A multidecadal simulation of Atlantic tropical cyclones using a variable‐resolution global atmospheric general circulation model

Using a variable‐resolution option within the National Center for Atmospheric Research/Department of Energy Community Atmosphere Model (CAM) Spectral Element (SE) global model, a refined nest at 0.25° (∼28 km) horizontal resolution located over the North Atlantic is embedded within a global 1° (∼111 km) grid. The grid is designed such that fine grid cells are located where tropical cyclones (TCs) are observed to occur during the Atlantic TC season (June–November). Two simulations are compared, one with refinement and one control case with no refinement (globally uniform 1° grid). Both simulations are integrated for 23 years using Atmospheric Model Intercomparison Protocols. TCs are tracked using an objective detection algorithm. The variable‐resolution simulation produces significantly more TCs than the unrefined simulation. Storms that do form in the refined nest are much more intense, with multiple storms strengthening to Saffir‐Simpson category 3 intensity or higher. Both count and spatial distribution of TC genesis and tracks in the variable‐resolution simulation are well matched to observations and represent significant improvements over the unrefined simulation. Some degree of interannual skill is noted, with the variable‐resolution grid able to reproduce the observed connection between Atlantic TCs and the El Niño‐Southern Oscillation (ENSO). It is shown that Genesis Potential Index (GPI) is well matched between the refined and unrefined simulations, implying that the introduction of variable‐resolution does not affect the synoptic environment. Potential “upscale” effects are noted in the variable‐resolution simulation, suggesting stronger TCs in refined nests may play a role in meridional transport of momentum, heat, and moisture. Key Points Variable‐resolution models can improve the representation of tropical cyclones CAM produces realistic Atlantic TC climatology at 0.25° resolution Addition of local refinement in CAM does not impact synoptic scalesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109331/1/jame20104.pd

Objective tropical cyclone extratropical transition detection in high‐resolution reanalysis and climate model data

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high‐resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable‐resolution Community Atmosphere Model (CAM) at two different resolutions (ΔX∼55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, ΔX∼38 km), and the ERA‐Interim Reanalysis (ERA‐I, ΔX∼80 km). The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA‐I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High‐resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold‐core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.Key PointsAn objective detection technique for tracking tropical cyclone extratropical transition in gridded climate data is describedObjectively calculated extratropical transition climatology in high‐resolution reanalyses closely match observational studiesTropical cyclones in CAM take too long to undergo extratropical transition highlighting model biases requiring further investigationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/1/jame20355_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/2/jame20355.pd

Physics searches at the LHC

With the LHC up and running, the focus of experimental and theoretical high energy physics will soon turn to an interpretation of LHC data in terms of the physics of electroweak symmetry breaking and the TeV scale. We present here a broad review of models for new TeV-scale physics and their LHC signatures. In addition, we discuss possible new physics signatures and describe how they can be linked to specific models of physics beyond the Standard Model. Finally, we illustrate how the LHC era could culminate in a detailed understanding of the underlying principles of TeV-scale physics.Comment: 184 pages, 55 figures, 14 tables, hundreds of references; scientific feedback is welcome and encouraged. v2: text, references and Overview Table added; feedback still welcom

Variance estimation for integrated population models

Abstract State-space models are widely used in ecology. However, it is well known that in practice it can be difficult to estimate both the process and observation variances that occur in such models. We consider this issue for integrated population models,which incorporate state-space models for population dynamics. To some extent, the mechanism of integrated population models protects against this problem, but it can still arise, and two illustrations are provided, in each of which the observation variance is estimated as zero. In the context of an extended case study involving data on British Grey herons, we consider alternative approaches for dealing with the problem when it occurs. In particular, we consider penalised likelihood, a method based on fitting splines and a method of pseudo-replication, which is undertaken via a simple bootstrap procedure. For the case study of the paper, it is shown that when it occurs, an estimate of zero observation variance is unimportant for inference relating to the model parameters of primary interest. This unexpected finding is supported by a simulation study

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