Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs

Analysis of streamflow characteristics over Northeastern Canada in a changing climate

An analysis of streamflow characteristics (i.e. mean annual and seasonal flows and extreme high and low flows) in current and future climates for 21 watersheds of north-east Canada covering mainly the province of Quebec is presented in this article. For the analysis, streamflows are derived from a 10-member ensemble of Canadian Regional Climate Model (CRCM) simulations, driven by the Canadian Global Climate Model simulations, of which five correspond to current 1970–1999 period, while the other five correspond to future 2041–2070 period. For developing projected changes of streamflow characteristics from current to future periods, two different approaches are used: one based on the concept of ensemble averaging while the other approach is based on merged samples of current and similarly future simulations following multiple comparison tests. Verification of the CRCM simulated streamflow characteristics for the 1970–1999 period suggests that the model simulated mean hydrographs and high flow characteristics compare well with those observed, while the model tends to underestimate low flow extremes. Results of projected changes to mean annual streamflow suggest statistically significant increases nearly all over the study domain, while those for seasonal streamflow show increases/decreases depending on the season. Two- and 5-year return levels of 15-day low flows are projected to increase significantly over most part of the study domain, though the changes are small in absolute terms. Based on the ensemble averaging approach, changes to 10- and 30-year return levels of high flows are not generally found significant. However, when a similar analysis is performed using longer samples, significant increases to high flow return levels are found mainly for northernmost watersheds. This study highlights the need for longer samples, particularly for extreme events in the development of robust projections

Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989-2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2-6°C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCM

Evaluation of the Algorithms and Parameterizations for Ground Thawing and Freezing Simulation in Permafrost Regions

Ground thawing and freezing depths (GTFDs) strongly influence the hydrology and energy balances of permafrost regions. Current methods to simulate GTFD differ in algorithm type, soil parameterization, representation of latent heat, and unfrozen water content. In this study, five algorithms (one semiempirical, two analytical, and two numerical), three soil thermal conductivity parameterizations, and three unfrozen water parameterizations were evaluated against detailed field measurements at four field sites in Canada’s discontinuous permafrost region. Key findings include: (1) de Vries’ parameterization is recommended to determine the thermal conductivity in permafrost soils; (2) the three unfrozen water parameterization methods exhibited little difference in terms of GTFD simulations, yet the segmented linear function is the simplest to be implemented; (3) the semiempirical algorithm reasonably simulates thawing at permafrost sites and freezing at seasonal frost sites with site-specific calibration. However, large interannual and intersite variations in calibration coefficients limit its applicability for dynamic analysis; (4) when driven by surface forcing, analytical algorithms performed marginally better than the semiempirical algorithm. The inclusion of bottom forcing improved analytical algorithm performance, yet their results were still poor compared with those achieved by numerical algorithms; (5) when supplied with the optimal inputs, soil parameterizations, and model configurations, the numerical algorithm with latent heat treated as an apparent heat capacity achieved the best GTFD simulations among all algorithms at all sites. Replacing the observed bottom temperature with a zero heat flux boundary condition did not significantly reduce simulation accuracy, while assuming a saturated profile caused large errors at several sites

Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers

Background: Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis. Long non-coding RNAs, as a new, relatively unstudied class of transcripts, provide a rich opportunity to identify both functional drivers and cancer-type-specific biomarkers. However, despite the potential importance of long non-coding RNAs to the cancer field, no comprehensive survey of long non-coding RNA expression across various cancers has been reported. Results: We performed a sequencing-based transcriptional survey of both known long non-coding RNAs and novel intergenic transcripts across a panel of 64 archival tumor samples comprising 17 diagnostic subtypes of adenocarcinomas, squamous cell carcinomas and sarcomas. We identified hundreds of transcripts from among the known 1,065 long non-coding RNAs surveyed that showed variability in transcript levels between the tumor types and are therefore potential biomarker candidates. We discovered 1,071 novel intergenic transcribed regions and demonstrate that these show similar patterns of variability between tumor types. We found that many of these differentially expressed cancer transcripts are also expressed in normal tissues. One such novel transcript specifically expressed in breast tissue was further evaluated using RNA in situ hybridization on a panel of breast tumors. It was shown to correlate with low tumor grade and estrogen receptor expression, thereby representing a potentially important new breast cancer biomarker. Conclusions: This study provides the first large survey of long non-coding RNA expression within a panel of solid cancers and also identifies a number of novel transcribed regions differentially expressed across distinct cancer types that represent candidate biomarkers for future research

SMART trial: A randomized clinical trial of self-monitoring in behavioral weight management-design and baseline findings.

BACKGROUND: The primary form of treatment for obesity today is behavioral therapy. Self-monitoring diet and physical activity plays an important role in interventions targeting behavior and weight change. The SMART weight loss trial examined the impact of replacing the standard paper record used for self-monitoring with a personal digital assistant (PDA). This paper describes the design, methods, intervention, and baseline sample characteristics of the SMART trial. METHODS: The SMART trial used a 3-group design to determine the effects of different modes of self-monitoring on short- and long-term weight loss and on adherence to self-monitoring in a 24-month intervention. Participants were randomized to one of three conditions (1) use of a standard paper record (PR); (2) use of a PDA with dietary and physical activity software (PDA); or (3), use of a PDA with the same software plus a customized feedback program (PDA + FB). RESULTS: We screened 704 individuals and randomized 210. There were statistically but not clinically significant differences among the three cohorts in age, education, HDL cholesterol, blood glucose and systolic blood pressure. At 24 months, retention rate for the first of three cohorts was 90%. CONCLUSIONS: To the best of our knowledge, the SMART trial is the first large study to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper records. This study has the potential to reveal significant details about self-monitoring patterns and whether technology can improve adherence to this vital intervention component

Regaining In-Group Continuity in Times of Anxiety about the Group's Future : A Study on the Role of Collective Nostalgia Across 27 Countries

Collective nostalgia for the good old days of the country thrives across the world. However, little is known about the social psychological dynamics of this collective emotion across cultures. We predicted that collective nostalgia is triggered by collective angst as it helps people to restore a sense of in-group continuity via stronger in-group belonging and out-group rejection (in the form of opposition to immigrants). Based on a sample (N = 5,956) of individuals across 27 countries, the general pattern of results revealed that collective angst predicts collective nostalgia, which subsequently relates to stronger feelings of in-group continuity via in-group belonging (but not via out-group rejection). Collective nostalgia generally predicted opposition to immigrants, but this was subsequently not related to in-group continuity. © 2018 Hogrefe Publishing.Peer reviewe

A prospective study of maternal, fetal and neonatal deaths in low- and middle-income countries

To quantify maternal, fetal and neonatal mortality in low- and middle-income countries, to identify when deaths occur and to identify relationships between maternal deaths and stillbirths and neonatal deaths