Western North Pacific Tropical Cyclone Formation and Structure Change in TCS-08 and TCS-08 Field Experiment Support

Long-term goals: The long-term goal of this project is to develop a better understanding of mesoscale and synoptic-scale processes associated with the entire life cycle of tropical cyclones in the western North Pacific. The inability to correctly identify tropical cyclone formation over the period of 24 h – 48 h poses a threat to shore and afloat assets across the western North Pacific. Furthermore, once a tropical cyclone has formed the predictability of structure changes during intensification of tropical cyclones is very low, which is due to complex physical processes that vary over a wide range of space and time scales. Periods of reduced predictability occur throughout the tropical cyclone life cycle, which includes the decaying stage. Because decaying tropical cyclones often transition to a fast-moving and rapidly- developing extratropical cyclone that may contain gale-, storm-, or hurricane-force winds, there is a need to improve understanding and prediction of the extratropical transition phase of a decaying tropical cyclone. The structural evolution of the transition from a tropical to an extratropical circulation involves rapid changes to the wind, cloud, and precipitation patterns that potentially impact maritime and shore-based facilities.N0001409WR2000

A multivariate geostatistical framework for combining multiple indices of abundance for disease vectors and reservoirs:a case study of rattiness in a low-income urban Brazilian community

A key requirement in studies of endemic vector-borne or zoonotic disease is an estimate of the spatial variation in vector or reservoir host abundance. For many vector species, multiple indices of abundance are available, but current approaches to choosing between or combining these indices do not fully exploit the potential inferential benefits that might accrue from modelling their joint spatial distribution. Here, we develop a class of multivariate generalized linear geostatistical models for multiple indices of abundance. We illustrate this novel methodology with a case study on Norway rats in a low-income urban Brazilian community, where rat abundance is a likely risk factor for human leptospirosis. We combine three indices of rat abundance to draw predictive inferences on a spatially continuous latent process, rattiness, that acts as a proxy for abundance. We show how to explore the association between rattiness and spatially varying environmental factors, evaluate the relative importance of each of the three contributing indices and assess the presence of residual, unexplained spatial variation, and identify rattiness hotspots. The proposed methodology is applicable more generally as a tool for understanding the role of vector or reservoir host abundance in predicting spatial variation in the risk of human disease

Horizontal gene transfer in Histophilus somni and its role in the evolution of pathogenic strain 2336, as determined by comparative genomic analyses

<p>Abstract</p> <p>Background</p> <p>Pneumonia and myocarditis are the most commonly reported diseases due to <it>Histophilus somni</it>, an opportunistic pathogen of the reproductive and respiratory tracts of cattle. Thus far only a few genes involved in metabolic and virulence functions have been identified and characterized in <it>H. somni </it>using traditional methods. Analyses of the genome sequences of several <it>Pasteurellaceae </it>species have provided insights into their biology and evolution. In view of the economic and ecological importance of <it>H. somni</it>, the genome sequence of pneumonia strain 2336 has been determined and compared to that of commensal strain 129Pt and other members of the <it>Pasteurellaceae</it>.</p> <p>Results</p> <p>The chromosome of strain 2336 (2,263,857 bp) contained 1,980 protein coding genes, whereas the chromosome of strain 129Pt (2,007,700 bp) contained only 1,792 protein coding genes. Although the chromosomes of the two strains differ in size, their average GC content, gene density (total number of genes predicted on the chromosome), and percentage of sequence (number of genes) that encodes proteins were similar. The chromosomes of these strains also contained a number of discrete prophage regions and genomic islands. One of the genomic islands in strain 2336 contained genes putatively involved in copper, zinc, and tetracycline resistance. Using the genome sequence data and comparative analyses with other members of the <it>Pasteurellaceae</it>, several <it>H. somni </it>genes that may encode proteins involved in virulence (<it>e.g</it>., filamentous haemaggutinins, adhesins, and polysaccharide biosynthesis/modification enzymes) were identified. The two strains contained a total of 17 ORFs that encode putative glycosyltransferases and some of these ORFs had characteristic simple sequence repeats within them. Most of the genes/loci common to both the strains were located in different regions of the two chromosomes and occurred in opposite orientations, indicating genome rearrangement since their divergence from a common ancestor.</p> <p>Conclusions</p> <p>Since the genome of strain 129Pt was ~256,000 bp smaller than that of strain 2336, these genomes provide yet another paradigm for studying evolutionary gene loss and/or gain in regard to virulence repertoire and pathogenic ability. Analyses of the complete genome sequences revealed that bacteriophage- and transposon-mediated horizontal gene transfer had occurred at several loci in the chromosomes of strains 2336 and 129Pt. It appears that these mobile genetic elements have played a major role in creating genomic diversity and phenotypic variability among the two <it>H. somni </it>strains.</p

Plasmids and Rickettsial Evolution: Insight from Rickettsia felis

BACKGROUND: The genome sequence of Rickettsia felis revealed a number of rickettsial genetic anomalies that likely contribute not only to a large genome size relative to other rickettsiae, but also to phenotypic oddities that have confounded the categorization of R. felis as either typhus group (TG) or spotted fever group (SFG) rickettsiae. Most intriguing was the first report from rickettsiae of a conjugative plasmid (pRF) that contains 68 putative open reading frames, several of which are predicted to encode proteins with high similarity to conjugative machinery in other plasmid-containing bacteria. METHODOLOGY/PRINCIPAL FINDINGS: Using phylogeny estimation, we determined the mode of inheritance of pRF genes relative to conserved rickettsial chromosomal genes. Phylogenies of chromosomal genes were in agreement with other published rickettsial trees. However, phylogenies including pRF genes yielded different topologies and suggest a close relationship between pRF and ancestral group (AG) rickettsiae, including the recently completed genome of R. bellii str. RML369-C. This relatedness is further supported by the distribution of pRF genes across other rickettsiae, as 10 pRF genes (or inactive derivatives) also occur in AG (but not SFG) rickettsiae, with five of these genes characteristic of typical plasmids. Detailed characterization of pRF genes resulted in two novel findings: the identification of oriV and replication termination regions, and the likelihood that a second proposed plasmid, pRFδ, is an artifact of the original genome assembly. CONCLUSION/SIGNIFICANCE: Altogether, we propose a new rickettsial classification scheme with the addition of a fourth lineage, transitional group (TRG) rickettsiae, that is unique from TG and SFG rickettsiae and harbors genes from possible exchanges with AG rickettsiae via conjugation. We offer insight into the evolution of a plastic plasmid system in rickettsiae, including the role plasmids may have played in the acquirement of virulence traits in pathogenic strains, and the likely origin of plasmids within the rickettsial tree

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Numerical weather prediction error over the North Pacific and western North America : an investigation with short-range ensemble techniques

Numerical weather prediction models, which are discretized approximations to the physical equations of the atmosphere, are a critical part of weather forecasting. They can project an observed state of the atmosphere into the future, but forecasts have many error sources. To counter this, several forecasts made from slightly different initial states or models can be made over the same domain and time period. This approach, called ensemble forecasting, can forecast uncertainty, and produce a better average forecast. In this study, ensemble forecasts are generated and analyzed to understand the nature of initial condition (IC) and model error over the North Pacific. A poorlypredicted storm event (a bust) in Feb. 1999 is a useful case study period. To approximate different aspects of IC uncertainty, three IC-perturbation methods are used: (1) ranked perturbations that target coherent structures in the analyses; (2) perturbations that simulate differences between operational analyses from major forecast centers; and (3) random perturbations. An ensemble of different model configurations approximates model uncertainty. Ensembles are verified several ways to separate model and IC uncertainty, and evaluate ensemble performance. It is found that during the period surrounding the bust, IC error is greater than model error. But for one critical forecast, model error is unusually high while error from ICs is unusually small. Comparison with rawinsonde observations shows that differences between operational analyses cannot account for analysis error. Ensembles generated with this information show that analysis differences contain some spatial information about analysis uncertainty, but the magnitude is too small. To account for total forecast error, model uncertainty must be included with IC uncertainty. Comparing different ensembles reveals that a scaled ranked-perturbation ensembles has the best characteristics, including perturbation magnitude, uncertainty growth vs. error growth, spread-error correlation, and shape of the variance spectrum. Its properties are verified by running an independent case study, and only minor differences are found. Contributions to the field of weather prediction include a new ranked-perturbation method that results in improved short-range ensemble-mean forecasts, an understanding of the relationship between analysis error and analysis differences, and the confirmation that model uncertainty is necessary to account for short-range forecast error.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofGraduat

An empirical ensemble mesoscale forecasting system

Seven short-term numerical weather prediction experiments test the feasibility of an ensemble mesoscale forecasting system that is designed to minimize the effects of analysis errors in the North Pacific. Each experiment consists of a five-member ensemble (4 + control) run once per day for eight days for the period 21-31 January 1990. The Mesoscale Compressible Community (MC2) model, run at Ax = 100 km over the North Pacific Ocean and western North America, serves as the experimental platform. Empirical perturbations called the Selective Introduction of Hazardous Modes (SIHM) define six of the experiments. The seventh experiment uses perturbations that are bred within the forecast cycle, and serves as a benchmark. Standard root mean square error (RMSE) statistics and surface cross sections are used for verification. SIHM perturbations are incipient cyclones that are added or subtracted from the initial analyses. Resolvable structures in the flow, such as low-level or stratospheric potential vorticity and jet-stream divergence, determine the locations of the perturbations. Perturbation size is set to match the most energetic wavelength in a particular latitude band, as derived from a spectral analysis. The strength of the incipient cyclones is designed to be within reasonable analysis errors published previously. One measure of the likely success of ensemble methods is the spread between different forecast members of the ensemble. The system lacks a desirable spread in RMSE development, and the curves converge at the end of many of the forecasts because of dominance of the common imposed boundary conditions. Spreads in sea-level pressure adequate to envelope most observations exist when the model predicts a storm system well. Precipitation consistently shows the most spread along the cross section. When the model completely misses an event, spreads are negligible.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofGraduat

The potential utility of high-resolution ensemble sensitivity analysis for observation placement during weak flow in complex terrain

The article of record as published may be found at http://dx.doi.org/10.1175/WAF-D-14-00066.1Expansion in the availability of relocatable near-surface atmospheric observing sensors introduces the question of where placement maximizes gain in forecast accuracy. As one possible method of addressing observation placement, the performance of ensemble sensitivity analysis (ESA) is examined for high-resolution (Dx 5 4 km) predictions in complex terrain and during weak flow. ESA can be inaccurate when the underlying assumptions of linear dynamics (and Gaussian statistics) are violated, or when the sensitivity cannot be robustly sampled. A case study of a fog event at Salt Lake City International Airport (KSLC) in Utah provides a useful basis for examining these issues, with the additional influence of complex terrain. A realistic upper-air observing network is used in perfect-model ensemble data assimilation experiments, providing the statistics for ESA. Results show that water vapor mixing ratios over KSLC are sensitive to potential temperature on the first model layer tens of kilometers away, 6 h prior to verification and prior to the onset of fog. Potential temperatures indicate inversion strength in the Salt Lake basin; the ESA predicts southerly flow and strengthened inversions will increase water vapor over KSLC. Linearity tests show that the nonlinear response is about twice the expected response. Experiments with smaller ensembles show that qualitatively similar conclusions about the sensitivity pattern can be reached with ensembles as small as 48 members, but smaller ensembles do not produce accurate sensitivity estimates. Taken together, the results motivate a closer look at the fundamental characteristics of ESA when dynamics (and therefore correlations) are weak.This research was funded in part by the Office of Naval Research under the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program

A Nonparametric Ensemble Postprocessing Approach for Short-Range Visibility Predictions in Data-Sparse Areas

The article of record as published may be found at http://dx.doi.org/10.1175/WAF-D-17-0066.1This work develops and tests the viability of obtaining skillful short-range (<20 h) visibility predictions using statistical postprocessing of a 4-km, 10-member Weather Research and Forecasting (WRF) ensemble configured to closely match the U.S. Air Force Mesoscale Ensemble Forecast System. The raw WRF predictions produce excessive forecasts of zero cloud water, which is simultaneously predicted by all ensemble members in 62% of observed fog cases, leading to zero ensemble dispersion and no skill in these cases. Adding dispersion to the clear cases by making upward adjustments to cloud water predictions from individual members not predicting fog on their own provides the best chance to increase the resolution and reliability of the ensemble. The technique leverages traits of a joint parameter space in the predictions and is generally most effective when the space is defined with a moisture parameter and a low-level stability parameter. Cross validation shows that the method adds significant overnight skill to predictions in valley and coastal regions compared to the raw WRF forecasts, with modest skill increases after sunrise. Postprocessing does not improve the highly skillful raw WRF predictions at the mountain test sites. Since the framework addresses only systematic WRF deficiencies and identifies parameter pairs with a clear, non-site-specific physical mechanism of predictive power, it has geographical transferability with less need for recalibration or observational record compared to other statistical postprocessing approaches.U.S. Air ForceNaval Postgraduate Schoo