Dataset Information

Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data.

ABSTRACT: A new measure of subseasonal variability is introduced that provides a scale-dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA-Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio-gravity (IG) modes increases as the scale reduces. Time series of globally integrated variability anomalies in ERA-Interim show an increase in variability after year 2000. In recent years the anomalies have been about 2% above the 1981-2010 average. The relative increase in variability projecting on the IG modes is larger and more persistent than for the Rossby modes. Although the IG part is a small component of the subseasonal variability, it is an important effect likely reflecting the observed increase in the tropical precipitation variability.

SUBMITTER: Zagar N

PROVIDER: S-EPMC6360454 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data.

Žagar N N Jelić D D Alexander M J MJ Manzini E E

Geophysical research letters 20181202 23

A new measure of subseasonal variability is introduced that provides a scale-dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA-Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio-gravity (IG) modes increases as the scale ...[more]

PMID: 30774167

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Project description:BackgroundRegional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes.MethodsWe assessed the effect of multi-day lag exposure for maximum near-surface air temperature (Tmax) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression.ResultsWe observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in Tmax on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria.ConclusionReanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Project description:Bifidobacteria are among the earliest colonizers of the human gut, conferring multiple health benefits. While multiple Bifidobacterium strains are used as probiotics, accumulating evidence suggests that the individual responses to probiotic supplementation may vary, likely due to a variety of factors, including strain type(s), gut community composition, dietary habits of the consumer, and other health/lifestyle conditions. Given the saccharolytic nature of bifidobacteria, the carbohydrate composition of the diet is one of the primary factors dictating the colonization efficiency of Bifidobacterium strains. Therefore, a comprehensive understanding of bifidobacterial glycan metabolism at the strain level is necessary to rationally design probiotic or synbiotic formulations that combine bacterial strains with glycans that match their nutrient preferences. In this study, we systematically reconstructed 66 pathways involved in the utilization of mono-, di-, oligo-, and polysaccharides by analyzing the representation of 565 curated functional roles (catabolic enzymes, transporters, transcriptional regulators) in 2973 non-redundant cultured Bifidobacterium isolates and metagenome-assembled genomes (MAGs). Our analysis uncovered substantial heterogeneity in the predicted glycan utilization capabilities at the species and strain level and revealed the presence of a yet undescribed phenotypically distinct clade within the Bifidobacterium longum species. We also identified Bangladeshi isolates harboring unique gene clusters tentatively implicated in the breakdown of xyloglucan and human milk oligosaccharides. Predicted carbohydrate utilization phenotypes were experimentally characterized and validated. Our large-scale genomic analysis expands the knowledge of carbohydrate metabolism in bifidobacteria and provides a foundation for rationally designing single- or multi-strain probiotic formulations of a given bifidobacterial species as well as synbiotic combinations of bifidobacterial strains matched with their preferred carbohydrate substrates.

Dataset Information

Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data.

Publications

Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data.

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