Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.

Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System

We present a parametric Kalman filter data assimilation system using GOSAT methane observations within the hemispheric CMAQ model. The assimilation system produces forecasts and analyses of concentrations and explicitly computes its evolving error variance while remaining computationally competitive with other data assimilation schemes such as 4-dimensional variational (4D-Var) and ensemble Kalman filter (EnKF). The error variance in this system is advected using the native advection scheme of the CMAQ model and updated at each analysis while the error correlations are kept fixed. We discuss extensions to the CMAQ model to include methane transport and emissions (both anthropogenic and natural) and perform a bias correction for the GOSAT observations. The results using synthetic observations show that the analysis error and analysis increments follow the advective flow while conserving the information content (i.e., total variance). We also demonstrate that the vertical error correlation contributes to the inference of variables down to the surface. In a companion paper, we use this assimilation system to obtain optimal assimilation of GOSAT observations.

Study of Nonlinear Models of Oscillatory Systems by Applying an Intelligent Computational Technique

In this paper, we have analyzed the mathematical model of various nonlinear oscillators arising in different fields of engineering. Further, approximate solutions for different variations in oscillators are studied by using feedforward neural networks (NNs) based on the backpropagated Levenberg–Marquardt algorithm (BLMA). A data set for different problem scenarios for the supervised learning of BLMA has been generated by the Runge–Kutta method of order 4 (RK-4) with the “NDSolve” package in Mathematica. The worth of the approximate solution by NN-BLMA is attained by employing the processing of testing, training, and validation of the reference data set. For each model, convergence analysis, error histograms, regression analysis, and curve fitting are considered to study the robustness and accuracy of the design scheme.

Aircraft Assembly Snags: Human Errors or Lack of Production Design?

To err is an intrinsic human trait, which means that human errors, at some point, are inevitable. Business improvement tools and practices neglect to deal with the root causes of human error; hence, they ignore certain design considerations that could possibly prevent or minimise such errors from occurring. Recognising this gap, this paper seeks to conceptualise a model that incorporates cognitive science literature based on a mistake-proofing concept, thereby offering a deeper, more profound level of human error analysis. An exploratory case study involving an aerospace assembly line was conducted to gain insights into the model developed. The findings of the case study revealed four different causes of human errors, as follows: (i) description similarity error, (ii) capture errors, (iii) memory lapse errors, and (iv) interruptions. Based on this analysis, error-proofing measures have been proposed accordingly. This paper lays the foundation for future work on the psychology behind human errors in the aerospace industry and highlights the importance of understanding human errors to avoid quality issues and rework in production settings, where labour input is of paramount importance.

The Pronunciation of English Low Vowels by Iraqi EFL Learners: An Intralingual Analysis

Iraqi EFL learners of English are reported to show accented pronunciation on the segmental level, which might affect their speech intelligibility. This study aimed to identify problems encountered by Iraqi EFL learners in the production of English low vowels and account for them from an intralingual perspective. The study also aimed to identify the effect of Iraqis' English language proficiency level on their pronunciation of English low vowels. Thus, learners were divided into beginners and advanced groups to determine differences between them based on their proficiency level in English. A production test was conducted to identify error patterns of twenty Iraqi EFL learners in producing low vowels. Learners’ recordings were acoustically analysed to validate the difficulties identified via the production test. Independent-samples t-tests were conducted to identify any significant differences in performance for the two groups. The results showed that learners encountered problems in the production of low vowels, especially /ɒ/, /æ/ and /ʌ/. The study concluded that these problems are probably ascribed to the complexities of the L2 vowel space, where vowels are close to each other and thus difficult to produce. Significant differences were identified between the two groups in terms of error means. Nonetheless, the comparison between the vowel chart obtained in this study and the charts offered in previous studies revealed that Iraqi EFL learners are still far from attaining approximant pronunciation. This requires reconsidering current texts, methodologies, and techniques used in teaching English pronunciation to allocate more attention to spectral differences among vowels. Keywords Low vowels production; Iraqi EFL learners; intralingual analysis; error patterns; acoustic analysis

CICE-LETKF Ensemble Analysis System with Application to Arctic Sea Ice Initialization

To study the effectiveness of methods to reduce errors for Arctic Sea ice initialization due to underestimation of background error covariance, an advanced ensemble analysis system has been developed. The system integrates the local ensemble transform Kalman filter (LETKF) with the community ice code (CICE). With a mixed layer ocean model used to compute the sea surface temperature (SST), the experiments on assimilation of observations of sea ice concentration (SIC) have been carried out. Assimilation experiments were performed over a 3-month period from January to March in 1997. The model was sequentially constrained with daily observation data. The effects of observation density, amplification factor for analysis error covariance, and relaxation of disturbance and spread on the results of SIC initialization were studied. It is shown that doubling the density of observation of SIC does not bring significant further improvement on the analysis result; when the ensemble size is doubled, most severe SIC biases in the Labrador, Greenland, Norwegian, and Barents seas are reduced; amplifying the analysis error covariance, relaxing disturbance, and relaxing spread all contribute to improving the reproduction of SIC with amplifying covariance with the largest magnitude.

Ocena wpływu przygotowania próbek na uzyskiwane wyniki analiz pirolitycznych

The aim of the work, the results of which are presented in the article, was to evaluate the influence of the method of sample preparation on the results of pyrolytic analyses: RockEval, Py-GC-FID (gas chromatography with FID detector) and Py-GC-IRMS (isotope mass spectrometry with gas chromatography). Mortars and ball mills are most often used to grind the samples. Three rock samples with a higher organic carbon content (shales) and five with a lower organic carbon content (including two samples of dolomites and three of anhydrites) were prepared. The rocks were homogenized and divided into three parts. Each part was ground: by hand in a mortar, in a ball mill for 5 minutes, and in a ball mill for 15 minutes. A total of 24 RockEval analyses, 48 Py-GC-FID analyses (two pyrolysis temperatures corresponding to RockEval pyrolysis conditions) and 24 Py-GC-IRMS analyses were performed. The grinding of the samples for the RockEval analyses is insignificant. The differences in the results seem to indicate the influence of the analysis error and the nature of the sample. For the Py-GC-FID methodology, the influence of milling on the results of desorption carried out at the temperature of 300ºC for most of the tested samples can be considered insignificant and negligible. At the temperature of 500ºC, various types of samples show some correlations, but they are insufficient to reject one of the methods of sample preparation. Therefore, it is important to analyze the results comprehensively, taking into account both the group composition and the distribution of pyrolysis products. In the case of the isotopic composition analyses (Py-GC-IRMS), also no differences in δ13C values related to different types of grinding samples can be found. Summarizing, all the results show a negligible influence of the method of grinding the samples on the results of pyrolysis analyses. Nevertheless, it is important that only one method of sample preparation is used for a separate sample series.

Teaching Macro Excel on Pre-service Mathematics Teachers: Analysis Error in Solving the Syntax Manually

The aim of this study is to describe errors output when pre-service mathematics teachers were writing output of the syntax that given in macro excel manually. This research is a qualitative descriptive research with 101 participants from 2nd year pre-service mathematics teachers from one of state university at Nusa Tenggara Barat, Indonesia. Instrument used consists of one syntax that has 8 outputs when it is run and that will be analysed using Newman’s procedures. The eight outputs come from 3 types of output, namely text, numbers, and count. The result showed that the average percentage of syntax output writing errors was 87.13%. It also indicated to reading errors of 48.51%, comprehension errors of 18.81%, transformation errors of 83.17%, process skill errors of 20.79%, and encoding errors of 87.13%. Based on the result, errors occur when participants incorrectly write output and wrong in writing the result of the count. In addition, factors that caused these errors are 1) participants were not trained in providing information that was in the problem, 2) participants did not read the instructions in the problem correctly, and 3) participants did not pay attention to the suitability of syntax and output as was learned before. This research can be a reference for lecturers to develop learning about programming languages that can make students understand the use of syntax with the emphasis on manual syntax learning which will make their logic easier when applyng the syntax on a computer.

The Role of Analysis Error in the Convergence of Reanalysis Production Streams in MERRA-2

ABSTRACTDue to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.

Investigating the Impact of Interlanguage on Adult EFL Learners in Indonesia: Strengths and Weaknesses

The study of second language acquisition (SLA) concerns not only the way to learn a second language (L2), but also the unique language system created by language learners (interlanguage). This qualitative study analyzed EFL learners’ interlanguage by focusing on their strengths and weaknesses in speaking English, especially on phonological, grammatical and pragmatic competence in speaking English. The language data were obtained from a recorded conversation between two non-native English speakers from Indonesia. The data were analysed by referring to contrastive analysis, error analysis and the socio-cultural perspective in SLA. The results indicated that although both learners had a strong L1 accent, the learners did not face any difficulty in constructing English sentences in the right sentence order (SVO). In addition, when facing difficulties in speaking English, the learners were seen to ask and provide support to each other, as well as to talk to themselves (private speech). In terms of weaknesses, the study found that the learners often mispronounced the letter “t” in English as the sound of “t” in Indonesian, made grammatical errors in subject and verb agreement, and applied Indonesia’s pragmatic concepts when speaking English. The study suggests that it is necessary to have a positive view on learners’ interlanguage as it can be used as a tool to learn a second language. Keywords: Contrastive analysis, error analysis, interlanguage, second language acquisition, socio-cultural perspective in SLA.