Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. In the companion paper [Sandu et al.(2011)] we derived an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. Here we apply this methodology to quantify two information metrics (the signal and degrees of freedom for signal) for satellite observations used in a global chemical data assimilation problem with the GEOS-Chem chemical transport model. The assimilation of a subset of data points characterized by the highest information content, gives analyses that are comparable in quality with the one obtained using the entire data set

A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. I: Methodology

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. This paper focuses on the four dimensional variational (4D-Var) data assimilation framework. Metrics from information theory are used to quantify the contribution of observations to decreasing the uncertainty with which the system state is known. We establish an interesting relationship between different information-theoretic metrics and the variational cost function/gradient under Gaussian linear assumptions. Based on this insight we derive an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. The approach is illustrated on linear and nonlinear test problems. In the companion paper [Singh et al.(2011)] the methodology is applied to a global chemical data assimilation problem

A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. In the companion paper (Sandu et al., 2012) we derive an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. Here we apply this methodology to quantify the signal and degrees of freedom for signal information metrics of satellite observations used in a global chemical data assimilation problem with the GEOS-Chem chemical transport model. The assimilation of a subset of data points characterized by the highest information content yields an analysis comparable in quality with the one obtained using the entire data set

A case study of the perceptions of stakeholders regarding transformational leadership processes and structures implemented in a high poverty, high achieving school

Title from PDF of title page (University of Missouri--Columbia, viewed on October 31, 2012).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Barbara N. MartinIncludes bibliographical references.Vita.Ed. D. University of Missouri--Columbia 2012."July 2012"Boyd-Zaharias and Pate-Bain (2008) postulated that low achievement and high dropout rates among poor students continue to “plague” (p. 40) public schools in the United States; and elaborated further by stating, “our nation will profit by or pay for whatever they become” (p. 40). Chenoweth (2009a, 2009b) and Haycock (2001) shared that the country continues to move forward with reform efforts though the achievement gap between poor students and their non-poor peers does not tend to close, rather it widens. Therefore, the achievement gap between poor students and their peers, a problem of practice, is the focus of this narrative case study.Includes bibliographical reference

Ensemble variational assimilation as a probabilistic estimator – Part 2: The fully non-linear case

The method of ensemble variational assimilation (EnsVAR), also known as ensemble of data assimilations (EDA), is implemented in fully non-linear conditions on the Lorenz-96 chaotic 40-parameter model. In the case of strong-constraint assimilation, it requires association with the method of quasi-static variational assimilation (QSVA). It then produces ensembles which possess as much reliability and resolution as in the linear case, and its performance is at least as good as that of ensemble Kalman filter (EnKF) and particle filter (PF). On the other hand, ensembles consisting of solutions that correspond to the absolute minimum of the objective function (as identified from the minimizations without QSVA) are significantly biased. In the case of weak-constraint assimilation, EnsVAR is fully successful without need for QSVA.</p

A Hybrid Approach to Estimating Error Covariances in Variational Data Assimilation

Data Assimilation (DA) involves the combination of observational data with the underlying dynamical principles governing the system under observation. In this work we combine the advantages of the two prominent advanced data assimilation systems, the 4D-Var and the ensemble methods. The proposed method consists of identifying the subspace spanned by the major 4D-Var error reduction directions. These directions are then removed from the background covariance through a Galerkin-type projection. This generates an updated error covariance information at both end points of an assimilation window. The error covariance information is updated between assimilation windows to capture the ``error of the day''. Numerical results using our new hybrid approach on a nonlinear model demonstrate how the background covariance matrix leads to an error covariance update that improves the 4D-Var DA results

The Effects of Language Mixing on Word Learning and Comprehension in Bilingual 3-year-olds

ABSTRACT The Effects of Language Mixing on Word Learning and Comprehension in Bilingual 3-year-olds Amel Jardak One challenge bilingual children face in their learning environment is language mixing (Bail et al., 2015; Byers-Heinlein, 2013), which occurs when two languages appear in the same sentence or conversation. Recent research shows that children are slower to process familiar words that occur at the point of language mixing (Byers-Heinlein et al., 2017). How does language mixing in the middle of a sentence affect the comprehension and the learning of words that occur after the mixed-input? We tested 3-year-old French-English bilinguals in two studies. In Study 1, children were tested on their comprehension of a noun that occurred either in a single-language sentence (e.g., “Look! Can you find the pretty cow?”) or following a mixed-language adjective (e.g., “Look! Can you find la jolie cow?”). We found that language mixing had no effect on the comprehension of following familiar nouns. In Study 2, children were taught two words, one in a single-language sentence (e.g., “Look! Do you see the dog on the teelo?”) and one in a mixed-language sentence (e.g., “Look! Do you see the chien on the walem?). We found that although children could correctly identify the novel target on both single- and mixed- language sentences, they were only able to learn the novel word that was taught in a single-language sentence. These results suggest that language mixing poses a challenge to word learning. Overall, these two studies demonstrate that the effects of language mixing on language acquisition depend both on the type of mixing and the type of language task

The use of phosphinothricin resistance as selectable marker for genetic transformation of grapevine

A transformation procedure with the bar gene as a selectable marker was established via Agrobacterium-mediated transformation using strain LBA4404 harbouring the vector pPZP200-bar-gus-intron. Recreation of embryogenic cells from transformation stress in PPT free medium for four weeks improved viability and number of GUS expressing cells. Concentration of 2.5 mg·l-1 PPT yielded highest selection efficiency. Transgenicity of the regenerated grapevine plants was confirmed by histochemical GUS assay and bar specific PCR and RT/PCR. With the described procedure, 20 % of regenerated embryos could be converted into transgenic grapevines.

Causal loops for analysis of the social dimension to complex systems

Better methods of analysis and communication are needed to analyse civil engineering and environmental systems that have a social dimension. Causal loops are examined as a way to improve analysis. Opposition to landfills is developed to show the role that causal loops could provide in social/technical systems analysis. The example leads to a conclusion that public access to an on-line database of monitoring data could help reduce opposition. Causal loops are highlighted as one way in which we can reorganise our thought and use a new language to analyse our increasingly complex civil engineering and environmental systems

Restraints on reporting conflict in West Papua

This is as much an experiment in investigative reporting as it is a thesis. It explores the possibility of carrying out “research journalism” on a specific issue in a New Zealand academic environment, after a failure to complete the mission within newsrooms. The thesis debates theoretical and practical “restraints” to reporting this conflict and New Zealand’s role in it. Such restraints might include the degree of conservatism and intractability in Western traditions and practices of both the mainstream media, and of the other potential “commentating power”, universities