Dataset Information

Local decadal prediction according to statistical/dynamical approaches.

ABSTRACT: Dynamical climate models present an initialization problem due to the poor availability of deep oceanic data, which is required for the model assimilation process. In this sense, teleconnection indices, defined from spatial and temporal patterns of climatic variables, are conceived as useful tools to complement them. In this work, the near-term climate predictability of 35 temperature and 36 precipitation time series of three cities (Barcelona, Bristol and Lisbon) was analysed using two approaches: (a) a statistical-dynamical combination of self-predictable teleconnection indices and long-term climate projections on a local scale and (b) dynamical model outputs obtained from drift-corrected decadal experiments. Fourier and wavelet analyses were used to assess the predictability of seven teleconnection indices thanks to a cross-validation process (with differentiated training and validation periods). The standardized absolute error of teleconnection-based prediction was compared with that obtained from a (9) multi-model ensemble based on the Coupled Model Intercomparison Project Phase 5. Results showed that decadal predictions at horizons between 20 and 30?years are adequate for temperature and precipitation if a teleconnection-based approach is used, while temperature is better predicted from a 5-year horizon using drift-corrected dynamical outputs.

SUBMITTER: Redolat D

PROVIDER: S-EPMC7687142 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Local decadal prediction according to statistical/dynamical approaches.

Redolat Dario D Monjo Robert R Paradinas Cesar C Pórtoles Javier J Gaitán Emma E Prado-Lopez Carlos C Ribalaygua Jaime J

International journal of climatology : a journal of the Royal Meteorological Society 20200320 13

Dynamical climate models present an initialization problem due to the poor availability of deep oceanic data, which is required for the model assimilation process. In this sense, teleconnection indices, defined from spatial and temporal patterns of climatic variables, are conceived as useful tools to complement them. In this work, the near-term climate predictability of 35 temperature and 36 precipitation time series of three cities (Barcelona, Bristol and Lisbon) was analysed using two approach ...[more]

PMID: 33281281

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Project description:BACKGROUND:Whenever suitable template structures are not available, usage of fragment-based protein structure prediction becomes the only practical alternative as pure ab initio techniques require massive computational resources even for very small proteins. However, inaccuracy of their energy functions and their stochastic nature imposes generation of a large number of decoys to explore adequately the solution space, limiting their usage to small proteins. Taking advantage of the uneven complexity of the sequence-structure relationship of short fragments, we adjusted the fragment insertion process by customising the number of available fragment templates according to the expected complexity of the predicted local secondary structure. Whereas the number of fragments is kept to its default value for coil regions, important and dramatic reductions are proposed for beta sheet and alpha helical regions, respectively. RESULTS:The evaluation of our fragment selection approach was conducted using an enhanced version of the popular Rosetta fragment-based protein structure prediction tool. It was modified so that the number of fragment candidates used in Rosetta could be adjusted based on the local secondary structure. Compared to Rosetta's standard predictions, our strategy delivered improved first models, +?24% and?+?6% in terms of GDT, when using 2000 and 20,000 decoys, respectively, while reducing significantly the number of fragment candidates. Furthermore, our enhanced version of Rosetta is able to deliver with 2000 decoys a performance equivalent to that produced by standard Rosetta while using 20,000 decoys. We hypothesise that, as the fragment insertion process focuses on the most challenging regions, such as coils, fewer decoys are needed to explore satisfactorily conformation spaces. CONCLUSIONS:Taking advantage of the high accuracy of sequence-based secondary structure predictions, we showed the value of that information to customise the number of candidates used during the fragment insertion process of fragment-based protein structure prediction. Experimentations conducted using standard Rosetta showed that, when using the recommended number of decoys, i.e. 20,000, our strategy produces better results. Alternatively, similar results can be achieved using only 2000 decoys. Consequently, we recommend the adoption of this strategy to either improve significantly model quality or reduce processing times by a factor 10.

Project description:Microarray technology has enabled the measurement of comprehensive transcriptomic information. However, each data entry may reflect trivial individual differences among samples and also contain technical noise. Therefore, the certainty of each observed difference should be confirmed at earlier steps of the analyses, and statistical tests are frequently used for this purpose. Since a microarray measures a huge number of genes and the results are processed simultaneously, concerns regarding problems of multiplicity have been raised to the tests. To deal with these problems, several methodologies have been proposed, making the tests very conservative. Indeed, arbitrary tuning of the test threshold has also been introduced to relax the test conditions. However, the appropriateness of the multiplicity problems as well as the compensation methods has not been confirmed. The appropriateness of the compensation methods was checked by means of coincidence of the premises of the methodologies with the observed characteristics found in real data of two typical platforms of microarray analysis. Normality was observed in within-group data variations, supporting applications of parametric tests. However, genes displayed their own tendencies in the magnitude of variations, and the distributions of P-values were rather complex and varied; these characteristics are inconsistent with the premises of the compensation methodologies. Additionally, the appropriateness of the proposed multiplicities is reconsidered. When we observed differences in the transcriptome, the family-wise error rate should not be considered, since analyses at higher levels would not be influenced by a few false positives among the huge numbers of true information. Likely, concerns for a false discovery rate are not suitable for the point null hypotheses on expression levels, since the rate of true null hypotheses should be rare in contradiction to the premise of the methodology. Although compensation methods have been recommended to deal with the problem of multiplicity, the compensations are actually inappropriate for many of the applications of transcriptome analyses. Compensations are not only unnecessary, but will increase the occurrence of false negative errors, and arbitrary adjustment of the threshold damages the objectivity of the tests. Rather, the results of parametric tests should be evaluated directly. This SuperSeries is composed of the SubSeries listed below.

Dataset Information

Local decadal prediction according to statistical/dynamical approaches.

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Local decadal prediction according to statistical/dynamical approaches.

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