'assortative mating' has been applied to describe two very different phenomena: (1 the tendency for individuals to choose phenotypically similar mates from among conspecifics; or (2 the tendency to prefer conspecific over hete- rospecific mates (behavioral reproductive isolation. Both forms of assortative mating are widespread in nature, but the relationship between these behaviors remains unclear. Namely, it is plausible that a preference for phenotypically similar conspecifics incidentally reduces the probability of mating with phenotypically divergent heterospecifics. We present a model to calculate how the level of reproductive isolation depends on intraspecific assortative mating and the phenotypic divergence between species. For empirically reasonable levels of intraspecific assortment on a single trait axis, we show that strong reproductive isolation requires very substantial phenotypic divergence. We illustrate this point by applying our model to empirical data from threespine stickleback Gasterosteus aculeatus and Darwin’s Finches (Geospiza spp. We conclude that typical levels of intraspecific assortment cannot generally be extrapolated to explain levels of interspecific reproductive isolation. Instead, reproductive isolation between species likely arises from different mate choice behaviors, or multivariate assortative mating [Current Zoology 58 (3: 481–489, 2012].

Over-Education and Assortative Matching in Partnerships: A Theoretical Analysis

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Tampieri, Alessandro

2016-01-01

This paper argues that assortative matching may explain over-education. Education determines individuals' income and, due to the presence of assortative matching, the quality of partners in personal, social and working life. Thus, an individual acquires education to improve the expected partners' quality. However, since every individual of the…

Actuality of assortment policy in the modern management of retail business enterprise

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Yefimova Yevheniia

2016-07-01

Full Text Available In the result of research it has been found, that the assortment policy defines the course of actions for managing a point-of-sale assortment which foresees clarification and specification of strategic purpose and current tasks; development and grounding of facilities, methods and forms of activity for their achievement; determination of the real resources providing the realization of the plan. The constituents of assortment policy of enterprise of retail business are identified. It is well-proved that with the help of assortment policy achievement of ultimate goals of an enterprise is provided, the constituents of commercial strategy associate together and the possibility of the most effective usage of resources has arrived.

Impact of awareness of cancer among acquaintances on cancer screening attendance.

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Eisinger, François; Blay, Jean-Yves; Morère, Jean-François; Coscas, Yvan; Calazel-Benque, Anne; Roussel, Claire; Pivot, Xavier

2011-01-01

Two nationwide observational surveys were carried out in France in 2005 and 2008 with the aim of assessing the impact on attitudes towards cancer screening of a positive history of cancer among a person's close circle of acquaintances (relatives, friends or colleagues). In 2005, 67% (993/1482) of people interviewed reported having someone in their close circle of acquaintances affected by cancer and in 2008, the rate was 80% (1158/1454). In 2008, having someone within a person's close circle of acquaintances affected by cancer did not increase the rate of screening for breast cancer (already high at >80%). However, it did increase the rate of screening for colorectal cancer [odds ratio (OR)=2.3; 95% confidence interval (CI)=1.6-3.3] and prostate cancer (OR=2.2; 95% CI=1.4-3.5). Knowing someone affected by cancer within the close circle of acquaintances clearly increases awareness, and thus could be an incentive for undergoing cancer screening. With regard to cancer types, such as prostate cancer, for which there is no national programme or media communication, this awareness might be the main source of information and motivation. The impact of awareness on screening behaviour seems to be greatest for the same cancer location as that in the affected acquaintance, as opposed to cancers at other sites. Increased awareness as observed in our survey, which may be attributable to less social stigma associated with a diagnosis of cancer, might increase the rate of screening attendance in the general population.

Assortative social learning and its implications for human (and animal?) societies.

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Katsnelson, Edith; Lotem, Arnon; Feldman, Marcus W

2014-07-01

Choosing from whom to learn is an important element of social learning. It affects learner success and the profile of behaviors in the population. Because individuals often differ in their traits and capabilities, their benefits from different behaviors may also vary. Homophily, or assortment, the tendency of individuals to interact with other individuals with similar traits, is known to affect the spread of behaviors in humans. We introduce models to study the evolution of assortative social learning (ASL), where assorting on a trait acts as an individual-specific mechanism for filtering relevant models from which to learn when that trait varies. We show that when the trait is polymorphic, ASL may maintain a stable behavioral polymorphism within a population (independently of coexistence with individual learning in a population). We explore the evolution of ASL when assortment is based on a nonheritable or partially heritable trait, and when ASL competes with different non-ASL strategies: oblique (learning from the parental generation) and vertical (learning from the parent). We suggest that the tendency to assort may be advantageous in the context of social learning, and that ASL might be an important concept for the evolutionary theory of social learning. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Assortative marriages by body mass index have increased simultaneously with the obesity epidemic

DEFF Research Database (Denmark)

Adeltoft, Teresa Ajslev; Ängquist, Lars Henrik; Silventoinen, Karri

2012-01-01

Background: The genetic predisposition to obesity may have contributed to the obesity epidemic through assortative mating. We investigated whether spouses were positively assorted by body mass index (BMI; = kg/m(2)) in late childhood, and whether changes in assorted marriage by upper BMI-percenti......Background: The genetic predisposition to obesity may have contributed to the obesity epidemic through assortative mating. We investigated whether spouses were positively assorted by body mass index (BMI; = kg/m(2)) in late childhood, and whether changes in assorted marriage by upper BMI......-percentiles occurred during the obesity epidemic. Methods: In the Copenhagen School Health Records Register (CSHRR) boys and girls with measures of BMI at age 13 years later became 37,792 spousal-pairs who married between 1945 and 2010. Trends in the spousal BMI correlations using sex-, age-, and birth cohort......-specific BMI z-scores across time were investigated. Odds ratios (ORs) of marriage among spouses both with BMI z-scores >90th or >95th percentile compared with marriage among spouses ≤90th percentile were analyzed for marriages entered during the years prior to (1945-1970), and during the obesity epidemic...

Marketing Analytics for High-Dimensional Assortments

NARCIS (Netherlands)

B.J.D. Jacobs (Bruno)

2017-01-01

textabstractOver the past two decades online retailing has become ubiquitous and today’s large online retailers enable customers to purchase virtually any product. As a consequence product assortments at such retailers are of a different order of magnitude compared to the traditional

Arranging the assortment to arouse choice

NARCIS (Netherlands)

Herpen, van Erica; Bosmans, Anick

2018-01-01

Food retailers can present specific products in a separate category (e.g., separate section for organic products) or integrated into the mainstream shelf. This study investigates how assortment organization influences consumers' variety perceptions and product choice. We argue and show that when an

METHODOLOGY OF KNOWLEDGE RESOURCES AUDIT FOR FORMATION OF PHARMACY ORGANIZATION ASSORTMENT

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I. M. Razdorskaya

2015-01-01

Full Text Available The timeliness of this subject is conditioned by the increase of a role of knowledge in pharmacy organizations (PO management, significance increase of non-material assets in a competition on the pharmaceutical market. The development and substantiation of methodology of knowledge resources audit significance on the example of drug assortment formation for allergic rhinitis treatment. We have used sociological, statistic, expert methods of a study. Close attention was paid to the method of target management, construction of target tree. The construction of the target tree of the knowledge resources audit was based on the main target establishment, targets of the first level, and eight subtargets. We have offered new special positions of assortment formation. “Formation of consumers’ loyalty” is the target of the first level, subtargets “Analysis of clients preferences”, “Transformation of clients preferences”, “Positioning of consumers by the compliance degree”. We have determined the relevance significance by the main target achievement – rational assortment formation. We have shown that the achievement of the first level target “Formation of consumers’  loyalty” conduce the achievement of the main target by 40%. The analysis of the current assortment and a process of assortment upgrading guarantee the achievement of the target by 30% each. The methodology is prospective for knowledge resources audit by the principal business processes of pharmacy organizations.  

Multi-Agent Information Classification Using Dynamic Acquaintance Lists.

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Mukhopadhyay, Snehasis; Peng, Shengquan; Raje, Rajeev; Palakal, Mathew; Mostafa, Javed

2003-01-01

Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

MARKETING STUDIES OF VETERINARY PHARMACY ORGANIZATIONS ASSORTMENT

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A. A. Deltsov

2015-01-01

Full Text Available Nowadays there is an active growth of veterinary pharmacy organizations and consumed medicinal drugs for veterinary use. Content-analysis showed that there was an insufficient number of studies devoted to the activity of veterinary pharmacies. The purpose of our work was the analysis of correspondence of range fullness of veterinary pharmacies to the contemporary state of pharmaceutical market of drugs for veterinary use. Veterinary clinics and pharmacies of Moscow and Moscow oblast were the object of our study. We have applied sociological methods (questionnaire, interview, marketing and statistic analysis methods. We have established that liquid dosage forms (53% occupy the biggest part of drugs in the State Registry of Veterinary Drugs. Solutions occupy 68% of this amount. Antimicrobial drugs for systematic use (40% are the most numerous drugs from pharmacotheraperutic group represented in the State Registry. Assortment of veterinary drugs is targeted mainly on a farm livestock (more than 50%. 58% of the market share is domestic drugs. Principal commodity groups which are released by veterinary pharmacies are feed-stuff (31% and drugs (30%. Pharmacy organizations does not have sufficient number of drugs in their assortment (fullness coefficient 7.9% which speaks about nonconformity of the assortment fullness.

Phenotypic assortment in wild primate networks: implications for the dissemination of information.

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Carter, Alecia J; Lee, Alexander E G; Marshall, Harry H; Ticó, Miquel Torrents; Cowlishaw, Guy

2015-05-01

Individuals' access to social information can depend on their social network. Homophily-a preference to associate with similar phenotypes-may cause assortment within social networks that could preclude information transfer from individuals who generate information to those who would benefit from acquiring it. Thus, understanding phenotypic assortment may lead to a greater understanding of the factors that could limit the transfer of information between individuals. We tested whether there was assortment in wild baboon (Papio ursinus) networks, using data collected from two troops over 6 years for six phenotypic traits-boldness, age, dominance rank, sex and the propensity to generate/exploit information-using two methods for defining a connection between individuals-time spent in proximity and grooming. Our analysis indicated that assortment was more common in grooming than proximity networks. In general, there was homophily for boldness, age, rank and the propensity to both generate and exploit information, but heterophily for sex. However, there was considerable variability both between troops and years. The patterns of homophily we observed for these phenotypes may impede information transfer between them. However, the inconsistency in the strength of assortment between troops and years suggests that the limitations to information flow may be quite variable.

Inducing self-organized criticality in a network toy model by neighborhood assortativity.

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Allen-Perkins, Alfonso; Galeano, Javier; Pastor, Juan Manuel

2016-11-01

Complex networks are a recent type of framework used to study complex systems with many interacting elements, such as self-organized criticality (SOC). The network nodes' tendency to link to other nodes of similar type is characterized by assortative mixing. Real networks exhibit assortative mixing by vertex degree, however, typical random network models, such as the Erdős-Rényi or the Barabási-Albert model, show no assortative arrangements. In this paper we introduce the notion of neighborhood assortativity as the tendency of a node to belong to a community (its neighborhood) showing an average property similar to its own. Imposing neighborhood assortative mixing by degree in a network toy model, SOC dynamics can be found. These dynamics are driven only by the network topology. The long-range correlations resulting from criticality have been characterized by means of fluctuation analysis and show an anticorrelation in the node's activity. The model contains only one parameter and its statistics plots for different values of the parameter can be collapsed into a single curve. The simplicity of the model allows us to perform numerical simulations and also to study analytically the statistics for a specific value of the parameter, making use of the Markov chains.

Arranging the assortment to arouse choice : Effects of goal-relevant assortment organization on food choice and variety perceptions

NARCIS (Netherlands)

van Herpen, E.; Bosmans, Anick

Food retailers can present specific products in a separate category (e.g., separate section for organic products) or integrated into the mainstream shelf. This study investigates how assortment organization influences consumers’ variety perceptions and product choice. We argue and show that when an

The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic.

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Han, Hye Joo; Schweickert, Richard; Xi, Zhuangzhuang; Viau-Quesnel, Charles

2016-04-01

For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream social network is not a copy of the cognitive social network. Waking life social networks tend to have positive assortativity; that is, people tend to be connected to others with similar connectivity. Instead, in our sample of dream social networks assortativity is more often negative or near 0, as in online social networks. We show that if characters appear via a random walk, negative assortativity can result, particularly if the random walk is biased as suggested by remote associations. Copyright © 2015 Cognitive Science Society, Inc.

Methods of forming and realization of assortment policy of retail business enterprises

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Kudenko Kiril

2016-07-01

Full Text Available Within the framework of the article systematisation of methods of forming and realisation of assortment policy of enterprises of retail business is done. Recommendations concerning the priority of the use of separate methods of forming and realisation of assortment policy with different purposes, taking into account their content, advantages and disadvantages are developed.

Assortative Mating for Psychopathy Components and its Effects on the Relationship Quality in Intimate Partners

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Igor Kardum

2017-05-01

Full Text Available In three studies, we examined assortative mating for psychopathy components as well as its effects on the relationship quality in intimate partners. Compared to the original structure we confirmed three factors of psychopathy: criminal tendencies (CT, erratic lifestyle (ELS and interpersonal manipulation (IM, while callous affect (CA was not replicated. Hypotheses regarding positive versus negative assortment, initial assortment versus convergence, and active assortment versus social homogamy were tested. All hypotheses were examined using both variable-centered approach (VCA and couple-centered approach (CCA. We found moderate positive assortment between intimate partners in psychopathy as a latent construct estimated by structural modelling. Furthermore, positive assortment for all three components of psychopathy was found either by using only VCA (CT, only CCA (IM or both approaches (ELS. Additionally, initial assortment rather than convergence hypothesis and active assortment rather than social homogamy hypothesis was confirmed for all three psychopathy components, with a slight tendency towards divergence and social homogamy. We explored the effects of similarity in psychopathy components on the women and men' relationship quality by using profile similarity and polynomial regression analyses. Profile similarity in IM was significantly positively related to women's relationship quality, while the results of the polynomial regression analyses were more complex, and showed that only (dissimilarity in CT did not exert any effect on women and men's relationship quality. Greater disagreement between women and men's ELS was related with more sharp decrease of women's relationship quality, while men's relationship quality decreased at the higher levels of women and men's ELS. Greater disagreement between women and men's IM results in a lower women's relationship quality, while women and men's relationship quality was higher when women's IM was

Enhanced memory performance thanks to neural network assortativity

International Nuclear Information System (INIS)

Franciscis, S. de; Johnson, S.; Torres, J. J.

2011-01-01

The behaviour of many complex dynamical systems has been found to depend crucially on the structure of the underlying networks of interactions. An intriguing feature of empirical networks is their assortativity--i.e., the extent to which the degrees of neighbouring nodes are correlated. However, until very recently it was difficult to take this property into account analytically, most work being exclusively numerical. We get round this problem by considering ensembles of equally correlated graphs and apply this novel technique to the case of attractor neural networks. Assortativity turns out to be a key feature for memory performance in these systems - so much so that for sufficiently correlated topologies the critical temperature diverges. We predict that artificial and biological neural systems could significantly enhance their robustness to noise by developing positive correlations.

Indirect reciprocity with negative assortment and limited information can promote cooperation.

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Brush, Eleanor; Brännström, Åke; Dieckmann, Ulf

2018-04-14

Cooperation is ubiquitous in biological and social systems, even though cooperative behavior is often costly and at risk of exploitation by non-cooperators. Several studies have demonstrated that indirect reciprocity, whereby some members of a group observe the behaviors of their peers and use this information to discriminate against previously uncooperative agents in the future, can promote prosocial behavior. Some studies have shown that differential propensities of interacting among and between different types of agents (interaction assortment) can increase the effectiveness of indirect reciprocity. No previous studies have, however, considered differential propensities of observing the behaviors of different types of agents (information assortment). Furthermore, most previous studies have assumed that discriminators possess perfect information about others and incur no costs for gathering and storing this information. Here, we (1) consider both interaction assortment and information assortment, (2) assume discriminators have limited information about others, and (3) introduce a cost for information gathering and storage, in order to understand how the ability of discriminators to stabilize cooperation is affected by these steps toward increased realism. We report the following findings. First, cooperation can persist when agents preferentially interact with agents of other types or when discriminators preferentially observe other discriminators, even when they have limited information. Second, contrary to intuition, increasing the amount of information available to discriminators can exacerbate defection. Third, introducing costs of gathering and storing information makes it more difficult for discriminators to stabilize cooperation. Our study is one of only a few studies to date that show how negative interaction assortment can promote cooperation and broadens the set of circumstances in which it is know that cooperation can be maintained. Copyright © 2018

Using Social Network Methods to Test for Assortment of Prosociality among Korean High School Students

Science.gov (United States)

Kim, Jun-Hong; Holman, Darryl J.; Goodreau, Steven M.

2015-01-01

Assortative interaction among altruistic individuals is a necessary condition for the evolution of cooperation. The requirement for assortment holds regardless of whether a meta-population is subdivided into distinct and isolated subgroups or has ephemeral boundaries with a high migration rate. The assumption, however, is rarely tested directly. In this paper, we develop a method to test for assortment of prosociality in network-structured data. The method is applied to a friendship network collected from 238 Korean students attending the same high school. A mixing matrix was used to explore the presence of assortative friendship among more prosocial individuals. An exponential random graph model of network structure that accounts for additional observed relational propensities (higher-than-expected number of people nominating no friends) and sampling constraints (upper bound on friendship nominations) found that individual prosociality predicted friendship propensity, and that individuals with higher prosocial scores had a higher probability of befriending other more prosocial individuals. The results reveal that a considerable level of assortment of prosociality characterizes this population. PMID:25915508

Gender Norms and Retaliatory Violence against Spouses and Acquaintances

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Feld, Scott L.; Felson, Richard B.

2008-01-01

This article examines an experiment embedded within a nationally representative survey of adult Americans to investigate gender norms regarding retaliatory violence between spouses and acquaintances. Contrary to claims that societal norms permit violence within marriage, respondents disapproved of retaliatory violence against spouses more than…

The Nature of Interactions between Students with Severe Disabilities and Their Friends and Acquaintances without Disabilities.

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Grenot-Scheyer, Marquita

1994-01-01

This study of 20 elementary-school children with severe disabilities examined differences in their interactions with friends without disabilities compared with interactions with acquaintances without disabilities. Friends and acquaintances did not differ in developmental level, language age, functional movement, or social competence. Group…

METHODS OF DETERMINATION THE INTERIOR POTENTIAL OF ENTERPRISE IN MAKING STRATEGICAL ASSORTMENT DECISIONS

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Svitlana Malyuk

2015-11-01

Full Text Available The analysis of the internal environment of the enterprise is aimed at assessing the strategic potential of the enterprise as a whole and its individual functional subsystems. The efficient activity of enterprise cannot be realized without a systematic definition and using the existing capabilities since, as a rule, the potential of the organization is higher than its actual implementation. It is not possible to put forward long-term goals, to form the most optimal strategy to achieve them without the characteristics of accumulated enterprises potential. From this point, the purpose of the paper is to study and establish the criteria that characterize the inner potential of the company during the implementation of assortment strategies. The method of evaluating of these indicators, as well as the selection of the assortment strategy according to the results has been suggested. Methods. The research of the internal potential of PJSC “Mykolaiv bakery № 1” is based on the expert questionnaire, which made it possible not only to identify a number of criteria for internal enterprises environment, which made it possible not only to identify a number of criteria for internal environment, as well as by experts to determine the parameter and boundary values of coefficients influencing the choice of the assortment strategy. The results of questionnaire showed that the main criteria of the characteristics of the internal potential of the company are: primary phases of the life cycle of the goods (were determined on the basis of the matrix "Market growth – Market Share"; prospects of producing the assortment groups of goods (calculated using the integral coefficient of goods assortment; changes in sales amount (described by trigonometric dependencies; degree of the goods assortment realization (evaluated using the coefficient of realization; assortments balance according to the Pareto rule (based on the Pareto rule, as well as expert survey; the

Romantic Partners, Friends, Friends with Benefits, and Casual Acquaintances As Sexual Partners

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Furman, Wyndol; Shaffer, Laura

2011-01-01

The purpose of the present study was to provide a detailed examination of sexual behavior with different types of partners. A sample of 163 young adults reported on their light nongenital, heavy nongenital, and genital sexual activity with romantic partners, friends, and casual acquaintances. They described their sexual activity with “friends with benefits” as well as with friends in general. Young adults were most likely to engage in sexual behavior with romantic partners, but sexual behavior also often occurred with some type of nonromantic partner. More young adults engaged in some form of sexual behavior with casual acquaintances than with friends with benefits. The frequencies of sexual behavior, however, were greater with friends with benefits than with friends or casual acquaintances. Interview and questionnaire data revealed that friends with benefits were typically friends, but not necessarily. Nonsexual activities were also less common with friends with benefits than other friends. Taken together, the findings illustrate the value of differentiating among different types of nonromantic partners and different levels of sexual behavior. PMID:21128155

An Evaluation of Practical Applicability of Multi-Assortment Production Break-Even Analysis based on Mining Companies

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Fuksa, Dariusz; Trzaskuś-Żak, Beata; Gałaś, Zdzisław; Utrata, Arkadiusz

2017-03-01

In the practice of mining companies, the vast majority of them produce more than one product. The analysis of the break-even, which is referred to as CVP (Cost-Volume-Profit) analysis (Wilkinson, 2005; Czopek, 2003) in their case is significantly constricted, given the necessity to include multi-assortment structure in the analysis, which may have more than 20 types of assortments (depending on the grain size) in their offer, as in the case of open-pit mines. The article presents methods of evaluation of break-even (volume and value) for both a single-assortment production and a multi-assortment production. The complexity of problem of break-even evaluation for multi-assortment production has resulted in formation of many methods, and, simultaneously, various approaches to its analysis, especially differences in accounting fixed costs, which may be either totally accounted for among particular assortments, relating to the whole company or partially accounted for among particular assortments and partially relating to the company, as a whole. The evaluation of the chosen methods of break-even analysis, given the availability of data, was based on two examples of mining companies: an open-pit mine of rock materials and an underground hard coal mine. The selection of methods was set by the available data provided by the companies. The data for the analysis comes from internal documentation of the mines - financial statements, breakdowns and cost calculations.

Convenience stores and the marketing of foods and beverages through product assortment.

Science.gov (United States)

Sharkey, Joseph R; Dean, Wesley R; Nalty, Courtney

2012-09-01

Product assortment (presence and variety) is a key in-store marketing strategy to influence consumer choice. Quantifying the product assortment of healthier and less-healthy foods and beverages in convenience stores can inform changes in the food environment. To document product assortment (i.e., presence and variety of specific foods and beverages) in convenience stores. Observational survey data were collected onsite in 2011 by trained promotora-researchers in 192 convenience stores. Frequencies of presence and distributions of variety were calculated in 2012. Paired differences were examined using the Wilcoxon matched-pairs signed-rank test. Convenience stores displayed a large product assortment of sugar-sweetened beverages (median 86.5 unique varieties); candy (76 varieties); salty snacks (77 varieties); fried chips (44 varieties); cookies and pastries (19 varieties); and frozen sweets (21 varieties). This compared with 17 varieties of non-sugar sweetened beverages and three varieties of baked chips. The Wilcoxon signed-rank test confirmed a (p<0.001) greater variety of sugar-sweetened than non-sugar-sweetened beverages, and of fried chips compared with baked chips. Basic food items provided by convenience stores included milk (84% of stores); fresh fruit (33%); fresh vegetables (35%); canned vegetables (78%); white bread (71%); and deli-style packaged meat (57%). Healthier versions of milk, canned fruit, canned tuna, bread, and deli-style packaged meat were displayed in 17%-71% of convenience stores. Convenience stores in this area provide a greater assortment of less-healthy compared with healthier foods and beverages. There are opportunities to influence consumer food choice through programs that alter the balance between healthier and less-healthy foods and beverages in existing convenience stores that serve rural and underserved neighborhoods and communities. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights

How acquainting shows verbally

DEFF Research Database (Denmark)

Hermann, Jesper

2004-01-01

A central tenet of the integrational view of language and communication is an anchoring in the acting and integrating behaviour of the communicants themselves. In this way the integrational approach has a certain phenomenological slant. What happens when this approach is combined with a ¿psycholo...... to some of William James' classical psychological observations. 16...... of linguistic exertion¿ based upon the descriptions of the  stream of thought, and of conception (>acquainting) by William James? Text-examples taken from an internet site for dieters illustrate the combined James'ian & integrational approach in practice. Some of the examples are also specifically related......A central tenet of the integrational view of language and communication is an anchoring in the acting and integrating behaviour of the communicants themselves. In this way the integrational approach has a certain phenomenological slant. What happens when this approach is combined with a ¿psychology...

Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow.

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Sachdeva, Himani; Barton, Nicholas H

2017-06-01

Assortative mating is an important driver of speciation in populations with gene flow and is predicted to evolve under certain conditions in few-locus models. However, the evolution of assortment is less understood for mating based on quantitative traits, which are often characterized by high genetic variability and extensive linkage disequilibrium between trait loci. We explore this scenario for a two-deme model with migration, by considering a single polygenic trait subject to divergent viability selection across demes, as well as assortative mating and sexual selection within demes, and investigate how trait divergence is shaped by various evolutionary forces. Our analysis reveals the existence of sharp thresholds of assortment strength, at which divergence increases dramatically. We also study the evolution of assortment via invasion of modifiers of mate discrimination and show that the ES assortment strength has an intermediate value under a range of migration-selection parameters, even in diverged populations, due to subtle effects which depend sensitively on the extent of phenotypic variation within these populations. The evolutionary dynamics of the polygenic trait is studied using the hypergeometric and infinitesimal models. We further investigate the sensitivity of our results to the assumptions of the hypergeometric model, using individual-based simulations. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Importance of small-degree nodes in assortative networks with degree-weight correlations

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Ma, Sijuan; Feng, Ling; Monterola, Christopher Pineda; Lai, Choy Heng

2017-10-01

It has been known that assortative network structure plays an important role in spreading dynamics for unweighted networks. Yet its influence on weighted networks is not clear, in particular when weight is strongly correlated with the degrees of the nodes as we empirically observed in Twitter. Here we use the self-consistent probability method and revised nonperturbative heterogenous mean-field theory method to investigate this influence on both susceptible-infective-recovered (SIR) and susceptible-infective-susceptible (SIS) spreading dynamics. Both our simulation and theoretical results show that while the critical threshold is not significantly influenced by the assortativity, the prevalence in the supercritical regime shows a crossover under different degree-weight correlations. In particular, unlike the case of random mixing networks, in assortative networks, the negative degree-weight correlation leads to higher prevalence in their spreading beyond the critical transmissivity than that of the positively correlated. In addition, the previously observed inhibition effect on spreading velocity by assortative structure is not apparent in negatively degree-weight correlated networks, while it is enhanced for that of the positively correlated. Detailed investigation into the degree distribution of the infected nodes reveals that small-degree nodes play essential roles in the supercritical phase of both SIR and SIS spreadings. Our results have direct implications in understanding viral information spreading over online social networks and epidemic spreading over contact networks.

Assortative mating for human height : A meta-analysis

NARCIS (Netherlands)

Stulp, Gert; Simons, Mirre J. P.; Grasman, Sara; Pollet, Thomas V.

ObjectivesThe study of assortative mating for height has a rich history in human biology. Although the positive correlation between the stature of spouses has often been noted in western populations, recent papers suggest that mating patterns for stature are not universal. The objective of this

Social Structure and Personality Assortment Among Married Couples

NARCIS (Netherlands)

Bekkers, René; Aken, Marcel A.G. van; Denissen, Jaap

2006-01-01

We study the influence of social structure on assortative mating for personality in a large national sample (n=3616) of married and cohabitating couples in the Netherlands. We find that couples with higher levels of education and from dissimilar religious origins are more similar with regard to

Management of Assortment Inventory Groups in Selected Foundry

Directory of Open Access Journals (Sweden)

Szymszal J.

2015-09-01

Full Text Available As experience shows the practical, reliable assessment and optimisation of total costs of logistical processes implemented in supply chains of foundry plants is a quite complex and complicated process, because it requires to enclose all, without exception, performed actions, including them in various reference cross-sections, systematic activities and finally transforming them in a totally homogenous collection. Only solid analysis and assessment of assortment management in logistical supply systems in foundry plants of particular assortment groups allows to lower the supply costs significantly. In the article the analysis and assessment of the newest implemented optimising algorithms are presented in the process stock management of selected material groups used in a production process of a chosen foundry plant. A practical solution to solve a problem of rotary stock cost minimisation is given as well as of costs while creating a stock with the usage of economical volume and value of order.

The Impact of Product Assortment Size and Attribute Quantity on Information Searches

DEFF Research Database (Denmark)

Dörnyei, Krisztina Rita; Chrysochou, Polymeros; Krystallis, Athanasios

2017-01-01

Purpose: This paper investigates the impact of assortment size and attribute quantity on the depth and content of consumer information searches. Design/methodology/approach: For a computer-aided experiment using an information display board, participants (n=393) were placed in a simulated shopping...... situation that involved choosing a product among three sets of frequently purchased, low-involvement, FMCG alternatives. Findings: The findings show that when the assortment size increases, consumers acquire information from more products and cues but sacrifice product attributes. In particular...

Emergence of clustering in an acquaintance model without homophily

International Nuclear Information System (INIS)

Bhat, Uttam; Krapivsky, P L; Redner, S

2014-01-01

We introduce an agent-based acquaintance model in which social links are created by processes in which there is no explicit homophily. In spite of the homogeneous nature of the social interactions, highly-clustered social networks can arise. The crucial feature of our model is that of variable transitive interactions. Namely, when an agent introduces two unconnected friends, the rate at which a connection actually occurs between them depends on the number of their mutual acquaintances. As this transitive interaction rate is varied, the social network undergoes a dramatic clustering transition. Close to the transition, the network consists of a collection of well-defined communities. As a function of time, the network can also undergo an incomplete gelation transition, in which the gel, or giant cluster, does not constitute the entire network, even at infinite time. Some of the clustering properties of our model also arise, but in a more gradual manner, in Facebook networks. Finally, we discuss a more realistic variant of our original model in which network realizations can be constructed that quantitatively match Facebook networks. (paper)

Emergence of clustering in an acquaintance model without homophily

Science.gov (United States)

Bhat, Uttam; Krapivsky, P. L.; Redner, S.

2014-11-01

We introduce an agent-based acquaintance model in which social links are created by processes in which there is no explicit homophily. In spite of the homogeneous nature of the social interactions, highly-clustered social networks can arise. The crucial feature of our model is that of variable transitive interactions. Namely, when an agent introduces two unconnected friends, the rate at which a connection actually occurs between them depends on the number of their mutual acquaintances. As this transitive interaction rate is varied, the social network undergoes a dramatic clustering transition. Close to the transition, the network consists of a collection of well-defined communities. As a function of time, the network can also undergo an incomplete gelation transition, in which the gel, or giant cluster, does not constitute the entire network, even at infinite time. Some of the clustering properties of our model also arise, but in a more gradual manner, in Facebook networks. Finally, we discuss a more realistic variant of our original model in which network realizations can be constructed that quantitatively match Facebook networks.

Assortative Mating by Ethnicity in Longevous Families

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Paola Sebastiani

2017-11-01

Full Text Available Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS, and the New England Centenarian Study (NECS. In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene–environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages.

Assortative Mating by Ethnicity in Longevous Families.

Science.gov (United States)

Sebastiani, Paola; Gurinovich, Anastasia; Bae, Harold; Andersen, Stacy L; Perls, Thomas T

2017-01-01

Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS), and the New England Centenarian Study (NECS). In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene-environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages.

Assortativity and Mixing by Sexual Behaviors and Sociodemographic Characteristics in Young Adult Heterosexual Dating Partnerships.

Science.gov (United States)

Malagón, Talía; Burchell, Ann; El-Zein, Mariam; Tellier, Pierre-Paul; Coutlée, François; Franco, Eduardo L

2017-06-01

Assortative sexual mixing, the tendency for individuals to choose partners with similar characteristics to themselves, may be an important contributor to the unequal distribution of sexually transmitted infections in populations. We analyzed the tendency for assortative mixing on demographic and sexual behaviors characteristics in newly formed young adults dating partnerships. Women aged 18 to 24 years and their male sexual partners of no more than 6 months were recruited during 2005 to 2010 at universities in Montreal, Canada. New dating partners were also prospectively recruited during the 2-year follow-up. We used Spearman and Newman coefficients to examine correlations between partners' demographic characteristics and sexual behaviors, and multivariable logistic modeling to determine which characteristics were assortative. Participants in 502 recruited partnerships were assortative on age (Spearman P = 0.60), smoking behavior (P = 0.43), ethnicity (Newman coefficient=0.39), lifetime number of sexual partners (P = 0.36), sex partner acquisition rates (P = 0.22), gap length between partnerships (P = 0.20), and on whether they had concurrent partners (P = 0.33). Partners were assortative on number of lifetime partners, sexual partner acquisition rates, concurrency, and gap length between partnerships even after adjustment for demographic characteristics. Reported condom use was correlated between initial and subsequently recruited partners (P = 0.35). There was little correlation between the frequencies of vaginal/oral/digital/anal sex between subsequent partnerships. Dating partnerships were substantially assortative on various sexual behaviors as well as demographic characteristics. Though not a representative population sample, our recruitment of relatively new partnerships reduces survivor bias inherent to cross-sectional surveys where stable long-term partnerships are more likely to be sampled.

CATEGORY MANAGEMENT IN THE MANAGEMENT OF MINIMUM ASSORTMENT OF THE PHARMACEUTICAL ORGANIZATION

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I. F. Samoshchenkova

2017-01-01

Full Text Available The main principle of the category management is the management of product category as a separate business unit. Category management directs the activities of the pharmaceutical organization to meet the consumer requirements and to provide customers with maximum benefits, which are expressed in the improved assortment,the attractive prices, the reduction of cases of lack of necessary goods, the simplifiedpurchase process. In article the structure of the category management and its role inthe minimum pharmaceutical assortment, a complex of the theoretical and practical issues affecting interrelation of the list of vital and essential medicines and the minimum range of medicines are considered. A number of the new elements supplementing the concept of category management is offered, and the corresponding generalizations are made. The objective of the research is to study the influence of category management on the structure in management of the minimum assortment of medicines of the pharmaceutical organization. Materials and methods. In the course of the solution of the set tasks, the methods of marketing and economic-mathematical analysis were used. Results and discussion. In the analysis of the assortment list of medicines for medical application, which is obligatory for the pharmaceutical enterprises of all forms of ownership, it was revealed that this assortment list is based on the List of Vital Essential and Necessary (VEN Drugs. The results of the analysis of the obligatory assortment list from the position of internal category management showed that 77.45% are medicines of the list of VEN Drugs; 46.08% are medicines of non-prescription dispensing. Proceeding from this it follows that the worthy, profitable price policy can be conducted only with 22.55% of the list; to develop standards of merchandising with 46.05%. The category management gives an opportunity to the pharmaceutical organization to specify its competitive strategy and to

Influenced but unaware: social influence on alcohol drinking among social acquaintances.

Science.gov (United States)

Dallas, Rebecca; Field, Matt; Jones, Andrew; Christiansen, Paul; Rose, Abi; Robinson, Eric

2014-05-01

Drinking partners may be influenced by each other's alcohol consumption. However, these effects have only been shown in artificially created social pairings and typically among same-sex young adults. Here, we test whether similarly strong influence effects occur among "real" pairs of social acquaintances (friends and partners) and whether people are aware of this influence on their alcohol consumption. Forty-six pairs of social acquaintances aged between 19 and 60 years old participated in a between-subjects experiment, in a semi-naturalistic bar laboratory setting. One member of each pair (the confederate) was randomly selected and asked to consume only alcoholic (alcohol condition) or soft drinks (nonalcohol condition), while the pair completed a game together in a bar setting. The other participant (naïve) was unaware of these drinking instructions. Postconsumption, we measured the extent to which naïve participants believed that their partner had influenced their own drinking behavior. A large effect of condition on alcohol consumption was observed, χ² (2) = 15.8, p < 0.001, Cramer's V = 0.59, whereby the number of alcoholic drinks selected by naïve participants in the alcohol confederate condition was significantly greater than in the nonalcohol confederate condition. The majority of naïve participants (81%) also tended to be unaware that their partner had influenced their alcohol consumption. Social acquaintances are influenced by each other's alcohol consumption and may not be aware of this influence on their behavior. Copyright © 2014 by the Research Society on Alcoholism.

Geographically selective assortment of cycles in pandemics: meta-analysis of data collected by Chizhevsky.

Science.gov (United States)

Gumarova, L; Cornélissen, G; Hillman, D; Halberg, F

2013-10-01

In the incidence patterns of cholera, diphtheria and croup during the past when they were of epidemic proportions, we document a set of cycles (periods), one of which was reported and discussed by A. L. Chizhevsky in the same data with emphasis on the mirroring in human disease of the ~11-year sunspot cycle. The data in this study are based on Chizhevsky’s book The Terrestrial Echo of Solar Storms and on records from the World Health Organization. For meta-analysis, we used the extended linear and nonlinear cosinor. We found a geographically selective assortment of various cycles characterizing the epidemiology of infections, which is the documented novel topic of this paper, complementing the earlier finding in the 21st century or shortly before, of a geographically selective assortment of cycles characterizing human sudden cardiac death. Solar effects, if any, interact with geophysical processes in contributing to this assortment.

Female preference for male color is necessary and sufficient for assortative mating in 2 cichlid sister species

NARCIS (Netherlands)

Selz, Oliver M.; Pierotti, Michele E. R.; Maan, Martine E.; Schmid, Corinne; Seehausen, Ole

2014-01-01

A critical step for speciation in the face of gene flow is the origination of reproductive isolation. The evolution of assortative mating greatly facilitates this process. Assortative mating can be mediated by one or multiple cues across an array of sensory modalities. We here explore possible cues

"Nobody Told Me It Was Rape": A Parent's Guide for Talking with Teenagers about Acquaintance Rape and Sexual Exploitation.

Science.gov (United States)

Adams, Caren; Fay, Jennifer

This book was written to help parents talk to their adolescent children about acquaintance rape and sexual exploitation. It may also be useful to family life educators presenting units on rape and sexual exploitation. Acquaintance rape and sexual exploitation are explained in the first section. The second section discusses talking with teenagers…

Assimilative and non-assimilative color spreading in the watercolor configuration

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Eiji eKimura

2014-09-01

Full Text Available A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect. The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC is paired with a blue outer contour (OC, yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and OC luminances (Experiment 1 as well as the background luminance (Experiment 2. The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminances (IC contrast was smaller than that of the OC (OC contrast, the induced color became similar to the IC color (assimilative spreading. In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading. Extending these findings, Experiment 3 showed that bilateral color spreading, e.g., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading [Grossberg, S. & Mingolla, E. (1985 Percept. Psychophys., 38, 141-171] and extended for the watercolor effect [Pinna, B., & Grossberg, S. (2005 J. Opt. Soc. Am. A, 22, 2207-2221]. However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

Assimilative and non-assimilative color spreading in the watercolor configuration.

Science.gov (United States)

Kimura, Eiji; Kuroki, Mikako

2014-01-01

A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect). The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC) is paired with a blue outer contour (OC), yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and the OC luminance (Experiment 1) as well as the background luminance (Experiment 2). The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminance (IC contrast) was smaller in size than that of the OC (OC contrast), the induced color became similar to the IC color (assimilative spreading). In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading). Extending these findings, Experiment 3 showed that bilateral color spreading, i.e., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and the non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading (Grossberg and Mingolla, 1985) and extended for the watercolor effect (Pinna and Grossberg, 2005). However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

Income inequality and educational assortative mating: Evidence from the Luxembourg Income Study.

Science.gov (United States)

Monaghan, David

2015-07-01

Though extensive research has explored the prevalence of educational assortative mating, what causes its variation across countries and over time is not well understood. Using data from the Luxembourg Income Study Database, I investigate the hypothesis that assortative mating by income is influenced by income inequality between educational strata. I find that in countries with greater returns to education, the odds of any sort of union that crosses educational boundaries is substantially reduced. However, I do not find substantial evidence of an effect of changes in returns to education on marital sorting within countries. Educational and labor market parity between males and females appear to be negatively related to marital sorting. Copyright © 2015 Elsevier Inc. All rights reserved.

Representing a Model Using Data Mining Approach for Maximizing Profit with Considering Product Assortment and Space Allocation Decisions

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Manoochehr Ansari

2016-12-01

Full Text Available The choice of which products to stock among numerous competing products and how much space to allocate to those products are central decisions for retailers. This study aimed to apply data mining approach so that, we got needed information from large datasets of sale transactions to find the relations between products and to make product assortments. Thus, we represented a model for product assortment and space allocation. Research population was transactional data of a store, the sample included transactional data of one-month period in the time series. Data were collected in October and November, 2015 from Shaghayegh store. 525 transactions with regard to 79 different products were analyzed. Based on the result 10 product assortments formed although some products were allocated to more than 1 product category. By solving profit equation and finding volume increase indices we allocated spaces for each product assortment.

High incidence of GJB2 gene mutations among assortatively mating ...

Indian Academy of Sciences (India)

High incidence of GJB2 gene mutations among assortatively mating hearing impaired families in Kerala: future implications. Amritkumar Pavithra, Justin Margret Jeffrey, Jayasankaran Chandru, Arabandi Ramesh and C. R. Srikumari Srisailapathy. J. Genet. 93, 207–213. Table 1. Consolidated table of GJB2 mutation status ...

Assortative mating and differential male mating success in an ash hybrid zone population

Directory of Open Access Journals (Sweden)

Frascaria-Lacoste Nathalie

2006-11-01

Full Text Available Abstract Background The structure and evolution of hybrid zones depend mainly on the relative importance of dispersal and local adaptation, and on the strength of assortative mating. Here, we study the influence of dispersal, temporal isolation, variability in phenotypic traits and parasite attacks on the male mating success of two parental species and hybrids by real-time pollen flow analysis. We focus on a hybrid zone population between the two closely related ash species Fraxinus excelsior L. (common ash and F. angustifolia Vahl (narrow-leaved ash, which is composed of individuals of the two species and several hybrid types. This population is structured by flowering time: the F. excelsior individuals flower later than the F. angustifolia individuals, and the hybrid types flower in-between. Hybrids are scattered throughout the population, suggesting favorable conditions for their local adaptation. We estimate jointly the best-fitting dispersal kernel, the differences in male fecundity due to variation in phenotypic traits and level of parasite attack, and the strength of assortative mating due to differences in flowering phenology. In addition, we assess the effect of accounting for genotyping error on these estimations. Results We detected a very high pollen immigration rate and a fat-tailed dispersal kernel, counter-balanced by slight phenological assortative mating and short-distance pollen dispersal. Early intermediate flowering hybrids, which had the highest male mating success, showed optimal sex allocation and increased selfing rates. We detected asymmetry of gene flow, with early flowering trees participating more as pollen donors than late flowering trees. Conclusion This study provides striking evidence that long-distance gene flow alone is not sufficient to counter-act the effects of assortative mating and selfing. Phenological assortative mating and short-distance dispersal can create temporal and spatial structuring that appears

Quantifying the risk of pandemic influenza virus evolution by mutation and re-assortment.

Science.gov (United States)

Reperant, Leslie A; Grenfell, Bryan T; Osterhaus, Albert D M E

2015-12-08

Large outbreaks of zoonotic influenza A virus (IAV) infections may presage an influenza pandemic. However, the likelihood that an airborne-transmissible variant evolves upon zoonotic infection or co-infection with zoonotic and seasonal IAVs remains poorly understood, as does the relative importance of accumulating mutations versus re-assortment in this process. Using discrete-time probabilistic models, we determined quantitative probability ranges that transmissible variants with 1-5 mutations and transmissible re-assortants evolve after a given number of zoonotic IAV infections. The systematic exploration of a large population of model parameter values was designed to account for uncertainty and variability in influenza virus infection, epidemiological and evolutionary processes. The models suggested that immunocompromised individuals are at high risk of generating IAV variants with pandemic potential by accumulation of mutations. Yet, both immunocompetent and immunocompromised individuals could generate high viral loads of single and double mutants, which may facilitate their onward transmission and the subsequent accumulation of additional 1-2 mutations in newly-infected individuals. This may result in the evolution of a full transmissible genotype along short chains of contact transmission. Although co-infection with zoonotic and seasonal IAVs was shown to be a rare event, it consistently resulted in high viral loads of re-assortants, which may facilitate their onward transmission among humans. The prevention or limitation of zoonotic IAV infection in immunocompromised and contact individuals, including health care workers, as well as vaccination against seasonal IAVs-limiting the risk of co-infection-should be considered fundamental tools to thwart the evolution of a novel pandemic IAV by accumulation of mutations and re-assortment. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Acquaintance ratings of the Big Five personality traits: incremental validity beyond and interactive effects with self-reports in the prediction of workplace deviance.

Science.gov (United States)

Kluemper, Donald H; McLarty, Benjamin D; Bing, Mark N

2015-01-01

It is widely established that the Big Five personality traits of conscientiousness, agreeableness, and emotional stability are antecedents to workplace deviance (Berry, Ones, & Sackett, 2007). However, these meta-analytic findings are based on self-reported personality traits. A recent meta-analysis by Oh, Wang, and Mount (2011) identified the value of acquaintance-reported personality in the prediction of job performance. The current investigation extends prior work by comparing the validities of self- and acquaintance-reported personality in the prediction of workplace deviance across 2 studies. We also hypothesized and tested an interactive, value-added integration of self- with acquaintance-reported personality using socioanalytic personality theory (R. T. Hogan, 1991). Both studies assessed self- and acquaintance-rated Big Five traits, along with supervisor-rated workplace deviance. However, the studies varied the measures of workplace deviance, and the 2nd study also included a self-rated workplace deviance criterion for additional comparison. Across both studies, the traits of conscientiousness and agreeableness were strong predictors of workplace deviance, and acquaintance-reported personality provided incremental validity beyond self-reports. Additionally, acquaintance-reported conscientiousness and agreeableness moderated the prediction of workplace deviance by interacting with the corresponding self-reported traits. Implications for personality theory and measurement are discussed along with applications for practice. (c) 2015 APA, all rights reserved.

Assortative flocking in crossbills and implications for ecological speciation.

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Smith, Julie W; Sjoberg, Stephanie M; Mueller, Matthew C; Benkman, Craig W

2012-10-22

How reproductive isolation is related to divergent natural selection is a central question in speciation. Here, we focus on several ecologically specialized taxa or 'call types' of red crossbills (Loxia curvirostra complex), one of the few groups of birds providing much evidence for ecological speciation. Call types differ in bill sizes and feeding capabilities, and also differ in vocalizations, such that contact calls provide information on crossbill phenotype. We found that two call types of red crossbills were more likely to approach playbacks of their own call type than those of heterotypics, and that their propensity to approach heterotypics decreased with increasing divergence in bill size. Although call similarity also decreased with increasing divergence in bill size, comparisons of responses to familiar versus unfamiliar call types indicate that the decrease in the propensity to approach heterotypics with increasing divergence in bill size was a learned response, and not a by-product of calls diverging pleiotropically as bill size diverged. Because crossbills choose mates while in flocks, assortative flocking could lead indirectly to assortative mating as a by-product. These patterns of association therefore provide a mechanism by which increasing divergent selection can lead to increasing reproductive isolation.

You can't always get what you want: size assortative mating by mutual mate choice as a resolution of sexual conflict

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Thünken Timo

2009-06-01

Full Text Available Abstract Background Assortative mating patterns for mate quality traits like body size are often observed in nature. However, the underlying mechanisms that cause assortative mating patterns are less well known. Sexual selection is one important explanation for assortment, suggesting that i one (usually the female or both sexes could show preferences for mates of similar size or ii mutual mate choice could resolve sexual conflict over quality traits into assortment. We tested these hypotheses experimentally in the socially monogamous cichlid fish Pelvicachromis taeniatus, in which mate choice is mutual. Results In mate choice experiments, both sexes preferred large mates irrespective of own body size suggesting mating preferences are not size-assortative. Especially males were highly selective for large females, probably because female body size signals direct fitness benefits. However, when potential mates were able to interact and assess each other mutually they showed size-assortative mating patterns, i.e. the likelihood to mate was higher in pairs with low size differences between mates. Conclusion Due to variation in body size, general preferences for large mating partners result in a sexual conflict: small, lower quality individuals who prefer themselves large partners are unacceptable for larger individuals. Relative size mismatches between mates translate into a lower likelihood to mate, suggesting that the threshold to accept mates depends on own body size. These results suggest that the underlying mechanism of assortment in P. taeniatus is mutual mate choice resolving the sexual conflict over mates, rather than preference for mates of similar size.

Intergenerational income mobility – top incomes and assortative mating in Denmark

DEFF Research Database (Denmark)

Hussain, M. Azhar; Bonke, Jens; Munk, Martin D.

2011-01-01

This article investigates intergenerational income mobility among top-income people in Denmark focusing on the impact of assortative mating. Earnings and capital income are the variables of interest included in the analyzes testing the hypothesis that both wealth and social heritage are transferred...

Victimization After Meeting With Online Acquaintances: A Cross-Sectional Survey of Adolescents in Malaysia.

Science.gov (United States)

Marret, Mary J; Choo, Wan-Yuen

2016-01-18

This study aimed to determine contact and privacy risks encountered by Malaysian adolescents with access to the Internet and mobile phones and factors associated with face-to-face meetings with online acquaintances as well as to estimate the prevalence of subsequent victimization. Secondary school students from randomly selected public schools in Selangor and Kuala Lumpur responded to an anonymous self-administered questionnaire (78% response rate). Out of 3,349 Internet or mobile phone users, 51% had been invited to meet offline with an online-meeting acquaintance and 30% complied. Of the 1,005 respondents who went to offline meetings, 55% had meetings with more than six people. Male gender, Malay ethnicity, online access at an Internet café, viewing pornography on the Internet, the absence of parental restrictions on visiting certain website and chat rooms, not being explicitly forbidden to meet strangers encountered online, and disclosure of personal information were significantly associated with increased odds of face-to-face meetings with online acquaintances. Verbal, physical, or sexual assaults were reported by 5.5% of the 1,005 including 13 males and five females who reported forced sexual intercourse. Similarities as well as differences in factors associated with risk-taking behavior compared with adolescents in Western countries have important implications on policy and intervention. © The Author(s) 2016.

Acquaintance molestation and youth-serving organizations.

Science.gov (United States)

Lanning, Kenneth V; Dietz, Park

2014-10-01

This article is based not only on the research literature but also on the extensive field experience of the authors in consulting with investigators, attorneys, and organizations on the prevention, investigation, prosecution, and civil litigation of molestation of children within or in connection with youth-serving organizations. Acquaintance molesters have often pursued careers or sought out paid or volunteer work with organizations through which they can meet children. To address the problem of such offenders, it is necessary for youth-serving organizations to recognize the diversity of sexual activity, the phenomena of "nice-guy" offenders and compliant child victims, and the grooming/seduction process, each of which is reviewed here. The four most important protection practices for organizations are screening; management, and supervision; response to suspicions, allegations, and complaints; and prevention and awareness programs. The authors recommend general approaches to each of these and describe the reasons many organizations resist implementing available preventive measures. © The Author(s) 2014.

Brief report on the effect of providing single versus assorted brand name condoms to hospital patients: a descriptive study

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Cagle Henry H

2001-06-01

Full Text Available Abstract Objectives This study examined condom acquisition by persons in a hospital setting when single versus assorted brand name condoms were provided. Methods Condom receptacles were placed in exam rooms of two clinics. During Phase 1, a single brand name was provided; for Phase 2, assorted brand names were added. Number of condoms taken was recorded for each phase. Results For one clinic there was nearly a two-fold increase in number of condoms taken (Phase 1 to Phase 2; for the second clinic there was negligible difference in number of condoms taken. Conclusions The provision of assorted brand name condoms, over a single brand name, can serve to increase condom acquisition. Locations of condoms and target population characteristics are related factors.

Juror Decision Making in Acquaintance and Marital Rape: The Influence of Clothing, Alcohol, and Preexisting Stereotypical Attitudes.

Science.gov (United States)

Osborn, Kirsty; Davis, Josh P; Button, Susan; Foster, John

2018-04-01

Stereotypical biases about women's roles in intimate relationships including their marital status and lifestyle choices such as clothing and alcohol use influence juror attributions of rape case defendant guilt, potentially reducing access to justice for victims. Across two mock-juror decision-making experiments, participants read identical fictitious sexual assault vignettes varying in intoxicated defendant-complainant relationship (married vs. acquaintance), accompanied by photographs of complainant clothing at the crime (body revealing vs. plain) and in court (smart vs. casual). Experiment 2 additionally described the defendant's alcohol consumption as either under or over the drink drive limit. Most participants delivered guilty verdicts (Experiment 1: 86.7%; Experiment 2: 75.5%), recommending mean prison sentences of 5.04 years in Experiment 1 ( n = 218 students) and 4.33 years in Experiment 2 ( n = 1,086 members of public). In Experiment 1, guilty verdict rates and sentences were significantly higher when the married-but not the acquaintance-complainant dressed smartly rather than casually in court. In Experiment 2, significantly more guilty verdicts were delivered by females (80.3%) than males (66.9%), while sentence lengths were longer in acquaintance ( M = 4.52 years) than married conditions ( M = 4.10). Significant interactions between defendant alcohol use and clothing choice of the married-but not the acquaintance complainant-at the crime also influenced sentencing decisions. Higher scores on additionally administered scales measuring rape myth acceptance and sexist attitudes, but not alcohol expectancies, predicted lenient sentencing decisions in both experiments. These findings highlight how "rape myths" concerning marriages drive juror decisions. Prosecuting lawyers should use these results to better challenge these attitudes in court. Internationally, rape is often unreported to the police, and married victims may be more willing to come forward if

Healthy snacks at the checkout counter: a lab and field study on the impact of shelf arrangement and assortment structure on consumer choices.

Science.gov (United States)

van Kleef, Ellen; Otten, Kai; van Trijp, Hans C M

2012-12-12

The essence of nudging is to adapt the environment in which consumers make decisions to help them make better choices, without forcing certain outcomes upon them. To determine how consumers can effectively be guided to select healthier snacks, we examine the effect of manipulating the assortment structure and shelf layout of an impulse display including both healthy and unhealthy snacks near the checkout counter of a canteen. Both a lab and field study applied a two-factor experimental design manipulating snack offerings both in an on-screen choice environment and a natural environment (hospital staff restaurant). Shelf arrangement (i.e. accessibility) was altered by putting healthy snacks at higher shelves versus lower shelves. Assortment structure (i.e. availability) was altered by offering an assortment that either included 25% or 75% healthy snacks. Participants in the lab study (n = 158) made a choice from a shelf display. A brief survey following snack selection asked participants to evaluate the assortment and their choice. The field experiment took place in a hospital canteen. Daily sales data were collected for a period of four weeks. On completion of the field study, employees (n = 92) filled out a questionnaire about all four displays and rated their attractiveness, healthiness and perceived freedom of choice. The lab study showed a higher probability of healthy snack choice when 75% of the assortment consisted of healthy snacks compared to conditions with 25% healthy snack assortments, even though choices were not rated less satisfying or more restrictive. Regarding shelf display location of healthy snacks, no significant differences were observed. There was also no significant shelf arrangement by assortment structure interactive effect. The field study replicated these findings, in that this assortment structure led to higher sales of healthy snacks. Sales of unhealthy and total snacks were not impacted by manipulations (no main or interaction effects

Healthy snacks at the checkout counter: A lab and field study on the impact of shelf arrangement and assortment structure on consumer choices

Directory of Open Access Journals (Sweden)

van Kleef Ellen

2012-12-01

Full Text Available Abstract Background The essence of nudging is to adapt the environment in which consumers make decisions to help them make better choices, without forcing certain outcomes upon them. To determine how consumers can effectively be guided to select healthier snacks, we examine the effect of manipulating the assortment structure and shelf layout of an impulse display including both healthy and unhealthy snacks near the checkout counter of a canteen. Methods Both a lab and field study applied a two-factor experimental design manipulating snack offerings both in an on-screen choice environment and a natural environment (hospital staff restaurant. Shelf arrangement (i.e. accessibility was altered by putting healthy snacks at higher shelves versus lower shelves. Assortment structure (i.e. availability was altered by offering an assortment that either included 25% or 75% healthy snacks. Participants in the lab study (n = 158 made a choice from a shelf display. A brief survey following snack selection asked participants to evaluate the assortment and their choice. The field experiment took place in a hospital canteen. Daily sales data were collected for a period of four weeks. On completion of the field study, employees (n = 92 filled out a questionnaire about all four displays and rated their attractiveness, healthiness and perceived freedom of choice. Results The lab study showed a higher probability of healthy snack choice when 75% of the assortment consisted of healthy snacks compared to conditions with 25% healthy snack assortments, even though choices were not rated less satisfying or more restrictive. Regarding shelf display location of healthy snacks, no significant differences were observed. There was also no significant shelf arrangement by assortment structure interactive effect. The field study replicated these findings, in that this assortment structure led to higher sales of healthy snacks. Sales of unhealthy and total snacks were

Healthy snacks at the checkout counter: A lab and field study on the impact of shelf arrangement and assortment structure on consumer choices

Science.gov (United States)

2012-01-01

Background The essence of nudging is to adapt the environment in which consumers make decisions to help them make better choices, without forcing certain outcomes upon them. To determine how consumers can effectively be guided to select healthier snacks, we examine the effect of manipulating the assortment structure and shelf layout of an impulse display including both healthy and unhealthy snacks near the checkout counter of a canteen. Methods Both a lab and field study applied a two-factor experimental design manipulating snack offerings both in an on-screen choice environment and a natural environment (hospital staff restaurant). Shelf arrangement (i.e. accessibility) was altered by putting healthy snacks at higher shelves versus lower shelves. Assortment structure (i.e. availability) was altered by offering an assortment that either included 25% or 75% healthy snacks. Participants in the lab study (n = 158) made a choice from a shelf display. A brief survey following snack selection asked participants to evaluate the assortment and their choice. The field experiment took place in a hospital canteen. Daily sales data were collected for a period of four weeks. On completion of the field study, employees (n = 92) filled out a questionnaire about all four displays and rated their attractiveness, healthiness and perceived freedom of choice. Results The lab study showed a higher probability of healthy snack choice when 75% of the assortment consisted of healthy snacks compared to conditions with 25% healthy snack assortments, even though choices were not rated less satisfying or more restrictive. Regarding shelf display location of healthy snacks, no significant differences were observed. There was also no significant shelf arrangement by assortment structure interactive effect. The field study replicated these findings, in that this assortment structure led to higher sales of healthy snacks. Sales of unhealthy and total snacks were not impacted by

Accuracy in estimation of timber assortments and stem distribution - A comparison of airborne and terrestrial laser scanning techniques

Science.gov (United States)

Kankare, Ville; Vauhkonen, Jari; Tanhuanpää, Topi; Holopainen, Markus; Vastaranta, Mikko; Joensuu, Marianna; Krooks, Anssi; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto

2014-11-01

Detailed information about timber assortments and diameter distributions is required in forest management. Forest owners can make better decisions concerning the timing of timber sales and forest companies can utilize more detailed information to optimize their wood supply chain from forest to factory. The objective here was to compare the accuracies of high-density laser scanning techniques for the estimation of tree-level diameter distribution and timber assortments. We also introduce a method that utilizes a combination of airborne and terrestrial laser scanning in timber assortment estimation. The study was conducted in Evo, Finland. Harvester measurements were used as a reference for 144 trees within a single clear-cut stand. The results showed that accurate tree-level timber assortments and diameter distributions can be obtained, using terrestrial laser scanning (TLS) or a combination of TLS and airborne laser scanning (ALS). Saw log volumes were estimated with higher accuracy than pulpwood volumes. The saw log volumes were estimated with relative root-mean-squared errors of 17.5% and 16.8% with TLS and a combination of TLS and ALS, respectively. The respective accuracies for pulpwood were 60.1% and 59.3%. The differences in the bucking method used also caused some large errors. In addition, tree quality factors highly affected the bucking accuracy, especially with pulpwood volume.

Date and acquaintance rape. Development and validation of a set of scales.

Science.gov (United States)

Walsh, J F; Devellis, B M; Devellis, R F

1997-02-01

Increasing recognition of the prevalence of date/acquaintance rape (DAR) in the US, especially among college women, has led to an understanding that the techniques needed to fend off attacks from friends and acquaintances differ from those used to prevent rape by strangers. This study developed and tested the reliability and validity of the following DAR constructs: perceived vulnerability (underestimation of vulnerability discourages adequate self-protection), self-efficacy, relational priority (neglecting self-interest to save a relationship), rape myth acceptance (subscribing to myths about rape allows women to avoid facing their own vulnerability), and commitment to self-defense. These constructs were also correlated with scales measuring masculinity, self-esteem, and degree of belief in a "just world." Data were gathered to test these constructs via a questionnaire administered to 800 female undergraduate dormitory residents (47% response rate). Analysis of the data allowed refinement of 50 items into 25 items that constitute reliable scales of perceived vulnerability, self-efficacy, and self-determination and a marginally reliable scale of victim-blaming (rape myth). Support was found for 5/6 predicted correlates between DAR scales and 3/5 hypothesized correlations between DAR scales and convergent/discrimination validity scales. Research into this rape prevention tool will continue.

Modern state of the assortment drugs for the treatment of vaginal candidosis

Directory of Open Access Journals (Sweden)

Юлия Валентиновна Левачкова

2015-12-01

Full Text Available Today the problem of treatment of vaginal candidosis and creation of effective drugs for the treatment of this disease is actual for modern gynecology and pharmacy.Aim: to explore the structure of the assortment of drugs for the treatment of vaginal candidosis, presented in the Ukrainian pharmaceutical market.Methods: Statistical and marketing methods of investigation of electronic and paper sources of information. Implemented analysis assortment based on the materials of the State Register drugs in Ukraine and Compendium.Results: in the treatment of vaginal candidosis greatest efficiency belongs fluconazole. According to the ATC classification drugs with fluconazole includes to 2 anatomical groups, among which the main proportion of drugs for systemic use. In the pharmaceutical market of Ukraine registered 103 drugs with a fluconazole, which are mainly represented by import manufacturers. The largest share of preparations (84.8% constitute solid forms (capsules and tablets.Conclusions: vaginal medications with fluconazole are not present. Considering that the suppositories have several advantages over other pharmaceutical forms, creation of the new drugs with fluconazole is a perspective direction for modern medicine and pharmacy

Acquaintance Rape Workshops: Their Effectiveness in Changing the Attitudes of First Year College Men

Science.gov (United States)

Earle, James P.

2009-01-01

The statistics on acquaintance rape and sexual assault against women are a clear indication that this is a problem that needs to be confronted. An increasing number of articles address the problems that rape survivors face and examine methods mental health professionals can use to assist survivors in dealing with these problems. Articles that…

Heritability, assortative mating and gender differences in violent crime: results from a total population sample using twin, adoption, and sibling models.

Science.gov (United States)

Frisell, Thomas; Pawitan, Yudi; Långström, Niklas; Lichtenstein, Paul

2012-01-01

Research addressing genetic and environmental determinants to antisocial behaviour suggests substantial variability across studies. Likewise, evidence for etiologic gender differences is mixed, and estimates might be biased due to assortative mating. We used longitudinal Swedish total population registers to estimate the heritability of objectively measured violent offending (convictions) in classic twin (N = 36,877 pairs), adoptee-parent (N = 5,068 pairs), adoptee-sibling (N = 10,610 pairs), and sibling designs (N = 1,521,066 pairs). Type and degree of assortative mating were calculated from comparisons between spouses of siblings and half-siblings, and across consecutive spouses. Heritability estimates for the liability of violent offending agreed with previously reported heritability for self-reported antisocial behaviour. While the sibling model yielded estimates similar to the twin model (A ≈ 55%, C ≈ 13%), adoptee-models appeared to underestimate familial effects (A ≈ 20-30%, C ≈ 0%). Assortative mating was moderate to strong (r (spouse) = 0.4), appeared to result from both phenotypic assortment and social homogamy, but had only minor effect on variance components. Finally, we found significant gender differences in the etiology of violent crime.

The cultural context of nondisclosure of alcohol-involved acquaintance rape among Asian American college women: a qualitative study.

Science.gov (United States)

Koo, Kelly H; Nguyen, Hong V; Andrasik, Michele P; George, William H

2015-01-01

With high college enrollment and increasing alcohol use, Asian American (AA) college women may be at particular risk for experiencing alcohol-involved acquaintance rape. Although AA women have expressed the weakest intentions to report rape when compared to other ethnic groups, cultural factors influencing these intentions remain unexamined. Guided by grounded theory, 17 self-identified AA college women were interviewed about how the average AA college woman would respond to an alcohol-involved acquaintance rape. Despite awareness of benefits of disclosing rape, participants emphasized that nondisclosure would be the normative response. Three themes emerged from participants: institutional, sociocultural, and psychological contexts of nondisclosure. At an institutional level, nondisclosure referenced mental health and police services, which included Asian stereotypes and mistrust of police. Within a sociocultural context, rape nondisclosure focused on negative consequences on relationships with parents and, to a lesser extent, on friendships. Emotional avoidance and not labeling an acquaintance rape as rape were psychological strategies for rape nondisclosure. Participant's conceptualizations of mental and physical health concerns, specifically post-rape concerns, were framed within sociocultural/macrostructural contexts and may not match that of the more individualistic U.S. mainstream conceptualizations of health. Culturally sensitive rape education may be more effective in increasing rape prevention and support.

Comparison between assimilated and non-assimilated experiments of the MACCii global reanalysis near surface ozone

Science.gov (United States)

Tsikerdekis, Athanasios; Katragou, Eleni; Zanis, Prodromos; Melas, Dimitrios; Eskes, Henk; Flemming, Johannes; Huijnen, Vincent; Inness, Antje; Kapsomenakis, Ioannis; Schultz, Martin; Stein, Olaf; Zerefos, Christos

2014-05-01

In this work we evaluate near surface ozone concentrations of the MACCii global reanalysis using measurements from the EMEP and AIRBASE database. The eight-year long reanalysis of atmospheric composition data covering the period 2003-2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system (Inness et al., 2013). The study mainly focuses in the differences between the assimilated and the non-assimilated experiments and aims to identify and quantify any improvements achieved by adding data assimilation to the system. Results are analyzed in eight European sub-regions and region-specific Taylor plots illustrate the evaluation and the overall predictive skill of each experiment. The diurnal and annual cycles of near surface ozone are evaluated for both experiments. Furthermore ozone exposure indices for crop growth (AOT40), human health (SOMO35) and the number of days that 8-hour ozone averages exceeded 60ppb and 90ppb have been calculated for each station based on both observed and simulated data. Results indicate mostly improvement of the assimilated experiment with respect to the high near surface ozone concentrations, the diurnal cycle and range and the bias in comparison to the non-assimilated experiment. The limitations of the comparison between assimilated and non-assimilated experiments for near surface ozone are also discussed.

THE ASSORTMENT STRUCTURE AND THE PRICE LEVELS AS A FACTOR OF MARKETING CHANNEL COMPETITIVENESS–EMPIRICAL EVIDENCE FROM THE REPUBLIC OF SERBIA

Directory of Open Access Journals (Sweden)

Jelena Končar

2016-12-01

Full Text Available In this paper, the authors point out the differences in the structure of the product assortment of retailers who show their offers on the Web, with the aim of proving that the structure of the assortment may be a factor of marketing channel competitiveness that the consumers recognize and that makes them opt for a certain marketing channel. On the same basis we aim to compare the prices of representative product categories, in order to determine the impact of prices on marketing channel competitiveness, without taking other factors of channel competitiveness into consideration. Based on the conducted research, we can conclude that having a number of categories of products in the assortment presents a competitive advantage for the retailer in the traditional marketing channel since retailers with electronic sales have a more diverse assortment in their retail store than online. Compared to “pure play” electronic retailers, the structure of assortment measured in number of categories of products that are on offer in e-stores is not significantly different between “pure play” and “bricks and clicks” electronic retailers. On the other hand, if we look at the price levels, there is a difference in prices of product categories on websites of “brick and click” retailers since prices in retail stores are higher than prices in the traditional retail store of the same retailer. However, offers on the website of “pure play” electronic retailers are higher compared to “brick and click” retailers.

VA-Index: Quantifying Assortativity Patterns in Networks with Multidimensional Nodal Attributes (Open Access)

Science.gov (United States)

2016-01-27

through a vector each element of which captures the different types of locations he visits. Simi- larly, reviewers/buyers on electronic markets such...IEEE Internet Computing 2010; 14(2):15–23. doi: 10.1109/ MIC .2010.25 21. Zhao K, Ngamassi L, Yen J, Maitland C, Tapia A. Assortativity patterns in multi

Change in BMI accurately predicted by social exposure to acquaintances.

Science.gov (United States)

Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

2013-01-01

Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (pchange in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

Geography, assortative mating, and the effects of sexual selection on speciation with gene flow.

Science.gov (United States)

Servedio, Maria R

2016-01-01

Theoretical and empirical research on the evolution of reproductive isolation have both indicated that the effects of sexual selection on speciation with gene flow are quite complex. As part of this special issue on the contributions of women to basic and applied evolutionary biology, I discuss my work on this question in the context of a broader assessment of the patterns of sexual selection that lead to, versus inhibit, the speciation process, as derived from theoretical research. In particular, I focus on how two factors, the geographic context of speciation and the mechanism leading to assortative mating, interact to alter the effect that sexual selection through mate choice has on speciation. I concentrate on two geographic contexts: sympatry and secondary contact between two geographically separated populations that are exchanging migrants and two mechanisms of assortative mating: phenotype matching and separate preferences and traits. I show that both of these factors must be considered for the effects of sexual selection on speciation to be inferred.

MODERN ASSORTMENT, PROPERTIES AND PERSPECTIVES OF MEDICAL DRESSINGS IMPROVEMENT OF WOUND TREATMENT

Directory of Open Access Journals (Sweden)

A. V. Mayorova

2018-01-01

Full Text Available The effectiveness of reparation is now characterized not only in terms of wound healing. The aesthetic result is also of great significance. Besides, it is important to ensure the comfort of medication, in order to combine the optimal therapy and the quality of life of the patient. The aim of the study was the literature review on the effective wound treatment with the help of modern dressings, including their assortment and prospects for improvement. Materials and methods. The materials of the study were reliable literary sources containing information about wounds, pathogenesis, the stages of the wound process and its possible violations; the assortment of modern wound coverings and the composition of biologically active substances that have a pharmacological effect; the results of preclinical and clinical trials and their prospects of use in aesthetic medicine. The research was carried out using the information retrieval and library databases (eLIBRARY, Cyberleninka, technical information. The research methods used in the work are: informational, analytical, descriptive. Results and discussion. As a result of generalization and analysis of modern publications devoted to the effective wound treatment, modern views on the wound process, wound coverings, their assortment and compositions are described. The results of pharmacological tests as well as the properties of biologically active substances and carrier polymers used are also presented. It is noted that the prospective compounds for including with the wound coverings and external drugs affecting the repair process at different stages of the wound process are tizol, bischofite, peptides (1-β-interleukin, ectoin. Conclusion. Thus, it has been established that modern wound dressings and dressings containing the substances of different pharmacological groups are offered for effective therapy: antiseptics, anesthetics, repair stimulators, antioxidants that affect different stages and elements

Fund Assortments and 401(k) Plan Participation: The Moderating Effect of Gender

OpenAIRE

Maureen Morrin; Susan Broniarczyk; J. Jeffrey Inman

2009-01-01

We report the results of a decision simulation conducted among 349 adults whose task was to invest in a hypothetical 401(k) retirement plan. We varied the number of mutual funds offered for investment and observed the effects on the incidence and extent of participation. The results indicate that larger fund assortments tend to reduce participation among women, but increase it among men. Implications and suggestions for future research are discussed.

Empowering Geoscience with Improved Data Assimilation Using the Data Assimilation Research Testbed "Manhattan" Release.

Science.gov (United States)

Raeder, K.; Hoar, T. J.; Anderson, J. L.; Collins, N.; Hendricks, J.; Kershaw, H.; Ha, S.; Snyder, C.; Skamarock, W. C.; Mizzi, A. P.; Liu, H.; Liu, J.; Pedatella, N. M.; Karspeck, A. R.; Karol, S. I.; Bitz, C. M.; Zhang, Y.

2017-12-01

The capabilities of the Data Assimilation Research Testbed (DART) at NCAR have been significantly expanded with the recent "Manhattan" release. DART is an ensemble Kalman filter based suite of tools, which enables researchers to use data assimilation (DA) without first becoming DA experts. Highlights: significant improvement in efficient ensemble DA for very large models on thousands of processors, direct read and write of model state files in parallel, more control of the DA output for finer-grained analysis, new model interfaces which are useful to a variety of geophysical researchers, new observation forward operators and the ability to use precomputed forward operators from the forecast model. The new model interfaces and example applications include the following: MPAS-A; Model for Prediction Across Scales - Atmosphere is a global, nonhydrostatic, variable-resolution mesh atmospheric model, which facilitates multi-scale analysis and forecasting. The absence of distinct subdomains eliminates problems associated with subdomain boundaries. It demonstrates the ability to consistently produce higher-quality analyses than coarse, uniform meshes do. WRF-Chem; Weather Research and Forecasting + (MOZART) Chemistry model assimilates observations from FRAPPÉ (Front Range Air Pollution and Photochemistry Experiment). WACCM-X; Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension assimilates observations of electron density to investigate sudden stratospheric warming. CESM (weakly) coupled assimilation; NCAR's Community Earth System Model is used for assimilation of atmospheric and oceanic observations into their respective components using coupled atmosphere+land+ocean+sea+ice forecasts. CESM2.0; Assimilation in the atmospheric component (CAM, WACCM) of the newly released version is supported. This version contains new and extensively updated components and software environment. CICE; Los Alamos sea ice model (in CESM) is used to assimilate

CATEGORY MANAGEMENT IN THE MANAGEMENT OF MINIMUM ASSORTMENT OF THE PHARMACEUTICAL ORGANIZATION

OpenAIRE

I. F. Samoshchenkova; R. Y. Garankina

2017-01-01

The main principle of the category management is the management of product category as a separate business unit. Category management directs the activities of the pharmaceutical organization to meet the consumer requirements and to provide customers with maximum benefits, which are expressed in the improved assortment,the attractive prices, the reduction of cases of lack of necessary goods, the simplifiedpurchase process. In article the structure of the category management and its role inthe ...

A survey on acquaintance, orientation and behavior of general medical practitioners toward periodontal diseases

Directory of Open Access Journals (Sweden)

Supreet Kaur

2015-01-01

Full Text Available Background: An association between oral conditions such as periodontal diseases and systemic conditions is noted. As such, periodontal disease is associated with an increased risk of systemic illnesses such as cardiovascular disease, diabetes, adverse pregnancy outcome, atherosclerosis, stroke and hospital acquired pneumonia. The concept of diagnosing and treating a potential patient to minimize the deleterious effects of this chronic infectious and inflammatory condition on systemic conditions represents both an unprecedented challenge and opportunity to our profession. Keeping this in view, the present survey was designed to evaluate the acquaintance, orientation and behavior of general medical practitioners; concerning the effects of periodontal disease on systemic health. Materials and Methods: A typed questionnaire carrying four sets of questions was distributed among general medical practitioners of seven different government and private medical colleges and hospitals. Questionnaire was developed to assess the acquaintance, orientation and behavior of general medical practitioners toward periodontal disease. Results: Most of the respondents have knowledge regarding the signs and symptoms of periodontal disease and its association with cardiovascular disease. However, majority of them do not know about the potential effect of periodontal disease on other organ systems. Conclusion: General medical practitioners have inadequate knowledge regarding periodontal diseases. Hence, oral health related training should be an integral part of the medical curriculum.

A survey on acquaintance, orientation and behavior of general medical practitioners toward periodontal diseases.

Science.gov (United States)

Kaur, Supreet; Khurana, Pankaj; Kaur, Harjit

2015-01-01

An association between oral conditions such as periodontal diseases and systemic conditions is noted. As such, periodontal disease is associated with an increased risk of systemic illnesses such as cardiovascular disease, diabetes, adverse pregnancy outcome, atherosclerosis, stroke and hospital acquired pneumonia. The concept of diagnosing and treating a potential patient to minimize the deleterious effects of this chronic infectious and inflammatory condition on systemic conditions represents both an unprecedented challenge and opportunity to our profession. Keeping this in view, the present survey was designed to evaluate the acquaintance, orientation and behavior of general medical practitioners; concerning the effects of periodontal disease on systemic health. A typed questionnaire carrying four sets of questions was distributed among general medical practitioners of seven different government and private medical colleges and hospitals. Questionnaire was developed to assess the acquaintance, orientation and behavior of general medical practitioners toward periodontal disease. Most of the respondents have knowledge regarding the signs and symptoms of periodontal disease and its association with cardiovascular disease. However, majority of them do not know about the potential effect of periodontal disease on other organ systems. General medical practitioners have inadequate knowledge regarding periodontal diseases. Hence, oral health related training should be an integral part of the medical curriculum.

Land Surface Data Assimilation

Science.gov (United States)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land

Fixed vs. random proportions demand models for the assortment planning problem under stockout-based substitution

NARCIS (Netherlands)

Honhon, D.B.L.P.; Seshardi, S.

2013-01-01

We consider the problem of determining the optimal assortment of products to offer in a given product category when each customer is characterized by a type, which is a list of products he is willing to buy in decreasing order of preference. We assume consumer-driven, dynamic, stockout-based

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

Science.gov (United States)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

Change in BMI accurately predicted by social exposure to acquaintances.

Directory of Open Access Journals (Sweden)

Rahman O Oloritun

Full Text Available Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC and R(2. This study found a model that explains 68% (p<0.0001 of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as

Effective Assimilation of Global Precipitation

Science.gov (United States)

Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

2012-12-01

Assimilating precipitation observations by modifying the moisture and sometimes temperature profiles has been shown successful in forcing the model precipitation to be close to the observed precipitation, but only while the assimilation is taking place. After the forecast start, the model tends to "forget" the assimilation changes and lose their extra skill after few forecast hours. This suggests that this approach is not an efficient way to modify the potential vorticity field, since this is the variable that the model would remember. In this study, the ensemble Kalman filter (EnKF) method is used to effectively change the potential vorticity field by allowing ensemble members with better precipitation to receive higher weights. In addition to using an EnKF, two other changes in the precipitation assimilation process are proposed to solve the problems related to the highly non-Gaussian nature of the precipitation variable: a) transform precipitation into a Gaussian distribution based on its climatological distribution, and b) only assimilate precipitation at the location where some ensemble members have positive precipitation. The idea is first tested by the observing system simulation experiments (OSSEs) using SPEEDY, a simplified but realistic general circulation model. When the global precipitation is assimilated in addition to conventional rawinsonde observations, both the analyses and the medium range forecasts are significantly improved as compared to only having rawinsonde observations. The improvement is much reduced when only modifying the moisture field with the same approach, which shows the importance of the error covariance between precipitation and all other model variables. The effect of precipitation assimilation is larger in the Southern Hemisphere than that in the Northern Hemisphere because the Northern Hemisphere analyses are already accurate as a result of denser rawinsonde stations. Assimilation of precipitation using a more comprehensive

Data Assimilation for Applied Meteorology

Science.gov (United States)

Haupt, S. E.

2012-12-01

Although atmospheric models provide a best estimate of the future state of the atmosphere, due to sensitivity to initial condition, it is difficult to predict the precise future state. For applied problems, however, users often depend on having accurate knowledge of that future state. To improve prediction of a particular realization of an evolving flow field requires knowledge of the current state of that field and assimilation of local observations into the model. This talk will consider how dynamic assimilation can help address the concerns of users of atmospheric forecasts. First, we will look at the value of assimilation for the renewable energy industry. If the industry decision makers can have confidence in the wind and solar power forecasts, they can build their power allocations around the expected renewable resource, saving money for the ratepayers as well as reducing carbon emissions. We will assess the value to that industry of assimilating local real-time observations into the model forecasts and the value that is provided. The value of the forecasts with assimilation is important on both short (several hour) to medium range (within two days). A second application will be atmospheric transport and dispersion problems. In particular, we will look at assimilation of concentration data into a prediction model. An interesting aspect of this problem is that the dynamics are a one-way coupled system, with the fluid dynamic equations affecting the concentration equation, but not vice versa. So when the observations are of the concentration, one must infer the fluid dynamics. This one-way coupled system presents a challenge: one must first infer the changes in the flow field from observations of the contaminant, then assimilate that to recover both the advecting flow and information on the subgrid processes that provide the mixing. To accomplish such assimilation requires a robust method to match the observed contaminant field to that modeled. One approach is

Towards a Comprehensive Dynamic-chemistry Assimilation for Eos-Chem: Plans and Status in NASA's Data Assimilation Office

Science.gov (United States)

Pawson, Steven; Lin, Shian-Jiann; Rood, Richard B.; Stajner, Ivanka; Nebuda, Sharon; Nielsen, J. Eric; Douglass, Anne R.

2000-01-01

In order to support the EOS-Chem project, a comprehensive assimilation package for the coupled chemical-dynamical system is being developed by the Data Assimilation Office at NASA GSFC. This involves development of a coupled chemistry/meteorology model and of data assimilation techniques for trace species and meteorology. The model is being developed using the flux-form semi-Lagrangian dynamical core of Lin and Rood, the physical parameterizations from the NCAR Community Climate Model, and atmospheric chemistry modules from the Atmospheric Chemistry and Dynamics branch at NASA GSFC. To date the following results have been obtained: (i) multi-annual simulations with the dynamics-radiation model show the credibility of the package for atmospheric simulations; (ii) initial simulations including a limited number of middle atmospheric trace gases reveal the realistic nature of transport mechanisms, although there is still a need for some improvements. Samples of these results will be shown. A meteorological assimilation system is currently being constructed using the model; this will form the basis for the proposed meteorological/chemical assimilation package. The latter part of the presentation will focus on areas targeted for development in the near and far terms, with the objective of Providing a comprehensive assimilation package for the EOS-Chem science experiment. The first stage will target ozone assimilation. The plans also encompass a reanalysis (ReSTS) for the 1991-1995 period, which includes the Mt. Pinatubo eruption and the time when a large number of UARS observations were available. One of the most challenging aspects of future developments will be to couple theoretical advances in tracer assimilation with the practical considerations of a real environment and eventually a near-real-time assimilation system.

Methodological Developments in Geophysical Assimilation Modeling

Science.gov (United States)

Christakos, George

2005-06-01

This work presents recent methodological developments in geophysical assimilation research. We revisit the meaning of the term "solution" of a mathematical model representing a geophysical system, and we examine its operational formulations. We argue that an assimilation solution based on epistemic cognition (which assumes that the model describes incomplete knowledge about nature and focuses on conceptual mechanisms of scientific thinking) could lead to more realistic representations of the geophysical situation than a conventional ontologic assimilation solution (which assumes that the model describes nature as is and focuses on form manipulations). Conceptually, the two approaches are fundamentally different. Unlike the reasoning structure of conventional assimilation modeling that is based mainly on ad hoc technical schemes, the epistemic cognition approach is based on teleologic criteria and stochastic adaptation principles. In this way some key ideas are introduced that could open new areas of geophysical assimilation to detailed understanding in an integrated manner. A knowledge synthesis framework can provide the rational means for assimilating a variety of knowledge bases (general and site specific) that are relevant to the geophysical system of interest. Epistemic cognition-based assimilation techniques can produce a realistic representation of the geophysical system, provide a rigorous assessment of the uncertainty sources, and generate informative predictions across space-time. The mathematics of epistemic assimilation involves a powerful and versatile spatiotemporal random field theory that imposes no restriction on the shape of the probability distributions or the form of the predictors (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated) and accounts rigorously for the uncertainty features of the geophysical system. In the epistemic cognition context the assimilation concept may be used to

Coupled assimilation for an intermediated coupled ENSO prediction model

Science.gov (United States)

Zheng, Fei; Zhu, Jiang

2010-10-01

The value of coupled assimilation is discussed using an intermediate coupled model in which the wind stress is the only atmospheric state which is slavery to model sea surface temperature (SST). In the coupled assimilation analysis, based on the coupled wind-ocean state covariance calculated from the coupled state ensemble, the ocean state is adjusted by assimilating wind data using the ensemble Kalman filter. As revealed by a series of assimilation experiments using simulated observations, the coupled assimilation of wind observations yields better results than the assimilation of SST observations. Specifically, the coupled assimilation of wind observations can help to improve the accuracy of the surface and subsurface currents because the correlation between the wind and ocean currents is stronger than that between SST and ocean currents in the equatorial Pacific. Thus, the coupled assimilation of wind data can decrease the initial condition errors in the surface/subsurface currents that can significantly contribute to SST forecast errors. The value of the coupled assimilation of wind observations is further demonstrated by comparing the prediction skills of three 12-year (1997-2008) hindcast experiments initialized by the ocean-only assimilation scheme that assimilates SST observations, the coupled assimilation scheme that assimilates wind observations, and a nudging scheme that nudges the observed wind stress data, respectively. The prediction skills of two assimilation schemes are significantly better than those of the nudging scheme. The prediction skills of assimilating wind observations are better than assimilating SST observations. Assimilating wind observations for the 2007/2008 La Niña event triggers better predictions, while assimilating SST observations fails to provide an early warning for that event.

"Well Acquainted with Books." The Founding Framers of 1787. With James Madison's List of Books for Congress.

Science.gov (United States)

Rutland, Robert A.

Published to commemorate the Constitution's bicentennial year and remind Americans that books and the life of the mind are vital national traditions, this volume contains both an essay, "Well Acquainted with Books: The Founding Framers of 1787," by Robert A. Rutland, and James Madison's List of Books for Congress, 1783. The essay…

Data assimilation in hydrological modelling

DEFF Research Database (Denmark)

Drecourt, Jean-Philippe

Data assimilation is an invaluable tool in hydrological modelling as it allows to efficiently combine scarce data with a numerical model to obtain improved model predictions. In addition, data assimilation also provides an uncertainty analysis of the predictions made by the hydrological model....... In this thesis, the Kalman filter is used for data assimilation with a focus on groundwater modelling. However the developed techniques are general and can be applied also in other modelling domains. Modelling involves conceptualization of the processes of Nature. Data assimilation provides a way to deal...... with model non-linearities and biased errors. A literature review analyzes the most popular techniques and their application in hydrological modelling. Since bias is an important problem in groundwater modelling, two bias aware Kalman filters have been implemented and compared using an artificial test case...

Data Assimilation in Integrated and Distributed Hydrological Models

DEFF Research Database (Denmark)

Zhang, Donghua

processes and provide simulations in refined temporal and spatial resolutions. Recent developments in measurement and sensor technologies have significantly improved the coverage, quality, frequency and diversity of hydrological observations. Data assimilation provides a great potential in relation...... point of view, different assimilation methodologies and techniques have been developed or customized to better serve hydrological assimilation. From the application point of view, real data and real-world complex catchments are used with the focus of investigating the models’ improvements with data...... a variety of model uncertainty sources and scales. Next the groundwater head assimilation experiment was tested in a much more complex catchment with assimilation of biased real observations. In such cases, the bias-aware assimilation method significantly outperforms the standard assimilation method...

Data Assimilation in Marine Models

DEFF Research Database (Denmark)

Frydendall, Jan

maximum likelihood framework. These issues are discussed in paper B. The third part of the thesis falls a bit out of the above context is work published in papers C, F. In the first paper, a simple data assimilation scheme was investigated to examine the potential benefits of incorporating a data......This thesis consists of six research papers published or submitted for publication in the period 2006-2009 together with a summary report. The main topics of this thesis are nonlinear data assimilation techniques and estimation in dynamical models. The focus has been on the nonlinear filtering...... techniques for large scale geophysical numerical models and making them feasible to work with in the data assimilation framework. The filtering techniques investigated are all Monte Carlo simulation based. Some very nice features that can be exploited in the Monte Carlo based data assimilation framework from...

Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

Science.gov (United States)

Kumar, Sujay V.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.; Rodell, Matthew; Reichle, Rolf; Li, Bailing; Jasinski, Michael; Mocko, David; Getirana, Augusto; De Lannoy, Gabrielle;

Physical education teachers' attitudes towards children with intellectual disability: the impact of time in service, gender, and previous acquaintance.

Science.gov (United States)

Ozer, D; Nalbant, S; Aǧlamıș, E; Baran, F; Kaya Samut, P; Aktop, A; Hutzler, Y

2013-11-01

This study investigated attitudes towards teaching students with intellectual disability (ID) within a representative sample of secondary school physical education (PE) teachers, and to determine the effects of age, gender, teaching experience, and having acquaintance with ID and students with ID on their attitudes. Participants were 729 secondary school PE teachers who worked in 81 major cities of Turkey. The Teachers Attitudes towards Children with Intellectual Disability Scale was administered. The statistical analysis revealed that there was no significant effect on factors and total attitudes scores of gender and having students with ID. Significant effects on factors and total attitudes score were found in teaching experiences and having acquaintance with ID. It is encouraged to maintain and further develop in-service education programmes of adapted physical activity for PE teachers. © 2012 The Authors. Journal of Intellectual Disability Research © John Wiley & Sons Ltd, MENCAP & IASSID.

Instant RubyMine assimilation

CERN Document Server

Jones, Dave

2013-01-01

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Get the job done and learn as you go. A practical guide comprising of easy-to-follow recipes which provide concise and clear steps to help you enter the world of RubyMine.Instant RubyMine is ideal for you, if you are new to RubyMine or well acquainted with the technology. All you need is basic knowledge of writing in Ruby or Ruby on Rails.

Skill Assessment in Ocean Biological Data Assimilation

Science.gov (United States)

Gregg, Watson W.; Friedrichs, Marjorie A. M.; Robinson, Allan R.; Rose, Kenneth A.; Schlitzer, Reiner; Thompson, Keith R.; Doney, Scott C.

2008-01-01

There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

Performance of alum and assorted coagulants in turbidity removal of muddy water

Science.gov (United States)

Malik, Qasim H.

2018-03-01

Coagulation is a primary and cost effective process in water treatment plants. Under optimum conditions, not only it effectively removes turbidity but also results in reduced sludge volume and subsequently minimizes sludge management costs. Highly turbid water from streams, canals, rivers and rain run offs was run through jar test for turbidity removal. The brown water with 250NTU turbidity when coagulated with alum and assorted coagulants proved that maximum turbidity removal was witnessed using alum dose of 0.25 g/l at ph 6 with a sedimentation time of 30 min.

Narcissism Guides Mate Selection: Humans Mate Assortatively, as Revealed by Facial Resemblance, following an Algorithm of “Self Seeking Like”

Directory of Open Access Journals (Sweden)

Liliana Alvarez

2004-01-01

Full Text Available Theoretical studies suggest that mating and pair formation is not likely to be random. Computer simulations suggested that sex among genetically complex organisms requires mate choice strategies for its evolutionary maintenance, to reduce excessive genetic variance produced by out-crossing. One strategy achieving this aim efficiently in computer simulations is assortative mating modeled as “self seeking like”. Another one is selection of “good genes”. Assortative mating increases the probability of finding a genetically similar mate, without fomenting inbreeding, achieving assortative mating without hindering the working of other mate selection strategies which aim to maximize the search for “good genes”, optimizing the working of sex in evolutionary terms. Here we present indirect evidence that in a significant proportion of human reproductive couples, the partners show much higher facial resemblances than can be expected by random pair formation, or as the outcome of “matching for attractiveness” or the outcome of competition for the most attractive partner accessible, as had been previously assumed. The data presented is compatible with the hypothesis derived from computer simulations, that human mate selection strategies achieve various aims: “self seeking like” (including matching for attractiveness and mating with the best available genes.

Assortive mating for personaltiy traits, educational level, religious affiliation, height, weight, adn body mass index in parents of Korean twin sample.

Science.gov (United States)

Hur, Yoon-Mi

2003-12-01

The degree of assortative mating for psychological and physical traits in Asian societies in relatively unknown. The present study examined assortative mating for educational level, personality traits, religious affiliation, height, weight, and body mass index in a korean sample. Age-adjusted spouse correlations were high for educational level (r = .63) and religious affiliation (r = .67), modest for most personality traits (rs = -.01 to .26), and trivial for height (r = .04), weight (r = .05)m and body mass index (r = .11). These results were remarkably similar to those found from the western samples. Implications of the present findings in behavior genetic studies and human mating patterns were briefly discussed.

Reflective acquaintance with other minds and the double-sided disclosure of the lived-body

DEFF Research Database (Denmark)

Farley, Adam

2014-01-01

This paper will consider the phenomenological disclosure of the reflecting-body vis-à-vis subject’s reflective acquaintance with other minds. To this end, phenomenological accounts regarding the double-sided disclosure of the lived-body will be expounded and developed. It will be argued...... be admitted across these modes. To this end, observations regarding the lived disclosure of reflective acts vis-à-vis their embodied conduct are provided; suggesting that a partial inversion of the lived-body’s double-sidedness occurs during the transition to the reflective mode. Directions for future...

ERP ASSIMILATION: AN END-USER APPROACH

Directory of Open Access Journals (Sweden)

Hurbean Luminita

2013-07-01

The paper discusses the ERP adoption based on the IT assimilation theory. The ERP lifecycle is associated with the IT assimilation steps. We propose a distribution of these steps along the lifecycle. Derived from the findings in the reviewed literature we will focus the cultural factors, in particular those related to the end-users (determined as a major impact factor in our previous study: Negovan et al., 2011. Our empirical study is centred on the end-users perspective and it tries to determine if and how their behaviour affects the achievement of the ERP assimilation steps. The paper reasons that organizations that understand the IT assimilation steps correlated to the ERP implementation critical factors are more likely to implement and use ERP successfully.

Effective assimilation of global precipitation: simulation experiments

Directory of Open Access Journals (Sweden)

Guo-Yuan Lien

2013-07-01

Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and

Saber y conocer: Un plan para su ensenaza (To know and to be acquainted with: A teaching plan).

Science.gov (United States)

Lizardi-Rivera, Carmen M.

1995-01-01

Focuses on how to teach English-speaking students of Spanish the practical distinction between the verbs, "saber" (to be cognizant of) and "conocer" (to be acquainted with). This article describes a solution proposed by K. Taylor for explaining the limits of the two verbs and examines similar proposals delineated in three other Spanish textbooks.…

Interdisciplinary Matchmaking: Choosing Collaborators by Skill, Acquaintance and Trust

Science.gov (United States)

Hupa, Albert; Rzadca, Krzysztof; Wierzbicki, Adam; Datta, Anwitaman

Social networks are commonly used to enhance recommender systems. Most of such systems recommend a single resource or a person. However, complex problems or projects usually require a team of experts that must work together on a solution. Team recommendation is much more challenging, mostly because of the complex interpersonal relations between members. This chapter presents fundamental concepts on how to score a team based on members' social context and their suitability for a particular project. We represent the social context of an individual as a three-dimensional social network (3DSN) composed of a knowledge dimension expressing skills, a trust dimension and an acquaintance dimension. Dimensions of a 3DSN are used to mathematically formalize the criteria for prediction of the team's performance. We use these criteria to formulate the team recommendation problem as a multi-criteria optimization problem. We demonstrate our approach on empirical data crawled from two web2.0 sites: onephoto.net and a social networking site. We construct 3DSNs and analyze properties of team's performance criteria.

Performance Comparison of Assorted Color Spaces for Multilevel Block Truncation Coding based Face Recognition

OpenAIRE

H.B. Kekre; Sudeep Thepade; Karan Dhamejani; Sanchit Khandelwal; Adnan Azmi

2012-01-01

The paper presents a performance analysis of Multilevel Block Truncation Coding based Face Recognition among widely used color spaces. In [1], Multilevel Block Truncation Coding was applied on the RGB color space up to four levels for face recognition. Better results were obtained when the proposed technique was implemented using Kekre’s LUV (K’LUV) color space [25]. This was the motivation to test the proposed technique using assorted color spaces. For experimental analysis, two face databas...

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System. Part 2; Assimilation Results

Science.gov (United States)

Capotondi, Antonietta; Holland, William R.; Malanotte-Rizzoli, Paola

1995-01-01

The improvement in the climatological behavior of a numerical model as a consequence of the assimilation of surface data is investigated. The model used for this study is a quasigeostrophic (QG) model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height that have been obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. Comparisons of the assimilation results with available in situ observations show a significant improvement in the degree of realism of the climatological model behavior, with respect to the model in which no data are assimilated. The remaining discrepancies in the model mean circulation seem to be mainly associated with deficiencies in the mean component of the surface data that are assimilated. On the other hand, the possibility of building into the model more realistic eddy characteristics through the assimilation of the surface eddy field proves very successful in driving components of the mean model circulation that are in relatively good agreement with the available observations. Comparisons with current meter time series during a time period partially overlapping the Geosat mission show that the model is able to 'correctly' extrapolate the instantaneous surface eddy signals to depths of approximately 1500 m. The correlation coefficient between current meter and model time series varies from values close to 0.7 in the top 1500 m to values as low as 0.1-0.2 in the deep ocean.

A simple lightning assimilation technique for improving ...

Science.gov (United States)

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

Spatial dependence of color assimilation by the watercolor effect.

Science.gov (United States)

Devinck, Frédéric; Delahunt, Peter B; Hardy, Joseph L; Spillmann, Lothar; Werner, John S

2006-01-01

Color assimilation with bichromatic contours was quantified for spatial extents ranging from von Bezold-type color assimilation to the watercolor effect. The magnitude and direction of assimilative hue change was measured as a function of the width of a rectangular stimulus. Assimilation was quantified by hue cancellation. Large hue shifts were required to null the color of stimuli < or = 9.3 min of arc in width, with an exponential decrease for stimuli increasing up to 7.4 deg. When stimuli were viewed through an achromatizing lens, the magnitude of the assimilation effect was reduced for narrow stimuli, but not for wide ones. These results demonstrate that chromatic aberration may account, in part, for color assimilation over small, but not large, surface areas.

Coupled atmosphere and land-surface assimilation of surface observations with a single column model and ensemble data assimilation

Science.gov (United States)

Rostkier-Edelstein, Dorita; Hacker, Joshua P.; Snyder, Chris

2014-05-01

Numerical weather prediction and data assimilation models are composed of coupled atmosphere and land-surface (LS) components. If possible, the assimilation procedure should be coupled so that observed information in one module is used to correct fields in the coupled module. There have been some attempts in this direction using optimal interpolation, nudging and 2/3DVAR data assimilation techniques. Aside from satellite remote sensed observations, reference height in-situ observations of temperature and moisture have been used in these studies. Among other problems, difficulties in coupled atmosphere and LS assimilation arise as a result of the different time scales characteristic of each component and the unsteady correlation between these components under varying flow conditions. Ensemble data-assimilation techniques rely on flow dependent observations-model covariances. Provided that correlations and covariances between land and atmosphere can be adequately simulated and sampled, ensemble data assimilation should enable appropriate assimilation of observations simultaneously into the atmospheric and LS states. Our aim is to explore assimilation of reference height in-situ temperature and moisture observations into the coupled atmosphere-LS modules(simultaneously) in NCAR's WRF-ARW model using the NCAR's DART ensemble data-assimilation system. Observing system simulation experiments (OSSEs) are performed using the single column model (SCM) version of WRF. Numerical experiments during a warm season are centered on an atmospheric and soil column in the South Great Plains. Synthetic observations are derived from "truth" WRF-SCM runs for a given date,initialized and forced using North American Regional Reanalyses (NARR). WRF-SCM atmospheric and LS ensembles are created by mixing the atmospheric and soil NARR profile centered on a given date with that from another day (randomly chosen from the same season) with weights drawn from a logit-normal distribution. Three

Organizing Products with Complements versus Substitutes: Effects on Store Preferences as a Function of Effort and Assortment Perceptions

NARCIS (Netherlands)

Diehl, K.; Herpen, van E.; Lamberton, C.

2015-01-01

Retailers often organize at least part of their assortment by displaying complementary products from different product categories together (e.g., a pair of pants with a shirt) rather than grouping items by product type (e.g., a pair of pants with other pants). However, little is known about how

Data assimilation of CALIPSO aerosol observations

Directory of Open Access Journals (Sweden)

T. T. Sekiyama

2010-01-01

Full Text Available We have developed an advanced data assimilation system for a global aerosol model with a four-dimensional ensemble Kalman filter in which the Level 1B data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO were successfully assimilated for the first time, to the best of the authors' knowledge. A one-month data assimilation cycle experiment for dust, sulfate, and sea-salt aerosols was performed in May 2007. The results were validated via two independent observations: 1 the ground-based lidar network in East Asia, managed by the National Institute for Environmental Studies of Japan, and 2 weather reports of aeolian dust events in Japan. Detailed four-dimensional structures of aerosol outflows from source regions over oceans and continents for various particle types and sizes were well reproduced. The intensity of dust emission at each grid point was also corrected by this data assimilation system. These results are valuable for the comprehensive analysis of aerosol behavior as well as aerosol forecasting.

Brief report: the association between non-suicidal self-injury, self-concept and acquaintance with self-injurious peers in a sample of adolescents.

Science.gov (United States)

Claes, Laurence; Houben, Adinda; Vandereycken, Walter; Bijttebier, Patricia; Muehlenkamp, Jennifer

2010-10-01

The current study investigated the association between non-suicidal self-injury (NSSI), self-concept and acquaintance with NSSI peers in a sample of 150 high school students (60% female) with a mean age of 15.56 (SD=2.00) years. Analyses showed that students with NSSI rated themselves lower on academic intelligence, physical attractiveness, social skills and emotional stability than their non-NSSI peers. The self-injurers also had more friends who engaged in NSSI, and having more NSSI acquaintances was negatively related to self-esteem. It could be that adolescents with lower self-esteem are more attracted to self-injuring peers, or that adolescents with low self-esteem are more vulnerable to copy NSSI to deal with their problems or to gain a certain identity in their peer group. Future studies must test these possible NSSI pathways.

How youth-serving organizations enable acquaintance molesters.

Science.gov (United States)

Boyle, Patrick

2014-10-01

In recent years, some of the country's most prominent institutions have been ensnared in child sex abuse scandals. While each abuse incident features its own particular circumstances, institutions that have been the subject of these scandals have displayed similar patterns of organizational behavior that allowed molesting to occur and molesters to escape accountability. We can learn from those patterns to better understand and combat acquaintance molestation in youth-serving organizations. Although sex abuse is an inherent risk in youth work, American youth-serving organizations have responded to this risk largely on a case-by-case basis after abuse incidents have been revealed, rather than through proactive strategies to reduce the risk of abuse and to respond effectively to allegations. An examination of abuse scandals reveals common patterns of behavior among paid and volunteer staff in organizations that did not enact comprehensive, proactive strategies: Faith in the organiation blinded staff to the liklihood of abuse; organizations kept workers ignorant about the extent of the abuse problem; when abuse accusations arose, staff gave the benefit of the doubt to the adult; when abuse accusations were confirmed, staffers did not know how to respond; and not knowing how to resopnd, staff prioritized the protection of the organization. As a result, child molesters have been falsely exonerated or not held accountable, abused children have been disbelieved, and abuse has continued. These organizations inadvertently achieved the opposite of their missions: They enabled child molesters at the expense of children. © The Author(s) 2014.

Modeling acquaintance networks based on balance theory

Directory of Open Access Journals (Sweden)

Vukašinović Vida

2014-09-01

Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

Multi-parametric variational data assimilation for hydrological forecasting

Science.gov (United States)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

First assimilations of COSMIC radio occultation data into the Electron Density Assimilative Model (EDAM

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M. J. Angling

2008-02-01

Full Text Available Ground based measurements of slant total electron content (TEC can be assimilated into ionospheric models to produce 3-D representations of ionospheric electron density. The Electron Density Assimilative Model (EDAM has been developed for this purpose. Previous tests using EDAM and ground based data have demonstrated that the information on the vertical structure of the ionosphere is limited in this type of data. The launch of the COSMIC satellite constellation provides the opportunity to use radio occultation data which has more vertical information. EDAM assimilations have been run for three time periods representing quiet, moderate and disturbed geomagnetic conditions. For each run, three data sets have been ingested – only ground based data, only COSMIC data and both ground based and COSMIC data. The results from this preliminary study show that both ground and space based data are capable of improving the representation of the vertical structure of the ionosphere. However, the analysis is limited by the incomplete deployment of the COSMIC constellation and the use of auto-scaled ionosonde data. The first of these can be addressed by repeating this type of study once full deployment has been achieved. The latter requires the manual scaling of ionosonde data; ideally an agreed data set would be scaled and made available to the community to facilitate comparative testing of assimilative models.

Chromatic assimilation unaffected by perceived depth of inducing light.

Science.gov (United States)

Shevell, Steven K; Cao, Dingcai

2004-01-01

Chromatic assimilation is a shift toward the color of nearby light. Several studies conclude that a neural process contributes to assimilation but the neural locus remains in question. Some studies posit a peripheral process, such as retinal receptive-field organization, while others claim the neural mechanism follows depth perception, figure/ground segregation, or perceptual grouping. The experiments here tested whether assimilation depends on a neural process that follows stereoscopic depth perception. By introducing binocular disparity, the test field judged in color was made to appear in a different depth plane than the light that induced assimilation. The chromaticity and spatial frequency of the inducing light, and the chromaticity of the test light, were varied. Chromatic assimilation was found with all inducing-light sizes and chromaticities, but the magnitude of assimilation did not depend on the perceived relative depth planes of the test and inducing fields. We found no evidence to support the view that chromatic assimilation depends on a neural process that follows binocular combination of the two eyes' signals.

Development of a data assimilation algorithm

DEFF Research Database (Denmark)

Thomsen, Per Grove; Zlatev, Zahari

2008-01-01

It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize efficien......It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize...... assimilation technique is applied. Therefore, it is important to study the interplay between the three components of the variational data assimilation techniques as well as to apply powerful parallel computers in the computations. Some results obtained in the search for a good combination of numerical methods...... computers, Mathematics and Computers in Simulation, 65 (2004) 557–577, Z. Zlatev, Computer Treatment of Large Air Pollution Models, Kluwer Academic Publishers, Dordrecht, Boston, London, 1995]. The ideas are rather general and can easily be applied in connection with other mathematical models....

Development of airborne remote sensing data assimilation system

International Nuclear Information System (INIS)

Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

2014-01-01

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

Temporal Reference, Attentional Modulation, and Crossmodal Assimilation

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Yingqi Wan

2018-06-01

Full Text Available Crossmodal assimilation effect refers to the prominent phenomenon by which ensemble mean extracted from a sequence of task-irrelevant distractor events, such as auditory intervals, assimilates/biases the perception (such as visual interval of the subsequent task-relevant target events in another sensory modality. In current experiments, using visual Ternus display, we examined the roles of temporal reference, materialized as the time information accumulated before the onset of target event, as well as the attentional modulation in crossmodal temporal interaction. Specifically, we examined how the global time interval, the mean auditory inter-intervals and the last interval in the auditory sequence assimilate and bias the subsequent percept of visual Ternus motion (element motion vs. group motion. We demonstrated that both the ensemble (geometric mean and the last interval in the auditory sequence contribute to bias the percept of visual motion. Longer mean (or last interval elicited more reports of group motion, whereas the shorter mean (or last auditory intervals gave rise to more dominant percept of element motion. Importantly, observers have shown dynamic adaptation to the temporal reference of crossmodal assimilation: when the target visual Ternus stimuli were separated by a long gap interval after the preceding sound sequence, the assimilation effect by ensemble mean was reduced. Our findings suggested that crossmodal assimilation relies on a suitable temporal reference on adaptation level, and revealed a general temporal perceptual grouping principle underlying complex audio-visual interactions in everyday dynamic situations.

Data Assimilation: Making Sense of Earth Observation

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William Albert Lahoz

2014-05-01

Full Text Available Climate change, air quality and environmental degradation are important societal challenges for the 21st Century. These challenges require an intelligent response from society, which in turn requires access to information about the Earth System. This information comes from observations and prior knowledge, the latter typically embodied in a model describing relationships between variables of the Earth System. Data assimilation provides an objective methodology to combine observational and model information to provide an estimate of the most likely state and its uncertainty for the whole Earth System. This approach adds value to the observations – by filling in the spatio-temporal gaps in observations; and to the model – by constraining it with the observations. In this review paper we motivate data assimilation as a methodology to fill in the gaps in observational information; illustrate the data assimilation approach with examples that span a broad range of features of the Earth System (atmosphere, including chemistry; ocean; land surface; and discuss the outlook for data assimilation, including the novel application of data assimilation ideas to observational information obtained using Citizen Science. Ultimately, a strong motivation of data assimilation is the many benefits it provides to users. These include: providing the initial state for weather and air quality forecasts; providing analyses and reanalyses for studying the Earth System; evaluating observations, instruments and models; assessing the relative value of elements of the Global Observing System (GOS; and assessing the added value of future additions to the GOS.

The Impact of the Assimilation of Aquarius Sea Surface Salinity Data in the GEOS Ocean Data Assimilation System

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Vernieres, Guillaume Rene Jean; Kovach, Robin M.; Keppenne, Christian L.; Akella, Santharam; Brucker, Ludovic; Dinnat, Emmanuel Phillippe

2014-01-01

Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations

AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system

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Chun Yang

2016-06-01

Full Text Available A method to assimilate all-sky radiances from the Advanced Microwave Scanning Radiometer 2 (AMSR2 was developed within the Weather Research and Forecasting (WRF model's data assimilation (WRFDA system. The four essential elements are: (1 extending the community radiative transform model's (CRTM interface to include hydrometeor profiles; (2 using total water Qt as the moisture control variable; (3 using a warm-rain physics scheme for partitioning the Qt increment into individual increments of water vapour, cloud liquid water and rain; and (4 adopting a symmetric observation error model for all-sky radiance assimilation.Compared to a benchmark experiment with no AMSR2 data, the impact of assimilating clear-sky or all-sky AMSR2 radiances on the analysis and forecast of Hurricane Sandy (2012 was assessed through analysis/forecast cycling experiments using WRF and WRFDA's three-dimensional variational (3DVAR data assimilation scheme. With more cloud/precipitation-affected data being assimilated around tropical cyclone (TC core areas in the all-sky AMSR2 assimilation experiment, better analyses were obtained in terms of the TC's central sea level pressure (CSLP, warm-core structure and cloud distribution. Substantial (>20 % error reduction in track and CSLP forecasts was achieved from both clear-sky and all-sky AMSR2 assimilation experiments, and this improvement was consistent from the analysis time to 72-h forecasts. Moreover, the all-sky assimilation experiment consistently yielded better track and CSLP forecasts than the clear-sky did for all forecast lead times, due to a better analysis in the TC core areas. Positive forecast impact from assimilating AMSR2 radiances is also seen when verified against the European Center for Medium-Range Weather Forecasts (ECMWF analysis and the Stage IV precipitation analysis, with an overall larger positive impact from the all-sky assimilation experiment.

Accelerating assimilation development for new observing systems using EFSO

Science.gov (United States)

Lien, Guo-Yuan; Hotta, Daisuke; Kalnay, Eugenia; Miyoshi, Takemasa; Chen, Tse-Chun

2018-03-01

To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

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Mitchell, K. E.

2006-12-01

The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

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B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ2 and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

Directory of Open Access Journals (Sweden)

B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ² and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Data Assimilation in Forest Inventory: First Empirical Results

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Mattias Nyström

2015-12-01

Full Text Available Data assimilation techniques were used to estimate forest stand data in 2011 by sequentially combining remote sensing based estimates of forest variables with predictions from growth models. Estimates of stand data, based on canopy height models obtained from image matching of digital aerial images at six different time-points between 2003 and 2011, served as input to the data assimilation. The assimilation routines were built on the extended Kalman filter. The study was conducted in hemi-boreal forest at the Remningstorp test site in southern Sweden (lat. 13°37′ N; long. 58°28′ E. The assimilation results were compared with two other methods used in practice for estimation of forest variables: the first was to use only the most recent estimate obtained from remotely sensed data (2011 and the second was to forecast the first estimate (2003 to the endpoint (2011. All three approaches were validated using nine 40 m radius validation plots, which were carefully measured in the field. The results showed that the data assimilation approach provided better results than the two alternative methods. Data assimilation of remote sensing time series has been used previously for calibrating forest ecosystem models, but, to our knowledge, this is the first study with real data where data assimilation has been used for estimating forest inventory data. The study constitutes a starting point for the development of a framework useful for sequentially utilizing all types of remote sensing data in order to provide precise and up-to-date estimates of forest stand parameters.

Multiscale Data Assimilation for Large-Eddy Simulations

Science.gov (United States)

Li, Z.; Cheng, X.; Gustafson, W. I., Jr.; Xiao, H.; Vogelmann, A. M.; Endo, S.; Toto, T.

2017-12-01

Large-eddy simulation (LES) is a powerful tool for understanding atmospheric turbulence, boundary layer physics and cloud development, and there is a great need for developing data assimilation methodologies that can constrain LES models. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility has been developing the capability to routinely generate ensembles of LES. The LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso) is generating simulations for shallow convection days at the ARM Southern Great Plains site in Oklahoma. One of major objectives of LASSO is to develop the capability to observationally constrain LES using a hierarchy of ARM observations. We have implemented a multiscale data assimilation (MSDA) scheme, which allows data assimilation to be implemented separately for distinct spatial scales, so that the localized observations can be effectively assimilated to constrain the mesoscale fields in the LES area of about 15 km in width. The MSDA analysis is used to produce forcing data that drive LES. With such LES workflow we have examined 13 days with shallow convection selected from the period May-August 2016. We will describe the implementation of MSDA, present LES results, and address challenges and opportunities for applying data assimilation to LES studies.

Assimilate unloading from maize (Zea mays L.) pedicel tissues. II. Effects of chemical agents on sugar, amino acid, and 14C-assimilate unloading

International Nuclear Information System (INIS)

Porter, G.A.; Knievel, D.P.; Shannon, J.C.

1987-01-01

Sugar, amino acid, and 14 C-assimilate release from attached maize (Zea mays L.) pedicels was studied following treatment with several chemical inhibitors. In the absence of these agents, sugar release was nearly linear over a 7-hour period. At least 13 amino acids were released with glutamine comprising over 30% of the total. Release was not affected by potassium concentration, 10-minute pretreatments with p-chloromercuribenzene sulfonic acid (PCMBS) or dithiothreitol, and low concentrations of CaCl 2 . Three hours or more exposure to PCMBS, dinitrophenol, N-ethylmaleimide, or 2,4,6-trinitrobenzene sulfonic acid strongly inhibited 14 C-assimilate, sugar, and amino acid release from the pedicel. These treatments also reduced 14 C-assimilate movement into the kernel bases. It is, therefore, likely that reduced unloading, caused by these relatively long-term exposures to chemical inhibitors, was related to reduced translocation of assimilates into treated kernels. Whether this effect is due to disruption of kernel metabolism and sieve element function or reduced assimilate unloading and subsequent accumulation of unlabeled assimilates within the pedicel tissues cannot be determined at this time

Assimilation of enterprise technology upgrades: a factor-based study

Science.gov (United States)

Claybaugh, Craig C.; Ramamurthy, Keshavamurthy; Haseman, William D.

2017-02-01

The purpose of this study is to gain a better understanding of the differences in the propensity of firms to initiate and commit to the assimilation of an enterprise technology upgrade. A research model is proposed that examines the influences that four technological and four organisational factors have on predicting assimilation of a technology upgrade. Results show that firms with a greater propensity to assimilate the new enterprise resource planning (ERP) version have a higher assessment of relative advantage, IS technical competence, and the strategic role of IS relative to those firms with a lower propensity to assimilate a new ERP version.

Negative Assortative Mating Based on Body Coloration in the Freshwater Platyfish (Poecillidae: Xiphophorus maculatus

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Tyler E. Frankel

2017-04-01

Full Text Available The ability of individuals within a population to survive and thrive is highly dependent upon the maintenance of genetic variation and phenotypic diversity, thereby ensuring adaptation to dynamic environments. A fundamental method of maintaining such variation is through a negative assortative mating strategy, in which individuals would be expected to reproductively select members of the opposite sex that exhibit dissimilar phenotypes. Employing three uniform body color morphs, red, yellow and blue, of the platyfish (Xiphophorus maculatus, this study was designed to investigate whether X. maculatus females would preferentially be attracted to males exhibiting an alternative color, thereby enabling an examination of the effect of male body coloration on mate choice by adult females. Mate choice was determined based on the initial preference of each female, as well as the amount of time females spent associating with each male. Initial preferences were analyzed using a binomial distribution test, and overall preference data using Wilcoxon signed rank tests. Red females initially selected for dissimilar colored males, and spent a significantly larger amount of time associating with blue and yellow males, as did yellow females with red and blue males. Blue females initially selected and spent a significantly larger amount of time associating with red males but, interestingly, showed no selective preference between blue and yellow males. In these experimental trials, the overall strong mate selection exhibited by female platyfish for males of dissimilar coloration is suggestive of a negative assortative mating strategy and provides evidence for the maintenance of color polymorphism in nature populations.

Religion, Marriage Markets, and Assortative Mating in the United States

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McClendon, David

2016-01-01

As interfaith marriage has become more common, religion is thought to be less important for sorting partners. However, prior studies on religious assortative mating use samples of prevailing marriages, which miss how local marriage markets shape both partner selection and marriage timing. Drawing on search theory and data from 8,699 young adults (ages 18–31) in the National Longitudinal Study of Youth 1997, the author examined the association between the concentration of co-religionists in local marriage markets and marriage timing and partner selection using event history methods. Religious concentration is associated with higher odds of transitioning to marriage and religious homogamy (conditional on marriage) for women and men at older ages (24–31) but not at younger ages (18–23). The association was also stronger for non-Hispanic Whites compared to other race-ethnic groups. The findings indicate that religion remains relevant in sorting partners for many young adults in today’s marriage market. PMID:27818530

[Use of illicit drugs and critical perspectives of drug users' relatives and acquaintances in Northern Rio de Janeiro City, Brazil].

Science.gov (United States)

Vargens, Octavio Muniz da Costa; Brands, Bruna; Adlaf, Edward; Giesbrecht, Norman; Simich, Laura; Wright, Maria da Gloria Miotto

2009-01-01

This article presents the partial results of a multicenter, qualitative study, which involved seven Latin-American countries and Canada. The results presented refer to Northern Rio de Janeiro (city), Brazil. The objective of the study was to describe the perspective of relatives/acquaintances of illicit drug users about protective and risk factors, prevention initiatives, treatment services, and legal aspects regarding illicit drugs. Interviews were performed with 99 individuals, who reported being affected by their relationship with an illicit drug user (relative or acquaintance), approaching their perspectives regarding the key-domains. Most participants were women (73.7%); relatives who used drugs were mostly men (78.2%); the most consumed drug was marijuana (77.8%). The highlighted protective factor was having recreational-sports activities in the community (88.9%), and the risk factor was curiosity for trying something new (94.4%). The main treatment services were Church Groups (51.5%), and participants stated that laws should be more punitive (82.8%). In conclusion, this information is essential to fight against drug use/abuse, showing that there is a need for actions that consider different perspectives at different levels.

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

Science.gov (United States)

Girotto, Manuela

2018-01-01

Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

On the role of perception in shaping phonological assimilation rules.

Science.gov (United States)

Hura, S L; Lindblom, B; Diehl, R L

1992-01-01

Assimilation of nasals to the place of articulation of following consonants is a common and natural process among the world's languages. Recent phonological theory attributes this naturalness to the postulated geometry of articulatory features and the notion of spreading (McCarthy, 1988). Others view assimilation as a result of perception (Ohala, 1990), or as perceptually tolerated articulatory simplification (Kohler, 1990). Kohler notes that certain consonant classes (such as nasals and stops) are more likely than other classes (such as fricatives) to undergo place assimilation to a following consonant. To explain this pattern, he proposes that assimilation tends not to occur when the members of a consonant class are relatively distinctive perceptually, such that their articulatory reduction would be particularly salient. This explanation, of course, presupposes that the stops and nasals which undergo place assimilation are less distinctive than fricatives, which tend not to assimilate. We report experimental results that confirm Kohler's perceptual assumption: In the context of a following word initial stop, fricatives were less confusable than nasals or unreleased stops. We conclude, in agreement with Ohala and Kohler, that perceptual factors are likely to shape phonological assimilation rules.

Assimilation of GNSS radio occultation observations in GRAPES

Science.gov (United States)

Liu, Y.; Xue, J.

2014-07-01

This paper reviews the development of the global navigation satellite system (GNSS) radio occultation (RO) observations assimilation in the Global/Regional Assimilation and PrEdiction System (GRAPES) of China Meteorological Administration, including the choice of data to assimilate, the data quality control, the observation operator, the tuning of observation error, and the results of the observation impact experiments. The results indicate that RO data have a significantly positive effect on analysis and forecast at all ranges in GRAPES not only in the Southern Hemisphere where conventional observations are lacking but also in the Northern Hemisphere where data are rich. It is noted that a relatively simple assimilation and forecast system in which only the conventional and RO observation are assimilated still has analysis and forecast skill even after nine months integration, and the analysis difference between both hemispheres is gradually reduced with height when compared with NCEP (National Centers for Enviromental Prediction) analysis. Finally, as a result of the new onboard payload of the Chinese FengYun-3 (FY-3) satellites, the research status of the RO of FY-3 satellites is also presented.

SMOS brightness temperature assimilation into the Community Land Model

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D. Rains

2017-11-01

Full Text Available SMOS (Soil Moisture and Ocean Salinity mission brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF as well as to the Community Microwave Emission Model (CMEM. Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010–2015. Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 % for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

Accuracy of Self-Esteem Judgments at Zero Acquaintance.

Science.gov (United States)

Hirschmüller, Sarah; Schmukle, Stefan C; Krause, Sascha; Back, Mitja D; Egloff, Boris

2018-04-01

Perceptions of strangers' self-esteem can have wide-ranging interpersonal consequences. Aiming to reconcile inconsistent results from previous research that had predominantly suggested that self-esteem is a trait that can hardly be accurately judged at zero acquaintance, we examined unaquainted others' accuracy in inferring individuals' actual self-esteem. Ninety-nine target participants (77 female; M age  = 23.5 years) were videotaped in a self-introductory situation, and self-esteem self-reports and reports by well-known informants were obtained as separate accuracy criteria. Forty unacquainted observers judged targets' self-esteem on the basis of these short video sequences (M = 23s, SD = 7.7). Results showed that both self-reported (r = .31, p = .002) and informant-reported self-esteem (r = .21, p = .040) of targets could be inferred by strangers. The degree of accuracy in self-esteem judgments could be explained with lens model analyses: Self- and informant-reported self-esteem predicted nonverbal and vocal friendliness, both of which predicted self-esteem judgments by observers. In addition, observers' accuracy in inferring informant-reported self-esteem was mediated by the utilization of targets' physical attractiveness. Besides using valid behavioral information to infer strangers' self-esteem, observers inappropriately relied on invalid behavioral information reflecting nonverbal, vocal, and verbal self-assuredness. Our findings show that strangers can quite accurately detect individuals' self-reported and informant-reported self-esteem when targets are observed in a public self-presentational situation. © 2017 Wiley Periodicals, Inc.

Covariance Function for Nearshore Wave Assimilation Systems

Science.gov (United States)

2018-01-30

which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE

Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

Science.gov (United States)

van Peet, Jacob C. A.; van der A, Ronald J.; Kelder, Hennie M.; Levelt, Pieternel F.

2018-02-01

A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.

Data assimilation the ensemble Kalman filter

CERN Document Server

Evensen, Geir

2007-01-01

Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...

Scalable and balanced dynamic hybrid data assimilation

Science.gov (United States)

Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

2017-04-01

Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them

Regional Ocean Data Assimilation

KAUST Repository

Edwards, Christopher A.; Moore, Andrew M.; Hoteit, Ibrahim; Cornuelle, Bruce D.

2015-01-01

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal

The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model. [Technical Report Series on Global Modeling and Data Assimilation

Science.gov (United States)

Koster, Randal D. (Editor); Rousseaux, Cecile Severine; Gregg, Watson W.

2014-01-01

In this paper, we investigated whether the assimilation of remotely-sensed chlorophyll data can improve the estimates of air-sea carbon dioxide fluxes (FCO2). Using a global, established biogeochemical model (NASA Ocean Biogeochemical Model, NOBM) for the period 2003-2010, we found that the global FCO2 values produced in the free-run and after assimilation were within -0.6 mol C m(sup -2) y(sup -1) of the observations. The effect of satellite chlorophyll assimilation was assessed in 12 major oceanographic regions. The region with the highest bias was the North Atlantic. Here the model underestimated the fluxes by 1.4 mol C m(sup -2) y(sup -1) whereas all the other regions were within 1 mol C m(sup -2) y(sup -1) of the data. The FCO2 values were not strongly impacted by the assimilation, and the uncertainty in FCO2 was not decreased, despite the decrease in the uncertainty in chlorophyll concentration. Chlorophyll concentrations were within approximately 25% of the database in 7 out of the 12 regions, and the assimilation improved the chlorophyll concentration in the regions with the highest bias by 10-20%. These results suggest that the assimilation of chlorophyll data does not considerably improve FCO2 estimates and that other components of the carbon cycle play a role that could further improve our FCO2 estimates.

Statistical techniques to extract information during SMAP soil moisture assimilation

Science.gov (United States)

Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

2017-12-01

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Nitrogen assimilation in soybean nodules, 1

International Nuclear Information System (INIS)

Ohyama, Takuji; Kumazawa, Kikuo

1980-01-01

In order to elucidate the pathways to assimilate the ammonia produced by N 2 -fixation in soybean nodules, 15 N-labeled compounds were administered to intact nodules or nodule slices pretreated with various inhibitors of nitrogen assimilation. After exposure to 15 N 2 , 15 N-incorporation into various nitrogenous compounds was investigated in attached nodules injected with methionine sulfoximine (MSX) or azaserine (AS). MSX treatment increased the 15 N content of ammonia more than 6 times, however, depressed 15 N content of most of amides and amino acids. AS treatment enhanced 15 N content of amido-N of glutamine as well as ammonia, but decreased amino-N of glutamine and most of amino acids. Experiments with nodule slices pretreated with MSX or AS solution and then fed with 15 N-labeled ammonia or amido- 15 N of glutamine showed the same trends. Aminooxyacetate inhibited nitrogen flow from glutamic acid to other amino acids. These results strongly indicate that the ammonia produced by N 2 -fixation is assimilated by GS/GOGAT system to glutamic acid and then transaminated to various amino acids in situ. 15 N-incorporation patterns in nodule slices fed with 15 N-labeled ammonia, hydroxylamine, nitrite were similar, but nitrate seemed to be reduced in a definite compartment and assimilated similarly as in intact nodules fed with 15 N 2 (author)

Assimilation of satellite color observations in a coupled ocean GCM-ecosystem model

Science.gov (United States)

Sarmiento, Jorge L.

1992-01-01

Monthly average coastal zone color scanner (CZCS) estimates of chlorophyll concentration were assimilated into an ocean global circulation model(GCM) containing a simple model of the pelagic ecosystem. The assimilation was performed in the simplest possible manner, to allow the assessment of whether there were major problems with the ecosystem model or with the assimilation procedure. The current ecosystem model performed well in some regions, but failed in others to assimilate chlorophyll estimates without disrupting important ecosystem properties. This experiment gave insight into those properties of the ecosystem model that must be changed to allow data assimilation to be generally successful, while raising other important issues about the assimilation procedure.

Development Of A Data Assimilation Capability For RAPID

Science.gov (United States)

Emery, C. M.; David, C. H.; Turmon, M.; Hobbs, J.; Allen, G. H.; Famiglietti, J. S.

2017-12-01

The global decline of in situ observations associated with the increasing ability to monitor surface water from space motivates the creation of data assimilation algorithms that merge computer models and space-based observations to produce consistent estimates of terrestrial hydrology that fill the spatiotemporal gaps in observations. RAPID is a routing model based on the Muskingum method that is capable of estimating river streamflow over large scales with a relatively short computing time. This model only requires limited inputs: a reach-based river network, and lateral surface and subsurface flow into the rivers. The relatively simple model physics imply that RAPID simulations could be significantly improved by including a data assimilation capability. Here we present the early developments of such data assimilation approach into RAPID. Given the linear and matrix-based structure of the model, we chose to apply a direct Kalman filter, hence allowing for the preservation of high computational speed. We correct the simulated streamflows by assimilating streamflow observations and our early results demonstrate the feasibility of the approach. Additionally, the use of in situ gauges at continental scales motivates the application of our new data assimilation scheme to altimetry measurements from existing (e.g. EnviSat, Jason 2) and upcoming satellite missions (e.g. SWOT), and ultimately apply the scheme globally.

Data assimilation in the decision support system RODOS

DEFF Research Database (Denmark)

Rojas-Palma, C.; Madsen, H.; Gering, F.

2003-01-01

. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...

Disconfirmed hedonic expectations produce perceptual contrast, not assimilation.

Science.gov (United States)

Zellner, Debra A; Strickhouser, Dinah; Tornow, Carina E

2004-01-01

In studies of hedonic ratings, contrast is the usual result when expectations about test stimuli are produced through the presentation of context stimuli, whereas assimilation is the usual result when expectations about test stimuli are produced through labeling, advertising, or the relaying of information to the subject about the test stimuli. Both procedures produce expectations that are subsequently violated, but the outcomes are different. The present studies demonstrate that both assimilation and contrast can occur even when expectations are produced by verbal labels and the degree of violation of the expectation is held constant. One factor determining whether assimilation or contrast occurs appears to be the certainty of the expectation. Expectations that convey certainty are produced by methods that lead to social influence on subjects' ratings, producing assimilation. When social influence is not a factor and subjects give judgments influenced only by the perceived hedonic value of the stimulus, contrast is the result.

Assimilation of Remotely Sensed Leaf Area Index into the Community Land Model with Explicit Carbon and Nitrogen Components using Data Assimilation Research Testbed

Science.gov (United States)

Ling, X.; Fu, C.; Yang, Z. L.; Guo, W.

2017-12-01

Information of the spatial and temporal patterns of leaf area index (LAI) is crucial to understand the exchanges of momentum, carbon, energy, and water between the terrestrial ecosystem and the atmosphere, while both in-situ observation and model simulation usually show distinct deficiency in terms of LAI coverage and value. Land data assimilation, combined with observation and simulation together, is a promising way to provide variable estimation. The Data Assimilation Research Testbed (DART) developed and maintained by the National Centre for Atmospheric Research (NCAR) provides a powerful tool to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to better understanding of all three. Here we systematically investigated the effects of data assimilation on improving LAI simulation based on NCAR Community Land Model with the prognostic carbon-nitrogen option (CLM4CN) linked with DART using the deterministic Ensemble Adjustment Kalman Filter (EAKF). Random 40-member atmospheric forcing was used to drive the CLM4CN with or without LAI assimilation. The Global Land Surface Satellite LAI data (GLASS LAI) LAI is assimilated into the CLM4CN at a frequency of 8 days, and LAI (and leaf carbon / nitrogen) are adjusted at each time step. The results show that assimilating remotely sensed LAI into the CLM4CN is an effective method for improving model performance. In detail, the CLM4-CN simulated LAI systematically overestimates global LAI, especially in low latitude with the largest bias of 5 m2/m2. While if updating both LAI and leaf carbon and leaf nitrogen simultaneously during assimilation, the analyzed LAI can be corrected, especially in low latitude regions with the bias controlled around ±1 m2/m2. Analyzed LAI could also represent the seasonal variation except for the Southern Temperate (23°S-90°S). The obviously improved regions located in the center of Africa, Amazon, the South of Eurasia, the northeast of

The importance of peers: assimilation patterns among second-generation Turkish immigrants in Western Europe

NARCIS (Netherlands)

Ali, S.; Fokkema, C.M.

2011-01-01

The two dominant approaches to immigrant assimilation, segmented assimilation and "new" assimilation theories, have been successful at reporting and analyzing between-group differences in assimilation patterns. However, studies of assimilation generally do not address differences at the individual

Assimilation of NUCAPS Retrieved Profiles in GSI for Unique Forecasting Applications

Science.gov (United States)

Berndt, Emily Beth; Zavodsky, Bradley; Srikishen, Jayanthi; Blankenship, Clay

2015-01-01

Hyperspectral IR profiles can be assimilated in GSI as a separate observation other than radiosondes with only changes to tables in the fix directory. Assimilation of profiles does produce changes to analysis fields and evidenced by: Innovations larger than +/-2.0 K are present and represent where individual profiles impact the final temperature analysis.The updated temperature analysis is colder behind the cold front and warmer in the warm sector. The updated moisture analysis is modified more in the low levels and tends to be drier than the original model background Analysis of model output shows: Differences relative to 13-km RAP analyses are smaller when profiles are assimilated with NUCAPS errors. CAPE is under-forecasted when assimilating NUCAPS profiles, which could be problematic for severe weather forecasting Refining the assimilation technique to incorporate an error covariance matrix and creating a separate GSI module to assimilate satellite profiles may improve results.

Assimilation of LAI time-series in crop production models

Science.gov (United States)

Kooistra, Lammert; Rijk, Bert; Nannes, Louis

2014-05-01

Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor

Impact of real-time measurements for data assimilation in reservoir simulation

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R; Krosche, M [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Pajonk, O [TU Braunschweig (Germany). Inst. fuer Wissenschaftliches Rechnen; Myrland, T [Morges Teknisk-Naturvitenskapelige Univ. (NTNU), Trondheim (Germany)

2008-10-23

This paper gives an overview on the conceptual background of data assimilation techniques. The framework of sequential data assimilation as described for the ensemble Kalman filter implementation allows a continuous integration of new measurement data. The initial diversity of ensemble members will be critical for the assimilation process and the ability to successfully assimilate measurement data. At the same time the initial ensemble will impact the propagation of uncertainties with crucial consequences for production forecasts. Data assimilation techniques have complimentary features compared to other optimization techniques built on selection or regression schemes. Specifically, EnKF is applicable to real field cases and defines an important perspective for facilitating continuous reservoir simulation model updates in a reservoir life cycle. (orig.)

Quality of clay-powders of industrial assortment

Energy Technology Data Exchange (ETDEWEB)

Lityayeva, Z A; Dzetl, B G; Goncharenko, N N; Naurova, I V; Rybchenko, V I; Voyevodin, L I

1979-01-01

Nomenclature was developed for the quality indicators of clay powders which took into consideration the foreign experience, and it is suggested that a suspension of clay powders be viewed as the simplest type of drilling. In this case the technique of preparing the suspensions approaches the maximum to that used in the recommended standard (TU-39-043-074). The output of solution is determined with standardized effective viscosity /eta/ ef =/sup 20/ /SUP cP/ on a series domestic rotary viscosimeter VSN-3 with gradient of shear velocity EPSILON=666 sec/sup -1/; with EPSILON=1022 sec /sup -1//eta/ /SUB ef/ = 15 cP. This makes it possible to obtain data comparable to the foreign standards regarding the output of the fluid from the powders. According to the suggested technique, the clay powder is dispersed for 20-30 minutes in water or saturated solution of NaC1 in a mixing unit ''Voronezh2'' with rotation frequency of 9000 rpm, is left to rest and is again dispersed for 15 minutes. Then the dynamic shear stress (P /SUB k2/ ), plastic viscosity (/eta/ /SUB ef/ ), coefficients of coagulation (K /SUB c/ ) and thyxotropic (K /SUB T/ ) structure-formation are defined. Measurements are made on the instrument FLR-1 of water output with 0.7 (B) or 0.1 (B) MPa. According to this technique, a comparison was made of the domestic powders of industrial assortment with the powder ''Aquagel'' widely used abroad. It was established that only the modified concrete powders with correct selection of reagents can compete with the foreign.

Joint Center for Satellite Data Assimilation Overview and Research Activities

Science.gov (United States)

Auligne, T.

2017-12-01

In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

Yeast identification: reassessment of assimilation tests as sole universal identifiers.

Science.gov (United States)

Spencer, J; Rawling, S; Stratford, M; Steels, H; Novodvorska, M; Archer, D B; Chandra, S

2011-11-01

To assess whether assimilation tests in isolation remain a valid method of identification of yeasts, when applied to a wide range of environmental and spoilage isolates. Seventy-one yeast strains were isolated from a soft drinks factory. These were identified using assimilation tests and by D1/D2 rDNA sequencing. When compared to sequencing, assimilation test identifications (MicroLog™) were 18·3% correct, a further 14·1% correct within the genus and 67·6% were incorrectly identified. The majority of the latter could be attributed to the rise in newly reported yeast species. Assimilation tests alone are unreliable as a universal means of yeast identification, because of numerous new species, variability of strains and increasing coincidence of assimilation profiles. Assimilation tests still have a useful role in the identification of common species, such as the majority of clinical isolates. It is probable, based on these results, that many yeast identifications reported in older literature are incorrect. This emphasizes the crucial need for accurate identification in present and future publications. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

DART: New Research Using Ensemble Data Assimilation in Geophysical Models

Science.gov (United States)

Hoar, T. J.; Raeder, K.

2015-12-01

The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART

A problem-solving environment for data assimilation in air quality modelling

NARCIS (Netherlands)

Velzen, N. van; Segers, A.J.

2010-01-01

A generic toolbox for data assimilation called COSTA (COmmon Set of Tools for the Assimilation of data) makes it possible to simplify the application of data assimilation to models and to try out various methods for a particular model. Concepts of object oriented programming are used to define

Assimilation of Doppler weather radar observations in a mesoscale ...

Indian Academy of Sciences (India)

Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation ... investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present ...... Results presented in this paper are based on.

Potential of an ensemble Kalman smoother for stratospheric chemical-dynamical data assimilation

Directory of Open Access Journals (Sweden)

Thomas Milewski

2013-02-01

Full Text Available A new stratospheric ensemble Kalman smoother (EnKS system is introduced, and the potential of assimilating posterior stratospheric observations to better constrain the whole model state at analysis time is investigated. A set of idealised perfect-model Observation System Simulation Experiments (OSSE assimilating synthetic limb-sounding temperature or ozone retrievals are performed with a chemistry–climate model. The impact during the analysis step is characterised in terms of the root mean square error reduction between the forecast state and the analysis state. The performances of (1 a fixed-lag EnKS assimilating observations spread over 48 hours and (2 an ensemble Kalman Filter (EnKF assimilating a denser network of observations are compared with a reference EnKF. The ozone assimilation with EnKS shows a significant additional reduction of analysis error of the order of 10% for dynamical and chemical variables in the extratropical upper troposphere lower stratosphere (UTLS and Polar Vortex regions when compared to the reference EnKF. This reduction has similar magnitude to the one achieved by the denser-network EnKF assimilation. Similarly, the temperature assimilation with EnKS significantly decreases the error in the UTLS for the wind variables like the denser-network EnKF assimilation. However, the temperature assimilation with EnKS has little or no significant impact on the temperature and ozone analyses, whereas the denser-network EnKF shows improvement with respect to the reference EnKF. The different analysis impacts from the assimilation of current and posterior ozone observations indicate the capacity of time-lagged background-error covariances to represent temporal interactions up to 48 hours between variables during the ensemble data assimilation analysis step, and the possibility to use posterior observations whenever additional current observations are unavailable. The possible application of the EnKS for reanalyses is

Assimilation of Aircraft Observations in High-Resolution Mesoscale Modeling

Directory of Open Access Journals (Sweden)

Brian P. Reen

2018-01-01

Full Text Available Aircraft-based observations are a promising source of above-surface observations for assimilation into mesoscale model simulations. The Tropospheric Airborne Meteorological Data Reporting (TAMDAR observations have potential advantages over some other aircraft observations including the presence of water vapor observations. The impact of assimilating TAMDAR observations via observation nudging in 1 km horizontal grid spacing Weather Research and Forecasting model simulations is evaluated using five cases centered over California. Overall, the impact of assimilating the observations is mixed, with the layer with the greatest benefit being above the surface in the lowest 1000 m above ground level and the variable showing the most consistent benefit being temperature. Varying the nudging configuration demonstrates the sensitivity of the results to details of the assimilation, but does not clearly demonstrate the superiority of a specific configuration.

A new approach in the design of an interactive environment for teaching Hamiltonian digraphs

International Nuclear Information System (INIS)

Iordan, A E; Panoiu, M

2014-01-01

In this article the authors present the necessary steps in object orientated design of an interactive environment that is dedicated to the process of acquaintances assimilation in Hamiltonian graphs theory domain, especially for the simulation of algorithms which determine the Hamiltonian trails and circuits. The modelling of the interactive environment is achieved through specific UML diagrams representing the steps of analysis, design and implementation. This interactive environment is very useful for both students and professors, because computer programming domain, especially digraphs theory domain is comprehended and assimilated with difficulty by students

Ensemble streamflow assimilation with the National Water Model.

Science.gov (United States)

Rafieeinasab, A.; McCreight, J. L.; Noh, S.; Seo, D. J.; Gochis, D.

2017-12-01

Through case studies of flooding across the US, we compare the performance of the National Water Model (NWM) data assimilation (DA) scheme to that of a newly implemented ensemble Kalman filter approach. The NOAA National Water Model (NWM) is an operational implementation of the community WRF-Hydro modeling system. As of August 2016, the NWM forecasts of distributed hydrologic states and fluxes (including soil moisture, snowpack, ET, and ponded water) over the contiguous United States have been publicly disseminated by the National Center for Environmental Prediction (NCEP) . It also provides streamflow forecasts at more than 2.7 million river reaches up to 30 days in advance. The NWM employs a nudging scheme to assimilate more than 6,000 USGS streamflow observations and provide initial conditions for its forecasts. A problem with nudging is how the forecasts relax quickly to open-loop bias in the forecast. This has been partially addressed by an experimental bias correction approach which was found to have issues with phase errors during flooding events. In this work, we present an ensemble streamflow data assimilation approach combining new channel-only capabilities of the NWM and HydroDART (a coupling of the offline WRF-Hydro model and NCAR's Data Assimilation Research Testbed; DART). Our approach focuses on the single model state of discharge and incorporates error distributions on channel-influxes (overland and groundwater) in the assimilation via an ensemble Kalman filter (EnKF). In order to avoid filter degeneracy associated with a limited number of ensemble at large scale, DART's covariance inflation (Anderson, 2009) and localization capabilities are implemented and evaluated. The current NWM data assimilation scheme is compared to preliminary results from the EnKF application for several flooding case studies across the US.

Displacement data assimilation

Energy Technology Data Exchange (ETDEWEB)

Rosenthal, W. Steven [Pacific Northwest Laboratory, Richland, WA 99354 (United States); Venkataramani, Shankar [Department of Mathematics and Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721 (United States); Mariano, Arthur J. [Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149 (United States); Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu [Department of Mathematics, Oregon State University, Corvallis, OR 97331 (United States)

2017-02-01

We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information is important. While the displacement transformation is generic, here we implement it within an ensemble Kalman Filter framework and demonstrate its effectiveness in tracking stochastically perturbed vortices.

Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

Science.gov (United States)

Keller, Christoph A.; Pawson, Steven; Wargan, Krzysztof; Weir, Brad

2018-01-01

The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

Assimilate unloading from maize (Zea mays L.) pedicel tissues

International Nuclear Information System (INIS)

Porter, G.A.; Knievel, D.P.; Shannon, J.C.

1987-01-01

Sugar and 14 C-assimilate release from the pedicel tissue of attached maize (Zea mays L.) kernels was studied following treatment with solute concentrations of up to 800 millimolal. Exposure and collection times ranged from 3 to 6 hours. Sugar and 14 C-assimilate unloading and collection in agar traps was reduced by 25 and 43%, respectively, following exposure to 800 millimolal mannitol. Inhibition of unloading was not specific to mannitol, since similar concentrations of glucose, fructose, or equimolar glucose plus fructose resulted in comparable inhibition. Ethylene glycol, a rapidly permeating solute which should not greatly influence cell turgor, did not inhibit 14 C-assimilate unloading. Based on these results, they suggest that inhibition of unloading by high concentrations of sugar or mannitol was due to reduced pedicel cell turgor. Changes in pedicel cell turgor may play a role in the regulation of assimilate transfer within the maize kernel

Model Uncertainty Quantification Methods In Data Assimilation

Science.gov (United States)

Pathiraja, S. D.; Marshall, L. A.; Sharma, A.; Moradkhani, H.

2017-12-01

Data Assimilation involves utilising observations to improve model predictions in a seamless and statistically optimal fashion. Its applications are wide-ranging; from improving weather forecasts to tracking targets such as in the Apollo 11 mission. The use of Data Assimilation methods in high dimensional complex geophysical systems is an active area of research, where there exists many opportunities to enhance existing methodologies. One of the central challenges is in model uncertainty quantification; the outcome of any Data Assimilation study is strongly dependent on the uncertainties assigned to both observations and models. I focus on developing improved model uncertainty quantification methods that are applicable to challenging real world scenarios. These include developing methods for cases where the system states are only partially observed, where there is little prior knowledge of the model errors, and where the model error statistics are likely to be highly non-Gaussian.

ASSIMILATION OF COARSE-SCALEDATAUSINGTHE ENSEMBLE KALMAN FILTER

KAUST Repository

Efendiev, Yalchin

2011-01-01

Reservoir data is usually scale dependent and exhibits multiscale features. In this paper we use the ensemble Kalman filter (EnKF) to integrate data at different spatial scales for estimating reservoir fine-scale characteristics. Relationships between the various scales is modeled via upscaling techniques. We propose two versions of the EnKF to assimilate the multiscale data, (i) where all the data are assimilated together and (ii) the data are assimilated sequentially in batches. Ensemble members obtained after assimilating one set of data are used as a prior to assimilate the next set of data. Both of these versions are easily implementable with any other upscaling which links the fine to the coarse scales. The numerical results with different methods are presented in a twin experiment setup using a two-dimensional, two-phase (oil and water) flow model. Results are shown with coarse-scale permeability and coarse-scale saturation data. They indicate that additional data provides better fine-scale estimates and fractional flow predictions. We observed that the two versions of the EnKF differed in their estimates when coarse-scale permeability is provided, whereas their results are similar when coarse-scale saturation is used. This behavior is thought to be due to the nonlinearity of the upscaling operator in the case of the former data. We also tested our procedures with various precisions of the coarse-scale data to account for the inexact relationship between the fine and coarse scale data. As expected, the results show that higher precision in the coarse-scale data yielded improved estimates. With better coarse-scale modeling and inversion techniques as more data at multiple coarse scales is made available, the proposed modification to the EnKF could be relevant in future studies.

Satellite Data Assimilation within KIAPS-LETKF system

Science.gov (United States)

Jo, Y.; Lee, S., Sr.; Cho, K.

2016-12-01

Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing an ensemble data assimilation system using four-dimensional local ensemble transform kalman filter (LETKF; Hunt et al., 2007) within KIAPS Integrated Model (KIM), referred to as "KIAPS-LETKF". KIAPS-LETKF system was successfully evaluated with various Observing System Simulation Experiments (OSSEs) with NCAR Community Atmospheric Model - Spectral Element (Kang et al., 2013), which has fully unstructured quadrilateral meshes based on the cubed-sphere grid as the same grid system of KIM. Recently, assimilation of real observations has been conducted within the KIAPS-LETKF system with four-dimensional covariance functions over the 6-hr assimilation window. Then, conventional (e.g., sonde, aircraft, and surface) and satellite (e.g., AMSU-A, IASI, GPS-RO, and AMV) observations have been provided by the KIAPS Package for Observation Processing (KPOP). Wind speed prediction was found most beneficial due to ingestion of AMV and for the temperature prediction the improvement in assimilation is mostly due to ingestion of AMSU-A and IASI. However, some degradation in the simulation of the GPS-RO is presented in the upper stratosphere, even though GPS-RO leads positive impacts on the analysis and forecasts. We plan to test the bias correction method and several vertical localization strategies for radiance observations to improve analysis and forecast impacts.

A study on assimilating potential vorticity data

Science.gov (United States)

Li, Yong; Ménard, Richard; Riishøjgaard, Lars Peter; Cohn, Stephen E.; Rood, Richard B.

1998-08-01

The correlation that exists between the potential vorticity (PV) field and the distribution of chemical tracers such as ozone suggests the possibility of using tracer observations as proxy PV data in atmospheric data assimilation systems. Especially in the stratosphere, there are plentiful tracer observations but a general lack of reliable wind observations, and the correlation is most pronounced. The issue investigated in this study is how model dynamics would respond to the assimilation of PV data. First, numerical experiments of identical-twin type were conducted with a simple univariate nuding algorithm and a global shallow water model based on PV and divergence (PV-D model). All model fields are successfully reconstructed through the insertion of complete PV data alone if an appropriate value for the nudging coefficient is used. A simple linear analysis suggests that slow modes are recovered rapidly, at a rate nearly independent of spatial scale. In a more realistic experiment, appropriately scaled total ozone data from the NIMBUS-7 TOMS instrument were assimilated as proxy PV data into the PV-D model over a 10-day period. The resulting model PV field matches the observed total ozone field relatively well on large spatial scales, and the PV, geopotential and divergence fields are dynamically consistent. These results indicate the potential usefulness that tracer observations, as proxy PV data, may offer in a data assimilation system.

Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

Science.gov (United States)

Susskind, Joel; Rosenberg, Bob

2016-01-01

We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.

Cholesterol Assimilation by Lactobacillus Probiotic Bacteria: An In Vitro Investigation

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Catherine Tomaro-Duchesneau

2014-01-01

Full Text Available Excess cholesterol is associated with cardiovascular diseases (CVD, an important cause of mortality worldwide. Current CVD therapeutic measures, lifestyle and dietary interventions, and pharmaceutical agents for regulating cholesterol levels are inadequate. Probiotic bacteria have demonstrated potential to lower cholesterol levels by different mechanisms, including bile salt hydrolase activity, production of compounds that inhibit enzymes such as 3-hydroxy-3-methylglutaryl coenzyme A, and cholesterol assimilation. This work investigates 11 Lactobacillus strains for cholesterol assimilation. Probiotic strains for investigation were selected from the literature: Lactobacillus reuteri NCIMB 11951, L. reuteri NCIMB 701359, L. reuteri NCIMB 702655, L. reuteri NCIMB 701089, L. reuteri NCIMB 702656, Lactobacillus fermentum NCIMB 5221, L. fermentum NCIMB 8829, L. fermentum NCIMB 2797, Lactobacillus rhamnosus ATCC 53103 GG, Lactobacillus acidophilus ATCC 314, and Lactobacillus plantarum ATCC 14917. Cholesterol assimilation was investigated in culture media and under simulated intestinal conditions. The best cholesterol assimilator was L. plantarum ATCC 14917 (15.18 ± 0.55 mg/1010 cfu in MRS broth. L. reuteri NCIMB 701089 assimilated over 67% (2254.70 ± 63.33 mg/1010 cfu of cholesterol, the most of all the strains, under intestinal conditions. This work demonstrates that probiotic bacteria can assimilate cholesterol under intestinal conditions, with L. reuteri NCIMB 701089 showing great potential as a CVD therapeutic.

Assimilation of Baba and Nyonya in Malaysia

OpenAIRE

Razaleigh Muhamat Kawangit

2015-01-01

This research set outs to explore the exact level of the social aspect of assimilation between Baba and Nyonya and their Malay counterparts in Malaysia. It was sure that assimilation in social aspect is a dilemma which Baba and Nyonya face when they interact with Malays as a dominant ethnic group. It suggests that when the process of interaction, their behavior changes in line with the identity of the Malays. This is because the majority influenced the minority in the Malaysian context. Whils...

Computational methods for data evaluation and assimilation

CERN Document Server

Cacuci, Dan Gabriel

2013-01-01

Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas. After presenting the fundamentals underlying the evaluation of experiment

A reduced adjoint approach to variational data assimilation

KAUST Repository

Altaf, Muhammad

2013-02-01

The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

A reduced adjoint approach to variational data assimilation

KAUST Repository

Altaf, Muhammad; El Gharamti, Mohamad; Heemink, Arnold W.; Hoteit, Ibrahim

2013-01-01

The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

Naming game with biased assimilation over adaptive networks

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Fu, Guiyuan; Zhang, Weidong

2018-01-01

The dynamics of two-word naming game incorporating the influence of biased assimilation over adaptive network is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he may refuse to accept the conveyed word from the speaker with a predefined probability, if the conveyed word is different from his current memory. Secondly, the adaptive network is formulated by rewiring the links. Theoretical analysis is developed to show that the population in NGBA will eventually reach global consensus on either A or B. Numerical simulation results show that the larger strength of biased assimilation on both words, the slower convergence speed, while larger strength of biased assimilation on only one word can slightly accelerate the convergence; larger population size can make the rate of convergence slower to a large extent when it increases from a relatively small size, while such effect becomes minor when the population size is large; the behavior of adaptively reconnecting the existing links can greatly accelerate the rate of convergence especially on the sparse connected network.

Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

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Susskind, Joel; Reale, Oreste

2010-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best

A study of regional-scale aerosol assimilation using a Stretch-NICAM

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Misawa, S.; Dai, T.; Schutgens, N.; Nakajima, T.

2013-12-01

Although aerosol is considered to be harmful to human health and it became a social issue, aerosol models and emission inventories include large uncertainties. In recent studies, data assimilation is applied to aerosol simulation to get more accurate aerosol field and emission inventory. Most of these studies, however, are carried out only on global scale, and there are only a few researches about regional scale aerosol assimilation. In this study, we have created and verified an aerosol assimilation system on regional scale, in hopes to reduce an error associated with the aerosol emission inventory. Our aerosol assimilation system has been developed using an atmospheric climate model, NICAM (Non-hydrostaric ICosahedral Atmospheric Model; Satoh et al., 2008) with a stretch grid system and coupled with an aerosol transport model, SPRINTARS (Takemura et al., 2000). Also, this assimilation system is based on local ensemble transform Kalman filter (LETKF). To validate this system, we used a simulated observational data by adding some artificial errors to the surface aerosol fields constructed by Stretch-NICAM-SPRINTARS. We also included a small perturbation in original emission inventory. This assimilation with modified observational data and emission inventory was performed in Kanto-plane region around Tokyo, Japan, and the result indicates the system reducing a relative error of aerosol concentration by 20%. Furthermore, we examined a sensitivity of the aerosol assimilation system by varying the number of total ensemble (5, 10 and 15 ensembles) and local patch (domain) size (radius of 50km, 100km and 200km), both of which are the tuning parameters in LETKF. The result of the assimilation with different ensemble number 5, 10 and 15 shows that the larger the number of ensemble is, the smaller the relative error become. This is consistent with ensemble Kalman filter theory and imply that this assimilation system works properly. Also we found that assimilation system

Impact of data assimilation on ocean current forecasts in the Angola Basin

Science.gov (United States)

Phillipson, Luke; Toumi, Ralf

2017-06-01

The ocean current predictability in the data limited Angola Basin was investigated using the Regional Ocean Modelling System (ROMS) with four-dimensional variational data assimilation. Six experiments were undertaken comprising a baseline case of the assimilation of salinity/temperature profiles and satellite sea surface temperature, with the subsequent addition of altimetry, OSCAR (satellite-derived sea surface currents), drifters, altimetry and drifters combined, and OSCAR and drifters combined. The addition of drifters significantly improves Lagrangian predictability in comparison to the baseline case as well as the addition of either altimetry or OSCAR. OSCAR assimilation only improves Lagrangian predictability as much as altimetry assimilation. On average the assimilation of either altimetry or OSCAR with drifter velocities does not significantly improve Lagrangian predictability compared to the drifter assimilation alone, even degrading predictability in some cases. When the forecast current speed is large, it is more likely that the combination improves trajectory forecasts. Conversely, when the currents are weaker, it is more likely that the combination degrades the trajectory forecast.

Temperature Data Assimilation with Salinity Corrections: Validation for the NSIPP Ocean Data Assimilation System in the Tropical Pacific Ocean, 1993-1998

Science.gov (United States)

Troccoli, Alberto; Rienecker, Michele M.; Keppenne, Christian L.; Johnson, Gregory C.

2003-01-01

The NASA Seasonal-to-Interannual Prediction Project (NSIPP) has developed an Ocean data assimilation system to initialize the quasi-isopycnal ocean model used in our experimental coupled-model forecast system. Initial tests of the system have focused on the assimilation of temperature profiles in an optimal interpolation framework. It is now recognized that correction of temperature only often introduces spurious water masses. The resulting density distribution can be statically unstable and also have a detrimental impact on the velocity distribution. Several simple schemes have been developed to try to correct these deficiencies. Here the salinity field is corrected by using a scheme which assumes that the temperature-salinity relationship of the model background is preserved during the assimilation. The scheme was first introduced for a zlevel model by Troccoli and Haines (1999). A large set of subsurface observations of salinity and temperature is used to cross-validate two data assimilation experiments run for the 6-year period 1993-1998. In these two experiments only subsurface temperature observations are used, but in one case the salinity field is also updated whenever temperature observations are available.

Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

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Lei Ren

2017-09-01

Full Text Available In order to improve the forecasting ability of numerical models, a sequential data assimilation scheme, nudging, was applied to blend remotely sensing high-frequency (HF radar surface currents with results from a three-dimensional numerical, EFDC (Environmental Fluid Dynamics Code model. For the first time, this research presents the most appropriate nudging parameters, which were determined from sensitivity experiments. To examine the influence of data assimilation cycle lengths on forecasts and to extend forecasting improvements, the duration of data assimilation cycles was studied through assimilating linearly interpolated temporal radar data. Data assimilation nudging parameters have not been previously analyzed. Assimilation of HF radar measurements at each model computational timestep outperformed those assimilation models using longer data assimilation cycle lengths; root-mean-square error (RMSE values of both surface velocity components during a 12 h model forecasting period indicated that surface flow fields were significantly improved when implementing nudging assimilation at each model computational timestep. The Data Assimilation Skill Score (DASS technique was used to quantitatively evaluate forecast improvements. The averaged values of DASS over the data assimilation domain were 26% and 33% for east–west and north–south velocity components, respectively, over the half-day forecasting period. Correlation of Averaged Kinetic Energy (AKE was improved by more than 10% in the best data assimilation model. Time series of velocity components and surface flow fields were presented to illustrate the improvement resulting from data assimilation application over time.

Assimilating the Future for Better Forecasts and Earlier Warnings

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Du, H.; Wheatcroft, E.; Smith, L. A.

2016-12-01

Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

Global Data Assimilation System (GDAS)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Data Assimilation System (GDAS) is the system used by the Global Forecast System (GFS) model to place observations into a gridded model space for the...

UNIFICATION AND APPLICATIONS OF MODERN OCEANIC/ATMOSPHERIC DATA ASSIMILATION ALGORITHMS

Institute of Scientific and Technical Information of China (English)

QIAO Fang-li; ZHANG Shao-qing; YUAN Ye-li

2004-01-01

The key mathematics and applications of various modern atmospheric/oceanic data assimilation methods including Optimal Interpolation(OI),4-dimensional variational approach(4D-Var)and filters were systematically reviewed and classified.Based on the data assimilation philosophy,I.e.,using model dynamics to extract the observational information,the common character of the problem,such as the probabilistic nature of the evolution of the atmospheric/oceanic system,noisy and irregularly spaced observations,and the advantages and disadvantages of these data assimilation algorithms,were discussed.In the filtering framework,all modern data assimilation algorithms were unified: OI/3D-Var is a stationary filter,4D-Var is a linear(Kalman)filter and an ensemble of Kalman filters is able to construct a nonlinear filter.The nonlinear filter such as the Ensemble Kalman Filter(ENKF),Ensemble Adjustment Kalman Filter(EAKF)and Ensemble Transformation Kalman Filter(ETKF)can,to some extent,account for the non-Gaussian information of the prior distribution from the model.The flow-dependent covariance estimated by an ensemble filter may be introduced to OI and 4D-Var to improve these traditional algorithms.In practice,the performance of algorithms may depend on the specific numerical model and the choice of algorithm may depend on the specific problem.However,the unification of algorithms allows us to establish a unified test system to evaluate these algorithms,which provides more insights into data assimilation philosophies and helps improve data assimilation techniques.

IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

Science.gov (United States)

Cho, K.; Hyoung-Wook, C.; Jo, Y.

2016-12-01

Korea institute of Atmospheric Prediction Systems (KIAPS) is developing NWP model with data assimilation systems. Local Ensemble Transform Kalman Filter (LETKF) system, one of the data assimilation systems, has been developed for KIAPS Integrated Model (KIM) based on cubed-sphere grid and has successfully assimilated real data. LETKF data assimilation system has been extended to 4D- LETKF which considers time-evolving error covariance within assimilation window and IASI radiance data assimilation using KPOP (KIAPS package for observation processing) with RTTOV (Radiative Transfer for TOVS). The LETKF system is implementing semi operational prediction including conventional (sonde, aircraft) observation and AMSU-A (Advanced Microwave Sounding Unit-A) radiance data from April. Recently, the semi operational prediction system updated radiance observations including GPS-RO, AMV, IASI (Infrared Atmospheric Sounding Interferometer) data at July. A set of simulation of KIM with ne30np4 and 50 vertical levels (of top 0.3hPa) were carried out for short range forecast (10days) within semi operation prediction LETKF system with ensemble forecast 50 members. In order to only IASI impact, our experiments used only conventional and IAIS radiance data to same semi operational prediction set. We carried out sensitivity test for IAIS thinning method (3D and 4D). IASI observation number was increased by temporal (4D) thinning and the improvement of IASI radiance data impact on the forecast skill of model will expect.

Differentiation between Trichophyton mentagrophytes and T. rubrum by sorbitol assimilation.

OpenAIRE

Rezusta, A; Rubio, M C; Alejandre, M C

1991-01-01

Trichophyton rubrum was easily differentiated from T. mentagrophytes by its ability to assimilate sorbitol with an API 20C AUX strip. One hundred percent of 36 T. rubrum strains and none of 147 T. mentagrophytes strains assimilated sorbitol.

Studies on the translocation and distribution characteristics of carbon assimilates in blackberry

International Nuclear Information System (INIS)

Wang Shuyu; Liu Hongjia

1990-08-01

The translocation and distribution characteristics of carbon assimilates were studied with the method of 14 CO 2 feeding. The results indicated that there were different translocation and distribution characteristics of carbon assimilates among the upper, middle and lower leaves in a shoot during annual cycle. Taking away leaves, sun-shading and drought could raise the exporting ratio of carbon assimilates in the feeding leaves and could change the distributing model of the tree. Most of the carbon assimilates were translocated to basic born branch after sun-shading and drought

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

Science.gov (United States)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Acquaintance Rape: Applying Crime Scene Analysis to the Prediction of Sexual Recidivism.

Science.gov (United States)

Lehmann, Robert J B; Goodwill, Alasdair M; Hanson, R Karl; Dahle, Klaus-Peter

2016-10-01

The aim of the current study was to enhance the assessment and predictive accuracy of risk assessments for sexual offenders by utilizing detailed crime scene analysis (CSA). CSA was conducted on a sample of 247 male acquaintance rapists from Berlin (Germany) using a nonmetric, multidimensional scaling (MDS) Behavioral Thematic Analysis (BTA) approach. The age of the offenders at the time of the index offense ranged from 14 to 64 years (M = 32.3; SD = 11.4). The BTA procedure revealed three behavioral themes of hostility, criminality, and pseudo-intimacy, consistent with previous CSA research on stranger rape. The construct validity of the three themes was demonstrated through correlational analyses with known sexual offending measures and criminal histories. The themes of hostility and pseudo-intimacy were significant predictors of sexual recidivism. In addition, the pseudo-intimacy theme led to a significant increase in the incremental validity of the Static-99 actuarial risk assessment instrument for the prediction of sexual recidivism. The results indicate the potential utility and validity of crime scene behaviors in the applied risk assessment of sexual offenders. © The Author(s) 2015.

Assimilation scheme of the Mediterranean Forecasting System: operational implementation

Directory of Open Access Journals (Sweden)

E. Demirov

Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

Assimilation scheme of the Mediterranean Forecasting System: operational implementation

Directory of Open Access Journals (Sweden)

E. Demirov

2003-01-01

Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

Assimilate partitioning during reproductive growth

International Nuclear Information System (INIS)

Finazzo, S.F.; Davenport, T.L.

1987-01-01

Leaves having various phyllotactic relationships to fruitlets were labeled for 1 hour with 10/sub r/Ci of 14 CO 2 . Fruitlets were also labeled. Fruitlets did fix 14 CO 2 . Translocation of radioactivity from the peel into the fruit occurred slowly and to a limited extent. No evidence of translocation out of the fruitlets was observed. Assimilate partitioning in avocado was strongly influenced by phyllotaxy. If a fruit and the labeled leaf had the same phyllotaxy then greater than 95% of the radiolabel was present in this fruit. When the fruit did not have the same phyllotaxy as the labeled leaf, the radiolabel distribution was skewed with 70% of the label going to a single adjacent position. Avocado fruitlets exhibit uniform labeling throughout a particular tissue. In avocado, assimilates preferentially move from leaves to fruits with the same phyllotaxy

Snow multivariable data assimilation for hydrological predictions in mountain areas

Science.gov (United States)

Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

2016-04-01

The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

Science.gov (United States)

Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

2017-12-01

Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

Science.gov (United States)

Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

Science.gov (United States)

Li, Chunguang; Maini, Philip K.

2005-10-01

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

Nitrogen assimilation in denitrifier Bacillus azotoformans LMG 9581T.

Science.gov (United States)

Sun, Yihua; De Vos, Paul; Willems, Anne

2017-12-01

Until recently, it has not been generally known that some bacteria can contain the gene inventory for both denitrification and dissimilatory nitrate (NO 3 - )/nitrite (NO 2 - ) reduction to ammonium (NH 4 + ) (DNRA). Detailed studies of these microorganisms could shed light on the differentiating environmental drivers of both processes without interference of organism-specific variation. Genome analysis of Bacillus azotoformans LMG 9581 T shows a remarkable redundancy of dissimilatory nitrogen reduction, with multiple copies of each denitrification gene as well as DNRA genes nrfAH, but a reduced capacity for nitrogen assimilation, with no nas operon nor amtB gene. Here, we explored nitrogen assimilation in detail using growth experiments in media with different organic and inorganic nitrogen sources at different concentrations. Monitoring of growth, NO 3 - NO 2 - , NH 4 + concentration and N 2 O production revealed that B. azotoformans LMG 9581 T could not grow with NH 4 + as sole nitrogen source and confirmed the hypothesis of reduced nitrogen assimilation pathways. However, NH 4 + could be assimilated and contributed up to 50% of biomass if yeast extract was also provided. NH 4 + also had a significant but concentration-dependent influence on growth rate. The mechanisms behind these observations remain to be resolved but hypotheses for this deficiency in nitrogen assimilation are discussed. In addition, in all growth conditions tested a denitrification phenotype was observed, with all supplied NO 3 - converted to nitrous oxide (N 2 O).

Employment and Wage Assimilation of Male First Generation Immigrants in Denmark

DEFF Research Database (Denmark)

Husted, Leif; Nielsen, Helena Skyt; Rosholm, Michael

2000-01-01

Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...... for unobserved cohort and individual effects and panel selectivity due to missing wage information. The results show that immigrants assimilate partially to Danes, but the assimilation process differs between refugees and non-refugees.......Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...

Employment and Wage assimilation of Male First Generation Immigrants in Denmark

DEFF Research Database (Denmark)

Husted, Leif; Nielsen, Helena Skyt; Rosholm, Michael

Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...... for unobserved cohort and individual effects and panel selectivity due to missing wage information. The results show that immigrants assimilate partially to Danes, but the assimilation process differs between refugees and non-refugees.......Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...

Employment and Wage Assimilation of Male First-generation immigrants in Denmark

DEFF Research Database (Denmark)

Husted, Leif; Nielsen, Helena Skyt; Rosholm, Michael

2001-01-01

Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...... for unobserved cohort and individual effects and panel selectivity due to missing wage information. The results show that immigrants assimilate partially to Danes, but the assimilation process differs between refugees and non-refugees....

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Science.gov (United States)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Assimilation of diazotrophic nitrogen into pelagic food webs.

Science.gov (United States)

Woodland, Ryan J; Holland, Daryl P; Beardall, John; Smith, Jonathan; Scicluna, Todd; Cook, Perran L M

2013-01-01

The fate of diazotrophic nitrogen (N(D)) fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that N(D) fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable N(D) (exuded from viable cyanobacterial cells) by palatable phytoplankton or microbial consortia. Alternatively, N(D) can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable N(D) (e.g., nitrate, ammonium) by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom) would be the primary pathway by which N(D) was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of N(D) by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of N(D) from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of N(D) to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-N(D) pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that N(D) can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes underlying

A virtual reality catchment for data assimilation experiments

Science.gov (United States)

Schalge, Bernd; Rihani, Jehan; Haese, Barbara; Baroni, Gabriele; Erdal, Daniel; Neuweiler, Insa; Hendricks-Franssen, Harrie-Jan; Geppert, Gernot; Ament, Felix; Kollet, Stefan; Cirpka, Olaf; Saavedra, Pablo; Han, Xujun; Attinger, Sabine; Kunstmann, Harald; Vereecken, Harry; Simmer, Clemens

2016-04-01

Current data assimilation (DA) systems often lack the possibility to assimilate measurements across compartments to accurately estimate states and fluxes in subsurface-land surface-atmosphere systems (SLAS). In order to develop a new DA framework that is able to realize this cross-compartmental assimilation a comprehensive testing environment is needed. Therefore a virtual reality (VR) catchment is constructed with the Terrestrial System Modeling Platform (TerrSysMP). This catchment mimics the Neckar catchment in Germany. TerrSysMP employs the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow coupled with the external coupler OASIS. We will show statistical tests to prove the plausibility of the VR. The VR is running in a fully-coupled mode (subsurface - land surface - atmosphere) which includes the interactions of subsurface dynamics with the atmosphere, such as the effects of soil moisture, which can influence near-surface temperatures, convection patterns or the surface heat fluxes. A reference high resolution run serves as the "truth" from which virtual observations are extracted with observation operators like virtual rain gauges, synoptic stations and satellite observations (amongst others). This effectively solves the otherwise often encountered data scarcity issues with respect to DA. Furthermore an ensemble of model runs at a reduced resolution is performed. This ensemble serves also for open loop runs to be compared with data assimilation experiments. The model runs with this ensemble served to identify sets of parameters that are especially sensitive to changes and have the largest impact on the system. These parameters were the focus of subsequent ensemble simulations and DA experiments. We will show to what extend the VR states can be re-constructed using data assimilation methods with only a limited number of virtual observations available.

Assimilation of diazotrophic nitrogen into pelagic food webs.

Directory of Open Access Journals (Sweden)

Ryan J Woodland

Full Text Available The fate of diazotrophic nitrogen (N(D fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that N(D fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable N(D (exuded from viable cyanobacterial cells by palatable phytoplankton or microbial consortia. Alternatively, N(D can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable N(D (e.g., nitrate, ammonium by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom would be the primary pathway by which N(D was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of N(D by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of N(D from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of N(D to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-N(D pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that N(D can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes

a Thtee-Dimensional Variational Assimilation Scheme for Satellite Aod

Science.gov (United States)

Liang, Y.; Zang, Z.; You, W.

2018-04-01

A three-dimensional variational data assimilation scheme is designed for satellite AOD based on the IMPROVE (Interagency Monitoring of Protected Visual Environments) equation. The observation operator that simulates AOD from the control variables is established by the IMPROVE equation. All of the 16 control variables in the assimilation scheme are the mass concentrations of aerosol species from the Model for Simulation Aerosol Interactions and Chemistry scheme, so as to take advantage of this scheme in providing comprehensive analyses of species concentrations and size distributions as well as be calculating efficiently. The assimilation scheme can save computational resources as the IMPROVE equation is a quadratic equation. A single-point observation experiment shows that the information from the single-point AOD is effectively spread horizontally and vertically.

SMAP Data Assimilation at NASA SPoRT

Science.gov (United States)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2016-01-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates

Science.gov (United States)

Lievens, H.; Reichle, R. H.; Liu, Q.; De Lannoy, G.; Dunbar, R. S.; Kim, S.; Das, N. N.; Cosh, M. H.; Walker, J. P.; Wagner, W.

2017-12-01

SMAP (Soil Moisture Active and Passive) radiometer observations at 40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model (CLSM) to generate the SMAP Level 4 Soil Moisture product. The use of C-band radar backscatter observations from Sentinel-1 has the potential to add value to the radiance assimilation by increasing the level of spatial detail. The specifications of Sentinel-1 are appealing, particularly its high spatial resolution (5 by 20 m in interferometric wide swath mode) and frequent revisit time (6 day repeat cycle for the Sentinel-1A and Sentinel-1B constellation). However, the shorter wavelength of Sentinel-1 observations implies less sensitivity to soil moisture. This study investigates the value of Sentinel-1 data for hydrologic simulations by assimilating the radar observations into CLSM, either separately from or simultaneously with SMAP radiometer observations. To facilitate the assimilation of the radar observations, CLSM is coupled to the water cloud model, simulating the radar backscatter as observed by Sentinel-1. The innovations, i.e. differences between observations and simulations, are converted into increments to the model soil moisture state through an Ensemble Kalman Filter. The assimilation impact is assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to 2017. The Sentinel-1 assimilation consistently improves surface soil moisture, whereas root-zone impacts are mostly neutral. Relatively larger improvements are obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performs best, demonstrating the complementary value of radar and radiometer observations.

Assimilation, partitioning, and nonstructural carbohydrates in sweet compared with grain sorghum

International Nuclear Information System (INIS)

Vietor, D.M.; Miller, F.R.

1990-01-01

Nonstructural carbohydrate concentrations in stems are greater for sweet than grain sorghums [Sorghum bicolor (L.) Moench]. Knowledge of plant characteristics associated with high nonstructural carbohydrates in sweet sorghum will air efforts to increase nonstructural carbohydrates in grain sorghum stems. This study tested the hypothesis that variation of CO 2 assimilation rate, leaf area, branching at upper nodes, and partitioning of 14 C-labeled assimilate to main stems are associated with variation of stem nonstructural carbohydrates. A sweet (Atlas X Rio) and a grain (ATx623 X RTx5388) hybrid, stages near and after physiological maturity, and defoliation and gibberellic acid (GA 3 ) treatments provided sources of variation for study. Concentrations of nonstructural carbohydrates in lower and upper stems of the sweet hybrid were 1.4 and 2.7 times higher, respectively, than for the grain hybrid, after physiological maturity. Variation in branching, including 14 C-assimilate partitioning to branches, was not consistently associated with hybrid differences in stem nonstructural carbohydrates. Increased recovery (twofold) of 14 C-assimilate in roots and labeled leaves corresponded with lower percentages of 14 C-assimilate and lower concentrations of nonstructural carbohydrates in stems of the grain hybrid. Leaf areas and leaf CO 2 exchange rate were twice as great for the sweet hybrid. Although defoliation of the sweet hybrid minimized leaf area differences between hybrids, the sweet hybrid accumulated twice as much nonstructural carbohydrates in branches after physiological maturity. Greater potentials for CO 2 assimilation and for 14 C-assimilate accumulation in mature stem tissue were associated with higher levels of stem nonstructural carbohydrates in the sweet compared with the grain hybrid

Assimilation of microwave brightness temperatures for soil moisture estimation using particle filter

International Nuclear Information System (INIS)

Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y

2014-01-01

Soil moisture plays a significant role in global water cycles. Both model simulations and remote sensing observations have their limitations when estimating soil moisture on a large spatial scale. Data assimilation (DA) is a promising tool which can combine model dynamics and remote sensing observations to obtain more precise ground soil moisture distribution. Among various DA methods, the particle filter (PF) can be applied to non-linear and non-Gaussian systems, thus holding great potential for DA. In this study, a data assimilation scheme based on the residual resampling particle filter (RR-PF) was developed to assimilate microwave brightness temperatures into the macro-scale semi-distributed Variance Infiltration Capacity (VIC) Model to estimate surface soil moisture. A radiative transfer model (RTM) was used to link brightness temperatures with surface soil moisture. Finally, the data assimilation scheme was validated by experimental data obtained at Arizona during the Soil Moisture Experiment 2004 (SMEX04). The results show that the estimation accuracy of soil moisture can be improved significantly by RR-PF through assimilating microwave brightness temperatures into VIC model. Both the overall trends and specific values of the assimilation results are more consistent with ground observations compared with model simulation results

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

Science.gov (United States)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Data Assimilation to Extract Soil Moisture Information from SMAP Observations

Directory of Open Access Journals (Sweden)

Jana Kolassa

2017-11-01

Full Text Available This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP observations. Neural network (NN and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

Study on transference of assimilate in filling summer maize using isotope 14C

International Nuclear Information System (INIS)

Fan Zhongxue; Wang Pu; Liang Zhenxing

2001-01-01

The dynamic of assimilate transference from the ear leaf to grain during effective grain filling stage was studied by 14 C tracer. The results showed that the rates of assimilate transportation out of the ear leaf and transference to grain changed very fast. The rate was very big in 4 - 6 hour just after 14 C feeding and decreased with time. The grain which accumulated 14 C-assimilate in a higher rate and got much more 14 C-assimilate in fixed time could develop into larger size

Global assimilation of X Project Loon stratospheric balloon observations

Science.gov (United States)

Coy, L.; Schoeberl, M. R.; Pawson, S.; Candido, S.; Carver, R. W.

2017-12-01

Project Loon has an overall goal of providing worldwide internet coverage using a network of long-duration super-pressure balloons. Beginning in 2013, Loon has launched over 1600 balloons from multiple tropical and middle latitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information over the oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing unique coverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon winds to winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon winds into the same comprehensive DAS. Results show that in middle latitudes the Loon winds and DAS winds agree well and assimilating the Loon winds have only a small impact on short-term forecasting of the Loon winds, however, in the tropics the loon winds and DAS winds often disagree substantially (8 m/s or more in magnitude) and in these cases assimilating the loon winds significantly improves the forecast of the loon winds. By highlighting cases where the Loon and DAS winds differ, these results can lead to improved understanding of stratospheric winds, especially in the tropics.

Assimilation of satellite altimeter data into an open ocean model

Science.gov (United States)

Vogeler, Armin; SchröTer, Jens

1995-08-01

Geosat sea surface height data are assimilated into an eddy-resolving quasi-geostrophic open ocean model using the adjoint technique. The method adjusts the initial conditions for all layers and is successful on the timescale of a few weeks. Time-varying values for the open boundaries are prescribed by a much larger quasi-geostrophic model of the Antarctic Circumpolar Current (ACC). Both models have the same resolution of approximately 20×20 km (1/3°×1/6°), have three layers, and include realistic bottom topography and coastlines. The open model box is embedded in the African sector of the ACC. For continuous assimilation of satellite data into the larger model the nudging technique is applied. These results are used for the adjoint optimization procedure as boundary conditions and as a first guess for the initial condition. For the open model box the difference between model and satellite sea surface height that remains after the nudging experiment amounts to a 19-cm root-mean-square error (rmse). By assimilation into the regional model this value can be reduced to a 6-cm rmse for an assimilation period of 20 days. Several experiments which attempt to improve the convergence of the iterative optimization method are reported. Scaling and regularization by smoothing have to be applied carefully. Especially during the first 10 iterations, the convergence can be improved considerably by low-pass filtering of the cost function gradient. The result of a perturbation experiment shows that for longer assimilation periods the influence of the boundary values becomes dominant and they should be determined inversely by data assimilation into the open ocean model.

Ethnicity, assimilation and harassment in the labor market

OpenAIRE

Epstein, Gil S.; Gang, Ira N.

2008-01-01

We often observe minority ethnic groups at a disadvantage relative to the majority. Why is this and what can be done about it? Efforts made to assimilate, and time, are two elements working to bring the minority into line with the majority. A third element, the degree to which the majority welcomes the minority, also plays a role. We develop a simple theoretical model useful for examining the consequences for assimilation and harassment of growth in the minority population, time, and the role...

Assimilation of SAPHIR radiance: impact on hyperspectral radiances in 4D-VAR

Science.gov (United States)

Indira Rani, S.; Doherty, Amy; Atkinson, Nigel; Bell, William; Newman, Stuart; Renshaw, Richard; George, John P.; Rajagopal, E. N.

2016-04-01

Assimilation of a new observation dataset in an NWP system may affect the quality of an existing observation data set against the model background (short forecast), which in-turn influence the use of an existing observation in the NWP system. Effect of the use of one data set on the use of another data set can be quantified as positive, negative or neutral. Impact of the addition of new dataset is defined as positive if the number of assimilated observations of an existing type of observation increases, and bias and standard deviation decreases compared to the control (without the new dataset) experiment. Recently a new dataset, Megha Tropiques SAPHIR radiances, which provides atmospheric humidity information, is added in the Unified Model 4D-VAR assimilation system. In this paper we discuss the impact of SAPHIR on the assimilation of hyper-spectral radiances like AIRS, IASI and CrIS. Though SAPHIR is a Microwave instrument, its impact can be clearly seen in the use of hyper-spectral radiances in the 4D-VAR data assimilation systems in addition to other Microwave and InfraRed observation. SAPHIR assimilation decreased the standard deviation of the spectral channels of wave number from 650 -1600 cm-1 in all the three hyperspectral radiances. Similar impact on the hyperspectral radiances can be seen due to the assimilation of other Microwave radiances like from AMSR2 and SSMIS Imager.

Are changes in sulfate assimilation pathway needed for evolution of C4 photosynthesis?

Directory of Open Access Journals (Sweden)

Silke Christine Weckopp

2015-01-01

Full Text Available C4 photosynthesis characteristically features a cell-specific localization of enzymes involved in CO2 assimilation in bundle sheath cells or mesophyll cells. Interestingly, enzymes of sulfur assimilation are also specifically present in bundle sheath cells of maize and many other C4 species. This localization, however, could not be confirmed in C4 species of the genus Flaveria. It was, therefore, concluded that the bundle sheath localization of sulfate assimilation occurs only in C4 monocots. However, recently the sulfate assimilation pathway was found coordinately enriched in bundle sheath cells of Arabidopsis, opening new questions about the significance of such cell-specific localization of the pathway. In addition, next generation sequencing revealed expression gradients of many genes from C3 to C4 species and mathematical modelling proposed a sequence of adaptations during the evolutionary path from C3 to C4. Indeed, such gradient, with higher expression of genes for sulfate reduction in C4 species, has been observed within the genus Flaveria. These new tools provide the basis for reexamining the intriguing question of compartmentalization of sulfur assimilation. Therefore, this review summarizes the findings on spatial separation of sulfur assimilation in C4 plants and Arabidopsis, assesses the information on sulfur assimilation provided by the recent transcriptomics data and discusses their possible impact on understanding this interesting feature of plant sulfur metabolism to find out whether changes in sulfate assimilation are part of a general evolutionary trajectory towards C4 photosynthesis.

Assimilation of SMOS Retrievals in the Land Information System

Science.gov (United States)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Kinetics of 15NH4+ assimilation in Zea mays

International Nuclear Information System (INIS)

Magalhaes, J.R.; Ju, G.C.; Rich, P.J.; Rhodes, D.

1990-01-01

Comparative studies of 15 NH 4 + assimilation were undertaken with a GDH1-null mutant of Zea mays and a related (but not strictly isogenic) GDH1-positive wild type from which this mutant was derived. The kinetics of 15 NH 4 + assimilation into free amino acids and total reduced nitrogen were monitored in both roots and shoots of 2-week-old seedlings supplied with 5 millimolar 99% ( 15 NH 4 ) 2 SO 4 via the aerated root medium in hydroponic culture over a 24-h period. The GDH1-null mutant, with a 10- to 15-fold lower total root GDH activity in comparison to the wild type, was found to exhibit a 40 to 50% lower rate of 15 NH 4 + assimilation into total reduced nitrogen. The lower rates of 15 NH 4 + assimilation in the mutant was associated with lower rates of labeling of several free amino acids (including glutamate, glutamine-amino N, aspartate, asparagine-amino N, and alanine) in both roots and shoots of the mutant in comparison to the wild type. Qualitatively, these labeling kinetics appear consistent with a reduced flux of 15 N via glutamate in the GDH1-null mutant. However, the responses of the two genotypes to the potent inhibitor of glutamine synthetase, methionine sulfoximine, and differences in morphology of the two genotypes (particularly a lower shoot:root ratio in the GDH1-null mutant) urge caution in concluding that GDH1 is solely responsible for these differences in ammonia assimilation rate

Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework

Science.gov (United States)

Attada, Raju; Parekh, Anant; Chowdary, J. S.; Gnanaseelan, C.

2018-04-01

This work is the first attempt to produce a multi-year downscaled regional reanalysis of the Indian summer monsoon (ISM) using the National Centers for Environmental Prediction (NCEP) operational analyses and Atmospheric Infrared Sounder (AIRS) version 5 temperature and moisture retrievals in a regional model. Reanalysis of nine monsoon seasons (2003-2011) are produced in two parallel setups. The first set of experiments simply downscale the original NCEP operational analyses, whilst the second one assimilates the AIRS temperature and moisture profiles. The results show better representation of the key monsoon features such as low level jet, tropical easterly jet, subtropical westerly jet, monsoon trough and the spatial pattern of precipitation when AIRS profiles are assimilated (compared to those without AIRS data assimilation). The distribution of temperature, moisture and meridional gradients of dynamical and thermodynamical fields over the monsoon region are better represented in the reanalysis that assimilates AIRS profiles. The change induced by AIRS data on the moist and thermodynamic conditions results in more realistic rendering of the vertical shear associated with the monsoon, which in turn leads to a proper moisture transport and the moist convective feedback. This feedback benefits the representation of the regional monsoon characteristics, the monsoon dynamics and the moist convective processes on the seasonal time scale. This study emphasizes the use of AIRS soundings for downscaling of ISM representation in a regional reanalysis.

Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework

KAUST Repository

Attada, Raju

2017-07-04

This work is the first attempt to produce a multi-year downscaled regional reanalysis of the Indian summer monsoon (ISM) using the National Centers for Environmental Prediction (NCEP) operational analyses and Atmospheric Infrared Sounder (AIRS) version 5 temperature and moisture retrievals in a regional model. Reanalysis of nine monsoon seasons (2003–2011) are produced in two parallel setups. The first set of experiments simply downscale the original NCEP operational analyses, whilst the second one assimilates the AIRS temperature and moisture profiles. The results show better representation of the key monsoon features such as low level jet, tropical easterly jet, subtropical westerly jet, monsoon trough and the spatial pattern of precipitation when AIRS profiles are assimilated (compared to those without AIRS data assimilation). The distribution of temperature, moisture and meridional gradients of dynamical and thermodynamical fields over the monsoon region are better represented in the reanalysis that assimilates AIRS profiles. The change induced by AIRS data on the moist and thermodynamic conditions results in more realistic rendering of the vertical shear associated with the monsoon, which in turn leads to a proper moisture transport and the moist convective feedback. This feedback benefits the representation of the regional monsoon characteristics, the monsoon dynamics and the moist convective processes on the seasonal time scale. This study emphasizes the use of AIRS soundings for downscaling of ISM representation in a regional reanalysis.

Multivariate and multiscale data assimilation in terrestrial systems: a review.

Science.gov (United States)

Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry

2012-11-26

More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review

Directory of Open Access Journals (Sweden)

Harry Vereecken

2012-11-01

Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

Assimilation as Attraction: Computing Distance, Similarity, and Locality in Phonology

Science.gov (United States)

Wayment, Adam

2009-01-01

This dissertation explores similarity effects in assimilation, proposing an Attraction Framework to analyze cases of parasitic harmony where a trigger-target pair only results in harmony if the trigger and target agree on other features. Attraction provides a natural model of these effects by relating the pressure for assimilation to the…

Assimilation of total lightning data using the three-dimensional variational method at convection-allowing resolution

Science.gov (United States)

Zhang, Rong; Zhang, Yijun; Xu, Liangtao; Zheng, Dong; Yao, Wen

2017-08-01

A large number of observational analyses have shown that lightning data can be used to indicate areas of deep convection. It is important to assimilate observed lightning data into numerical models, so that more small-scale information can be incorporated to improve the quality of the initial condition and the subsequent forecasts. In this study, the empirical relationship between flash rate, water vapor mixing ratio, and graupel mixing ratio was used to adjust the model relative humidity, which was then assimilated by using the three-dimensional variational data assimilation system of the Weather Research and Forecasting model in cycling mode at 10-min intervals. To find the appropriate assimilation time-window length that yielded significant improvement in both the initial conditions and subsequent forecasts, four experiments with different assimilation time-window lengths were conducted for a squall line case that occurred on 10 July 2007 in North China. It was found that 60 min was the appropriate assimilation time-window length for this case, and longer assimilation window length was unnecessary since no further improvement was present. Forecasts of 1-h accumulated precipitation during the assimilation period and the subsequent 3-h accumulated precipitation were significantly improved compared with the control experiment without lightning data assimilation. The simulated reflectivity was optimal after 30 min of the forecast, it remained optimal during the following 42 min, and the positive effect from lightning data assimilation began to diminish after 72 min of the forecast. Overall, the improvement from lightning data assimilation can be maintained for about 3 h.

Data assimilation in the decision support system RODOS

International Nuclear Information System (INIS)

Rojas-Palma, C.; Madsen, H.; Gering, F.; Puch, R.; Turcanu, C.; Astrup, P.; Mueller, H.; Richter, K.; Zheleznyak, M.; Treebushny, D.; Kolomeev, M.; Kamaev, D.; Wynn, H.

2003-01-01

Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements, can be used to improve such model predictions. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman filters,are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of the system. This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data. (author)

Dioxin and phthalate uptake and assimilation by the green mussel Perna viridis

International Nuclear Information System (INIS)

Wang, Wen-Xiong; Zhang, Qiong

2013-01-01

In this study, the aqueous uptake and dietary assimilation (trophic transfer) of two endocrine disrupting compounds (dioxin and phathalic acid) in the green mussel Perna viridis were quantified. During short-term exposure period, dioxin rapidly sorbed onto phytoplankton and its accumulation was much higher than that of phthalate. The uptake of these two compounds by the mussels increased with increasing temperature and salinity (for dioxin only). The dietary assimilation of the two contaminants was rather modest (10–64% for dioxin and 20–47% for phthalate), and was greatly dependent on the food species and concentration. Interestingly, dietary assimilation increased with increasing diatom food concentration. Gut passage time was partially responsible for the variable dietary assimilation. Given the high dissolved uptake rate and the modest dietary assimilation, aqueous exposure was predicted to be the dominant bioaccumulation source for both dioxin and phthalate in the green mussels under most conditions. -- Capsule: Aqueous uptake was the predominant pathway for dioxin and phthalate accumulation in marine green mussels

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

Science.gov (United States)

Susskind, Joel; Rosenberg, Robert I.; Iredell, Lena

2015-01-01

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

The structure of a food product assortment modulates the effect of providing choice on food intake.

Science.gov (United States)

Parizel, Odile; Sulmont-Rossé, Claire; Fromentin, Gilles; Delarue, Julien; Labouré, Hélène; Benamouzig, Robert; Marsset-Baglieri, Agnès

2016-09-01

Several authors showed that providing choice may increase food liking and food intake. However, the impact of choice may be modulated by assortment's characteristics, such as the number of alternatives or their dissimilarity. The present study compared the impact of choice on food liking and intake under the two following conditions: (1) when choosing a product to consume from among similar products versus dissimilar products; and (2) when choosing a product to consume from among pleasant products versus unpleasant products. Two experiments were carried out using the same design: the "apple puree" experiment (n = 80), where the volunteers choose from among similar products (apple purees varying in texture) and the "dessert" experiment (n = 80), where the volunteers choose from among dissimilar products (fruit dessert, dairy dessert, custard, pudding). During the first session, participants rated their liking for 12 products (apples purees or desserts). Then the participants were divided into a "pleasant" group (n = 40) in which volunteers were assigned three pleasant products, and an "unpleasant" group (n = 40) in which volunteers were assigned three unpleasant products. Finally, all of the volunteers participated in a choice session - volunteers were presented with their three assigned products and asked to choose one of the products, and a no-choice session - volunteers were served with one product that was randomly selected from among their three assigned products. Providing choice led to an increase in food liking in both experiments and an increase in food intake only for the desserts, namely only when the volunteers chose the product to consume from among "not too similar" alternatives. No effect of assortment's pleasantness was observed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assortative mating and the reversal of gender inequality in education in europe: an agent-based model.

Directory of Open Access Journals (Sweden)

André Grow

Full Text Available While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future.

Assortative mating and the reversal of gender inequality in education in europe: an agent-based model.

Science.gov (United States)

Grow, André; Van Bavel, Jan

2015-01-01

While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of the world. In many countries, women now excel men in terms of participation and success in higher education. This implies that, for the first time in history, there are more highly educated women than men reaching the reproductive ages and looking for a partner. We develop an agent-based computational model that explicates the mechanisms that may have linked the reversal of gender inequality in education with observed changes in educational assortative mating. Our model builds on the notion that individuals search for spouses in a marriage market and evaluate potential candidates based on preferences. Based on insights from earlier research, we assume that men and women prefer partners with similar educational attainment and high earnings prospects, that women tend to prefer men who are somewhat older than themselves, and that men prefer women who are in their mid-twenties. We also incorporate the insight that the educational system structures meeting opportunities on the marriage market. We assess the explanatory power of our model with systematic computational experiments, in which we simulate marriage market dynamics in 12 European countries among individuals born between 1921 and 2012. In these experiments, we make use of realistic agent populations in terms of educational attainment and earnings prospects and validate model outcomes with data from the European Social Survey. We demonstrate that the observed changes in educational assortative mating can be explained without any change in male or female preferences. We argue that our model provides a useful computational laboratory to explore and quantify the implications of scenarios for the future.

Assimilation of wind speed and direction observations: results from real observation experiments

Directory of Open Access Journals (Sweden)

Feng Gao

2015-06-01

Full Text Available The assimilation of wind observations in the form of speed and direction (asm_sd by the Weather Research and Forecasting Model Data Assimilation System (WRFDA was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satellite-derived Atmospheric Motion Vectors (AMV and surface dataset in Meteorological Assimilation Data Ingest System (MADIS were assimilated. This new method takes into account the observation errors of both wind speed (spd and direction (dir, and WRFDA background quality control (BKG-QC influences the choice of wind observations, due to data conversions between (u,v and (spd, dir. The impacts of BKG-QC, as well as the new method, on the wind analysis were analysed separately. Because the dir observational errors produced by different platforms are not known or tuned well in WRFDA, a practical method, which uses similar assimilation weights in comparative trials, was employed to estimate the spd and dir observation errors. The asm_sd produces positive impacts on analyses and short-range forecasts of spd and dir with smaller root-mean-square errors than the u,v-based system. The bias of spd analysis decreases by 54.8%. These improvements result partly from BKG-QC screening of spd and dir observations in a direct way, but mainly from the independent impact of spd (dir data assimilation on spd (dir analysis, which is the primary distinction from the standard WRFDA method. The potential impacts of asm_sd on precipitation forecasts were evaluated. Results demonstrate that the asm_sd is able to indirectly improve the precipitation forecasts by improving the prediction accuracies of key wind-related factors leading to precipitation (e.g. warm moist advection and frontogenesis.

Variational data assimilation schemes for transport and transformation models of atmospheric chemistry

Science.gov (United States)

Penenko, Alexey; Penenko, Vladimir; Tsvetova, Elena; Antokhin, Pavel

2016-04-01

The work is devoted to data assimilation algorithm for atmospheric chemistry transport and transformation models. In the work a control function is introduced into the model source term (emission rate) to provide flexibility to adjust to data. This function is evaluated as the constrained minimum of the target functional combining a control function norm with a norm of the misfit between measured data and its model-simulated analog. Transport and transformation processes model is acting as a constraint. The constrained minimization problem is solved with Euler-Lagrange variational principle [1] which allows reducing it to a system of direct, adjoint and control function estimate relations. This provides a physically-plausible structure of the resulting analysis without model error covariance matrices that are sought within conventional approaches to data assimilation. High dimensionality of the atmospheric chemistry models and a real-time mode of operation demand for computational efficiency of the data assimilation algorithms. Computational issues with complicated models can be solved by using a splitting technique. Within this approach a complex model is split to a set of relatively independent simpler models equipped with a coupling procedure. In a fine-grained approach data assimilation is carried out quasi-independently on the separate splitting stages with shared measurement data [2]. In integrated schemes data assimilation is carried out with respect to the split model as a whole. We compare the two approaches both theoretically and numerically. Data assimilation on the transport stage is carried out with a direct algorithm without iterations. Different algorithms to assimilate data on nonlinear transformation stage are compared. In the work we compare data assimilation results for both artificial and real measurement data. With these data we study the impact of transformation processes and data assimilation to the performance of the modeling system [3]. The

Storm surge model based on variational data assimilation method

Directory of Open Access Journals (Sweden)

Shi-li Huang

2010-06-01

Full Text Available By combining computation and observation information, the variational data assimilation method has the ability to eliminate errors caused by the uncertainty of parameters in practical forecasting. It was applied to a storm surge model based on unstructured grids with high spatial resolution meant for improving the forecasting accuracy of the storm surge. By controlling the wind stress drag coefficient, the variation-based model was developed and validated through data assimilation tests in an actual storm surge induced by a typhoon. In the data assimilation tests, the model accurately identified the wind stress drag coefficient and obtained results close to the true state. Then, the actual storm surge induced by Typhoon 0515 was forecast by the developed model, and the results demonstrate its efficiency in practical application.

Data Assimilation in Hydrodynamic Models of Continental Shelf Seas

DEFF Research Database (Denmark)

Sørensen, Jacob Viborg Tornfeldt

2004-01-01

. Assimilation of sea surface temperature and parameter estimation in hydrodynamic models are also considered. The main focus has been on the development of robust and efficient techniques applicable in real operational settings. The applied assimilation techniques all use a Kalman filter approach. They consist....... The assimilation schemes used in this work are primarily based on two ensemble based schemes, the Ensemble Kalman Filter and the Reduced Rank Square Root Kalman Filter. In order to investigate the applicability of these and derived schemes, the sensitivity to filter parameters, nonlinearity and bias is examined...... in artificial tests. Approximate schemes, which are theoretically presented as using regularised Kalman gains, are introduced and successfully applied in artificial as well real case scenarios. Particularly, distant dependent and slowly time varying or constant Kalman gains are shown to possess good hindcast...

Isolation and characterization of xylitol-assimilating mutants of recombinant Saccharomyces cerevisiae.

Science.gov (United States)

Tani, Tatsunori; Taguchi, Hisataka; Fujimori, Kazuhiro E; Sahara, Takehiko; Ohgiya, Satoru; Kamagata, Yoichi; Akamatsu, Takashi

2016-10-01

To clarify the mechanisms of xylitol utilization, three xylitol-assimilating mutants were isolated from recombinant Saccharomyces cerevisiae strains showing highly efficient xylose-utilization. The nucleotide sequences of the mutant genomes were analyzed and compared with those of the wild-type strains and the mutation sites were identified. gal80 mutations were common to all the mutants, and recessive to the wild-type allele. Hence we constructed a gal80Δ mutant and confirmed that the gal80Δ mutant showed a xylitol-assimilation phenotype. When the constructed gal80Δ mutant was crossed with the three isolated mutants, all diploid hybrids showed xylitol assimilation, indicating that the mutations were all located in the GAL80. We analyzed the role of the galactose permease Gal2, controlled by the regulatory protein Gal80, in assimilating xylitol. A gal2Δ gal80Δ double mutant did not show xylitol assimilation, whereas expression of GAL2 under the control of the TDH3 promoter in the GAL80 strain did result in assimilation. These data indicate that Gal2 was needed for xylitol assimilation in the wild-type strain. When the gal80 mutant with an initial cell concentration of A660 = 20 was used for batch fermentation in a complex medium containing 20 g/L xylose or 20 g/L xylitol at pH 5.0 and 30°C under oxygen limitation, the gal80 mutant consumed 100% of the xylose within 12 h, but xylitol within 100 h, indicating that xylose reductase is required for xylitol consumption in oxygen-limited conditions. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Transportation assimilation revisited: New evidence from repeated cross-sectional survey data

Science.gov (United States)

2018-01-01

Background Based on single cross-sectional data, prior research finds evidence of “transportation assimilation” among U.S. immigrants: the length of stay in the U.S. is negatively correlated with public transit use. This paper revisits this question by using repeated cross-sectional data, and examines the trend of transportation assimilation over time. Methods and results Using 1980, 1990, 2000 1% census and 2010 (1%) American Community Survey, I examine the relationship between the length of stay in the U.S. and public transit ridership among immigrants. I first run regressions separately in four data sets: I regress public transit ridership on the length of stay, controlling for other individual and geographic variables. I then compare the magnitudes of the relationship in four regressions. To study how the rate of transportation assimilation changes over time, I pool the data set and regress public transit ridership on the length of stay and its interactions with year dummies to compare the coefficients across surveys. Results confirm the conclusion of transportation assimilation: as the length of stay in the U.S. increases, an immigrant’s public transit use decreases. However, the repeated cross-section analysis suggests the assimilation rate has been decreasing in the past few decades. Conclusions This paper finds evidence of transportation assimilation: immigrants become less likely to ride public transit as the length of stay in the U.S. increases. The assimilation rate, however, has been decreasing over time. This paper finds that the rate of public transit ridership among new immigrants upon arrival, the geographic distribution of immigrants, and the changing demographics of the U.S. immigrants play roles in affecting the trend of transportation assimilation. PMID:29668676

Effects of Model Chemistry and Data Biases on Stratospheric Ozone Assimilation

National Research Council Canada - National Science Library

Coy, L; Allen, D. R; Eckermann, S. D; McCormack, J. P; Stajner, I; Hogan, T. F

2007-01-01

.... In this study, O-F statistics from the Global Ozone Assimilation Testing System (GOATS) are used to examine how ozone assimilation products and their associated O-F statistics depend on input data biases and ozone photochemistry parameterizations (OPP...

Impact of assimilation window length on diurnal features in a Mars atmospheric analysis

Directory of Open Access Journals (Sweden)

Yongjing Zhao

2015-05-01

Full Text Available Effective simulation of diurnal variability is an important aspect of many geophysical data assimilation systems. For the Martian atmosphere, thermal tides are particularly prominent and contribute much to the Martian atmospheric circulation, dynamics and dust transport. To study the Mars diurnal variability and Mars thermal tides, the Geophysical Fluid Dynamics Laboratory Mars Global Climate Model with the 4D-local ensemble transform Kalman filter (4D-LETKF is used to perform an analysis assimilating spacecraft temperature retrievals. We find that the use of a ‘traditional’ 6-hr assimilation cycle induces spurious forcing of a resonantly enhanced semi-diurnal Kelvin waves represented in both surface pressure and mid-level temperature by forming a wave 4 pattern in the diurnal averaged analysis increment that acts as a ‘topographic’ stationary forcing. Different assimilation window lengths in the 4D-LETKF are introduced to remove the artificially induced resonance. It is found that short assimilation window lengths not only remove the spurious resonance, but also push the migrating semi-diurnal temperature variation at 50 Pa closer to the estimated ‘true’ tides even in the absence of a radiatively active water ice cloud parameterisation. In order to compare the performance of different assimilation window lengths, short-term to mid-range forecasts based on the hour 00 and 12 assimilation are evaluated and compared. Results show that during Northern Hemisphere summer, it is not the assimilation window length, but the radiatively active water ice clouds that influence the model prediction. A ‘diurnal bias correction’ that includes bias correction fields dependent on the local time is shown to effectively reduce the forecast root mean square differences between forecasts and observations, compensate for the absence of water ice cloud parameterisation and enhance Martian atmosphere prediction. The implications of these results for

Impact of GPM Rainrate Data Assimilation on Simulation of Hurricane Harvey (2017)

Science.gov (United States)

Li, Xuanli; Srikishen, Jayanthi; Zavodsky, Bradley; Mecikalski, John

2018-01-01

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM was launched in February 2014 with Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) onboard. The GPM has a broad global coverage approximately 70deg S -70deg N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall To develop methodology to assimilate GPM surface precipitation data with Grid-point Statistical Interpolation (GSI) data assimilation system and WRF ARW model To investigate the potential and the value of utilizing GPM observation into NWP for operational environment The GPM rain rate data has been successfully assimilated using the GSI rain data assimilation package. Impacts of rain rate data have been found in temperature and moisture fields of initial conditions. 2.Assimilation of either GPM IMERG or GPROF rain product produces significant improvement in precipitation amount and structure for Hurricane Harvey (2017) forecast. Since IMERG data is available half-hourly, further forecast improvement is expected with continuous assimilation of IMERG data

Impact of AIRS radiance in the NCUM 4D-VAR assimilation system

Science.gov (United States)

Srinivas, Desamsetti; Indira Rani, S.; Mallick, Swapan; George, John P.; Sharma, Priti

2016-04-01

The hyperspectral radiances from Atmospheric InfraRed Sounder (AIRS), on board NASA-AQUA satellite, have been processed through the Observation Processing System (OPS) and assimilated in the Variational Assimilation (VAR) System of NCMRWF Unified Model (NCUM). Numerical experiments are conducted in order to study the impact of the AIRS radiance in the NCUM analysis and forecast system. NCMRWF receives AIRS radiance from EUMETCAST through MOSDAC. AIRS is a grating spectrometer having 2378 channels covering the thermal infrared spectrum between 3 and 15 μm. Out of 2378 channels, 324 channels are selected for assimilation according to the peaking of weighting function and meteorological importance. According to the surface type and day-night conditions, some of the channels are not assimilated in the VAR. Observation Simulation Experiments (OSEs) are conducted for a period of 15 days to see the impact of AIRS radiances in NCUM. Statistical parameters like bias and RMSE are calculated to see the real impact of AIRS radiances in the assimilation system. Assimilation of AIRS in the NCUM system reduced the bias and RMSE in the radiances from instruments onboard other satellites. The impact of AIRS is clearly seen in the hyperspectral radiances like IASI and CrIS and also in infrared (HIRS) and microwave (AMSU, ATMS, etc.) sensors.

Gender-assortative waist circumference in mother-daughter and father-son pairs, and its implications. An 11-year longitudinal study in children (EarlyBird 59).

Science.gov (United States)

Mostazir, M; Jeffery, A; Voss, L; Wilkin, T

2014-06-01

Body mass index (BMI) is reportedly gender assortative (mother-daughter, father-son) in contemporary children. We investigated the corresponding transmission of waist circumference (WC) and its implications. We measured parental WC at baseline and WC, height, weight and para-umbilical skin-fold (USF) annually in their offspring from 5 to 15 years (n = 223 trios). Parents were deemed normal metabolic risk (NR) or high risk (HR) according to World Health Organization (WHO) cut-points for WC (mothers 80 cm, fathers 94 cm). The residual from WC adjusted for BMI (WC|BMI ) was used as a surrogate for excess intra-abdominal fat, and its association with insulin resistance (HOMA2-IR) was sought. WC and USF were both gender assortative, while WC|BMI was not. WC was greater by 1.62 cm (P mothers, and by 1.32 cm (P surrogate in this analysis) is unrelated to parental waist circumference, but metabolically harmful. © 2013 The Authors. Pediatric Obesity © 2013 International Association for the Study of Obesity.

Data assimilation in integrated hydrological modelling

DEFF Research Database (Denmark)

Rasmussen, Jørn

Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... degree of parameterization which results in significant model uncertainty which cannot be reduced much due to observations often being scarce and often taking the form of point measurements. Data assimilation shows great promise for use in integrated hydrological models , as it allows for observations...... to be efficiently combined with models to improve model predictions, reduce uncertainty and estimate model parameters. In this thesis, a framework for assimilating multiple observation types and updating multiple components and parameters of a catchment scale integrated hydrological model is developed and tested...

Open source data assimilation framework for hydrological modeling

Science.gov (United States)

Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

2013-04-01

An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

Time compression diseconomies in environmental management: the effect of assimilation on environmental performance.

Science.gov (United States)

Lannelongue, Gustavo; Gonzalez-Benito, Javier; Gonzalez-Benito, Oscar; Gonzalez-Zapatero, Carmen

2015-01-01

This research addresses the relationship between an organisation's assimilation of its environmental management system (EMS), the experience it gains through it, and its environmental performance. Assimilation here refers to the degree to which the requirements of the management standard are integrated within a plant's daily operations. Basing ourselves on the heterogeneity of organisations, we argue that assimilation and experience will inform environmental performance. Furthermore, we posit that the relationship between assimilation and environmental performance depends on experience. The attempt to obtain greater assimilation in a shorter time leads an organisation to record a poorer environmental outcome, which we shall refer to as time compression diseconomies in environmental management. We provide empirical evidence based on 154 plants pertaining to firms in Spain subject to the European Union's CO2 Emissions Trading System. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regional Precipitation Forecast with Atmospheric InfraRed Sounder (AIRS) Profile Assimilation

Science.gov (United States)

Chou, S.-H.; Zavodsky, B. T.; Jedloved, G. J.

2010-01-01

Advanced technology in hyperspectral sensors such as the Atmospheric InfraRed Sounder (AIRS; Aumann et al. 2003) on NASA's polar orbiting Aqua satellite retrieve higher vertical resolution thermodynamic profiles than their predecessors due to increased spectral resolution. Although these capabilities do not replace the robust vertical resolution provided by radiosondes, they can serve as a complement to radiosondes in both space and time. These retrieved soundings can have a significant impact on weather forecasts if properly assimilated into prediction models. Several recent studies have evaluated the performance of specific operational weather forecast models when AIRS data are included in the assimilation process. LeMarshall et al. (2006) concluded that AIRS radiances significantly improved 500 hPa anomaly correlations in medium-range forecasts of the Global Forecast System (GFS) model. McCarty et al. (2009) demonstrated similar forecast improvement in 0-48 hour forecasts in an offline version of the operational North American Mesoscale (NAM) model when AIRS radiances were assimilated at the regional scale. Reale et al. (2008) showed improvements to Northern Hemisphere 500 hPa height anomaly correlations in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) global system with the inclusion of partly cloudy AIRS temperature profiles. Singh et al. (2008) assimilated AIRS temperature and moisture profiles into a regional modeling system for a study of a heavy rainfall event during the summer monsoon season in Mumbai, India. This paper describes an approach to assimilate AIRS temperature and moisture profiles into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimensional variational (3DVAR) assimilation system (WRF-Var; Barker et al. 2004). Section 2 describes the AIRS instrument and how the quality indicators are used to intelligently select the highest-quality data for assimilation

Lidar data assimilation for improved analyses of volcanic aerosol events

Science.gov (United States)

Lange, Anne Caroline; Elbern, Hendrik

2014-05-01

Observations of hazardous events with release of aerosols are hardly analyzable by today's data assimilation algorithms, without producing an attenuating bias. Skillful forecasts of unexpected aerosol events are essential for human health and to prevent an exposure of infirm persons and aircraft with possibly catastrophic outcome. Typical cases include mineral dust outbreaks, mostly from large desert regions, wild fires, and sea salt uplifts, while the focus aims for volcanic eruptions. In general, numerical chemistry and aerosol transport models cannot simulate such events without manual adjustments. The concept of data assimilation is able to correct the analysis, as long it is operationally implemented in the model system. Though, the tangent-linear approximation, which describes a substantial precondition for today's cutting edge data assimilation algorithms, is not valid during unexpected aerosol events. As part of the European COPERNICUS (earth observation) project MACC II and the national ESKP (Earth System Knowledge Platform) initiative, we developed a module that enables the assimilation of aerosol lidar observations, even during unforeseeable incidences of extreme emissions of particulate matter. Thereby, the influence of the background information has to be reduced adequately. Advanced lidar instruments comprise on the one hand the aspect of radiative transfer within the atmosphere and on the other hand they can deliver a detailed quantification of the detected aerosols. For the assimilation of maximal exploited lidar data, an appropriate lidar observation operator is constructed, compatible with the EURAD-IM (European Air Pollution and Dispersion - Inverse Model) system. The observation operator is able to map the modeled chemical and physical state on lidar attenuated backscatter, transmission, aerosol optical depth, as well as on the extinction and backscatter coefficients. Further, it has the ability to process the observed discrepancies with lidar

Data Assimilation of Lightning using 1D+3D/4D WRF Var Assimilation Schemes with Non-Linear Observation Operators

Science.gov (United States)

Navon, M. I.; Stefanescu, R.; Fuelberg, H. E.; Marchand, M.

2012-12-01

NASA's launch of the GOES-R Lightning Mapper (GLM) in 2015 will provide continuous, full disc, high resolution total lightning (IC + CG) data. The data will be available at a horizontal resolution of approximately 9 km. Compared to other types of data, the assimilation of lightning data into operational numerical models has received relatively little attention. Previous efforts of lightning assimilation mostly have employed nudging. This paper will describe the implementation of 1D+3D/4D Var assimilation schemes of existing ground-based WTLN (Worldwide Total Lightning Network) lightning observations using non-linear observation operators in the incremental WRFDA system. To mimic the expected output of GLM, the WTLN data were used to generate lightning super-observations characterized by flash rates/81 km2/20 min. A major difficulty associated with variational approaches is the complexity of the observation operator that defines the model equivalent of lightning. We use Convective Available Potential Energy (CAPE) as a proxy between lightning data and model variables. This operator is highly nonlinear. Marecal and Mahfouf (2003) have shown that nonlinearities can prevent direct assimilation of rainfall rates in the ECMWF 4D-VAR (using the incremental formulation proposed by Courtier et al. (1994)) from being successful. Using data from the 2011 Tuscaloosa, AL tornado outbreak, we have proved that the direct assimilation of lightning data into the WRF 3D/4D - Var systems is limited due to this incremental approach. Severe threshold limits must be imposed on the innovation vectors to obtain an improved analysis. We have implemented 1D+3D/4D Var schemes to assimilate lightning observations into the WRF model. Their use avoids innovation vector constrains from preventing the inclusion of a greater number of lightning observations Their use also minimizes the problem that nonlinearities in the moist convective scheme can introduce discontinuities in the cost function

Bias Correction for Assimilation of Retrieved AIRS Profiles of Temperature and Humidity

Science.gov (United States)

Blakenship, Clay; Zavodsky, Bradley; Blackwell, William

2014-01-01

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral radiometer aboard NASA's Aqua satellite designed to measure atmospheric profiles of temperature and humidity. AIRS retrievals are assimilated into the Weather Research and Forecasting (WRF) model over the North Pacific for some cases involving "atmospheric rivers". These events bring a large flux of water vapor to the west coast of North America and often lead to extreme precipitation in the coastal mountain ranges. An advantage of assimilating retrievals rather than radiances is that information in partly cloudy fields of view can be used. Two different Level 2 AIRS retrieval products are compared: the Version 6 AIRS Science Team standard retrievals and a neural net retrieval from MIT. Before assimilation, a bias correction is applied to adjust each layer of retrieved temperature and humidity so the layer mean values agree with a short-term model climatology. WRF runs assimilating each of the products are compared against each other and against a control run with no assimilation. Forecasts are against ERA reanalyses.

An integrated GIS application system for soil moisture data assimilation

Science.gov (United States)

Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

2014-11-01

The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

Science.gov (United States)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

Studies on translocation of tritiated assimilates into potatoes and wheat grains

International Nuclear Information System (INIS)

Mueller, J.; Diabate, S.; Strack, S.; Raskob, W.

1993-01-01

Tritium released in the enviroment may be converted to organically bound tritium (OBT), mainly by photosynthesis in green leaves. Tritiated assimilates can be translocated from leaves to storage organs of crop plants. This should be considered in models calculating the dose due to the ingestion pathway. This paper describes experiments with wheat and potatoes, which have been designed to study the translocation of tritiated assimilates. Additionally, gas exchange measurements have been performed with the leaves of those plants. A model has been developed to estimate the generation of OBT and the translocation of tritiated assimilates into edible plant parts. (orig.) [de

Data assimilation of GNSS zenith total delays from a Nordic processing centre

Science.gov (United States)

Lindskog, Magnus; Ridal, Martin; Thorsteinsson, Sigurdur; Ning, Tong

2017-11-01

Atmospheric moisture-related information estimated from Global Navigation Satellite System (GNSS) ground-based receiver stations by the Nordic GNSS Analysis Centre (NGAA) have been used within a state-of-the-art kilometre-scale numerical weather prediction system. Different processing techniques have been implemented to derive the moisture-related GNSS information in the form of zenith total delays (ZTDs) and these are described and compared. In addition full-scale data assimilation and modelling experiments have been carried out to investigate the impact of utilizing moisture-related GNSS data from the NGAA processing centre on a numerical weather prediction (NWP) model initial state and on the ensuing forecast quality. The sensitivity of results to aspects of the data processing, station density, bias-correction and data assimilation have been investigated. Results show benefits to forecast quality when using GNSS ZTD as an additional observation type. The results also show a sensitivity to thinning distance applied for GNSS ZTD observations but not to modifications to the number of predictors used in the variational bias correction applied. In addition, it is demonstrated that the assimilation of GNSS ZTD can benefit from more general data assimilation enhancements and that there is an interaction of GNSS ZTD with other types of observations used in the data assimilation. Future plans include further investigation of optimal thinning distances and application of more advanced data assimilation techniques.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

Science.gov (United States)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

CUMULATE ROCKS ASSOCIATED WITH CARBONATE ASSIMILATION, HORTAVÆR COMPLEX, NORTH-CENTRAL NORWAY

Science.gov (United States)

Barnes, C. G.; Prestvik, T.; Li, Y.

2009-12-01

The Hortavær igneous complex intruded high-grade metamorphic rocks of the Caledonian Helgeland Nappe Complex at ca. 466 Ma. The complex is an unusual mafic-silicic layered intrusion (MASLI) because the principal felsic rock type is syenite and because the syenite formed in situ rather than by deep-seated partial melting of crustal rocks. Magma differentiation in the complex was by assimilation, primarily of calc-silicate rocks and melts with contributions from marble and semi-pelites, plus fractional crystallization. The effect of assimilation of calcite-rich rocks was to enhance stability of fassaitic clinopyroxene at the expense of olivine, which resulted in alkali-rich residual melts and lowering of silica activity. This combination of MASLI-style emplacement and carbonate assimilation produced three types of cumulate rocks: (1) Syenitic cumulates formed by liquid-crystal separation. As sheets of mafic magma were loaded on crystal-rich syenitic magma, residual liquid was expelled, penetrating the overlying mafic sheets in flame structures, and leaving a cumulate syenite. (2) Reaction cumulates. Carbonate assimilation, illustrated by a simple assimilation reaction: olivine + calcite + melt = clinopyroxene + CO2 resulted in cpx-rich cumulates such as clinopyroxenite, gabbro, and mela-monzodiorite, many of which contain igneous calcite. (3) Magmatic skarns. Calc-silicate host rocks underwent partial melting during assimilation, yielding a Ca-rich melt as the principal assimilated material and permitting extensive reaction with surrounding magma to form Kspar + cpx + garnet-rich ‘cumulate’ rocks. Cumulate types (2) and (3) do not reflect traditional views of cumulate rocks but instead result from a series of melt-present discontinuous (peritectic) reactions and partial melting of calc-silicate xenoliths. In the Hortavær complex, such cumulates are evident because of the distinctive peritectic cumulate assemblages. It is unclear whether assimilation of �

Probabilistic forecasting and Bayesian data assimilation

CERN Document Server

Reich, Sebastian

2015-01-01

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...

Snowpack modeling in the context of radiance assimilation for snow water equivalent mapping

Science.gov (United States)

Durand, M. T.; Kim, R. S.; Li, D.; Dumont, M.; Margulis, S. A.

2017-12-01

Data assimilation is often touted as a means of overcoming deficiences in both snowpack modeling and snowpack remote sensing. Direct assimilation of microwave radiances, rather than assimilating microwave retrievals, has shown promise, in this context. This is especially the case for deep mountain snow, which is often assumed to be infeasible to measure with microwave measurements, due to saturation issues. We first demonstrate that the typical way of understanding saturation has often been misunderstood. We show that deep snow leads to a complex microwave signature, but not to saturation per se, because of snowpack stratigraphy. This explains why radiance assimilation requires detailed snowpack models that adequatley stratgigraphy to function accurately. We examine this with two case studies. First, we show how the CROCUS predictions of snowpack stratigraphy allows for assimilation of airborne passive microwave measurements over three 1km2 CLPX Intensive Study Areas. Snowpack modeling and particle filter analysis is performed at 120 m spatial resolution. When run without the benefit of radiance assimilation, CROCUS does not fully capture spatial patterns in the data (R2=0.44; RMSE=26 cm). Assimlilation of microwave radiances for a single flight recovers the spatial pattern of snow depth (R2=0.85; RMSE = 13 cm). This is despite the presence of deep snow; measured depths range from 150 to 325 cm. Adequate results are obtained even for partial forest cover, and bias in precipitation forcing. The results are severely degraded if a three-layer snow model is used, however. The importance of modeling snowpack stratigraphy is highlighted. Second, we compare this study to a recent analysis assimilating spaceborne radiances for a 511 km2 sub-watershed of the Kern River, in the Sierra Nevada. Here, the daily Level 2A AMSR-E footprints (88 km2) are assimilated into a model running at 90 m spatial resolution. The three-layer model is specially adapted to predict "effective

Becoming a vampire without being bitten: the narrative collective-assimilation hypothesis.

Science.gov (United States)

Gabriel, Shira; Young, Ariana F

2011-08-01

We propose the narrative collective-assimilation hypothesis--that experiencing a narrative leads one to psychologically become a part of the collective described within the narrative. In a test of this hypothesis, participants read passages from either a book about wizards (from the Harry Potter series) or a book about vampires (from the Twilight series). Both implicit and explicit measures revealed that participants who read about wizards psychologically became wizards, whereas those who read about vampires psychologically became vampires. The results also suggested that narrative collective assimilation is psychologically meaningful and relates to the basic human need for connection. Specifically, the tendency to fulfill belongingness needs through group affiliation moderated the extent to which narrative collective assimilation occurred, and narrative collective assimilation led to increases in life satisfaction and positive mood, two primary outcomes of belonging. The implications for the importance of narratives, the need to belong to groups, and social surrogacy are discussed.

A new air quality modelling approach at the regional scale using lidar data assimilation

International Nuclear Information System (INIS)

Wang, Y.

2013-01-01

Assimilation of lidar observations for air quality modelling is investigated via the development of a new model, which assimilates ground-based lidar network measurements using optimal interpolation (OI) in a chemistry transport model. First, a tool for assimilating PM 10 (particulate matter with a diameter lower than 10 μm) concentration measurements on the vertical is developed in the air quality modelling platform POLYPHEMUS. It is applied to western Europe for one month from 15 July to 15 August 2001 to investigate the potential impact of future ground-based lidar networks on analysis and short-term forecasts (the description of the future) of PM 10 . The efficiency of assimilating lidar network measurements is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. A sensitivity study on the number and location of required lidars is also performed to help define an optimal lidar network for PM 10 forecasts. Secondly, a new model for simulating normalised lidar signals (PR 2 ) is developed and integrated in POLYPHEMUS. Simulated lidar signals are compared to hourly ground-based mobile and in-situ lidar observations performed during the MEGAPOLI (Mega-cities: Emissions, urban, regional and Global Atmospheric Pollution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. It is found that the model correctly reproduces the vertical distribution of aerosol optical properties and their temporal variability. Additionally, two new algorithms for assimilating lidar signals are presented and evaluated during MEGAPOLI. The aerosol simulations without and with lidar data assimilation are evaluated using the AIRPARIF (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and the usefulness of assimilating lidar profiles for aerosol forecasts. Finally

Nocturnal uptake and assimilation of nitrogen dioxide by C3 and CAM plants.

Science.gov (United States)

Takahashi, Misa; Konaka, Daisuke; Sakamoto, Atsushi; Morikawa, Hiromichi

2005-01-01

In order to investigate nocturnal uptake and assimilation of NO2 by C3 and crassulacean acid metabolism (CAM) plants, they were fumigated with 4 microl l(-1) 15N-labeled nitrogen dioxide (NO2) for 8 h. The amount of NO2 and assimilation of NO2 by plants were determined by mass spectrometry and Kjeldahl-nitrogen based mass spectrometry, respectively. C3 plants such as kenaf (Hibiscus cannabinus), tobacco (Nicotiana tabacum) and ground cherry (Physalis alkekengi) showed a high uptake and assimilation during daytime as high as 1100 to 2700 ng N mg(-1) dry weight. While tobacco and ground cherry strongly reduced uptake and assimilation of NO2 during nighttime, kenaf kept high nocturnal uptake and assimilation of NO2 as high as about 1500 ng N mg(-1) dry weight. Stomatal conductance measurements indicated that there were no significant differences to account for the differences in the uptake of NO2 by tobacco and kenaf during nighttime. CAM plants such as Sedum sp., Kalanchoe blossfeldiana (kalanchoe) and Aloe arborescens exhibited nocturnal uptake and assimilation of NO2. However, the values of uptake and assimilation of NO2 both during daytime and nighttime was very low (at most about 500 ng N mg(-1) dry weight) as compared with those of above mentioned C3 plants. The present findings indicate that kenaf is an efficient phytoremediator of NO2 both during daytime and nighttime.

Sequential assimilation of multi-mission dynamical topography into a global finite-element ocean model

Directory of Open Access Journals (Sweden)

S. Skachko

2008-12-01

Full Text Available This study focuses on an accurate estimation of ocean circulation via assimilation of satellite measurements of ocean dynamical topography into the global finite-element ocean model (FEOM. The dynamical topography data are derived from a complex analysis of multi-mission altimetry data combined with a referenced earth geoid. The assimilation is split into two parts. First, the mean dynamic topography is adjusted. To this end an adiabatic pressure correction method is used which reduces model divergence from the real evolution. Second, a sequential assimilation technique is applied to improve the representation of thermodynamical processes by assimilating the time varying dynamic topography. A method is used according to which the temperature and salinity are updated following the vertical structure of the first baroclinic mode. It is shown that the method leads to a partially successful assimilation approach reducing the rms difference between the model and data from 16 cm to 2 cm. This improvement of the mean state is accompanied by significant improvement of temporal variability in our analysis. However, it remains suboptimal, showing a tendency in the forecast phase of returning toward a free run without data assimilation. Both the mean difference and standard deviation of the difference between the forecast and observation data are reduced as the result of assimilation.

Assimilation of ASCAT near-surface soil moisture into the French SIM hydrological model

Science.gov (United States)

Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.

2011-06-01

The impact of assimilating near-surface soil moisture into the SAFRAN-ISBA-MODCOU (SIM) hydrological model over France is examined. Specifically, the root-zone soil moisture in the ISBA land surface model is constrained over three and a half years, by assimilating the ASCAT-derived surface degree of saturation product, using a Simplified Extended Kalman Filter. In this experiment ISBA is forced with the near-real time SAFRAN analysis, which analyses the variables required to force ISBA from relevant observations available before the real time data cut-off. The assimilation results are tested against ISBA forecasts generated with a higher quality delayed cut-off SAFRAN analysis. Ideally, assimilating the ASCAT data will constrain the ISBA surface state to correct for errors in the near-real time SAFRAN forcing, the most significant of which was a substantial dry bias caused by a dry precipitation bias. The assimilation successfully reduced the mean root-zone soil moisture bias, relative to the delayed cut-off forecasts, by close to 50 % of the open-loop value. The improved soil moisture in the model then led to significant improvements in the forecast hydrological cycle, reducing the drainage, runoff, and evapotranspiration biases (by 17 %, 11 %, and 70 %, respectively). When coupled to the MODCOU hydrogeological model, the ASCAT assimilation also led to improved streamflow forecasts, increasing the mean discharge ratio, relative to the delayed cut off forecasts, from 0.68 to 0.76. These results demonstrate that assimilating near-surface soil moisture observations can effectively constrain the SIM model hydrology, while also confirming the accuracy of the ASCAT surface degree of saturation product. This latter point highlights how assimilation experiments can contribute towards the difficult issue of validating remotely sensed land surface observations over large spatial scales.

Volcanic Ash Data Assimilation System for Atmospheric Transport Model

Science.gov (United States)

Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

2017-12-01

The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

Data Assimilation - Advances and Applications

Energy Technology Data Exchange (ETDEWEB)

Williams, Brian J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2014-07-30

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batch sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.

A coherent structure approach for parameter estimation in Lagrangian Data Assimilation

Science.gov (United States)

Maclean, John; Santitissadeekorn, Naratip; Jones, Christopher K. R. T.

2017-12-01

We introduce a data assimilation method to estimate model parameters with observations of passive tracers by directly assimilating Lagrangian Coherent Structures. Our approach differs from the usual Lagrangian Data Assimilation approach, where parameters are estimated based on tracer trajectories. We employ the Approximate Bayesian Computation (ABC) framework to avoid computing the likelihood function of the coherent structure, which is usually unavailable. We solve the ABC by a Sequential Monte Carlo (SMC) method, and use Principal Component Analysis (PCA) to identify the coherent patterns from tracer trajectory data. Our new method shows remarkably improved results compared to the bootstrap particle filter when the physical model exhibits chaotic advection.

IMITATING MODEL OF ASSIMILATION AND FORGETTING OF THE LOGICALLY CONNECTED INFORMATION

Directory of Open Access Journals (Sweden)

Robert Valerievich Mayer

2017-09-01

Full Text Available The educational material we present as a set of a number of information blocks consisting of learning material elements (LMEs; therefore its assimilation and forgetting occurs differently, than in the Ebbinghaus’s experiments. The purpose of the article is constructing of a computer model of assimilation and forgetting of the logically connected information allowing: 1 to prove the fast rise of understanding while training; 2 to receive the forgetting curve for the comprehended information. The modeling methods help to receive the graphs of the knowledge level dependence on time. It is shown, that the processes of assimilation and forgetting occurs according to the logistic law.

Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission

Directory of Open Access Journals (Sweden)

A. F. Arellano Jr.

2007-11-01

Full Text Available We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3 with simplified chemistry and the Data Assimilation Research Testbed (DART assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT satellite instrument. We verify the system performance using independent CO observations taken on board the NSF/NCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B. Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence. The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (~140 ppbv. Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements.

Downscaling the 2D Bénard convection equations using continuous data assimilation

KAUST Repository

Altaf, Muhammad; Titi, E. S.; Gebrael, T.; Knio, Omar; Zhao, L.; McCabe, Matthew; Hoteit, Ibrahim

2017-01-01

We consider a recently introduced continuous data assimilation (CDA) approach for downscaling a coarse resolution configuration of the 2D Bénard convection equations into a finer grid. In this CDA, a nudging term, estimated as the misfit between some interpolants of the assimilated coarse-grid measurements and the fine-grid model solution, is added to the model equations to constrain the model. The main contribution of this study is a performance analysis of CDA for downscaling measurements of temperature and velocity. These measurements are assimilated either separately or simultaneously, and the results are compared against those resulting from the standard point-to-point nudging approach (NA). Our numerical results suggest that the CDA solution outperforms that of NA, always converging to the true solution when the velocity is assimilated as has been theoretically proven. Assimilation of temperature measurements only may not always recover the true state as demonstrated in the case study. Various runs are conducted to evaluate the sensitivity of CDA to noise in the measurements, the size, and the time frequency of the measured grid, suggesting a more robust behavior of CDA compared to that of NA.

Downscaling the 2D Bénard convection equations using continuous data assimilation

KAUST Repository

Altaf, Muhammad

2017-02-27

We consider a recently introduced continuous data assimilation (CDA) approach for downscaling a coarse resolution configuration of the 2D Bénard convection equations into a finer grid. In this CDA, a nudging term, estimated as the misfit between some interpolants of the assimilated coarse-grid measurements and the fine-grid model solution, is added to the model equations to constrain the model. The main contribution of this study is a performance analysis of CDA for downscaling measurements of temperature and velocity. These measurements are assimilated either separately or simultaneously, and the results are compared against those resulting from the standard point-to-point nudging approach (NA). Our numerical results suggest that the CDA solution outperforms that of NA, always converging to the true solution when the velocity is assimilated as has been theoretically proven. Assimilation of temperature measurements only may not always recover the true state as demonstrated in the case study. Various runs are conducted to evaluate the sensitivity of CDA to noise in the measurements, the size, and the time frequency of the measured grid, suggesting a more robust behavior of CDA compared to that of NA.

Biomass assimilation in coupled ecohydrodynamical model of the Mediterranean Sea

Science.gov (United States)

Crispi, G.; Bournaski, E.; Crise, A.

2003-04-01

Data assimilation has raised new interest in the last years in the context of the environmental sciences. The swift increment of the attention paid to it in oceanography is due to the coming age of operational services for the marine environment which is going to dramatically increase the demand for accurate, timely and reliable estimates of the space and time distribution both for physical and in a near future for biogeochemical fields. Data assimilation combines information derived from measurements with knowledge of the rules that govern the evolution of the system of interest through formalization and implementation in numerical models. The importance of ocean data assimilation has been recognized by several international programmes as JGOFS, GOOS and CLIVAR. This work presents an eco-hydrodynamic model of the Mediterranean Sea developed at the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS, Trieste, Italy. It includes 3-D MOM-based hydrodynamics of the Mediterranean Sea, coupled with biochemical model of Nitrogen, Phytoplankton, Zooplankton, and Detritus (NPZD). Monthly mean wind forcings are adopted to force this MOM-NPZD model. For better prediction and analysis of N, P, Z and D distributions in the sea the model needs data assimilation from biomass observations on the sea surface. Chosen approach for evaluating performances of data assimilation techniques in coupled model is the definition of a twin experiment testbed where a reference run is carried out assuming its result as the truth. We define a sampling strategy to obtain different datasets to be incorporated in another ecological model in successive runs in order to appraise the potential of the data assimilation and sampling strategy. The runs carried out with different techniques and different spatio-temporal coverages are compared in order to evaluate the sensitivity to different coverage of dataset. The discussed alternative way is to assume the ecosystem at steady state and

Educational Attainment Influences Levels of Homozygosity through Migration and Assortative Mating

Science.gov (United States)

Abdellaoui, Abdel; Hottenga, Jouke-Jan; Willemsen, Gonneke; Bartels, Meike; van Beijsterveldt, Toos; Ehli, Erik A.; Davies, Gareth E.; Brooks, Andrew; Sullivan, Patrick F.; Penninx, Brenda W. J. H.; de Geus, Eco J.; Boomsma, Dorret I.

2015-01-01

Individuals with a higher education are more likely to migrate, increasing the chance of meeting a spouse with a different ancestral background. In this context, the presence of strong educational assortment can result in greater ancestry differences within more educated spouse pairs, while less educated individuals are more likely to mate with someone with whom they share more ancestry. We examined the association between educational attainment and F roh (= the proportion of the genome consisting of runs of homozygosity [ROHs]) in ~2,000 subjects of Dutch ancestry. The subjects’ own educational attainment showed a nominally significant negative association with F roh (p = .045), while the contribution of parental education to offspring F roh was highly significant (father: p migration rates among more educated parents. Parental education also showed a high spouse correlation (Spearman’s ρ = .66, p = 3 × 10-262). We show that less educated parents are less likely to mate with the more mobile parents with a higher education, creating systematic differences in homozygosity due to ancestry differences not directly captured by ancestry-informative principal components (PCs). Understanding how behaviors influence the genomic structure of a population is highly valuable for studies on the genetic etiology of behavioral, cognitive, and social traits. PMID:25734509

A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

Science.gov (United States)

Li, Yi; Toumi, Ralf

2017-08-01

In this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.

Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

Science.gov (United States)

Susskind, Joel; Reale, Oreste

2009-01-01

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

Science.gov (United States)

Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

2015-04-01

Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi

Error Covariance Estimation of Mesoscale Data Assimilation

National Research Council Canada - National Science Library

Xu, Qin

2005-01-01

The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...

Manufacturer and retailer brands in food retail assortments: Notes from a shopping trip across Europe

DEFF Research Database (Denmark)

Esbjerg, Lars; Grunert, Klaus G.; Bech-Larsen, Tino

and perform a variety of activities and services, which provide added value in the eyes of consumers (Burt 2000). In this connection, branding is becoming increasingly important, as food retailers develop their own brands within and across product categories. Many retailers are attempting to cultivate...... an overall brand identity in order to protect and identify their market offering (Burt & Sparks 2002). The assortment of products food retailers offer typically includes manufacturer brands, re-tailer brands and generic or unbranded products. In recent years, increasing competition in food retailing has made...... retailers is discussed. Then, the findings from a shopping trip across Europe are presented. Finally, a discussion of the findings is provided and it is briefly considered how the findings of this study were used as input for a study of consumer perceptions of the brand architectures of food retailers...

Translocation and distribution of 14C-assimilation products in soybeans with different growth property

International Nuclear Information System (INIS)

Yoshida, Koichi; Gotoh, Kanji

1975-01-01

To 3 different kinds of soybeans, Tokachinagaha (Determinate), Koganejiro (Intermediate), and Harosoy (Indeterminate), 14 C was given at 3 stages of growth, namely, initial flowering, young pod development, and seed fattening periods. The 14 C assimilation efficiency, namely, the value of total 14 C assimilated divided by the area of the leaves which assimilated 14 C, was large when the leaf area was small. The value decreased with the increase of the leaf area. The rate of translocation of 14 C assimilation products was 20-50% in the period of initial flowering. The rate was highest in Tokachinagaha, followed by Koganejiro and Harosoy in this order. The difference was small in the period of young pod development. In the period of initial flowering, the distribution of 14 C to lower leaves and branches was high in Harosoy. In the period of young pod development, 30-40% of the assimilated 14 C was found in stems. This distribution is possibly due to temporary storage. In the period of seed fattening, 80-90% of the assimilated 14 C was present in pods and seeds. It was then concluded that the movement of assimilated products is high in the determinate type in the initial growth period. In the seed fattening period, the rate is high in the indeterminate type soy beans. (Fukutomi, T.)

Data assimilation for air quality models

DEFF Research Database (Denmark)

Silver, Jeremy David

2014-01-01

-dimensional optimal interpolation procedure (OI), an Ensemble Kalman Filter (EnKF), and a three-dimensional variational scheme (3D-var). The three assimilation procedures are described and tested. A multi-faceted approach is taken for the verification, using independent measurements from surface air-quality...

The coupling of high-speed high resolution experimental data and LES through data assimilation techniques

Science.gov (United States)

Harris, S.; Labahn, J. W.; Frank, J. H.; Ihme, M.

2017-11-01

Data assimilation techniques can be integrated with time-resolved numerical simulations to improve predictions of transient phenomena. In this study, optimal interpolation and nudging are employed for assimilating high-speed high-resolution measurements obtained for an inert jet into high-fidelity large-eddy simulations. This experimental data set was chosen as it provides both high spacial and temporal resolution for the three-component velocity field in the shear layer of the jet. Our first objective is to investigate the impact that data assimilation has on the resulting flow field for this inert jet. This is accomplished by determining the region influenced by the data assimilation and corresponding effect on the instantaneous flow structures. The second objective is to determine optimal weightings for two data assimilation techniques. The third objective is to investigate how the frequency at which the data is assimilated affects the overall predictions. Graduate Research Assistant, Department of Mechanical Engineering.

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

Science.gov (United States)

Blakenship, Clay; Zavodsky, Bradley; Cae, Jonathan

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Nonlinear problems in data-assimilation : Can synchronization help?

Science.gov (United States)

Tribbia, J. J.; Duane, G. S.

2009-12-01

Over the past several years, operational weather centers have initiated ensemble prediction and assimilation techniques to estimate the error covariance of forecasts in the short and the medium range. The ensemble techniques used are based on linear methods. The theory This technique s been shown to be a useful indicator of skill in the linear range where forecast errors are small relative to climatological variance. While this advance has been impressive, there are still ad hoc aspects of its use in practice, like the need for covariance inflation which are troubling. Furthermore, to be of utility in the nonlinear range an ensemble assimilation and prediction method must be capable of giving probabilistic information for the situation where a probability density forecast becomes multi-modal. A prototypical, simplest example of such a situation is the planetary-wave regime transition where the pdf is bimodal. Our recent research show how the inconsistencies and extensions of linear methodology can be consistently treated using the paradigm of synchronization which views the problems of assimilation and forecasting as that of optimizing the forecast model state with respect to the future evolution of the atmosphere.

Data assimilation and model evaluation experiment datasets

Science.gov (United States)

Lai, Chung-Cheng A.; Qian, Wen; Glenn, Scott M.

1994-01-01

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Probability Maps for the Visualization of Assimilation Ensemble Flow Data

KAUST Repository

Hollt, Thomas

2015-05-25

Ocean forecasts nowadays are created by running ensemble simulations in combination with data assimilation techniques. Most of these techniques resample the ensemble members after each assimilation cycle. This means that in a time series, after resampling, every member can follow up on any of the members before resampling. Tracking behavior over time, such as all possible paths of a particle in an ensemble vector field, becomes very difficult, as the number of combinations rises exponentially with the number of assimilation cycles. In general a single possible path is not of interest but only the probabilities that any point in space might be reached by a particle at some point in time. In this work we present an approach using probability-weighted piecewise particle trajectories to allow such a mapping interactively, instead of tracing quadrillions of individual particles. We achieve interactive rates by binning the domain and splitting up the tracing process into the individual assimilation cycles, so that particles that fall into the same bin after a cycle can be treated as a single particle with a larger probability as input for the next time step. As a result we loose the possibility to track individual particles, but can create probability maps for any desired seed at interactive rates.

Judge me, judge me not: The role of eye size and observer gender on acquaintance rape

Directory of Open Access Journals (Sweden)

María Clara Ferrão

2016-01-01

Full Text Available The purpose of this study was to examine the effect of eye size and observer gender on perceived initial attraction, honesty, and attributions of responsibility for rape. A 3 (eye size: small vs. normal vs. large x 2 (observer gender: female vs. male experimental design was tested. Ninety participants (45 women and 45 men observed one of three randomly assigned female faces (with eye size manipulation, and rated initial attraction and honesty. They were then asked to read an acquaintance rape scenario with a traditional woman, rating the victim and perpetrator responsibility. Eye size was shown to affect all the study variables: the female face with large eyes was seen as more attractive and honest, was held less responsible for her own victimization, and the offender was held more responsible. Gender was proven to affect perceived initial attraction and victim responsibility. Theoretical and práctical implications were discussed.

Improving operational flood forecasting through data assimilation

Science.gov (United States)

Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

2010-05-01

Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial

The OSSE Framework at the NASA Global Modeling and Assimilation Office (GMAO)

Science.gov (United States)

Moradi, I.; Prive, N.; McCarty, W.; Errico, R. M.; Gelaro, R.

2017-12-01

This abstract summarizes the OSSE framework developed at the Global Modeling and Assimilation Office at the National Aeronautics and Space Administration (NASA/GMAO). Some of the OSSE techniques developed at GMAO including simulation of realistic observations, e.g., adding errors to simulated observations, are now widely used by the community to evaluate the impact of new observations on the weather forecasts. This talk presents some of the recent progresses and challenges in simulating realistic observations, radiative transfer modeling support for the GMAO OSSE activities, assimilation of OSSE observations into data assimilation systems, and evaluating the impact of simulated observations on the forecast skills.

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

Science.gov (United States)

Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

2018-03-01

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

Distribution and utilization of 14C-labelled assimilate in debranched soybeans

International Nuclear Information System (INIS)

Kokubun, Makie; Asahi, Yukimitsu

1985-01-01

Effects of debranching of soybean plants on the distribution and utilization of 14 C assimilate were studied. Leaves at different positions in the canopy were allowed to assimilate 14 CO 2 either at early flowering, at early pod growth, or at early pod-filling stage. Radioactivity at 24 hours or 7 days after labelling was measured in the component parts. Debranching increased the dry weight of the main stem resulting from greater increase at the lower section of the stem. The debranched plants had the leaves of higher assimilatory efficiency and delayed senescence. The leaves at lower position of the debranched plants exported 14 C less at flowering but more at early pod growth than those of controls. When 14 C was incorporated from upper leaves, the difference in the distribution pattern between the debranched and control plants was little. A greater portion of 14 C assimilate fixed at the lower leaves of the debranched plants was present at pods and stem + petioles of the lower section, in contrast to those of controls which exported some of the assimilate to the branches. Lower leaves of the debranched plants remained active even during pod growth stage, and a part of the fixed 14 C was translocated slowly into the root. The pattern of distribution and utilization of assimilate in debranched soybeans may account for the adaptability of the main stem type to higher planting density. (author)

Data Assimilation by delay-coordinate nudging

Science.gov (United States)

Pazo, Diego; Lopez, Juan Manuel; Carrassi, Alberto

2016-04-01

A new nudging method for data assimilation, delay-coordinate nudging, is presented. Delay-coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time-step. Numerical experiments with a low order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an un-optimized formulation of the delay-nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay-coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal-to-decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures.

Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

Science.gov (United States)

Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

2018-03-01

Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

Sensitivity of Satellite Altimetry Data Assimilation on a Weapon Acoustic Preset Using MODAS

National Research Council Canada - National Science Library

Chu, Peter; Mancini, Steven; Gottshall, Eric; Cwalina, David; Barron, Charlie N

2007-01-01

...) is analyzed with SSP derived from the modular ocean data assimilation system (MODAS). The MODAS fields differ in that one uses altimeter data assimilated from three satellites while the other uses no altimeter data...

Application of data assimilation methods for analysis and integration of observed and modeled Arctic Sea ice motions

Science.gov (United States)

Meier, Walter Neil

This thesis demonstrates the applicability of data assimilation methods to improve observed and modeled ice motion fields and to demonstrate the effects of assimilated motion on Arctic processes important to the global climate and of practical concern to human activities. Ice motions derived from 85 GHz and 37 GHz SSM/I imagery and estimated from two-dimensional dynamic-thermodynamic sea ice models are compared to buoy observations. Mean error, error standard deviation, and correlation with buoys are computed for the model domain. SSM/I motions generally have a lower bias, but higher error standard deviations and lower correlation with buoys than model motions. There are notable variations in the statistics depending on the region of the Arctic, season, and ice characteristics. Assimilation methods are investigated and blending and optimal interpolation strategies are implemented. Blending assimilation improves error statistics slightly, but the effect of the assimilation is reduced due to noise in the SSM/I motions and is thus not an effective method to improve ice motion estimates. However, optimal interpolation assimilation reduces motion errors by 25--30% over modeled motions and 40--45% over SSM/I motions. Optimal interpolation assimilation is beneficial in all regions, seasons and ice conditions, and is particularly effective in regimes where modeled and SSM/I errors are high. Assimilation alters annual average motion fields. Modeled ice products of ice thickness, ice divergence, Fram Strait ice volume export, transport across the Arctic and interannual basin averages are also influenced by assimilated motions. Assimilation improves estimates of pollutant transport and corrects synoptic-scale errors in the motion fields caused by incorrect forcings or errors in model physics. The portability of the optimal interpolation assimilation method is demonstrated by implementing the strategy in an ice thickness distribution (ITD) model. This research presents an

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

Science.gov (United States)

Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

2006-01-01

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

Science.gov (United States)

Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

2018-03-01

An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

Impact of Information Incongruity and Authors Group Membership on Assimilation and Accommodation

Science.gov (United States)

Moskaliuk, J.; Matschke, C.

2018-01-01

Learning is a complex process that can be differentiated into assimilation and accommodation. The Internet enables both types of learning through collaboration. There is, however, little research investigating the specific impact of social and information incongruity on assimilation and accommodation. The current research investigates how the…

Data assimilation in the hydrological dispersion module of Rodos

International Nuclear Information System (INIS)

Madsen, H.

2003-01-01

Full text: The Hydrological Dispersion Module (HDM) of the Real Time On-line Decision Support System for Nuclear Emergencies in Europe (RODOS) simulates the transport and dispersion of radionuclides in the aquatic environment. This includes wash-off from watersheds following an atmospheric deposition as well as direct releases and transport and sedimentation in rivers, lakes and reservoirs. The output from the HDM is used by the aquatic food and dose module in RODOS for calculating the transfer of radionuclides to man and the resulting radiation exposure. A data assimilation system is presently being developed for the HDM that effectively combines the numerical models with radionuclide measurements in order to improve the capabilities for prediction of radionuclide contamination of the aquatic environment. In addition, the data assimilation system offers a consistent framework for addressing model and measurement uncertainties and quantifying the resulting prediction uncertainty of the radionuclide contamination. The system will provide decision makers with more accurate forecasts of the radionuclide contamination as well as the associated uncertainty, and hence provide the basis for more efficient emergency management. One of the main uncertainties in the modelling of radionuclide wash-off from watersheds is related to the concentration and spatial distribution of the radionuclide deposition. In addition, for key model parameters such as wash-off coefficients, partition coefficients, and exchange rates for the 'water - suspended sediment' and 'suspended sediment - bottom layer' systems only rough and highly uncertain estimates can be given which introduce additional uncertainties. In the case of direct release into the water bodies, the uncertainty of the release rate will further add to the model prediction uncertainty. The deposition and the associated uncertainty are obtained from the Deposition Monitoring Module (DeMM). Thus, when gamma dose rate measurements

Ocean Data Assimilation in the Gulf of Mexico Using 3D VAR Approach - Preliminary Results

Science.gov (United States)

Paturi, S.; Garraffo, Z. D.; Cummings, J. A.; Rivin, I.; Mehra, A.; Kim, H. C.

2016-12-01

Approaches to ocean data assimilation vary widely, both in terms of the sophistication of the method and the observations assimilated.A three-dimensional variational (3DVAR) data assimilation system, part of the Navy Coupled Ocean Data Assimilation (NCODA) system developed at Navy Research Laboratory (NRL), is used for assimilating Sea Surface Temperature (SST) and Sea Surface Height (SSH) in the Gulf of Mexico (GoM). The NCODA 3DVAR produces simultaneous analyses of temperature, salinity, and vector velocity and uses all possible sources of ocean data observations.The Hybrid Coordinate Ocean Model (HYCOM) is used for the simulations, at 1/25o grid resolution for July 2011 period. After successful implementation of NCODA 3DVAR in the GoM, the system will be extended to the global ocean with the intent of making it operational.

Discharge data assimilation in a distributed hydrologic model for flood forecasting purposes

Science.gov (United States)

Ercolani, G.; Castelli, F.

2017-12-01

Flood early warning systems benefit from accurate river flow forecasts, and data assimilation may improve their reliability. However, the actual enhancement that can be obtained in the operational practice should be investigated in detail and quantified. In this work we assess the benefits that the simultaneous assimilation of discharge observations at multiple locations can bring to flow forecasting through a distributed hydrologic model. The distributed model, MOBIDIC, is part of the operational flood forecasting chain of Tuscany Region in Central Italy. The assimilation system adopts a mixed variational-Monte Carlo approach to update efficiently initial river flow, soil moisture, and a parameter related to runoff production. The evaluation of the system is based on numerous hindcast experiments of real events. The events are characterized by significant rainfall that resulted in both high and relatively low flow in the river network. The area of study is the main basin of Tuscany Region, i.e. Arno river basin, which extends over about 8300 km2 and whose mean annual precipitation is around 800 mm. Arno's mainstream, with its nearly 240 km length, passes through major Tuscan cities, as Florence and Pisa, that are vulnerable to floods (e.g. flood of November 1966). The assimilation tests follow the usage of the model in the forecasting chain, employing the operational resolution in both space and time (500 m and 15 minutes respectively) and releasing new flow forecasts every 6 hours. The assimilation strategy is evaluated in respect to open loop simulations, i.e. runs that do not exploit discharge observations through data assimilation. We compare hydrographs in their entirety, as well as classical performance indexes, as error on peak flow and Nash-Sutcliffe efficiency. The dependence of performances on lead time and location is assessed. Results indicate that the operational forecasting chain can benefit from the developed assimilation system, although with a

Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France

Science.gov (United States)

Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.

2011-12-01

This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM) model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%), this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage) induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased) climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation.

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

Science.gov (United States)

De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

2016-01-01

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval

The Computational Complexity, Parallel Scalability, and Performance of Atmospheric Data Assimilation Algorithms

Science.gov (United States)

Lyster, Peter M.; Guo, J.; Clune, T.; Larson, J. W.; Atlas, Robert (Technical Monitor)

2001-01-01

The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.

Data assimilation of citizen collected information for real-time flood hazard mapping

Science.gov (United States)

Sayama, T.; Takara, K. T.

2017-12-01

Many studies in data assimilation in hydrology have focused on the integration of satellite remote sensing and in-situ monitoring data into hydrologic or land surface models. For flood predictions also, recent studies have demonstrated to assimilate remotely sensed inundation information with flood inundation models. In actual flood disaster situations, citizen collected information including local reports by residents and rescue teams and more recently tweets via social media also contain valuable information. The main interest of this study is how to effectively use such citizen collected information for real-time flood hazard mapping. Here we propose a new data assimilation technique based on pre-conducted ensemble inundation simulations and update inundation depth distributions sequentially when local data becomes available. The propose method is composed by the following two-steps. The first step is based on weighting average of preliminary ensemble simulations, whose weights are updated by Bayesian approach. The second step is based on an optimal interpolation, where the covariance matrix is calculated from the ensemble simulations. The proposed method was applied to case studies including an actual flood event occurred. It considers two situations with more idealized one by assuming continuous flood inundation depth information is available at multiple locations. The other one, which is more realistic case during such a severe flood disaster, assumes uncertain and non-continuous information is available to be assimilated. The results show that, in the first idealized situation, the large scale inundation during the flooding was estimated reasonably with RMSE effective. Nevertheless, the applications of the proposed data assimilation method demonstrated a high potential of this method for assimilating citizen collected information for real-time flood hazard mapping in the future.

Motion estimation by data assimilation in reduced dynamic models

International Nuclear Information System (INIS)

Drifi, Karim

2013-01-01

Motion estimation is a major challenge in the field of image sequence analysis. This thesis is a study of the dynamics of geophysical flows visualized by satellite imagery. Satellite image sequences are currently underused for the task of motion estimation. A good understanding of geophysical flows allows a better analysis and forecast of phenomena in domains such as oceanography and meteorology. Data assimilation provides an excellent framework for achieving a compromise between heterogeneous data, especially numerical models and observations. Hence, in this thesis we set out to apply variational data assimilation methods to estimate motion on image sequences. As one of the major drawbacks of applying these assimilation techniques is the considerable computation time and memory required, we therefore define and use a model reduction method in order to significantly decrease the necessary computation time and the memory. We then explore the possibilities that reduced models provide for motion estimation, particularly the possibility of strictly imposing some known constraints on the computed solutions. In particular, we show how to estimate a divergence free motion with boundary conditions on a complex spatial domain [fr

Real-data tests of a single-Doppler radar assimilation system

Science.gov (United States)

Nehrkorn, Thomas; Hegarty, James; Hamill, Thomas M.

1994-06-01

Real data tests of a single-Doppler radar data assimilation and forecast system have been conducted for a Florida sea breeze case. The system consists of a hydrostatic mesoscale model used for prediction of the preconvective boundary layer, an objective analysis that combines model first guess fields with radar derived horizontal winds, a thermodynamic retrieval scheme that obtains temperature information from the three-dimensional wind field and its temporal evolution, and a Newtonian nudging scheme for forcing the model forecast to closer agreement with the analysis. As was found in earlier experiments with simulated data, assimilation using Newtonian nudging benefits from temperature data in addition to wind data. The thermodynamic retrieval technique was successful in retrieving a horizontal temperature gradient from the radar-derived wind fields that, when assimilated into the model, led to a significantly improved forecast of the seabreeze strength and position.

Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

Science.gov (United States)

Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

2017-12-01

Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

Photosynthesis and assimilate partitioning characteristics of the coconut palm as observed by carbon-14 labelling

International Nuclear Information System (INIS)

Jayasekara, K.S.; Jayaswkara, K.S.; Bowen, G.D.

2000-01-01

A technique was developed on the use of carbon dioxide(carbon-14 labelled) rapid labelling of foliage and to ascertain photosynthesis and partitioning characteristics of labelled assimilate into other parts of the coconut palm. An eight-year-old Tall x Tall young coconut palm growing under field conditions at Bandirippuwa Estate and with six developing bunches , was selected for this study. The labelling was carried out on a bright sunny day and soil was at field capacity. Seventh leaf from the youngest open leaf was used for labelling with 5 mCi of sodium bi carbonate (Carbon-14 labelled). The results revealed that within 24 hours, 60% of the labelled assimilate was partitioned into other parts of the palm and at the end of the seventh day about 18% of the labelled assimilate still remained in the labelled leaf. Among the developing bunches fifth and sixth bunches from the youngest developing bunch received more labelled assimilate than young developing bunches above them. It was revealed that partitioning of assimilate into various ''sinks'' is determined by the developmental stage or activeness of the ''sink''. The proportion of C-14 labelled carbon assimilate, partitioned into developing bunches was substantially low compared to the total amount of labelled carbon fixed by the labelled leaf. Further, it was observed that partitioning of assimilated labelled carbon into the young leaves above, as well as the mature leaves below the labelled leaf. The complex vascular anatomy of the palms could be attributed to this pattern of partitioning of assimilates into upper and lower leaves from the labelled leaf

Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

Directory of Open Access Journals (Sweden)

Xujun Han

Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

Science.gov (United States)

Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

2015-01-01

The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

Development of KIAPS Observation Processing Package for Data Assimilation System

Science.gov (United States)

Kang, Jeon-Ho; Chun, Hyoung-Wook; Lee, Sihye; Han, Hyun-Jun; Ha, Su-Jin

2015-04-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. Data assimilation team at KIAPS has been developing the observation processing system (KIAPS Package for Observation Processing: KPOP) to provide optimal observations to the data assimilation system for the KIAPS Global Model (KIAPS Integrated Model - Spectral Element method based on HOMME: KIM-SH). Currently, the KPOP is capable of processing the satellite radiance data (AMSU-A, IASI), GPS Radio Occultation (GPS-RO), AIRCRAFT (AMDAR, AIREP, and etc…), and synoptic observation (SONDE and SURFACE). KPOP adopted Radiative Transfer for TOVS version 10 (RTTOV_v10) to get brightness temperature (TB) for each channel at top of the atmosphere (TOA), and Radio Occultation Processing Package (ROPP) 1-dimensional forward module to get bending angle (BA) at each tangent point. The observation data are obtained from the KMA which has been composited with BUFR format to be converted with ODB that are used for operational data assimilation and monitoring at the KMA. The Unified Model (UM), Community Atmosphere - Spectral Element (CAM-SE) and KIM-SH model outputs are used for the bias correction (BC) and quality control (QC) of the observations, respectively. KPOP provides radiance and RO data for Local Ensemble Transform Kalman Filter (LETKF) and also provides SONDE, SURFACE and AIRCRAFT data for Three-Dimensional Variational Assimilation (3DVAR). We are expecting all of the observation type which processed in KPOP could be combined with both of the data assimilation method as soon as possible. The preliminary results from each observation type will be introduced with the current development status of the KPOP.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

KAUST Repository

Altaf, M. U.

2016-09-01

Soil moisture is a crucial component of the hydrologic cycle, significantly influencing runoff, infiltration, recharge, evaporation and transpiration processes. Models characterizing these processes require soil moisture as an input, either directly or indirectly. Better characterization of the spatial variability of soil moisture leads to better predictions from hydrologic/climate models. In-situ measurements have fine resolution, but become impractical in terms of coverage over large extents. Remotely sensed data have excellent spatial coverage extents, but suffer from poorer spatial and temporal resolution. We present here an innovative approach to downscaling coarse resolution soil moisture data by combining data assimilation and physically based modeling. In this approach, we exploit the features of Continuous Data Assimilation (CDA). A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model’s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (e.g., HYDRUS) are subjected to data assimilation conditioned upon the coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. The large scale features of the model output are constrained to the observations, and as a consequence, the misfit at the fine scale is reduced. The advantage of this approach is that fine resolution soil moisture maps can be generated across large spatial extents, given the coarse resolution data. The data assimilation approach also enables multi-scale data generation which is helpful to match the soil moisture input data to the corresponding modeling scale. Application of this approach is likely in generating fine and intermediate resolution soil

A data assimilation tool for the Pagasitikos Gulf ecosystem dynamics: Methods and benefits

KAUST Repository

Korres, Gerasimos

2012-06-01

Within the framework of the European INSEA project, an advanced assimilation system has been implemented for the Pagasitikos Gulf ecosystem. The system is based on a multivariate sequential data assimilation scheme that combines satellite ocean sea color (chlorophyll-a) data with the predictions of a three-dimensional coupled physical-biochemical model of the Pagasitikos Gulf ecosystem presented in a companion paper. The hydrodynamics are solved with a very high resolution (1/100°) implementation of the Princeton Ocean Model (POM). This model is nested within a coarser resolution model of the Aegean Sea which is part of the Greek POSEIDON forecasting system. The forecast of the Aegean Sea model, itself nested and initialized from a Mediterranean implementation of POM, is also used to periodically re-initalize the Pagatisikos hydrodynamics model using variational initialization techniques. The ecosystem dynamics of Pagasitikos are tackled with a stand-alone implementation of the European Seas Ecosystem Model (ERSEM). The assimilation scheme is based on the Singular Evolutive Extended Kalman (SEEK) filter, in which the error statistics are parameterized by means of a suitable set of Empirical Orthogonal Functions (EOFs).The assimilation experiments were performed for year 2003 and additionally for a 9-month period over 2006 during which the physical model was forced with the POSEIDON-ETA 6-hour atmospheric fields. The assimilation system is validated by assessing the relevance of the system in fitting the data, the impact of the assimilation on non-observed biochemical processes and the overall quality of the forecasts. Assimilation of either GlobColour in 2003 or SeaWiFS in 2006 chlorophyll-a data enhances the identification of the ecological state of the Pagasitikos Gulf. Results, however, suggest that subsurface ecological observations are needed to improve the controllability of the ecosystem in the deep layers. © 2011 Elsevier B.V.

Assimilation and transformation of benzene by higher plants

Energy Technology Data Exchange (ETDEWEB)

Durmishidze, S V; Ugrekhelidze, D Sh; Dzhikiya, A N

1974-01-01

Higher plants are capable of assimilating benzene, the molecules of which are subjected to deep chemical transformations; the products of its metabolism move along the plant. Taking part in total metabolism, carbon atoms of benzene molecules incorporate into composition of low-molecular compounds of the plant cell. The bulk of benzene carbon incorporates into composition of organic acids and a comparatively small part - into composition of amino acids. In the metabolism process benzene carbon localizes mainly in the chloroplasts. Phenol, muconic acid and CO/sub 2/ are isolated and identified from the products of benzene enzymatic oxidation. A range of benzene assimilation by higher plants is extremely wide. 9 references, 5 tables.

Data assimilation of depth-distributed satellite chlorophyll-α in two Mediterranean contrasting sites

KAUST Repository

Kalaroni, S.

2016-04-12

A new approach for processing the remote sensing chlorophyll-α (Chl-α) before assimilating into an ecosystem model is applied in two contrasting, regarding productivity and nutrients availability, Mediterranean sites: the DYFAMED and POSEIDON E1-M3A fixed point open ocean observatories. The new approach derives optically weighted depth-distributed Chl-α profiles from satellite data based on the model simulated Chl-α vertical distribution and light attenuation coefficient. We use the 1D version of the operational ecological 3D POSEIDON model, based on the European Regional Seas Ecosystem Model (ERSEM). The required hydrodynamic properties are obtained (off-line) from the POSEIDON operational 3D hydrodynamic Mediterranean basin scale model. The data assimilation scheme is the Singular Evolutive Interpolated Kalman (SEIK) filter, the ensemble variant of the Singular Evolutive Extended Kalman (SEEK) filter. The performance of the proposed assimilation approach was evaluated against the Chl-α satellite data and the seasonal averages of available in-situ data for nitrate, phosphate and Chl-α. An improvement of the model simulated near-surface and subsurface maximum Chl-α concentrations is obtained, especially at the DYFAMED site. Model nitrate is improved with assimilation, particularly with the new approach assimilating depth-distributed Chl-α, while model phosphate is slightly worse after assimilation. Additional sensitivity experiments were performed, showing a better performance of the new approach under different scenarios of model Chl-α deviation from pseudo-observations of surface Chl-α.

Data assimilation of depth-distributed satellite chlorophyll-α in two Mediterranean contrasting sites

KAUST Repository

Kalaroni, S.; Tsiaras, K.; Petihakis, G.; Hoteit, Ibrahim; Economou-Amilli, A.; G.Triantafyllou

2016-01-01

A new approach for processing the remote sensing chlorophyll-α (Chl-α) before assimilating into an ecosystem model is applied in two contrasting, regarding productivity and nutrients availability, Mediterranean sites: the DYFAMED and POSEIDON E1-M3A fixed point open ocean observatories. The new approach derives optically weighted depth-distributed Chl-α profiles from satellite data based on the model simulated Chl-α vertical distribution and light attenuation coefficient. We use the 1D version of the operational ecological 3D POSEIDON model, based on the European Regional Seas Ecosystem Model (ERSEM). The required hydrodynamic properties are obtained (off-line) from the POSEIDON operational 3D hydrodynamic Mediterranean basin scale model. The data assimilation scheme is the Singular Evolutive Interpolated Kalman (SEIK) filter, the ensemble variant of the Singular Evolutive Extended Kalman (SEEK) filter. The performance of the proposed assimilation approach was evaluated against the Chl-α satellite data and the seasonal averages of available in-situ data for nitrate, phosphate and Chl-α. An improvement of the model simulated near-surface and subsurface maximum Chl-α concentrations is obtained, especially at the DYFAMED site. Model nitrate is improved with assimilation, particularly with the new approach assimilating depth-distributed Chl-α, while model phosphate is slightly worse after assimilation. Additional sensitivity experiments were performed, showing a better performance of the new approach under different scenarios of model Chl-α deviation from pseudo-observations of surface Chl-α.

Single-column data assimilation for the Atmospheric Radiation Measurement (ARM) Program

International Nuclear Information System (INIS)

Louis, J.F.

1994-01-01

The main purpose of the ARM program is to provide the necessary data to develop, test and validate the parameterization of clouds and of their interactions with the radiation field, and the computation of radiative transfer in climate models. For various reasons, much of the ARM observations will be imperfect, incomplete, redundant, indirect and unrepresentative. Various techniques of data assimilation have been developed to deal with these problems. The variational data assimilation and adjoint method applied to a single column model is described here. A model is used to simulate the evolution of the atmosphere during an assimilation period. As the model is run, a cost function is computed which is essentially a measure of simulation errors. The method then consists in adjusting some model parameters to minimize the cost function. Optimization of the model parameters needs to be done with a much longer series of data, to cover different meteorological situations. Once parameters are set, nudging terms are used as control variables. The Derber nudging method will require considerable tuning, especially in defining the vertical profiles of the nudging terms. Extensive tests are currently underway of both model optimization and data assimilation

The Global Structure of UTLS Ozone in GEOS-5: A Multi-Year Assimilation of EOS Aura Data

Science.gov (United States)

Wargan, Krzysztof; Pawson, Steven; Olsen, Mark A.; Witte, Jacquelyn C.; Douglass, Anne R.; Ziemke, Jerald R.; Strahan, Susan E.; Nielsen, J. Eric

2015-01-01

Eight years of ozone measurements retrieved from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder, both on the EOS Aura satellite, have been assimilated into the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. This study thoroughly evaluates this assimilated product, highlighting its potential for science. The impact of observations on the GEOS-5 system is explored by examining the spatial distribution of the observation-minus-forecast statistics. Independent data are used for product validation. The correlation coefficient of the lower-stratospheric ozone column with ozonesondes is 0.99 and the bias is 0.5%, indicating the success of the assimilation in reproducing the ozone variability in that layer. The upper-tropospheric assimilated ozone column is about 10% lower than the ozonesonde column but the correlation is still high (0.87). The assimilation is shown to realistically capture the sharp cross-tropopause gradient in ozone mixing ratio. Occurrence of transport-driven low ozone laminae in the assimilation system is similar to that obtained from the High Resolution Dynamics Limb Sounder (HIRDLS) above the 400 K potential temperature surface but the assimilation produces fewer laminae than seen by HIRDLS below that surface. Although the assimilation produces 5 - 8 fewer occurrences per day (up to approximately 20%) during the three years of HIRDLS data, the interannual variability is captured correctly. This data-driven assimilated product is complementary to ozone fields generated from chemistry and transport models. Applications include study of the radiative forcing by ozone and tracer transport near the tropopause.

Comparison of Sequential and Variational Data Assimilation

Science.gov (United States)

Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Weerts, Albrecht

2017-04-01

Data assimilation is a valuable tool to improve model state estimates by combining measured observations with model simulations. It has recently gained significant attention due to its potential in using remote sensing products to improve operational hydrological forecasts and for reanalysis purposes. This has been supported by the application of sequential techniques such as the Ensemble Kalman Filter which require no additional features within the modeling process, i.e. it can use arbitrary black-box models. Alternatively, variational techniques rely on optimization algorithms to minimize a pre-defined objective function. This function describes the trade-off between the amount of noise introduced into the system and the mismatch between simulated and observed variables. While sequential techniques have been commonly applied to hydrological processes, variational techniques are seldom used. In our believe, this is mainly attributed to the required computation of first order sensitivities by algorithmic differentiation techniques and related model enhancements, but also to lack of comparison between both techniques. We contribute to filling this gap and present the results from the assimilation of streamflow data in two basins located in Germany and Canada. The assimilation introduces noise to precipitation and temperature to produce better initial estimates of an HBV model. The results are computed for a hindcast period and assessed using lead time performance metrics. The study concludes with a discussion of the main features of each technique and their advantages/disadvantages in hydrological applications.

MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

Science.gov (United States)

Valdes-Abellan, Javier; Pachepsky, Yakov; Martinez, Gonzalo

2018-01-01

Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

Conditions for successful data assimilation

Science.gov (United States)

Morzfeld, M.; Chorin, A. J.

2013-12-01

Many applications in science and engineering require that the predictions of uncertain models be updated by information from a stream of noisy data. The model and the data jointly define a conditional probability density function (pdf), which contains all the information one has about the process of interest and various numerical methods can be used to study and approximate this pdf, e.g. the Kalman filter, variational methods or particle filters. Given a model and data, each of these algorithms will produce a result. We are interested in the conditions under which this result is reasonable, i.e. consistent with the real-life situation one is modeling. In particular, we show, using idealized models, that numerical data assimilation is feasible in principle only if a suitably defined effective dimension of the problem is not excessive. This effective dimension depends on the noise in the model and the data, and in physically reasonable problems it can be moderate even when the number of variables is huge. In particular, we find that the effective dimension being moderate induces a balance condition between the noises in the model and the data; this balance condition is often satisfied in realistic applications or else the noise levels are excessive and drown the underlying signal. We also study the effects of the effective dimension on particle filters in two instances, one in which the importance function is based on the model alone, and one in which it is based on both the model and the data. We have three main conclusions: (1) the stability (i.e., non-collapse of weights) in particle filtering depends on the effective dimension of the problem. Particle filters can work well if the effective dimension is moderate even if the true dimension is large (which we expect to happen often in practice). (2) A suitable choice of importance function is essential, or else particle filtering fails even when data assimilation is feasible in principle with a sequential algorithm

GRACE-Assimilated Drought Indicators for the U.S. Drought Monitor

Science.gov (United States)

Rui, Hualan; Vollmer, Bruce; Teng, Bill; Loeser, Carlee; Beaudoing, Hiroko; Rodell, Matt

2018-01-01

The Gravity Recovery and Climate Experiment (GRACE) mission detects changes in Earth's gravity field by precisely monitoring the changes in distance between two satellites orbiting the Earth in tandem. Scientists at NASA's Goddard Space Flight Center generate GRACE-assimilated groundwater and soil moisture drought indicators each week, for drought monitor-related studies and applications. The GRACE-assimilated Drought Indicator Version 2.0 data product (GRACE-DA-DM V2.0) is archived at, and distributed by, the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center). More information about the data and data access is available on the data product landing page at https://disc.gsfc.nasa.gov/datasets /GRACEDADM_CLSM0125US_7D_2.0/summary. The GRACE-DA-DM V2.0 data product contains three drought indicators: Groundwater Percentile, Root Zone Soil Moisture Percentile, and Surface Soil Moisture Percentile. The drought indicators are of wet or dry conditions, expressed as a percentile, indicating the probability of occurrence within the period of record from 1948 to 2012. These GRACE-assimilated drought indicators, with improved spatial and temporal resolutions, should provide a more comprehensive and objective identification of drought conditions. This presentation describes the basic characteristics of the data and data services at NASA GES DISC and collaborative organizations, and uses a few examples to demonstrate the simple ways to explore the GRACE-assimilated drought indicator data.

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

Science.gov (United States)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

Comment on "A bacterium that degrades and assimilates poly(ethylene terephthalate)".

Science.gov (United States)

Yang, Yu; Yang, Jun; Jiang, Lei

2016-08-19

Yoshida et al (Report, 11 March 2016, p. 1196) reported that the bacterium Ideonella sakaiensis 201-F6 can degrade and assimilate poly(ethylene terephthalate) (PET). However, the authors exaggerated degradation efficiency using a low-crystallinity PET and presented no straightforward experiments to verify depolymerization and assimilation of PET. Thus, the authors' conclusions are rather misleading. Copyright © 2016, American Association for the Advancement of Science.

Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

Science.gov (United States)

Crumley, R. L.; Hill, D. F.; Arendt, A. A.; Wikstrom Jones, K.; Wolken, G. J.; Setiawan, L.

2017-12-01

Modeling seasonal snow pack in alpine environments includes a multiplicity of challenges caused by a lack of spatially extensive and temporally continuous observational datasets. This is partially due to the difficulty of collecting measurements in harsh, remote environments where extreme gradients in topography exist, accompanied by large model domains and inclement weather. Engaging snow enthusiasts, snow professionals, and community members to participate in the process of data collection may address some of these challenges. In this study, we use SnowModel to estimate seasonal snow water equivalence (SWE) in the Thompson Pass region of Alaska while incorporating snow depth measurements collected by citizen scientists. We develop a modeling approach to assimilate hundreds of snow depth measurements from participants in the Community Snow Observations (CSO) project (www.communitysnowobs.org). The CSO project includes a mobile application where participants record and submit geo-located snow depth measurements while working and recreating in the study area. These snow depth measurements are randomly located within the model grid at irregular time intervals over the span of four months in the 2017 water year. This snow depth observation dataset is converted into a SWE dataset by employing an empirically-based, bulk density and SWE estimation method. We then assimilate this data using SnowAssim, a sub-model within SnowModel, to constrain the SWE output by the observed data. Multiple model runs are designed to represent an array of output scenarios during the assimilation process. An effort to present model output uncertainties is included, as well as quantification of the pre- and post-assimilation divergence in modeled SWE. Early results reveal pre-assimilation SWE estimations are consistently greater than the post-assimilation estimations, and the magnitude of divergence increases throughout the snow pack evolution period. This research has implications beyond the

[Laws and policies on illicit drugs in Brazil and the perspective of drug users' family members and acquaintances: a study in the City of Ribeirão Preto, São Paulo, Brazil].

Science.gov (United States)

Ventura, Carla Aparecida Arena; Brands, Bruna; Adlaf, Edward; Giesbrecht, Norman; Simich, Laura; Wright, Maria da Gloria Miotto; Ferreira, Paulo Sérgio

2009-01-01

Brazilian drugs legislation has evolved from a prohibitionist system to a less repressive one in terms of drug users. The objective of this study was to identify the perception of relatives and acquaintances of drug users living in Ribeirão Preto, São Paulo, Brazil, about the country's laws and policies on drugs. Data collection was performed using a structured questionnaire. The sample consisted of 100 drug users' relatives or acquaintances, selected at a public health service. Respondents' relationships with the drug user were as follows: 31% friend, 23% sibling, 15% child and 7% spouse. Most users (78%) were men, with an average age of 26 years. Results confirm that national laws and policies have a direct effect on individuals' attitude and behaviors. There is a lack of trust in the police and a general perception that, despite recent chances that favor user rehabilitation, the laws on drugs do not respect users' human rights.

Variational data assimilative modeling of the Gulf of Maine in spring and summer 2010

Science.gov (United States)

Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.

2015-05-01

A data assimilative ocean circulation model is used to hindcast the Gulf of Maine [GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantly improved after data assimilation. The data-assimilative model hindcast reproduces the temporal and spatial evolution of the ocean state, showing that a sea level depression southwest of the Scotian Shelf played a critical role in shaping the gulf-wide circulation. Heat budget analysis further demonstrates that both advection and surface heat flux contribute to temperature variability. The estimated time scale for coastal water to travel from the Scotian Shelf to the Jordan Basin is around 60 days, which is consistent with previous estimates based on in situ observations. Our study highlights the importance of resolving upstream and offshore forcing conditions in predicting the coastal circulation in the GOM.

Response of an eddy-permitting ocean model to the assimilation of sparse in situ data

Science.gov (United States)

Li, Jian-Guo; Killworth, Peter D.; Smeed, David A.

2003-04-01

The response of an eddy-permitting ocean model to changes introduced by data assimilation is studied when the available in situ data are sparse in both space and time (typical for the majority of the ocean). Temperature and salinity (T&S) profiles from the WOCE upper ocean thermal data set were assimilated into a primitive equation ocean model over the North Atlantic, using a simple nudging scheme with a time window of about 2 days and a horizontal spatial radius of about 1°. When data are sparse the model returns to its unassimilated behavior, locally "forgetting" or rejecting the assimilation, on timescales determined by the local advection and diffusion. Increasing the spatial weighting radius effectively reduces both processes and hence lengthens the model restoring time (and with it, the impact of assimilation). Increasing the nudging factor enhances the assimilation effect but has little effect on the model restoring time.

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

Science.gov (United States)

Rienecker, Michele M.; Balmaseda, Magdalena; Awaji, Toshiyuki; Barnier, Bernard; Behringer, David; Bell, Mike; Bourassa, Mark; Brasseur, Pierre; Breivik, Lars-Anders; Carton, James;

Radiance Assimilation Shows Promise for Snowpack Characterization: A 1-D Case Study

Science.gov (United States)

Durand, Michael; Kim, Edward; Margulis, Steve

2008-01-01

We demonstrate an ensemble-based radiometric data assimilation (DA) methodology for estimating snow depth and snow grain size using ground-based passive microwave (PM) observations at 18.7 and 36.5 GHz collected during the NASA CLPX-1, March 2003, Colorado, USA. A land surface model was used to develop a prior estimate of the snowpack states, and a radiative transfer model was used to relate the modeled states to the observations. Snow depth bias was -53.3 cm prior to the assimilation, and -7.3 cm after the assimilation. Snow depth estimated by a non-DA-based retrieval algorithm using the same PM data had a bias of -18.3 cm. The sensitivity of the assimilation scheme to the grain size uncertainty was evaluated; over the range of grain size uncertainty tested, the posterior snow depth estimate bias ranges from -2.99 cm to -9.85 cm, which is uniformly better than both the prior and retrieval estimates. This study demonstrates the potential applicability of radiometric DA at larger scales.

Assortative mating and directional or stabilizing selection for a non-linear function of traits in Tribolium.

Science.gov (United States)

Campo, J L; Gil, M G

1993-01-12

Assortative or random mating following selection in either direction on a non-linear index (experiment 1) or stabilizing selection for pupal length (experiment 2) were carried out for five generations in two lines of Tribolium castaneum (A and R, respectively), with three replicates each. The selected proportion was 25% in all lines. In experiment 1, the selection criterion was designed to increase the aggregate value of adult weight and the first- and second-order powers of pupal length. The A and R lines gave significant responses for the aggregate value (184 ± 6 and 161 ± 14, respectively), pupal length (0.74 ± 0.02 and 0.64 ± 0.05, respectively), and adult weight (0.79 ± 0.03 and 0.78 ± 0.12, respectively). Although the A line was not significantly better than the R line, there was a consistent advantage for assortative mating over random mating, the mean response for aggregate value and pupal length being approximately 1.15 times greater for the A line. In experiment 2 the selection criterion was the square of the deviation from the mean pupal length (stabilizing selection); both lines did not show any change for pupal length. The phenotypic variance showed a significant decrease in the A and R lines, due to a decrease in between-family variance. The assortatively and randomly mated lines were similar for these changes in phenotypic variation. RESUMEN: Aparemiento clasificado y selección direccional o estabilizante para una función no lineal en Tribolium. Dos líneas de Tribolium castaneum fueron seleccionadas direccionalmente para un índice no lineal (experimento 1) o estabilizantemente para longitud de pupa (experimento 2), apareando los animales seleccionados clasificadamente (A) o aleatoriamente (R). Había tres repeticiones por experimento y línea, siendo la proporción de selección el 25%. En el experimento 1, el objetivo de selección incluía el peso adulto así como la longitud de pupa y su cuadrado. Ambas líneas dieron respuesta

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

KAUST Repository

Toye, Habib

2017-05-26

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

Ensemble Kalman Filter data assimilation and storm surge experiments of tropical cyclone Nargis

Directory of Open Access Journals (Sweden)

Le Duc

2015-07-01

Full Text Available Data assimilation experiments on Myanmar tropical cyclone (TC, Nargis, using the Local Ensemble Transform Kalman Filter (LETKF method and the Japan Meteorological Agency (JMA non-hydrostatic model (NHM were performed to examine the impact of LETKF on analysis performance in real cases. Although the LETKF control experiment using NHM as its driving model (NHM–LETKF produced a weak vortex, the subsequent 3-day forecast predicted Nargis’ track and intensity better than downscaling from JMA's global analysis. Some strategies to further improve the final analysis were considered. They were sea surface temperature (SST perturbations and assimilation of TC advisories. To address SST uncertainty, SST analyses issued by operational forecast centres were used in the assimilation window. The use of a fixed source of SST analysis for each ensemble member was more effective in practice. SST perturbations were found to have slightly positive impact on the track forecasts. Assimilation of TC advisories could have a positive impact with a reasonable choice of its free parameters. However, the TC track forecasts exhibited northward displacements, when the observation error of intensities was underestimated in assimilation of TC advisories. The use of assimilation of TC advisories was considered in the final NHM–LETKF by choosing an appropriate set of free parameters. The extended forecast based on the final analysis provided meteorological forcings for a storm surge simulation using the Princeton Ocean Model. Probabilistic forecasts of the water levels at Irrawaddy and Yangon significantly improved the results in the previous studies.

SWOT data assimilation for operational reservoir management on the upper Niger River Basin

Science.gov (United States)

Munier, S.; Polebistki, A.; Brown, C.; Belaud, G.; Lettenmaier, D. P.

2015-01-01

The future Surface Water and Ocean Topography (SWOT) satellite mission will provide two-dimensional maps of water elevation for rivers with width greater than 100 m globally. We describe a modeling framework and an automatic control algorithm that prescribe optimal releases from the Selingue dam in the Upper Niger River Basin, with the objective of understanding how SWOT data might be used to the benefit of operational water management. The modeling framework was used in a twin experiment to simulate the "true" system state and an ensemble of corrupted model states. Virtual SWOT observations of reservoir and river levels were assimilated into the model with a repeat cycle of 21 days. The updated state was used to initialize a Model Predictive Control (MPC) algorithm that computed the optimal reservoir release that meets a minimum flow requirement 300 km downstream of the dam. The data assimilation results indicate that the model updates had a positive effect on estimates of both water level and discharge. The "persistence," which describes the duration of the assimilation effect, was clearly improved (greater than 21 days) by integrating a smoother into the assimilation procedure. We compared performances of the MPC with SWOT data assimilation to an open-loop MPC simulation. Results show that the data assimilation resulted in substantial improvements in the performances of the Selingue dam management with a greater ability to meet environmental requirements (the number of days the target is missed falls to zero) and a minimum volume of water released from the dam.

International migration and educational assortative mating in Mexico and the United States.

Science.gov (United States)

Choi, Kate H; Mare, Robert D

2012-05-01

This paper examines the relationship between migration and marriage by describing how the distributions of marital statuses and assortative mating patterns vary by individual and community experiences of migration. In Mexico, migrants and those living in areas with high levels of out-migration are more likely to be in heterogamous unions. This is because migration increases the relative attractiveness of single return migrants while disproportionately reducing the number of marriageable men in local marriage markets. In the United States, the odds of homogamy are lower for migrants compared with nonmigrants; however, they do not vary depending on the volume of migration in communities. Migrants are more likely than nonmigrants to "marry up" educationally because the relatively small size of this group compels them to expand their pool of potential spouses to include nonmigrants, who tend to be better educated than they are. Among migrants, the odds of marrying outside of one's education group increase the most among the least educated. In Mexican communities with high rates of out-migration, the odds of marrying outside of one's education group are highest among those with the highest level of education. These findings suggest that migration disrupts preferences and opportunities for homogamy by changing social arrangements and normative climates.

The Assimilation of Diazotroph-Derived Nitrogen by Scleractinian Corals Depends on Their Metabolic Status

Directory of Open Access Journals (Sweden)

Vanessa N. Bednarz

2017-01-01

Full Text Available Tropical corals are associated with a diverse community of dinitrogen (N2-fixing prokaryotes (diazotrophs providing the coral an additional source of bioavailable nitrogen (N in oligotrophic waters. The overall activity of these diazotrophs changes depending on the current environmental conditions, but to what extent it affects the assimilation of diazotroph-derived N (DDN by corals is still unknown. Here, in a series of 15N2 tracer experiments, we directly quantified DDN assimilation by scleractinian corals from the Red Sea exposed to different environmental conditions. We show that DDN assimilation strongly varied with the corals’ metabolic status or with phosphate availability in the water. The very autotrophic shallow-water (~5 m corals showed low or no DDN assimilation, which significantly increased under elevated phosphate availability (3 µM. Corals that depended more on heterotrophy (i.e., bleached and deep-water [~45 m] corals assimilated significantly more DDN, which contributed up to 15% of the corals’ N demand (compared to 1% in shallow corals. Furthermore, we demonstrate that a substantial part of the DDN assimilated by deep corals was likely obtained from heterotrophic feeding on fixed N compounds and/or diazotrophic cells in the mucus. Conversely, in shallow corals, the net release of mucus, rich in organic carbon compounds, likely enhanced diazotroph abundance and activity and thereby the release of fixed N to the pelagic and benthic reef community. Overall, our results suggest that DDN assimilation by corals varies according to the environmental conditions and is likely linked to the capacity of the coral to acquire nutrients from seawater.

Data assimilation and PWR primary measurement

International Nuclear Information System (INIS)

Mercier, Thibaud

2015-01-01

A Pressurized Water Reactor (PWR) Reactor Coolant System (RCS) is a highly complex physical process: heterogeneous power, flow and temperature distributions are difficult to be accurately measured, since instrumentations are limited in number, thus leading to the relevant safety and protection margins. EDF R and D is seeking to assess the potential benefits of applying Data Assimilation to a PWR's RCS (Reactor Coolant System) measurements, in order to improve the estimators for parameters of a reactor's operating setpoint, i.e. improving accuracy and reducing uncertainties and biases of measured RCS parameters. In this thesis, we define a 0D semi-empirical model for RCS, satisfying the description level usually chosen by plant operators, and construct a Monte-Carlo Method (inspired from Ensemble Methods) in order to use this model with Data Assimilation tools. We apply this method on simulated data in order to assess the reduction of uncertainties on key parameters: results are beyond expectations, however strong hypothesis are required, implying a careful preprocessing of input data. (author)

Spatial Assimilation in Denmark?

DEFF Research Database (Denmark)

Andersen, Hans Skifter

2010-01-01

market and discrimination, which limits the housing possibilities for ethnic minorities. Another explanation could be that immigrants for different reasons choose to settle in so-called ethnic enclaves where they can find an ethnic social network, which can support them in their new country....... In traditional research literature about immigration it has been shown that for many immigrants living in enclaves has been a temporary situation. The 'spatial assimilation theory' says that this situation ends when the family has become more integrated in the new society and then moves to other parts...

Information-Based Analysis of Data Assimilation (Invited)

Science.gov (United States)

Nearing, G. S.; Gupta, H. V.; Crow, W. T.; Gong, W.

2013-12-01

Data assimilation is defined as the Bayesian conditioning of uncertain model simulations on observations for the purpose of reducing uncertainty about model states. Practical data assimilation methods make the application of Bayes' law tractable either by employing assumptions about the prior, posterior and likelihood distributions (e.g., the Kalman family of filters) or by using resampling methods (e.g., bootstrap filter). We propose to quantify the efficiency of these approximations in an OSSE setting using information theory and, in an OSSE or real-world validation setting, to measure the amount - and more importantly, the quality - of information extracted from observations during data assimilation. To analyze DA assumptions, uncertainty is quantified as the Shannon-type entropy of a discretized probability distribution. The maximum amount of information that can be extracted from observations about model states is the mutual information between states and observations, which is equal to the reduction in entropy in our estimate of the state due to Bayesian filtering. The difference between this potential and the actual reduction in entropy due to Kalman (or other type of) filtering measures the inefficiency of the filter assumptions. Residual uncertainty in DA posterior state estimates can be attributed to three sources: (i) non-injectivity of the observation operator, (ii) noise in the observations, and (iii) filter approximations. The contribution of each of these sources is measurable in an OSSE setting. The amount of information extracted from observations by data assimilation (or system identification, including parameter estimation) can also be measured by Shannon's theory. Since practical filters are approximations of Bayes' law, it is important to know whether the information that is extracted form observations by a filter is reliable. We define information as either good or bad, and propose to measure these two types of information using partial

Understanding determinants of consumer mobile health usage intentions, assimilation, and channel preferences.

Science.gov (United States)

Rai, Arun; Chen, Liwei; Pye, Jessica; Baird, Aaron

2013-08-02

Consumer use of mobile devices as health service delivery aids (mHealth) is growing, especially as smartphones become ubiquitous. However, questions remain as to how consumer traits, health perceptions, situational characteristics, and demographics may affect consumer mHealth usage intentions, assimilation, and channel preferences. We examine how consumers' personal innovativeness toward mobile services (PIMS), perceived health conditions, health care availability, health care utilization, demographics, and socioeconomic status affect their (1) mHealth usage intentions and extent of mHealth assimilation, and (2) preference for mHealth as a complement or substitute for in-person doctor visits. Leveraging constructs from research in technology acceptance, technology assimilation, consumer behavior, and health informatics, we developed a cross-sectional online survey to study determinants of consumers' mHealth usage intentions, assimilation, and channel preferences. Data were collected from 1132 nationally representative US consumers and analyzed by using moderated multivariate regressions and ANOVA. The results indicate that (1) 430 of 1132 consumers in our sample (37.99%) have started using mHealth, (2) a larger quantity of consumers are favorable to using mHealth as a complement to in-person doctor visits (758/1132, 66.96%) than as a substitute (532/1132, 47.00%), and (3) consumers' PIMS and perceived health conditions have significant positive direct influences on mHealth usage intentions, assimilation, and channel preferences, and significant positive interactive influences on assimilation and channel preferences. The independent variables within the moderated regressions collectively explained 59.70% variance in mHealth usage intentions, 60.41% in mHealth assimilation, 34.29% in preference for complementary use of mHealth, and 45.30% in preference for substitutive use of mHealth. In a follow-up ANOVA examination, we found that those who were more favorable

Variational data assimilation for the optimized ozone initial state and the short-time forecasting

Directory of Open Access Journals (Sweden)

S.-Y. Park

2016-03-01

Full Text Available In this study, we apply the four-dimensional variational (4D-Var data assimilation to optimize initial ozone state and to improve the predictability of air quality. The numerical modeling systems used for simulations of atmospheric condition and chemical formation are the Weather Research and Forecasting (WRF model and the Community Multiscale Air Quality (CMAQ model. The study area covers the capital region of South Korea, where the surface measurement sites are relatively evenly distributed. The 4D-Var code previously developed for the CMAQ model is modified to consider background error in matrix form, and various numerical tests are conducted. The results are evaluated with an idealized covariance function for the appropriateness of the modified codes. The background error is then constructed using the NMC method with long-term modeling results, and the characteristics of the spatial correlation scale related to local circulation are analyzed. The background error is applied in the 4D-Var research, and a surface observational assimilation is conducted to optimize the initial concentration of ozone. The statistical results for the 12 h assimilation periods and the 120 observatory sites show a 49.4 % decrease in the root mean squared error (RMSE, and a 59.9 % increase in the index of agreement (IOA. The temporal variation of spatial distribution of the analysis increments indicates that the optimized initial state of ozone concentration is transported to inland areas by the clockwise-rotating local circulation during the assimilation windows. To investigate the predictability of ozone concentration after the assimilation window, a short-time forecasting is carried out. The ratios of the RMSE (root mean squared error with assimilation versus that without assimilation are 8 and 13 % for the +24 and +12 h, respectively. Such a significant improvement in the forecast accuracy is obtained solely by using the optimized initial state. The potential

The impact of atmospheric data assimilation on wave simulations in the Red Sea

KAUST Repository

Langodan, Sabique

2016-03-11

Although wind and wave modeling is rather successful in the open ocean, modeling enclosed seas, particularly seas with small basins and complex orography, presents challenges. Here, we use data assimilation to improve wind and wave simulations in the Red Sea. We generated two sets of wind fields using a nested, high-resolution Weather Research and Forecasting model implemented with (VARFC) and without (CTL) assimilation of observations. Available conventional and satellite data were assimilated using the consecutive integration method with daily initializations over one year (2009). By evaluating the two wind products against in-situ data from synoptic stations, buoys, scatterometers, and altimeters, we found that seasonal patterns of wind and wave variability were well reproduced in both experiments. Statistical scores for simulated winds computed against QuikSCAT, buoy, and synoptic station observations suggest that data assimilation decreases the root-mean-square error to values between 1 and 2 m s-1 and reduces the scatter index by 30% compared to the CTL. Sensitivity clearly increased around mountain gaps, where the channeling effect is better described by VARFC winds. The impact of data assimilation is more pronounced in wave simulations, particularly during extreme winds and in the presence of mountain jets. © 2016 Elsevier Ltd. All rights reserved.

Retrieving moisture profiles from precipitable water measurements using a variational data assimilation approach

Energy Technology Data Exchange (ETDEWEB)

Guo, Y.R.; Zou, X.; Kuo, Y.H. [National Center for Atmospheric Research, Boulder, CO (United States)

1996-04-01

Atmospheric moisture distribution is directly related to the formation of clouds and precipitation and affects the atmospheric radiation and climate. Currently, several remote sensing systems can measure precipitable water (PW) with fairly high accuracy. As part of the development of an Integrated Data Assimilation and Sounding System in support of the Atmospheric Radiation Measurement Program, retrieving the 3-D water vapor fields from PW measurements is an important problem. A new four dimensional variational (4DVAR) data assimilation system based on the Penn State/National Center for Atmospheric Research (NCAR) mesoscale model (MM5) has been developed by Zou et al. (1995) with the adjoint technique. In this study, we used this 4DVAR system to retrieve the moisture profiles. Because we do not have a set of real observed PW measurements now, the special soundings collected during the Severe Environmental Storm and Mesoscale Experiment (SESAME) in 1979 were used to simulate a set of PW measurements, which were then assimilated into the 4DVAR system. The accuracy of the derived water vapor fields was assessed by direct comparison with the detailed specific humidity soundings. The impact of PW assimilation on precipitation forecast was examined by conducting a series of model forecast experiments started from the different initial conditions with or without data assimilation.

Data assimilation with inequality constraints

Science.gov (United States)

Thacker, W. C.

If values of variables in a numerical model are limited to specified ranges, these restrictions should be enforced when data are assimilated. The simplest option is to assimilate without regard for constraints and then to correct any violations without worrying about additional corrections implied by correlated errors. This paper addresses the incorporation of inequality constraints into the standard variational framework of optimal interpolation with emphasis on our limited knowledge of the underlying probability distributions. Simple examples involving only two or three variables are used to illustrate graphically how active constraints can be treated as error-free data when background errors obey a truncated multi-normal distribution. Using Lagrange multipliers, the formalism is expanded to encompass the active constraints. Two algorithms are presented, both relying on a solution ignoring the inequality constraints to discover violations to be enforced. While explicitly enforcing a subset can, via correlations, correct the others, pragmatism based on our poor knowledge of the underlying probability distributions suggests the expedient of enforcing them all explicitly to avoid the computationally expensive task of determining the minimum active set. If additional violations are encountered with these solutions, the process can be repeated. Simple examples are used to illustrate the algorithms and to examine the nature of the corrections implied by correlated errors.

Key aspects of stratospheric tracer modeling using assimilated winds

Directory of Open Access Journals (Sweden)

B. Bregman

2006-01-01

Full Text Available This study describes key aspects of global chemistry-transport models and their impact on stratospheric tracer transport. We concentrate on global models that use assimilated winds from numerical weather predictions, but the results also apply to tracer transport in general circulation models. We examined grid resolution, numerical diffusion, air parcel dispersion, the wind or mass flux update frequency, and time interpolation. The evaluation is performed with assimilated meteorology from the "operational analyses or operational data" (OD from the European Centre for Medium-Range Weather Forecasts (ECMWF. We also show the effect of the mass flux update frequency using the ECMWF 40-year re-analyses (ERA40. We applied the three-dimensional chemistry-transport Tracer Model version 5 (TM5 and a trajectory model and performed several diagnoses focusing on different transport regimes. Covering different time and spatial scales, we examined (1 polar vortex dynamics during the Arctic winter, (2 the large-scale stratospheric meridional circulation, and (3 air parcel dispersion in the tropical lower stratosphere. Tracer distributions inside the Arctic polar vortex show considerably worse agreement with observations when the model grid resolution in the polar region is reduced to avoid numerical instability. The results are sensitive to the diffusivity of the advection. Nevertheless, the use of a computational cheaper but diffusive advection scheme is feasible for tracer transport when the horizontal grid resolution is equal or smaller than 1 degree. The use of time interpolated winds improves the tracer distributions, particularly in the middle and upper stratosphere. Considerable improvement is found both in the large-scale tracer distribution and in the polar regions when the update frequency of the assimilated winds is increased from 6 to 3 h. It considerably reduces the vertical dispersion of air parcels in the tropical lower stratosphere. Strong

Dark matter assimilation into the baryon asymmetry

International Nuclear Information System (INIS)

D'Eramo, Francesco; Fei, Lin; Thaler, Jesse

2012-01-01

Pure singlets are typically disfavored as dark matter candidates, since they generically have a thermal relic abundance larger than the observed value. In this paper, we propose a new dark matter mechanism called a ssimilation , which takes advantage of the baryon asymmetry of the universe to generate the correct relic abundance of singlet dark matter. Through assimilation, dark matter itself is efficiently destroyed, but dark matter number is stored in new quasi-stable heavy states which carry the baryon asymmetry. The subsequent annihilation and late-time decay of these heavy states yields (symmetric) dark matter as well as (asymmetric) standard model baryons. We study in detail the case of pure bino dark matter by augmenting the minimal supersymmetric standard model with vector-like chiral multiplets. In the parameter range where this mechanism is effective, the LHC can discover long-lived charged particles which were responsible for assimilating dark matter

Adjustment of trendy, gaming and less assimilated tweens in the United States.

Science.gov (United States)

Comulada, W Scott; Rotheram-Borus, Mary Jane; Carey, George; Poris, Michelle; Lord, Lynwood R; Mayfield Arnold, Elizabeth

2011-09-01

Youth transitioning from childhood to adolescence (tweens) are exposed to increasing amounts of media and advertisement. Tweens have also emerged as a major marketing segment for corporate America with increasing buying power.We examine how tweens relate to popular culture messages and the association of different orientations to popular culture on adjustment. A secondary data analysis was conducted on a marketing survey of 3527 tweens, aged 10-14 years, obtained from 49 schools using stratified sampling methods. A sample of children nationwide described their preferences on popular culture and measures of psychosocial adjustment. Using cluster analysis, we identified three main clusters or adaptation styles of tweens: (1) those who enjoyed gaming, (2) trendy youth and (3) youth less assimilated into popular culture. There were differences in clusters based on adjustment indices. Gaming and trendy tweens reported higher self-perceptions of being smart, caring and confident compared to less assimilated tweens. However, gaming and trendy tweens worried more about fitting in than less assimilated tweens. Gaming and trendy tweens also endorsed future goals and traditional values more strongly than less assimilated tweens. Trendy tweens reported the strongest positive feelings about substance use. Results suggest that for each method of adaptation (gamer, trendy and less assimilated), there are unique differences in adjustment that can impact the child's future. Parents and service providers must recognize the complexity of these decisions and be sensitive to the unique needs of youth as they move from childhood to adolescence.

The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

Science.gov (United States)

Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

2017-04-01

Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the

Application of statistical dynamical turbulence closures to data assimilation

International Nuclear Information System (INIS)

O'Kane, Terence J; Frederiksen, Jorgen S

2010-01-01

We describe the development of an accurate yet computationally tractable statistical dynamical closure theory for general inhomogeneous turbulent flows, coined the quasi-diagonal direct interaction approximation closure (QDIA), and its application to problems in data assimilation. The QDIA provides prognostic equations for evolving mean fields, covariances and higher-order non-Gaussian terms, all of which are also required in the formulation of data assimilation schemes for nonlinear geophysical flows. The QDIA is a generalization of the class of direct interaction approximation theories, initially developed by Kraichnan (1959 J. Fluid Mech. 5 497) for isotropic turbulence, to fully inhomogeneous flows and has been further generalized to allow for both inhomogeneous and non-Gaussian initial conditions and long integrations. A regularization procedure or empirical vertex renormalization that ensures correct inertial range spectra is also described. The aim of this paper is to provide a coherent mathematical description of the QDIA turbulence closure and closure-based data assimilation scheme we have labeled the statistical dynamical Kalman filter. The mathematical formalism presented has been synthesized from recent works of the authors with some additional material and is presented in sufficient detail that the paper is of a pedagogical nature.

Straight-line assimilation in home-leaving? A comparison of Turks, Somalis and Danes

DEFF Research Database (Denmark)

Nielsen, Rikke Skovgaard

2016-01-01

The purpose of this paper is to test the evidence for spatial assimilation and straight-line assimilation in the transition of leaving home in Denmark. Based on data from the extensive Danish registers, the paper analyses the home-leaving patterns of Danes, Turkish immigrants, Turkish descendants...

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

KAUST Repository

Altaf, Muhammad

2016-01-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model\\'s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Variational Data Assimilative Modeling of the Gulf of Maine Circulation in Spring and Summer 2010

OpenAIRE

Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.

2015-01-01

A data assimilative ocean circulation model is used to hindcast the Gulf of Maine (GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantl...

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

Science.gov (United States)

Scholze, Marko; Buchwitz, Michael; Dorigo, Wouter; Guanter, Luis; Quegan, Shaun

2017-07-01

The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

KAUST Repository

Viswanadhapalli, Yesubabu

2015-08-20

The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

Variational data assimilation using targetted random walks

KAUST Repository

Cotter, S. L.

2011-02-15

The variational approach to data assimilation is a widely used methodology for both online prediction and for reanalysis. In either of these scenarios, it can be important to assess uncertainties in the assimilated state. Ideally, it is desirable to have complete information concerning the Bayesian posterior distribution for unknown state given data. We show that complete computational probing of this posterior distribution is now within the reach in the offline situation. We introduce a Markov chain-Monte Carlo (MCMC) method which enables us to directly sample from the Bayesian posterior distribution on the unknown functions of interest given observations. Since we are aware that these methods are currently too computationally expensive to consider using in an online filtering scenario, we frame this in the context of offline reanalysis. Using a simple random walk-type MCMC method, we are able to characterize the posterior distribution using only evaluations of the forward model of the problem, and of the model and data mismatch. No adjoint model is required for the method we use; however, more sophisticated MCMC methods are available which exploit derivative information. For simplicity of exposition, we consider the problem of assimilating data, either Eulerian or Lagrangian, into a low Reynolds number flow in a two-dimensional periodic geometry. We will show that in many cases it is possible to recover the initial condition and model error (which we describe as unknown forcing to the model) from data, and that with increasing amounts of informative data, the uncertainty in our estimations reduces. © 2011 John Wiley & Sons, Ltd.

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

Science.gov (United States)

Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

2016-01-01

Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns.

Science.gov (United States)

Pepe, Alberto; Rodriguez, Marko A

2010-09-01

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research centerin the development and application of wireless and sensor network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers' propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.

Assimilation of radar-based nowcast into HIRLAM NWP model

DEFF Research Database (Denmark)

Jensen, David Getreuer; Petersen, Claus; Rasmussen, Michael R.

2015-01-01

The present study introduces a nowcast scheme that assimilates radar extrapolation data (RED) into a nowcasting version of the high resolution limited area model (HIRLAM) numerical weather prediction (NWP) model covering the area of Denmark. The RED are based on the Co-TREC (tracking radar echoes...... by correlation) methodology and are generated from cleaned radar mosaics from the Danish weather radar network. The assimilation technique is a newly developed method that increases model precipitation by increasing low-level convergence and decreasing convergence aloft in order to increase the vertical velocity....... The level of improved predictability relies on the RED quality, which again relies on the type of event....

Assimilative model for ionospheric dynamics employing delay, Doppler, and direction of arrival measurements from multiple HF channels

Science.gov (United States)

Fridman, Sergey V.; Nickisch, L. J.; Hausman, Mark; Zunich, George

2016-03-01

We describe the development of new HF data assimilation capabilities for our ionospheric inversion algorithm called GPSII (GPS Ionospheric Inversion). Previously existing capabilities of this algorithm included assimilation of GPS total electron content data as well as assimilation of backscatter ionograms. In the present effort we concentrated on developing assimilation tools for data related to HF propagation channels. Measurements of propagation delay, angle of arrival, and the ionosphere-induced Doppler from any number of known propagation links can now be utilized by GPSII. The resulting ionospheric model is consistent with all assimilated measurements. This means that ray tracing simulations of the assimilated propagation links are guaranteed to be in agreement with measured data within the errors of measurement. The key theoretical element for assimilating HF data is the raypath response operator (RPRO) which describes response of raypath parameters to infinitesimal variations of electron density in the ionosphere. We construct the RPRO out of the fundamental solution of linearized ray tracing equations for a dynamic magnetoactive plasma. We demonstrate performance and internal consistency of the algorithm using propagation delay data from multiple oblique ionograms (courtesy of Defence Science and Technology Organisation, Australia) as well as with time series of near-vertical incidence sky wave data (courtesy of the Intelligence Advanced Research Projects Activity HFGeo Program Government team). In all cases GPSII produces electron density distributions which are smooth in space and in time. We simulate the assimilated propagation links by performing ray tracing through GPSII-produced ionosphere and observe that simulated data are indeed in agreement with assimilated measurements.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

Science.gov (United States)

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

DEFF Research Database (Denmark)

Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

2015-01-01

Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

Regional Ocean Modeling System (ROMS): CNMI: Data Assimilating

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the Commonwealth of the Northern Mariana Islands (CNMI)...

Data assimilation strategies for volcano geodesy

Science.gov (United States)

Zhan, Yan; Gregg, Patricia M.

2017-09-01

Ground deformation observed using near-real time geodetic methods, such as InSAR and GPS, can provide critical information about the evolution of a magma chamber prior to volcanic eruption. Rapid advancement in numerical modeling capabilities has resulted in a number of finite element models targeted at better understanding the connection between surface uplift associated with magma chamber pressurization and the potential for volcanic eruption. Robust model-data fusion techniques are necessary to take full advantage of the numerical models and the volcano monitoring observations currently available. In this study, we develop a 3D data assimilation framework using the Ensemble Kalman Filter (EnKF) approach in order to combine geodetic observations of surface deformation with geodynamic models to investigate volcanic unrest. The EnKF sequential assimilation method utilizes disparate data sets as they become available to update geodynamic models of magma reservoir evolution. While the EnKF has been widely applied in hydrologic and climate modeling, the adaptation for volcano monitoring is in its initial stages. As such, our investigation focuses on conducting a series of sensitivity tests to optimize the EnKF for volcano applications and on developing specific strategies for assimilation of geodetic data. Our numerical experiments illustrate that the EnKF is able to adapt well to the spatial limitations posed by GPS data and the temporal limitations of InSAR, and that specific strategies can be adopted to enhance EnKF performance to improve model forecasts. Specifically, our numerical experiments indicate that: (1) incorporating additional iterations of the EnKF analysis step is more efficient than increasing the number of ensemble members; (2) the accuracy of the EnKF results are not affected by initial parameter assumptions; (3) GPS observations near the center of uplift improve the quality of model forecasts; (4) occasionally shifting continuous GPS stations to

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

Science.gov (United States)

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Assimilation or Ethnicization: An Exploration of Inland Tibet Class Education Policy and Practice

Science.gov (United States)

Miaoyan, Yang; Dunzhu, Nima

2015-01-01

Assimilation and ethnicization are mainstream voices in current studies of ethnic relations. The former suspects that current social system arrangements are meant to assimilate minority groups into the cultural system of the mainstream ethnic group, while the latter believes that current systemic arrangements will cause minority groups to tend…

Advances in the development of an integrated data assimilation and sounding system

International Nuclear Information System (INIS)

Dabberdt, W.F.; Parsons, D.; Kuo, Y.H.; Dudhia, J.; Guo, Y.R.; Van Baelen, J.; Martin, C.; Oncley, S.

1994-01-01

The Integrated Data Assimilation and Sounding System (IDASS) provides continuous high-resolution tropospheric profiles. The measurement system (Integrated Sounding System, or ISS) is developed around a suite of in situ and active and passive remote sensors. Observations from ISS networks provide a high-resolution description of atmospheric structure on the mesoscale. Measurements are coupled with a state-of-the-art mesoscale modeling system. The mesoscale data assimilation scheme is the Newtonian nudging technique. In the mesoscale data assimilation process, observations of wind, temperature, and humidity are used to nudge or relax the time-dependent model variables to the observed values. The end product is a highly resolved four-dimensional meteorological data set (including three components of wind, temperature, humidity, cloud water, and integrated moisture)

Assimilation and subcellular partitioning of elements by grass shrimp collected along an impact gradient

International Nuclear Information System (INIS)

Seebaugh, David R.; Wallace, William G.

2009-01-01

Chronic exposure to polluted field conditions can impact metal bioavailability in prey and may influence metal transfer to predators. The present study investigated the assimilation of Cd, Hg and organic carbon by grass shrimp Palaemonetes pugio, collected along an impact gradient within the New York/New Jersey Harbor Estuary. Adult shrimp were collected from five Staten Island, New York study sites, fed 109 Cd- or 203 Hg-labeled amphipods or 14 C-labeled meals and analyzed for assimilation efficiencies (AE). Subsamples of amphipods and shrimp were subjected to subcellular fractionation to isolate metal associated with a compartment presumed to contain trophically available metal (TAM) (metal associated with heat-stable proteins [HSP - e.g., metallothionein-like proteins], heat-denatured proteins [HDP - e.g., enzymes] and organelles [ORG]). TAM- 109 Cd% and TAM- 203 Hg% in radiolabeled amphipods were ∼64% and ∼73%, respectively. Gradients in AE- 109 Cd% (∼54% to ∼75%) and AE- 203 Hg% (∼61% to ∼78%) were observed for grass shrimp, with the highest values exhibited by shrimp collected from sites within the heavily polluted Arthur Kill complex. Population differences in AE- 14 C% were not observed. Assimilated 109 Cd% partitioned to the TAM compartment in grass shrimp varied between ∼67% and ∼75%. 109 Cd bound to HSP in shrimp varied between ∼15% and ∼47%, while 109 Cd associated with metal-sensitive HDP was ∼17% to ∼44%. Percentages of assimilated 109 Cd bound to ORG were constant at ∼10%. Assimilated 203 Hg% associated with TAM in grass shrimp did not exhibit significant variation. Percentages of assimilated 203 Hg bound to HDP (∼47%) and ORG (∼11%) did not vary among populations and partitioning of 203 Hg to HSP was not observed. Using a simplified biokinetic model of metal accumulation from the diet, it is estimated that site-specific variability in Cd AE by shrimp and tissue Cd burdens in field-collected prey (polychaetes Nereis spp

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

Science.gov (United States)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Towards assimilation of InSAR data in operational weather models

Science.gov (United States)

Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

2017-04-01

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

Science.gov (United States)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

Science.gov (United States)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

Directory of Open Access Journals (Sweden)

K. Andrea Scott

2015-09-01

Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution....

Regional Ocean Modeling System (ROMS): Oahu: Data Assimilating

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 2-day, 3-hourly data assimilating hindcast for the region surrounding the island of Oahu at approximately 1-km resolution....

Port du hijab et « défaut d’assimilation »

OpenAIRE

Hajjat, Abdellali

2013-01-01

Dans le cadre de deux procédures d’attribution de la nationalité française, l’administration doit évaluer le « degré d’assimilation » des candidats. Le gouvernement peut ainsi refuser l’acquisition de la nationalité au motif du « défaut d’assimilation » pour la procédure de naturalisation (article 21-24 du code civil) et pour l’acquisition par mariage (article 21-4). Cet article analyse le « sens pratique de la mesure » de l’assimilation et prend pour objet un cas particulièrement problématiq...

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

Science.gov (United States)

Nowottnick, Ed; Yorks, John; McGill, Matt; Scott, Stan; Palm, Stephen; Hlavka, Dennis; Hart, William; Selmer, Patrick; Kupchock, Andrew; Pauly, Rebecca

2017-01-01

Using GEOS-5, we are developing a 1D ENS approach for assimilating CATS near real time observations of total attenuated backscatter at 1064 nm: a) After performing a 1-ENS assimilation of a cloud-free profile, the GEOS-5 analysis closely followed observed total attenuated backscatter. b) Vertical localization length scales were varied for the well-mixed PBL and the free troposphere After assimilating a cloud free segment of a CATS granule, the fine detail of a dust event was obtained in the GEOS-5 analysis for both total attenuated backscatter and extinction. Future Work: a) Explore horizontal localization and test within a cloudy aerosol layer. b) Address noisy analysis increments in the free troposphere where both CATS and GEOS-5 aerosol loadings are low. c) Develop a technique to screen CATS ground return from profiles. d) "Dynamic" lidar ratio that will evolve in conjunction with simulated aerosol mixtures.

Modeling ionospheric pre-reversal enhancement and plasma bubble growth rate using data assimilation

Science.gov (United States)

Rajesh, P. K.; Lin, C. C. H.; Chen, C. H.; Matsuo, T.

2017-12-01

We report that assimilating total electron content (TEC) into a coupled thermosphere-ionosphere model by using the ensemble Kalman filter results in improved specification and forecast of eastward pre-reversal enhancement (PRE) electric field (E-field). Through data assimilation, the ionospheric plasma density, thermospheric winds, temperature and compositions are adjusted simultaneously. The improvement of dusk-side PRE E-field over the prior state is achieved primarily by intensification of eastward neutral wind. The improved E-field promotes a stronger plasma fountain and deepens the equatorial trough. As a result, the horizontal gradients of Pedersen conductivity and eastward wind are increased due to greater zonal electron density gradient and smaller ion drag at dusk, respectively. Such modifications provide preferable conditions and obtain a strengthened PRE magnitude closer to the observation. The adjustment of PRE E-field is enabled through self-consistent thermosphere and ionosphere coupling processes captured in the model. The assimilative outputs are further utilized to calculate the flux tube integrated Rayleigh-Taylor instability growth rate during March 2015 for investigation of global plasma bubble occurrence. Significant improvements in the calculated growth rates could be achieved because of the improved update of zonal electric field in the data assimilation forecast. The results suggest that realistic estimate or prediction of plasma bubble occurrence could be feasible by taking advantage of the data assimilation approach adopted in this work.

Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

KAUST Repository

Butler, T.; Altaf, Muhammad; Dawson, C.; Hoteit, Ibrahim; Luo, X.; Mayo, T.

2012-01-01

levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Science.gov (United States)

Lievens, H.; Martens, B.; Verhoest, N. E. C.; Hahn, S.; Reichle, R. H.; Miralles, D. G.

2017-01-01

Active radar backscatter (s?) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s? and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s? or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s? and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

PROCESSES OF ASSIMILATION INVOLVING DENTAL STOP CONSOANTS /t, d/ IN BRASILIAN PORTUGUESE

Directory of Open Access Journals (Sweden)

Dermeval da HORA

2015-06-01

Full Text Available The major aim of this paper is to present, based on quantitative sociolinguistics, a analyse of the process of progressive assimilation that involve the dental stop consonants. First of all, one overview about the regressive assimilation, which was extensively studied in Brazilian Portuguese, will be present. Then, the contexts of progressive assimilation in the speech community of Itabaiana-PB will be analyzed. The motivation for this paper is the fact that, in the dialect from Itabaiana, the process of progressive assimilation, in words such as muito ‘many/much’ and gosto ‘like”, in which the preceding phonological context exerts influence over the following one, tend to undergo the process of regressive assimilation, such as as pote ‘pot’ and bote ‘boat’, more useful when we think about the Brazilian Portuguese. The theoretical approach underlying the research is the variation theory, or quantitative Sociolinguistics, pioneered by William Labov (1972. The data collected had already been electronically stored in the corpus from Projeto Variação Linguística da Paraíba – VALPB. The sample consists of 36 informants from the community, being stratified according to gender, age group and years of schooling. As result, the computer program Goldvarb (SANKOFF; TAGLIAMONTE; SMITH, 2005 pointed as favorite to the application of the rule: the gender (male gender, the level of schooling (no scholar historic since the primary, the following phonological context (high back vowel, the precedent phonological context (monophthong, and the tonicity (post-stressed syllable.

IASI hyperspectral radiances in the NCMRWF 4D-VAR assimilation system: OSE

Science.gov (United States)

Sharma, Priti; Indira Rani, S.; Mallick, Swapan; Srinivas, D.; George, John P.; Dasgupta, Munmun

2016-04-01

Accuracy of global NWP depends more on the contribution of satellite data than the surface based observations. This is achieved through the better usage of satellite data within the data assimilation system. Efforts are going on at NCMRWF to add more and more satellite data in the assimilation system both from Indian and international satellites in geostationary and polar orbits. Impact of the new dataset is assessed through Observation System Experiments (OSEs), through which the impact of the data is evaluated comparing the forecast output with that of a control run. This paper discusses one such OSEs with Infrared Atmospheric Sounder Interferometer (IASI) onboard MetOp-A and B. IASI is the main payload instrument for the purpose of supporting NWP. IASI provides information on the vertical structure of the atmospheric temperature and humidity with an accuracy of 1K and a vertical resolution of 1 km, which is necessary to improve NWP. IASI measures the radiance emitted from the Earth in 8641 channels, covering the spectral interval 645-2760 cm-1. The high volume data resulting from IASI presents many challenges, particularly in the area of assimilation. Out of these 8641 channels, 314 channels are selected depending on the relevance of information in each channel to assimilate in the NCMRWF 4D-VAR assimilation system. Studies show that the use of IASI data in NWP accounts for 40% of the impact of all satellite observations in the NWP forecasts, especially microwave and hyperspectral infrared sounding techniques are found to give the largest impacts

Cultural assimilation, cultural diffusion and the origin of the wealth of nations

OpenAIRE

Ashraf, Quamrul; Galor, Oded

2007-01-01

This research argues that variations in the interplay between cultural assimilation and cultural diffusion have played a significant role in giving rise to differential patterns of economic development across the globe. Societies that were geographically less vulnerable to cultural diffusion, benefited from enhanced assimilation, lower cultural diversity and, thus, more intense accumulation of society-specific human capital, enabling them to flourish in the technological paradigm that charact...

The effect of acetylcholine on 14C-assimilates translocation of Isatis tinctoria L

International Nuclear Information System (INIS)

Yang Chongjun; Tang Feiyu; Zhang Ping; Guo Yuhai

2004-01-01

The effects of acetylcholine on 14 C-assimilates translocation are studied with source-channel-sink of Isatis tinctoria L. The experiments show that 0.01 mmol/L treatments of acetylcholine on the phloem, can improve the output of 14 C-assimilates in leaves indicating that acetylcholine enhances the activity of phloem transport. (authors)

Screen-level non-GTS data assimilation in a limited-area mesoscale model

Directory of Open Access Journals (Sweden)

M. Milelli

2010-06-01

Full Text Available The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle. The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particularly improved by the new-data assimilation, but, on the other hand, it has not been destroyed

An assimilation test of Doppler radar reflectivity and radial velocity from different height layers in improving the WRF rainfall forecasts

Science.gov (United States)

Tian, Jiyang; Liu, Jia; Yan, Denghua; Li, Chuanzhe; Chu, Zhigang; Yu, Fuliang

2017-12-01

Hydrological forecasts require high-resolution and accurate rainfall information, which is one of the most difficult variables to be captured by the mesoscale Numerical Weather Prediction (NWP) systems. Radar data assimilation is an effective method for improving rainfall forecasts by correcting the initial and lateral boundary conditions of the NWP system. The aim of this study is to explore an efficient way of utilizing the Doppler radar observations for data assimilation, which is implemented by exploring the effect of assimilating radar data from different height layers on the improvement of the NWP rainfall accuracy. The Weather Research and Forecasting (WRF) model is used for numerical rainfall forecast in the Zijingguan catchment located in the ;Jing-Jin-Ji; (Beijing-Tianjin-Hebei) Region of Northern China, and the three-dimensional variational data assimilation (3-DVar) technique is adopted to assimilate the radar data. Radar reflectivity and radial velocity are assimilated separately and jointly. Each type of radar data is divided into seven data sets according to the height layers: (1) 2000 m, and (7) all layers. The results show that radar reflectivity assimilation leads to better results than radial velocity assimilation. The accuracy of the forecasted rainfall deteriorates with the rise of the height of the assimilated radar reflectivity. The same results can be found when assimilating radar reflectivity and radial velocity at the same time. The conclusions of this study provide a reference for efficient assimilation of the radar data in improving the NWP rainfall products.

Advanced Data Assimilation for Geosciences : Lecture Notes of the Les Houches School of Physics

CERN Document Server

Bocquet, Marc; Cosme, Emmanuel; Cugliandolo, Leticia F

2014-01-01

This book gathers notes from lectures and seminars given during a three-week school on theoretical and applied data assimilation held in Les Houches in 2012. Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography and atmospheric chemistry, with extensions to other geophysical sciences. The physical complexity and ...

Testbed model and data assimilation for ARM

International Nuclear Information System (INIS)

Louis, J.F.

1992-01-01

The objectives of this contract are to further develop and test the ALFA (AER Local Forecast and Assimilation) model originally designed at AER for local weather prediction and apply it to three distinct but related purposes in connection with the Atmospheric Radiation Measurement (ARM) program: (a) to provide a testbed that simulates a global climate model in order to facilitate the development and testing of new cloud parametrizations and radiation models; (b) to assimilate the ARM data continuously at the scale of a climate model, using the adjoint method, thus providing the initial conditions and verification data for testing parameumtions; (c) to study the sensitivity of a radiation scheme to cloud parameters, again using the adjoint method, thus demonstrating the usefulness of the testbed model. The data assimilation will use a variational technique that minimizes the difference between the model results and the observation during the analysis period. The adjoint model is used to compute the gradient of a measure of the model errors with respect to nudging terms that are added to the equations to force the model output closer to the data. The radiation scheme that will be included in the basic ALFA model makes use of a gen two-stream approximation, and is designed for vertically inhonogeneous, multiple-scattering atmospheres. The sensitivity of this model to the definition of cloud parameters will be studied. The adjoint technique will also be used to compute the sensitivities. This project is designed to provide the Science Team members with the appropriate tools and modeling environment for proper testing and tuning of new radiation models and cloud parametrization schemes

Nitrogen uptake and assimilation by corn roots

International Nuclear Information System (INIS)

Yoneyama, Tadakatsu; Akiyama, Yoko; Kumazawa, Kikuo

1977-01-01

The site of nitrogen uptake in the apical root zone of corn was experimentally investigated. Two experiments were performed. The one is to see the assimilation of nitrate and ammonium and the effects of low temperature on it. The 4-day-old roots were treated with 15 N-labelled inorganic nitrogen of 20 ppm N in 5 x 10 -4 M CaSO 4 solution at 30 deg. C and 0 deg. C. The other is to see the nitrogen uptake at apical root zone and the utilization of newly absorbed nitrogen at the root top. The 4-day-old roots were transferred into 5 x 10 -4 M CaSO 4 solution containing 15 N-labelled ammonium nitrate of 40 ppm N. As a result, the effect of low temperature on the nitrogen uptake appeared to be more drastic in the case of nitrate than ammonium. The 15 N content of amino acids indicates that ammonium is assimilated into amino acids even at 0 deg. C, but nitrate is not. The ammonium nitrogen seemed to be absorbed at both cell dividing and elongating zones. On the other hand, nitrate nitrogen seemed to be strongly absorbed at cell elongating zone. The nitrogen in the apical part may be supplied not only by direct absorption but also by translocation from the basal part. The clear difference was found in the utilization of nitrate and ammonium nitrogen at the root top when the root was elongating. This may be due to the difference of assimilation products of inorganic nitrogen. Newly absorbed ammonium nitrogen is more utilizable for the growth of root top than nitrate nitrogen. (Iwakiri, K.)

CATS Near Real Time Data Products: Applications for Assimilation Into the NASA GEOS-5 AGCM

Science.gov (United States)

Hlavka, D. L.; Nowottnick, E. P.; Yorks, J. E.; Da Silva, A.; McGill, M. J.; Palm, S. P.; Selmer, P. A.; Pauly, R. M.; Ozog, S.

2017-01-01

From February 2015 through October 2017, the NASA Cloud-Aerosol Transport System (CATS) backscatter lidar operated on the International Space Station (ISS) as a technology demonstration for future Earth Science Missions, providing vertical measurements of cloud and aerosols properties. Owing to its location on the ISS, a cornerstone technology demonstration of CATS was the capability to acquire, process, and disseminate near-real time (NRT) data within 6 hours of observation time. CATS NRT data has several applications, including providing notification of hazardous events for air traffic control and air quality advisories, field campaign flight planning, as well as for constraining cloud and aerosol distributions in via data assimilation in aerosol transport models.   Recent developments in aerosol data assimilation techniques have permitted the assimilation of aerosol optical thickness (AOT), a 2-dimensional column integrated quantity that is reflective of the simulated aerosol loading in aerosol transport models. While this capability has greatly improved simulated AOT forecasts, the vertical position, a key control on aerosol transport, is often not impacted when 2-D AOT is assimilated. Here, we present preliminary efforts to assimilate CATS aerosol observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model and assimilation system using a 1-D Variational (1-D VAR) ensemble approach, demonstrating the utility of CATS for future Earth Science Missions.

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

KAUST Repository

Khaki, M.

2017-07-06

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

Regularities in the 14C assimilates supply of fruit in old peach trees

International Nuclear Information System (INIS)

Petrov, A.; Manolov, P.

1977-01-01

Autoradiography and 14 C assimilates were used in trials with five-year vase pruned trees of the Dixired peach variety. The labelled assimilates as entries from 14 CO 2 dressed shoots in the skeletal parts were transposted by a narrow phloem strip and directed either towards the fruits or down to the trunk and root system. The cumulation of labelled assimilates in fruits is determined by a series of factors. The main of them was the coincidence of the fruitbearing branchlet base with the radioactive phloem strip of the carrying it skeletal part. The leaves/fruits ratio in regard to the fruitbearing branchlet was a more slightly acting factor and in all probability contributing to the going of photoassimilates in fruits only in the case of coincidence of the basal part of fruitbearing branchlet with the radioactive steam. The transport to the fruits was both basipetal and acropetal. The 14 C assimilates stream towards the root system could get fully exhausted and stopped by branchlets covered with numerous fruits and insufficient leafage disposed on the radioactive strip. On the other hand, the basipetal 14 C assimilates stream at the base of the erected skeletal parts, caused by a strong acceptable organ the root system, hampers the labelled assimilates supply even of those fruitbearing branchlets with a low leaves/fruits ratio whose basal parts coincided with the radioactive strip. To this contributed also the great difference in the thicknesses between the skeletal part and the side fruitbearing branchlets. The examined transport type explained to some extent the slighter growth of fruits in the lower part of compact peach tree crowns reg ardless of the great leafage presence in this top parts. (author)

A Framework for Research on E-Learning Assimilation in SMEs: A Strategic Perspective

Science.gov (United States)

Raymond, Louis; Uwizeyemungu, Sylvestre; Bergeron, Francois; Gauvin, Stephane

2012-01-01

Purpose: This study aims to propose an integrative conceptual framework of e-learning adoption and assimilation that is adapted to the specific context of small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature on the state of e-learning usage in SMEs and on the IT adoption and assimilation factors that can be…

Oxidation and Assimilation of Carbohydrates by Micrococcus sodonensis1

Science.gov (United States)

Perry, Jerome J.; Evans, James B.

1966-01-01

Perry, Jerome J. (North Carolina State University, Raleigh), and James B. Evans. Oxidation and assimilation of carbohydrates by Micrococcus sodonensis. J. Bacteriol. 91:33–38. 1966.—Micrococcus sodonensis is a biotin-requiring strict aerobe that cannot utilize carbohydrates as sole sources of carbon and energy. However, addition of mannose, glucose, sucrose, or maltose to a medium on which the organism can grow resulted in an increase in total growth. M. sodonensis oxidized these sugars without induction, thus indicating the presence of constitutive enzymes for their transport, activation, and metabolism. Under appropriate nonproliferating cell conditions, glucose was readily incorporated into essential constituents of the cell. When glucose-1-C14 and glucose-6-C14 were oxidized by nonproliferating cells, the label was found in both the protein and nucleic acid fractions of the cell. The respiratory quotients of cells oxidizing glucose in saline and in phosphate buffer indicated assimilation of sugar carbon in buffer and virtually no assimilation in saline. The ability of M. sodonensis to completely oxidize glucose and to grow on intermediates of glucose oxidation but not on glucose suggests that glucose may suppress or repress some reaction(s) necessary for growth, and that growth substrates either derepress or circumvent this block. PMID:5903100

Unscented Kalman filter assimilation of time-lapse self-potential data for monitoring solute transport

Science.gov (United States)

Cui, Yi-an; Liu, Lanbo; Zhu, Xiaoxiong

2017-08-01

Monitoring the extent and evolution of contaminant plumes in local and regional groundwater systems from existing landfills is critical in contamination control and remediation. The self-potential survey is an efficient and economical nondestructive geophysical technique that can be used to investigate underground contaminant plumes. Based on the unscented transform, we have built a Kalman filtering cycle to conduct time-lapse data assimilation for monitoring the transport of solute based on the solute transport experiment using a bench-scale physical model. The data assimilation was formed by modeling the evolution based on the random walk model and observation correcting based on the self-potential forward. Thus, monitoring self-potential data can be inverted by the data assimilation technique. As a result, we can reconstruct the dynamic process of the contaminant plume instead of using traditional frame-to-frame static inversion, which may cause inversion artifacts. The data assimilation inversion algorithm was evaluated through noise-added synthetic time-lapse self-potential data. The result of the numerical experiment shows validity, accuracy and tolerance to the noise of the dynamic inversion. To validate the proposed algorithm, we conducted a scaled-down sandbox self-potential observation experiment to generate time-lapse data that closely mimics the real-world contaminant monitoring setup. The results of physical experiments support the idea that the data assimilation method is a potentially useful approach for characterizing the transport of contamination plumes using the unscented Kalman filter (UKF) data assimilation technique applied to field time-lapse self-potential data.

How exogenous nitric oxide regulates nitrogen assimilation in wheat seedlings under different nitrogen sources and levels.

Science.gov (United States)

Balotf, Sadegh; Islam, Shahidul; Kavoosi, Gholamreza; Kholdebarin, Bahman; Juhasz, Angela; Ma, Wujun

2018-01-01

Nitrogen (N) is one of the most important nutrients for plants and nitric oxide (NO) as a signaling plant growth regulator involved in nitrogen assimilation. Understanding the influence of exogenous NO on nitrogen metabolism at the gene expression and enzyme activity levels under different sources of nitrogen is vitally important for increasing nitrogen use efficiency (NUE). This study investigated the expression of key genes and enzymes in relation to nitrogen assimilation in two Australian wheat cultivars, a popular high NUE cv. Spitfire and a normal NUE cv. Westonia, under different combinations of nitrogen and sodium nitroprusside (SNP) as the NO donor. Application of NO increased the gene expressions and activities of nitrogen assimilation pathway enzymes in both cultivars at low levels of nitrogen. At high nitrogen supplies, the expressions and activities of N assimilation genes increased in response to exogenous NO only in cv. Spitfire but not in cv. Westonia. Exogenous NO caused an increase in leaf NO content at low N supplies in both cultivars, while under high nitrogen treatments, cv. Spitfire showed an increase under ammonium nitrate (NH4NO3) treatment but cv. Westonia was not affected. N assimilation gene expression and enzyme activity showed a clear relationship between exogenous NO, N concentration and N forms in primary plant nitrogen assimilation. Results reveal the possible role of NO and different nitrogen sources on nitrogen assimilation in Triticum aestivum plants.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

Science.gov (United States)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Development and validation of a system of assimilation indices: A mixed method approach to understand change in psychotherapy.

Science.gov (United States)

Neto, David D; Baptista, Telmo M; Dent-Brown, Kim

2015-06-01

Assimilation is an important process in understanding change in psychotherapy. Similar to other psychological processes, assimilation may be traceable in the speech of clients by attending to its signs or indices. In the present research, we aimed to build a system of indices of assimilation. This research follows a mixed method design. The indices were derived through qualitative analysis, using grounded theory. Subsequently, the indices were adjusted quantitatively and applied to 30 single psychotherapy sessions of adult clients with depression and 11 therapists. Forty-two indices were found and grouped into the following five process categories of assimilation: external distress, pain, noticing, decentring and action. The indices showed good inter-rater reliability and internal consistency. Except for noticing, all process categories correlated significantly with each other according to conceptual proximity. The system of indices also showed convergent validity with an existing coding system of assimilation for two process categories. The results suggest that the system of indices is a useful approach for understanding assimilation. The consideration of assimilation in a continuous fashion through sub-processes may help to extend our knowledge of this process and provide a tool for clinical practice. Assimilation is an important process in understanding change in psychotherapy in the sense that it takes into account insight and action-related processes. Clients convey in their speech signs or indices of the assimilation process which can be observed both in the style and content of their utterances. Using these indices, therapists can continuously assess assimilation and use this information in choosing interventions. Limitations: This study follows a cross-sectional design and does not allow consideration of the predictive value of the indices. The outcome of the therapy was not taken into account, which restricts validity considerations to the comparison with

Impact of SLA assimilation in the Sicily Channel Regional Model: model skills and mesoscale features

Directory of Open Access Journals (Sweden)

A. Olita

2012-07-01

Full Text Available The impact of the assimilation of MyOcean sea level anomalies along-track data on the analyses of the Sicily Channel Regional Model was studied. The numerical model has a resolution of 1/32° degrees and is capable to reproduce mesoscale and sub-mesoscale features. The impact of the SLA assimilation is studied by comparing a simulation (SIM, which does not assimilate data with an analysis (AN assimilating SLA along-track multi-mission data produced in the framework of MyOcean project. The quality of the analysis was evaluated by computing RMSE of the misfits between analysis background and observations (sea level before assimilation. A qualitative evaluation of the ability of the analyses to reproduce mesoscale structures is accomplished by comparing model results with ocean colour and SST satellite data, able to detect such features on the ocean surface. CTD profiles allowed to evaluate the impact of the SLA assimilation along the water column. We found a significant improvement for AN solution in terms of SLA RMSE with respect to SIM (the averaged RMSE of AN SLA misfits over 2 years is about 0.5 cm smaller than SIM. Comparison with CTD data shows a questionable improvement produced by the assimilation process in terms of vertical features: AN is better in temperature while for salinity it gets worse than SIM at the surface. This suggests that a better a-priori description of the vertical error covariances would be desirable. The qualitative comparison of simulation and analyses with synoptic satellite independent data proves that SLA assimilation allows to correctly reproduce some dynamical features (above all the circulation in the Ionian portion of the domain and mesoscale structures otherwise misplaced or neglected by SIM. Such mesoscale changes also infer that the eddy momentum fluxes (i.e. Reynolds stresses show major changes in the Ionian area. Changes in Reynolds stresses reflect a different pumping of eastward momentum from the eddy to

Scalar and Vector Spherical Harmonics for Assimilation of Global Datasets in the Ionosphere and Thermosphere

Science.gov (United States)

Miladinovich, D.; Datta-Barua, S.; Bust, G. S.; Ramirez, U.

2017-12-01

Understanding physical processes during storm time in the ionosphere-thermosphere (IT) system is limited, in part, due to the inability to obtain accurate estimates of IT states on a global scale. One reason for this inability is the sparsity of spatially distributed high quality data sets. Data assimilation is showing promise toward enabling global estimates by blending high quality observational data sets with established climate models. We are continuing development of an algorithm called Estimating Model Parameters for Ionospheric Reverse Engineering (EMPIRE) to enable assimilation of global datasets for storm time estimates of IT drivers. EMPIRE is a data assimilation algorithm that uses a Kalman filtering routine to ingest model and observational data. The EMPIRE algorithm is based on spherical harmonics which provide a spherically symmetric, smooth, continuous, and orthonormal set of basis functions suitable for a spherical domain such as Earth's IT region (200-600 km altitude). Once the basis function coefficients are determined, the newly fitted function represents the disagreement between observational measurements and models. We apply spherical harmonics to study the March 17, 2015 storm. Data sources include Fabry-Perot interferometer neutral wind measurements and global Ionospheric Data Assimilation 4 Dimensional (IDA4D) assimilated total electron content (TEC). Models include Weimer 2000 electric potential, International Geomagnetic Reference Field (IGRF) magnetic field, and Horizontal Wind Model 2014 (HWM14) neutral winds. We present the EMPIRE assimilation results of Earth's electric potential and thermospheric winds. We also compare EMPIRE storm time E cross B ion drift estimates to measured drifts produced from the Super Dual Auroral Radar Network (SuperDARN) and Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) measurement datasets. The analysis from these results will enable the generation of globally assimilated

Improving carbon model phenology using data assimilation

Science.gov (United States)

Exrayat, Jean-François; Smallman, T. Luke; Bloom, A. Anthony; Williams, Mathew

2015-04-01

Carbon cycle dynamics is significantly impacted by ecosystem phenology, leading to substantial seasonal and inter-annual variation in the global carbon balance. Representing inter-annual variability is key for predicting the response of the terrestrial ecosystem to climate change and disturbance. Existing terrestrial ecosystem models (TEMs) often struggle to accurately simulate observed inter-annual variability. TEMs often use different phenological models based on plant functional type (PFT) assumptions. Moreover, due to a high level of computational overhead in TEMs they are unable to take advantage of globally available datasets to calibrate their models. Here we describe the novel CARbon DAta MOdel fraMework (CARDAMOM) for data assimilation. CARDAMOM is used to calibrate the Data Assimilation Linked Ecosystem Carbon version 2 (DALEC2) model using Bayes' Theorem within a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC). CARDAMOM provides a framework which combines knowledge from observations, such as remotely sensed LAI, and heuristic information in the form of Ecological and Dynamical Constraints (EDCs). The EDCs are representative of real world processes and constrain parameter interdependencies and constrain carbon dynamics. We used CARDAMOM to bring together globally spanning datasets of LAI and the DALEC2 and DALEC2-GSI models. These analyses allow us to investigate the sensitivity ecosystem processes to the representation of phenology. DALEC2 uses an analytically solved model of phenology which is invariant between years. In contrast DALEC2-GSI uses a growing season index (GSI) calculated as a function of temperature, vapour pressure deficit (VPD) and photoperiod to calculate bud-burst and leaf senescence, allowing the model to simulate inter-annual variability in response to climate. Neither model makes any PFT assumptions about the phenological controls of a given ecosystem, allowing the data alone to determine the impact of the meteorological

Dynamic Responses of the Earth's Outer Core to Assimilation of Observed Geomagnetic Secular Variation

Science.gov (United States)

Kuang, Weijia; Tangborn, Andrew

2014-01-01

Assimilation of surface geomagnetic observations and geodynamo models has advanced very quickly in recent years. However, compared to advanced data assimilation systems in meteorology, geomagnetic data assimilation (GDAS) is still in an early stage. Among many challenges ranging from data to models is the disparity between the short observation records and the long time scales of the core dynamics. To better utilize available observational information, we have made an effort in this study to directly assimilate the Gauss coefficients of both the core field and its secular variation (SV) obtained via global geomagnetic field modeling, aiming at understanding the dynamical responses of the core fluid to these additional observational constraints. Our studies show that the SV assimilation helps significantly to shorten the dynamo model spin-up process. The flow beneath the core-mantle boundary (CMB) responds significantly to the observed field and its SV. The strongest responses occur in the relatively small scale flow (of the degrees L is approx. 30 in spherical harmonic expansions). This part of the flow includes the axisymmetric toroidal flow (of order m = 0) and non-axisymmetric poloidal flow with m (is) greater than 5. These responses can be used to better understand the core flow and, in particular, to improve accuracies of predicting geomagnetic variability in future.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

Science.gov (United States)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems

KAUST Repository

Luo, Xiaodong

2014-12-01

This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-offbetween efficiency and accuracy.

Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim

2014-01-01

This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-offbetween efficiency and accuracy.

An algorithm for variational data assimilation of contact concentration measurements for atmospheric chemistry models

Science.gov (United States)

Penenko, Alexey; Penenko, Vladimir

2014-05-01

Contact concentration measurement data assimilation problem is considered for convection-diffusion-reaction models originating from the atmospheric chemistry study. High dimensionality of models imposes strict requirements on the computational efficiency of the algorithms. Data assimilation is carried out within the variation approach on a single time step of the approximated model. A control function is introduced into the source term of the model to provide flexibility for data assimilation. This function is evaluated as the minimum of the target functional that connects its norm to a misfit between measured and model-simulated data. In the case mathematical model acts as a natural Tikhonov regularizer for the ill-posed measurement data inversion problem. This provides flow-dependent and physically-plausible structure of the resulting analysis and reduces a need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. The advantage comes at the cost of the adjoint problem solution. This issue is solved within the frameworks of splitting-based realization of the basic convection-diffusion-reaction model. The model is split with respect to physical processes and spatial variables. A contact measurement data is assimilated on each one-dimensional convection-diffusion splitting stage. In this case a computationally-efficient direct scheme for both direct and adjoint problem solution can be constructed based on the matrix sweep method. Data assimilation (or regularization) parameter that regulates ratio between model and data in the resulting analysis is obtained with Morozov discrepancy principle. For the proper performance the algorithm takes measurement noise estimation. In the case of Gaussian errors the probability that the used Chi-squared-based estimate is the upper one acts as the assimilation parameter. A solution obtained can be used as the initial guess for data assimilation algorithms that assimilate

Molecular Epidemiology of a novel re-assorted epidemic strain of equine influenza virus in Pakistan in 2015-16.

Science.gov (United States)

Khan, Amjad; Mushtaq, Muhammad Hassan; Ahmad, Mansur Ud Din; Nazir, Jawad; Farooqi, Shahid Hussain; Khan, Asghar

2017-08-15

A widespread epidemic of equine influenza (EI) occurred in nonvaccinated equine population across multiple districts in Khyber Pakhtunkhwa Province of Pakistan during 2015-2016. An epidemiological surveillance study was conducted from Oct 2015 to April 2016 to investigate the outbreak. EI virus strains were isolated in embryonated eggs from suspected equines swab samples and were subjected to genome sequencing using M13 tagged segment specific primers. Phylogenetic analyses of the nucleotide sequences were concluded using Geneious. Haemagglutinin (HA), Neuraminidase (NA), Matrix (M) and nucleoprotein (NP) genes nucleotide and amino acid sequences of the isolated viruses were aligned with those of OIE recommended, FC-1, FC-2, and contemporary isolates of influenza A viruses from other species. HA and NA genes amino acid sequences were very similar to Tennessee/14 and Malaysia/15 of FC-1 and clustered with the contemporary isolates recently reported in the USA. Phylogenetic analysis showed that these viruses were mostly identical (with 99.6% and 97.4% nucleotide homology) to, and were reassortants containing chicken/Pakistan/14 (H7N3) and Canine/Beijing/10 (H3N2) like M and NP genes. Genetic analysis indicated that A/equine/Pakistan/16 viruses were most probably the result of several re-assortments between the co-circulating avian and equine viruses, and were genetically unlike the other equine viruses due to the presence of H7N3 or H3N2 like M and NP genes. Epidemiological data analysis indicated the potential chance of mixed, and management such as mixed farming system by keeping equine, canine and backyard poultry together in confined premises as the greater risk factors responsible for the re-assortments. Other factors might have contributed to the spread of the epidemic, including low awareness level, poor control of equine movements, and absence of border control disease strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

NOAA HRD's HEDAS Data Assimilation System's performance for the 2010 Atlantic Hurricane Season

Science.gov (United States)

Sellwood, K.; Aksoy, A.; Vukicevic, T.; Lorsolo, S.

2010-12-01

The Hurricane Ensemble Data Assimilation System (HEDAS) was developed at the Hurricane Research Division (HRD) of NOAA, in conjunction with an experimental version of the Hurricane Weather and Research Forecast model (HWRFx), in an effort to improve the initial representation of the hurricane vortex by utilizing high resolution in-situ data collected during NOAA’s Hurricane Field Program. HEDAS implements the “ensemble square root “ filter of Whitaker and Hamill (2002) using a 30 member ensemble obtained from NOAA/ESRL’s ensemble Kalman filter (EnKF) system and the assimilation is performed on a 3-km nest centered on the hurricane vortex. As part of NOAA’s Hurricane Forecast Improvement Program (HFIP), HEDAS will be run in a semi-operational mode for the first time during the 2010 Atlantic hurricane season and will assimilate airborne Doppler radar winds, dropwindsonde and flight level wind, temperature, pressure and relative humidity, and Stepped Frequency Microwave Radiometer surface wind observations as they become available. HEDAS has been implemented in an experimental mode for the cases of Hurricane Bill, 2009 and Paloma, 2008 to confirm functionality and determine the optimal configuration of the system. This test case demonstrates the importance of assimilating thermodynamic data in addition to wind observations and the benefit of increasing the quantity and distribution of observations. Applying HEDAS to a larger sample of storm forecasts would provide further insight into the behavior of the model when inner core aircraft observations are assimilated. The main focus of this talk will be to present a summary of HEDAS performance in the HWRFx model for the inaugural season. The HEDAS analyses and the resulting HWRFx forecasts will be compared with HWRFx analyses and forecasts produced concurrently using the HRD modeling group’s vortex initialization which does not employ data assimilation. The initial vortex and subsequent forecasts will be

A New Methodology for the Extension of the Impact of Data Assimilation on Ocean Wave Prediction

Science.gov (United States)

2008-07-01

Assimilation method The analysis fields used were corrected by an assimilation method developed at the Norwegian Meteorological Insti- tute ( Breivik and Reistad...523–535 525 becomes equal to the solution obtained by optimal interpolation (see Bratseth 1986 and Breivik and Reistad 1994). The iterations begin with...updated accordingly. A more detailed description of the assimilation method is given in Breivik and Reistad (1994). 2.3 Kolmogorov–Zurbenko filters

Assimilation of lake water surface temperature observations using an extended Kalman filter

Directory of Open Access Journals (Sweden)

Ekaterina Kourzeneva

2014-10-01

Full Text Available A new extended Kalman filter (EKF-based algorithm to assimilate lake water surface temperature (LWST observations into the lake model/parameterisation scheme Freshwater Lake (FLake has been developed. The data assimilation algorithm has been implemented into the stand-alone offline version of FLake. The mixed and non-mixed regimes in lakes are treated separately by the EKF algorithm. The timing of the ice period is indicated implicitly: no ice if water surface temperature is measured. Numerical experiments are performed using operational in-situ observations for 27 lakes and merged observations (in-situ plus satellite for 4 lakes in Finland. Experiments are analysed, potential problems are discussed, and the role of early spring observations is studied. In general, results of experiments are promising: (1 the impact of observations (calculated as the normalised reduction of the LWST root mean square error comparing to the free model run is more than 90% and (2 in cross-validation (when observations are partly assimilated, partly used for validation the normalised reduction of the LWST error standard deviation is more than 65%. The new data assimilation algorithm will allow prognostic variables in the lake parameterisation scheme to be initialised in operational numerical weather prediction models and the effects of model errors to be corrected by using LWST observations.

Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea

Science.gov (United States)

Kaufman, Daniel E.; Friedrichs, Marjorie A. M.; Hemmings, John C. P.; Smith, Walker O., Jr.

2018-01-01

The Ross Sea is a region characterized by high primary productivity in comparison to other Antarctic coastal regions, and its productivity is marked by considerable variability both spatially (1-50 km) and temporally (days to weeks). This variability presents a challenge for inferring phytoplankton dynamics from observations that are limited in time or space, which is often the case due to logistical limitations of sampling. To better understand the spatiotemporal variability in Ross Sea phytoplankton dynamics and to determine how restricted sampling may skew dynamical interpretations, high-resolution bio-optical glider measurements were assimilated into a one-dimensional biogeochemical model adapted for the Ross Sea. The assimilation of data from the entire glider track using the micro-genetic and local search algorithms in the Marine Model Optimization Testbed improves the model-data fit by ˜ 50 %, generating rates of integrated primary production of 104 g C m-2 yr-1 and export at 200 m of 27 g C m-2 yr-1. Assimilating glider data from three different latitudinal bands and three different longitudinal bands results in minimal changes to the simulations, improves the model-data fit with respect to unassimilated data by ˜ 35 %, and confirms that analyzing these glider observations as a time series via a one-dimensional model is reasonable on these scales. Whereas assimilating the full glider data set produces well-constrained simulations, assimilating subsampled glider data at a frequency consistent with cruise-based sampling results in a wide range of primary production and export estimates. These estimates depend strongly on the timing of the assimilated observations, due to the presence of high mesoscale variability in this region. Assimilating surface glider data subsampled at a frequency consistent with available satellite-derived data results in 40 % lower carbon export, primarily resulting from optimized rates generating more slowly sinking diatoms. This

Delineating Hydrofacies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics

Energy Technology Data Exchange (ETDEWEB)

Song, Xuehang [Florida State Univ., Tallahassee, FL (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ye, Ming [Florida State Univ., Tallahassee, FL (United States); Dai, Zhenxue [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hammond, Glenn Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-07-01

This study develops a new framework of facies-based data assimilation for characterizing spatial distribution of hydrofacies and estimating their associated hydraulic properties. This framework couples ensemble data assimilation with transition probability-based geostatistical model via a parameterization based on a level set function. The nature of ensemble data assimilation makes the framework efficient and flexible to be integrated with various types of observation data. The transition probability-based geostatistical model keeps the updated hydrofacies distributions under geological constrains. The framework is illustrated by using a two-dimensional synthetic study that estimates hydrofacies spatial distribution and permeability in each hydrofacies from transient head data. Our results show that the proposed framework can characterize hydrofacies distribution and associated permeability with adequate accuracy even with limited direct measurements of hydrofacies. Our study provides a promising starting point for hydrofacies delineation in complex real problems.

Intelligent, net or wireless enabled fluorosensors for high throughput monitoring of assorted crops

International Nuclear Information System (INIS)

Barócsi, Attila

2013-01-01

Phenotypic characterization of assorted crops of different genotypes requires large data sets of diverse types for statistical reliability. Temporal monitoring of plant fluorescence is able to capture the dynamics of the photosynthesis process that is summarized in a number of parameters for which the genotypic heritability can be calculated. In this paper, an intelligent sensor system is presented that is capable of high-throughput production of baseline-corrected temporal fluorescence curves with many feature points. These are obtained by integrating several (direct and modulated) measurement methods applied at different wavelengths. Simultaneously, temporal change of the sample's emission and the ambient reference temperatures are recorded. Multiple sensors can be deployed easily in large span greenhouse environments with centralized data collection over wired or wireless infrastructure. The unique features of the sensors are a compact, embedded signal guiding fibre optic system, instrument-standard variable tubular detector and source modules, net or wireless enabling for remote control and fast, quasi real-time data collection. Along with the instrumentation, some representative phenotyping data are also presented that were taken on a subset of pepper recombinant inbred line population. It is also demonstrated that transient fluorescence feature points yield high heritability, offering a high confidence level for distinguishing the pepper genotypes. (paper)

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

Science.gov (United States)

Leuenberger, D.; Rossa, A.

2007-12-01

Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic

Directory of Open Access Journals (Sweden)

P. Sakov

2012-08-01

Full Text Available We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003–2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation in the North Atlantic and the sea-ice variability in the Arctic. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates – a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in-situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed several flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level.

Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

Directory of Open Access Journals (Sweden)

Seungpil Jung

2018-02-01

Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

Regulation of assimilate partitioning by daylength and spectral quality

Energy Technology Data Exchange (ETDEWEB)

Britz, S.J. [USDA-Climate Stress Lab., Beltsville, MD (United States)

1994-12-31

Photosynthesis is the process by which plants utilize light energy to assimilate and transform carbon dioxide into products that support growth and development. The preceding review provides an excellent summary of photosynthetic mechanisms and diurnal patterns of carbon metabolism with emphasis on the importance of gradual changes in photosynthetically-active radiation at dawn and dusk. In addition to these direct effects of irradiance, there are indirect effects of light period duration and spectral quality on carbohydrate metabolism and assimilate partitioning. Both daylength and spectral quality trigger developmental phenomena such as flowering (e.g., photoperiodism) and shade avoidance responses, but their effects on partitioning of photoassimilates in leaves are less well known. Moreover, the adaptive significance to the plants of such effects is sometimes not clear.

Insights on the impact of systematic model errors on data assimilation performance in changing catchments

Science.gov (United States)

Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.

2018-03-01

The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.

A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes

Science.gov (United States)

Haussaire, J.-M.; Bocquet, M.

2015-08-01

Bocquet and Sakov (2013) have introduced a low-order model based on the coupling of the chaotic Lorenz-95 model which simulates winds along a mid-latitude circle, with the transport of a tracer species advected by this zonal wind field. This model, named L95-T, can serve as a playground for testing data assimilation schemes with an online model. Here, the tracer part of the model is extended to a reduced photochemistry module. This coupled chemistry meteorology model (CCMM), the L95-GRS model, mimics continental and transcontinental transport and the photochemistry of ozone, volatile organic compounds and nitrogen oxides. Its numerical implementation is described. The model is shown to reproduce the major physical and chemical processes being considered. L95-T and L95-GRS are specifically designed and useful for testing advanced data assimilation schemes, such as the iterative ensemble Kalman smoother (IEnKS) which combines the best of ensemble and variational methods. These models provide useful insights prior to the implementation of data assimilation methods on larger models. We illustrate their use with data assimilation schemes on preliminary, yet instructive numerical experiments. In particular, online and offline data assimilation strategies can be conveniently tested and discussed with this low-order CCMM. The impact of observed chemical species concentrations on the wind field can be quantitatively estimated. The impacts of the wind chaotic dynamics and of the chemical species non-chaotic but highly nonlinear dynamics on the data assimilation strategies are illustrated.

4DVAR data Assimilation with the Regional Ocean Modeling System (ROMS): Impact on the Water Mass Distributions in the Yellow Sea

Science.gov (United States)

Lee, Joon-Ho; Kim, Taekyun; Pang, Ig-Chan; Moon, Jae-Hong

2018-04-01

In this study, we evaluate the performance of the recently developed incremental strong constraint 4-dimensional variational (4DVAR) data assimilation applied to the Yellow Sea (YS) using the Regional Ocean Modeling System (ROMS). Two assimilation experiments are compared: assimilating remote-sensed sea surface temperature (SST) and both the SST and in-situ profiles measured by shipboard CTD casts into a regional ocean modeling from January to December of 2011. By comparing the two assimilation experiments against a free-run without data assimilation, we investigate how the assimilation affects the hydrographic structures in the YS. Results indicate that the SST assimilation notably improves the model behavior at the surface when compared to the nonassimilative free-run. The SST assimilation also has an impact on the subsurface water structure in the eastern YS; however, the improvement is seasonally dependent, that is, the correction becomes more effective in winter than in summer. This is due to a strong stratification in summer that prevents the assimilation of SST from affecting the subsurface temperature. A significant improvement to the subsurface temperature is made when the in-situ profiles of temperature and salinity are assimilated, forming a tongue-shaped YS bottom cold water from the YS toward the southwestern seas of Jeju Island.

Nonlinear data assimilation

CERN Document Server

Van Leeuwen, Peter Jan; Reich, Sebastian

2015-01-01

This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.

Impact of interspecific competition and drought on the allocation of new assimilates in trees.

Science.gov (United States)

Hommel, R; Siegwolf, R; Zavadlav, S; Arend, M; Schaub, M; Galiano, L; Haeni, M; Kayler, Z E; Gessler, A

2016-09-01

In trees, the interplay between reduced carbon assimilation and the inability to transport carbohydrates to the sites of demand under drought might be one of the mechanisms leading to carbon starvation. However, we largely lack knowledge on how drought effects on new assimilate allocation differ between species with different drought sensitivities and how these effects are modified by interspecific competition. We assessed the fate of (13) C labelled assimilates in above- and belowground plant organs and in root/rhizosphere respired CO2 in saplings of drought-tolerant Norway maple (Acer platanoides) and drought-sensitive European beech (Fagus sylvatica) exposed to moderate drought, either in mono- or mixed culture. While drought reduced stomatal conductance and photosynthesis rates in both species, both maintained assimilate transport belowground. Beech even allocated more new assimilate to the roots under moderate drought compared to non-limited water supply conditions, and this pattern was even more pronounced under interspecific competition. Even though maple was a superior competitor compared to beech under non-limited soil water conditions, as indicated by the changes in above- and belowground biomass of both species in the interspecific competition treatments, we can state that beech was still able to efficiently allocate new assimilate belowground under combined drought and interspecific competition. This might be seen as a strategy to maintain root osmotic potential and to prioritise root functioning. Our results thus show that beech tolerates moderate drought stress plus competition without losing its ability to supply belowground tissues. It remains to be explored in future work if this strategy is also valid during long-term drought exposure. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.

Data assimilation method based on the constraints of confidence region

Science.gov (United States)

Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

2018-03-01

The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

Regional Ocean Data Assimilation

KAUST Repository

Edwards, Christopher A.

2015-01-03

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework

KAUST Repository

Attada, Raju; Parekh, Anant; Chowdary, J. S.; Gnanaseelan, C.

2017-01-01

in the reanalysis that assimilates AIRS profiles. The change induced by AIRS data on the moist and thermodynamic conditions results in more realistic rendering of the vertical shear associated with the monsoon, which in turn leads to a proper moisture transport

Alternative reproductive tactics and inverse size-assortment in a high-density fish spawning aggregation.

Science.gov (United States)

Karkarey, Rucha; Zambre, Amod; Isvaran, Kavita; Arthur, Rohan

2017-02-28

At high densities, terrestrial and marine species often employ alternate reproductive tactics (ARTs) to maximize reproductive benefits. We describe ARTs in a high-density and unfished spawning aggregation of the squaretail grouper (Plectropomus areolatus) in Lakshadweep, India. As previously reported for this species, territorial males engage in pair-courtship, which is associated with a pair-spawning tactic. Here, we document a previously unreported school-courtship tactic; where territorial males court multiple females in mid-water schools, which appears to culminate in a unique 'school-spawning' tactic. Courtship tactics were conditional on body size, local mate density and habitat, likely associated with changing trade-offs between potential mating opportunities and intra-sexual competition. Counter-intuitively, the aggregation showed a habitat-specific inverse size-assortment: large males courted small females on the reef slope while small males courted equal-sized or larger females on the shelf. These patterns remained stable across two years of observation at high, unfished densities. These unique density-dependent behaviours may disappear from this aggregation as overall densities decline due to increasing commercial fishing pressure, with potentially large consequences for demographics and fitness.

Data ingestion and assimilation in ionospheric models

Czech Academy of Sciences Publication Activity Database

Burešová, Dalia; Nava, B.; Galkin, I.; Angling, M.; Stankov, S. M.; Coisson, P.

2009-01-01

Roč. 52, 3/4 (2009), s. 235-253 ISSN 1593-5213 R&D Projects: GA ČR GA205/08/1356; GA MŠk OC 091 Institutional research plan: CEZ:AV0Z30420517 Keywords : ionosphere * models * data assimilation * data ingestion Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.548, year: 2009

Genome assortment, not serogroup, defines Vibrio cholerae pandemic strains

Energy Technology Data Exchange (ETDEWEB)

Brettin, Thomas S [Los Alamos National Laboratory; Bruce, David C [Los Alamos National Laboratory; Challacombe, Jean F [Los Alamos National Laboratory; Detter, John C [Los Alamos National Laboratory; Han, Cliff S [Los Alamos National Laboratory; Munik, A C [Los Alamos National Laboratory; Chertkov, Olga [Los Alamos National Laboratory; Meincke, Linda [Los Alamos National Laboratory; Saunders, Elizabeth [Los Alamos National Laboratory; Choi, Seon Y [SEOUL NATL. UNIV.; Haley, Bradd J [U. MARYLAND; Taviani, Elisa [U. MARYLAND; Jeon, Yoon - Seong [INTL. VACCINE INST. SEOUL; Kim, Dong Wook [INTL. VACCINE INST. SEOUL; Lee, Jae - Hak [SEOUL NATL. UNIV.; Walters, Ronald A [PNNL; Hug, Anwar [NATL. INST. CHOLERIC ENTERIC DIS.; Colwell, Rita R [U. MARYLAND

2009-01-01

Vibrio cholerae, the causative agent of cholera, is a bacterium autochthonous to the aquatic environment, and a serious public health threat. V. cholerae serogroup O1 is responsible for the previous two cholera pandemics, in which classical and El Tor biotypes were dominant in the 6th and the current 7th pandemics, respectively. Cholera researchers continually face newly emerging and re-emerging pathogenic clones carrying combinations of new serogroups as well as of phenotypic and genotypic properties. These genotype and phenotype changes have hampered control of the disease. Here we compare the complete genome sequences of 23 strains of V. cholerae isolated from a variety of sources and geographical locations over the past 98 years in an effort to elucidate the evolutionary mechanisms governing genetic diversity and genesis of new pathogenic clones. The genome-based phylogeny revealed 12 distinct V. cholerae phyletic lineages, of which one, designated the V. cholerae core genome (CG), comprises both O1 classical and EI Tor biotypes. All 7th pandemic clones share nearly identical gene content, i.e., the same genome backbone. The transition from 6th to 7th pandemic strains is defined here as a 'shift' between pathogenic clones belonging to the same O1 serogroup, but from significantly different phyletic lineages within the CG clade. In contrast, transition among clones during the present 7th pandemic period can be characterized as a 'drift' between clones, differentiated mainly by varying composition of laterally transferred genomic islands, resulting in emergence of variants, exemplified by V.cholerae serogroup O139 and V.cholerae O1 El Tor hybrid clones that produce cholera toxin of classical biotype. Based on the comprehensive comparative genomics presented in this study it is concluded that V. cholerae undergoes extensive genetic recombination via lateral gene transfer, and, therefore, genome assortment, not serogroup, should be used to

Leaching of assimilable silicon species from fly ash

International Nuclear Information System (INIS)

Piekos, R.; Paslawska, S.

1998-01-01

The objective of this study was to investigate the leaching of assimilable silicon species from coal fly ash with distilled water, sea waterand synthetic sea water at various fly ash/water ratios, pHs and temperatures. At the 1 g/100 ml fly ash/water ratio, less than 1 mg Si was found in 11 of aqueous slurries over the pH range 4-8 after 2 h at ambient temperature. The leaching was most effective at pH 10.5. At the fly ash/waterratio indicated, the pH of the suspensions decreased from 10.4 to 8.4 after 5days. The pH of fly ash slurries in sea water varied only slightly over time as compared with that in distilled water. Generally, the leaching of assimilable silicon species with distilled water was more intense than that with the sea water. 27 refs., 6 figs., 3 tabs

Evaluation of a Soil Moisture Data Assimilation System Over West Africa

Science.gov (United States)

Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.

2009-05-01

A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model

Limitations of wind extraction from 4D-Var assimilation of ozone

Directory of Open Access Journals (Sweden)

D. R. Allen

2013-03-01

Full Text Available Time-dependent variational data assimilation allows the possibility of extracting wind information from observations of ozone or other trace gases. Since trace gas observations are not available at sufficient resolution for deriving feature-track winds, they must be combined with model background information to produce an analysis. If done with time-dependent variational assimilation, wind information may be extracted via the adjoint of the linearized tracer continuity equation. This paper presents idealized experiments that illustrate the mechanics of tracer–wind extraction and demonstrate some of the limitations of this procedure. We first examine tracer–wind extraction using a simple one-dimensional advection equation. The analytic solution for a single trace gas observation is discussed along with numerical solutions for multiple observations. The limitations of tracer–wind extraction are then explored using highly idealized ozone experiments performed with a development version of the Navy Global Environmental Model (NAVGEM in which globally distributed hourly stratospheric ozone profiles are assimilated in a single 6 h update cycle in January 2009. Starting with perfect background ozone conditions, but imperfect dynamical conditions, ozone errors develop over the 6 h background window. Wind increments are introduced in the analysis in order to reduce the differences between background ozone and ozone observations. For "perfect" observations (unbiased and no random error, this results in root-mean-square (RMS vector wind error reductions of up to ~4 m s−1 in the winter hemisphere and tropics. Wind extraction is more difficult in the summer hemisphere due to weak ozone gradients and smaller background wind errors. The limitations of wind extraction are also explored for observations with imposed random errors and for limited sampling patterns. As expected, the amount of wind information extracted degrades as observation errors or

Development of the Nonstationary Incremental Analysis Update Algorithm for Sequential Data Assimilation System

Directory of Open Access Journals (Sweden)

Yoo-Geun Ham

2016-01-01

Full Text Available This study introduces a modified version of the incremental analysis updates (IAU, called the nonstationary IAU (NIAU method, to improve the assimilation accuracy of the IAU while keeping the continuity of the analysis. Similar to the IAU, the NIAU is designed to add analysis increments at every model time step to improve the continuity in the intermittent data assimilation. However, unlike the IAU, the NIAU procedure uses time-evolved forcing using the forward operator as corrections to the model. The solution of the NIAU is superior to that of the forward IAU, of which analysis is performed at the beginning of the time window for adding the IAU forcing, in terms of the accuracy of the analysis field. It is because, in the linear systems, the NIAU solution equals that in an intermittent data assimilation method at the end of the assimilation interval. To have the filtering property in the NIAU, a forward operator to propagate the increment is reconstructed with only dominant singular vectors. An illustration of those advantages of the NIAU is given using the simple 40-variable Lorenz model.

Regime-dependence of Impacts of Radar Rainfall Data Assimilation

Science.gov (United States)

Craig, G. C.; Keil, C.

2009-04-01

Experience from the first operational trials of assimilation of radar data in kilometre scale numerical weather prediction models (operating without cumulus parameterisation) shows that the positive impact of the radar data on convective precipitation forecasts typically decay within a few hours, although certain cases show much longer impacts. Here the impact time of radar data assimilation is related to characteristics of the meteorological environment. This QPF uncertainty is investigated using an ensemble of 10 forecasts at 2.8 km horizontal resolution based on different initial and boundary conditions from a global forecast ensemble. Control forecasts are compared with forecasts where radar reflectivity data is assimilated using latent heat nudging. Examination of different cases of convection in southern Germany suggests that the forecasts can be separated into two regimes using a convective timescale. Short impact times are associated with short convective timescales that are characteristic of equilibrium convection. In this regime the statistical properties of the convection are constrained by the large-scale forcing, and effects of the radar data are lost within a few hours as the convection rapidly returns to equilibrium. When the convective timescale is large (non-equilibrium conditions), the impact of the radar data is longer since convective systems are triggered by the latent heat nudging and are able to persist for many hours in the very unstable conditions present in these cases.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

Energy Technology Data Exchange (ETDEWEB)

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov [NASA Ames Research Center, Moffett Field, Mountain View, CA 94035 (United States)

2016-11-01

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relatively new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

Science.gov (United States)

Sič, Bojan; El Amraoui, Laaziz; Piacentini, Andrea; Marécal, Virginie; Emili, Emanuele; Cariolle, Daniel; Prather, Michael; Attié, Jean-Luc

2016-11-01

In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We

Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment

NARCIS (Netherlands)

Curnel, Y.; Wit, de A.J.W.; Duveiller, G.; Defourny, P.

2011-01-01

An Observing System Simulation Experiment (OSSE) has been defined to assess the potentialities of assimilating winter wheat leaf area index (LAI) estimations derived from remote sensing into the crop growth model WOFOST. Two assimilation strategies are considered: one based on Ensemble Kalman Filter

Turbulent viscosity optimized by data assimilation

Directory of Open Access Journals (Sweden)

Y. Leredde

Full Text Available As an alternative approach to classical turbulence modelling using a first or second order closure, the data assimilation method of optimal control is applied to estimate a time and space-dependent turbulent viscosity in a three-dimensional oceanic circulation model. The optimal control method, described for a 3-D primitive equation model, involves the minimization of a cost function that quantifies the discrepancies between the simulations and the observations. An iterative algorithm is obtained via the adjoint model resolution. In a first experiment, a k + L model is used to simulate the one-dimensional development of inertial oscillations resulting from a wind stress at the sea surface and with the presence of a halocline. These results are used as synthetic observations to be assimilated. The turbulent viscosity is then recovered without the k + L closure, even with sparse and noisy observations. The problems of controllability and of the dimensions of the control are then discussed. A second experiment consists of a two-dimensional schematic simulation. A 2-D turbulent viscosity field is estimated from data on the initial and final states of a coastal upwelling event.

Key words. Oceanography: general (numerical modelling · Oceanography: physical (turbulence · diffusion · and mixing processes

Homophily and assimilation among sportactive adolescent substance users

NARCIS (Netherlands)

Pearson, M; Steglich, Ch.; Snijders, T.A.B.

2006-01-01

We analyse the co-evolution of social networks and substance use behaviour of adolescents and address the problem of separating the effects of homophily and assimilation. Adolescents who prefer friends with the same substance-use behaviour exhibit the homophily principle. Adolescents who adapt their

Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model

Directory of Open Access Journals (Sweden)

François Counillon

2016-12-01

Full Text Available We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM for the period 1950–2010 (doi: 10.11582/2016.00002. NorCPM is based on the Norwegian Earth System Model and uses the ensemble Kalman filter for data assimilation (DA. Here, we assimilate SST from the stochastic HadISST2 historical reconstruction. The accuracy, reliability and drift are investigated using both assimilated and independent observations. NorCPM is slightly overdispersive against assimilated observations but shows stable performance through the analysis period. It demonstrates skills against independent measurements: sea surface height, heat and salt content, in particular in the Equatorial and North Pacific, the North Atlantic Subpolar Gyre (SPG region and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the vertical temperature variability there, in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using a flow-dependent assimilation method and constructing the covariance in isopycnal coordinates are investigated in the SPG region. Isopycnal coordinates discretisation is found to better capture the vertical structure than standard depth-coordinate discretisation, because it leads to a deeper influence of the assimilated surface observations. The vertical covariance shows a pronounced seasonal and decadal variability that highlights the benefit of flow-dependent DA method. This study demonstrates the potential of NorCPM to compute an ocean re-analysis for the 19th and 20th centuries when SST observations are available.

Data assimilation in modeling ocean processes: A bibliographic study

Digital Repository Service at National Institute of Oceanography (India)

Mahadevan, R.; Fernandes, A.A.; Saran, A.K.

An annotated bibliography on studies related to data assimilation in modeling ocean processes has been prepared. The bibliography listed here is not comprehensive and is not prepared from the original references. Information obtainable from...

Global SWOT Data Assimilation of River Hydrodynamic Model; the Twin Simulation Test of CaMa-Flood

Science.gov (United States)

Ikeshima, D.; Yamazaki, D.; Kanae, S.

2016-12-01

CaMa-Flood is a global scale model for simulating hydrodynamics in large scale rivers. It can simulate river hydrodynamics such as river discharge, flooded area, water depth and so on by inputting water runoff derived from land surface model. Recently many improvements at parameters or terrestrial data are under process to enhance the reproducibility of true natural phenomena. However, there are still some errors between nature and simulated result due to uncertainties in each model. SWOT (Surface water and Ocean Topography) is a satellite, which is going to be launched in 2021, can measure open water surface elevation. SWOT observed data can be used to calibrate hydrodynamics model at river flow forecasting and is expected to improve model's accuracy. Combining observation data into model to calibrate is called data assimilation. In this research, we developed data-assimilated river flow simulation system in global scale, using CaMa-Flood as river hydrodynamics model and simulated SWOT as observation data. Generally at data assimilation, calibrating "model value" with "observation value" makes "assimilated value". However, the observed data of SWOT satellite will not be available until its launch in 2021. Instead, we simulated the SWOT observed data using CaMa-Flood. Putting "pure input" into CaMa-Flood produce "true water storage". Extracting actual daily swath of SWOT from "true water storage" made simulated observation. For "model value", we made "disturbed water storage" by putting "noise disturbed input" to CaMa-Flood. Since both "model value" and "observation value" are made by same model, we named this twin simulation. At twin simulation, simulated observation of "true water storage" is combined with "disturbed water storage" to make "assimilated value". As the data assimilation method, we used ensemble Kalman filter. If "assimilated value" is closer to "true water storage" than "disturbed water storage", the data assimilation can be marked effective. Also

Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation

Science.gov (United States)

Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.

2010-12-01

Rainfall-runoff models are crucial tools for long-term assessment of flash floods or real-time forecasting. This work focuses on the calibration of a distributed parsimonious event-based rainfall-runoff model using data assimilation. The model combines a SCS-derived runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The SCS-derived runoff model is parametrized by the initial water deficit, the discharge coefficient for the soil reservoir and a lagged discharge coefficient. The Lag and Route routing model is parametrized by the velocity of travel and the lag parameter. These parameters are assumed to be constant for a given catchment except for the initial water deficit and the velocity travel that are event-dependent (landuse, soil type and moisture initial conditions). In the present work, a BLUE filtering technique was used to calibrate the initial water deficit and the velocity travel for each flood event assimilating the first available discharge measurements at the catchment outlet. The advantages of the BLUE algorithm are its low computational cost and its convenient implementation, especially in the context of the calibration of a reduced number of parameters. The assimilation algorithm was applied on two Mediterranean catchment areas of different size and dynamics: Gardon d'Anduze and Lez. The Lez catchment, of 114 km2 drainage area, is located upstream Montpellier. It is a karstic catchment mainly affected by floods in autumn during intense rainstorms with short Lag-times and high discharge peaks (up to 480 m3.s-1 in September 2005). The Gardon d'Anduze catchment, mostly granite and schistose, of 545 km2 drainage area, lies over the departements of Lozère and Gard. It is often affected by flash and devasting floods (up to 3000 m3.s-1 in September 2002). The discharge observations at the beginning of the flood event are assimilated so that the BLUE algorithm provides optimal values for the initial water deficit and the

Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

Science.gov (United States)

Jones, Thomas A.; Stensrud, David; Wicker, Louis; Minnis, Patrick; Palikonda, Rabindra

2015-01-01

Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

Science.gov (United States)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

Science.gov (United States)

Girotto, Manuela

2018-01-01

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

Assimilation of qualitative hydrological information in water-related risk framework

Science.gov (United States)

Mazzoleni, Maurizio; Alfonso, Leonardo; Solomatine, Dimitri

2013-04-01

In recent years water-related risks are increasing worldwide. In particular, floods have been one of the most damaging natural disasters in Europe, in terms of economic losses. Non-structural measures such as flood risk mapping are generally used to reduce the impact of flood in important area. The increasing data availability makes it possible to develop new models which can be used to assimilate different kinds of information and reduce the uncertainty of the state of a basin. The aim of this work is to propose a methodology to assimilate uncertain, qualitative information within hydrological models in order to improve the evaluation of catchment responses. Qualitative information is defined here as the one that can be interpreted as and assimilated into a hydrological model as a fuzzy value, for instance those coming from text messages or citizen's pictures. The methodology is applied in the Brue catchment, located in the South West of England, having a drainage area of 135 km2, average annual rainfall of 867 mm and average discharge of 1.92 m3/s at Lovington considering the period among 1961 and 1990. In order to estimate the response of the catchment to a flood event with given intensity, a conceptual distributed hydrological model was implemented. First, the basin was divided in different sub-basins, then, the hydrograph at the outlet section was estimated using a Nash cascade model and the propagation of the flood wave was carried out considering the lag time in the other each sub-basins. The assimilation of the qualitative information was carried out using different techniques. The results of this work show how the spatial location and uncertainty of the qualitative information can affect the flow hydrograph in the outlet section and the consequent flood extent in the downstream area. This study is part of the FP7 European Project WeSenseIt.

The Culure Assimilator: An Approach to Cross-Cultural Training

Science.gov (United States)

Fiedler, Fred E.; And Others

1971-01-01

Evaluates the cultural assimilator, a kind of training manual to help members of one culture understand and adjust to another culture. Describes those constructed for the Arab countries, Iran, Thailand, Central America, and Greece. (MB)

Diffusion Filters for Variational Data Assimilation of Sea Surface Temperature in an Intermediate Climate Model

Directory of Open Access Journals (Sweden)

Xuefeng Zhang

2015-01-01

Full Text Available Sequential, adaptive, and gradient diffusion filters are implemented into spatial multiscale three-dimensional variational data assimilation (3DVAR as alternative schemes to model background error covariance matrix for the commonly used correction scale method, recursive filter method, and sequential 3DVAR. The gradient diffusion filter (GDF is verified by a two-dimensional sea surface temperature (SST assimilation experiment. Compared to the existing DF, the new GDF scheme shows a superior performance in the assimilation experiment due to its success in extracting the spatial multiscale information. The GDF can retrieve successfully the longwave information over the whole analysis domain and the shortwave information over data-dense regions. After that, a perfect twin data assimilation experiment framework is designed to study the effect of the GDF on the state estimation based on an intermediate coupled model. In this framework, the assimilation model is subject to “biased” initial fields from the “truth” model. While the GDF reduces the model bias in general, it can enhance the accuracy of the state estimation in the region that the observations are removed, especially in the South Ocean. In addition, the higher forecast skill can be obtained through the better initial state fields produced by the GDF.

Effect of Elevated Carbon Dioxide Concentration on Carbon Assimilation under Fluctuating Light

Czech Academy of Sciences Publication Activity Database

Holišová, Petra; Zitová, Martina; Klem, Karel; Urban, Otmar

2012-01-01

Roč. 41, č. 6 (2012), s. 1931-1938 ISSN 0047-2425 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA ČR(CZ) GAP501/10/0340; GA MŠk(CZ) LM2010007; GA AV ČR IAA600870701 Institutional support: RVO:67179843 Keywords : carbon * light * beech * spruce * carbon assimilation * elevat e carbon * dioxide concentration * mol * photosynthetic * assimilation * carbon dioxide * dioxide * concentracion * leave * photosynthetic efficiency Subject RIV: EH - Ecology, Behaviour Impact factor: 2.353, year: 2012

Abscisic acid and assimilate partitioning during seed development

NARCIS (Netherlands)

Bruijn, de S.M.

1993-01-01

This thesis describes the influence of abscisic acid (ABA) on the transport of assimilates to seeds and the deposition of reserves in seeds. It is well-known from literature that ABA accumulates in seeds during development, and that ABA concentrations in seeds correlate rather well with

The occupational assimilation of Hispanics in the U.S.: evidence from panel data

OpenAIRE

Maude Toussaint-Comeau

2004-01-01

This study investigates whether Hispanic immigrants assimilate in occupational status with natives and the factors that determine occupational status. A theoretical framework is proposed that models occupational status and convergence of Hispanics relative to U.S.-born non-Hispanics as a function of human capital and demographic exogenous variables, U.S. experience (assimilation effects) and periods of migration (cohort effects). In addition, the model also controls for aggregate economic con...

Antarctic Ocean Tides from GRACE Intersatellite Tracking Data and Hydrodynamic Assimilation

Science.gov (United States)

Erofeeva, S.; Han, S.; Ray, R.; Egbert, G.; Luthcke, S.

2007-12-01

Long-wavelength components of the oceanic tides surrounding Antarctica are estimated from over three years of GRACE satellite-to-satellite ranging measurements. An inversion is performed for the major constituents M2, O1, and S2, parameterized as localized average mass anomalies relative to a prior tidal model. Satellite state adjustments are made simultaneously. These long-wavelength anomalies are then assimilated into a high-resolution regional hydrodynamic tidal model. Comparisons to independent "ground truth" data, previously collected by King and Padman, show that assimilation of the GRACE inversions results in improved accuracy, for all three constituents.

Immigrants' continuing bonds with their native culture: assimilation analysis of three interviews.

Science.gov (United States)

Henry, Hani M; Stiles, William B; Biran, Mia W; Mosher, James K; Brinegar, Meredith Glick; Banerjee, Prashant

2009-06-01

Three case studies of immigrants to the US from China, Iraq, and Mexico were used to build a theory of acculturation in immigrants by integrating the continuing bonds model, which describes mourning in bereavement with the assimilation model, which describes psychological change in psychotherapy. Participants were interviewed about the loss of their native culture and their life in the US. One participant had not fully assimilated the loss of her native culture, but used her continuing bonds with her culture as a source of solace. Another participant used his continuing bonds with his culture as a source of solace, but these bonds had become a source of conflict with the host culture. The third participant had largely assimilated the loss of his native culture such that the voices of this culture were linked via meaning bridges with the voices of the host culture, and the continuing bonds were resources that helped him in his land of immigration.

Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

Science.gov (United States)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.

Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST

Directory of Open Access Journals (Sweden)

Weijing Chen

2017-03-01

Full Text Available Uncertainties in model parameters can easily result in systematic differences between model states and observations, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this research, a soil moisture assimilation scheme is developed to jointly assimilate AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System brightness temperature (TB and MODIS (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (LST products, which also corrects model bias by simultaneously updating model states and parameters with a dual ensemble Kalman filter (DEnKS. Common Land Model (CoLM and a Radiative Transfer Model (RTM are adopted as model and observation operator, respectively. The assimilation experiment was conducted in Naqu on the Tibet Plateau from 31 May to 27 September 2011. The updated soil temperature at surface obtained by assimilating MODIS LST serving as inputs of RTM is to reduce the differences between the simulated and observed TB, then AMSR-E TB is assimilated to update soil moisture and model parameters. Compared with in situ measurements, the accuracy of soil moisture estimation derived from the assimilation experiment has been tremendously improved at a variety of scales. The updated parameters effectively reduce the states bias of CoLM. The results demonstrate the potential of assimilating AMSR-E TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study indicates that the developed scheme is an effective way to retrieve downscaled soil moisture when assimilating the coarse-scale microwave TB.

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

Science.gov (United States)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Uncertainty of Flood Forecasting Based on Radar Rainfall Data Assimilation

Directory of Open Access Journals (Sweden)

Xinchi Chen

2016-01-01

Full Text Available Precipitation is the core data input to hydrological forecasting. The uncertainty in precipitation forecast data can lead to poor performance of predictive hydrological models. Radar-based precipitation measurement offers advantages over ground-based measurement in the quantitative estimation of temporal and spatial aspects of precipitation, but errors inherent in this method will still act to reduce the performance. Using data from White Lotus River of Hubei Province, China, five methods were used to assimilate radar rainfall data transformed from the classified Z-R relationship, and the postassimilation data were compared with precipitation measured by rain gauges. The five sets of assimilated rainfall data were then used as input to the Xinanjiang model. The effect of precipitation data input error on runoff simulation was analyzed quantitatively by disturbing the input data using the Breeding of Growing Modes method. The results of practical application demonstrated that the statistical weight integration and variational assimilation methods were superior. The corresponding performance in flood hydrograph prediction was also better using the statistical weight integration and variational methods compared to the others. It was found that the errors of radar rainfall data disturbed by the Breeding of Growing Modes had a tendency to accumulate through the hydrological model.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater