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Estimating the uncertainty of areal precipitation using data assimilation
We present a method to estimate spatially and temporally variable uncertainty of areal precipitation data. The aim of the method is to merge measurements from different sources, remote sensing and in situ, into a combined precipitation product and to provide an associated dynamic uncertainty estimate. This estimate should provide an accurate representation of uncertainty both in time and space, an adjustment to additional observations merged into the product through data assimilation, and flow dependency. Such a detailed uncertainty description is important for example to generate precipitation ensembles for probabilistic hydrological modelling or to specify accurate error covariances when using precipitation observations for data assimilation into numerical weather prediction models. The presented method uses the Local Ensemble Transform Kalman Filter and an ensemble nowcasting model. The model provides information about the precipitation displacement over time and is continuously updated by assimilation of observations. In this way, the precipitation product and its uncertainty estimate provided by the nowcasting ensemble evolve consistently in time and become flow-dependent. The method is evaluated in a proof of concept study focusing on weather radar data of four precipitation events. The study demonstrates that the dynamic areal uncertainty estimate outperforms a constant benchmark uncertainty value in all cases for one of the evaluated scores, and in half the number of cases for the other score. Thus, the flow dependency introduced by the coupling of data assimilation and nowcasting enables a more accurate spatial and temporal distribution of uncertainty. The mixed results achieved in the second score point out the importance of a good probabilistic nowcasting scheme for the performance of the method
Health care and the cross-section of US stock returns
Health care costs represent a large and growing component of business and consumer expenditures in the US. Medical inflation represents these costs, and it differs from aggregate inflation and other market factors with respect to its rate of growth, statistical properties and the extent to which it can be hedged by households and firms. Using multiple model specifications for the 25-year period from 1985 to 2009, we find medical inflation is robustly priced in the cross-section of US stock returns. It commands a risk premium of between 31 and 51 basis points per annum per unit change in beta. Medical inflation is also unique in that it represents the only inflationary component that robustly explains the cross-section of stock returns in this manner and is not subsumed by other common factors in the literature. These results quantify the health care industry’s unique and significant role in the US economy and stock market, further rationalizing the substantial attention this industry receives
Effect of Excess Dietary Crude Protein from Corn Gluten Meal or Soybean Meal on Reproductive Function of Beef Cows Consuming Low Quality Forage
Coproducts of the ethanol industry are a concentrated package of crude protein (CP) which can be fed to beef cows in conjunction with low quality forage to make economical diets that meets nutrient requirements. With this pairing, having excess dietary CP is likely; however the effects of these excessive CP diets on beef cow reproduction have not been made clear. In addition, the effects of excess dietary CP from feedstuffs that differ in rumen degradability are not known. In the present study, we studied the effects of diets containing 150% of metabolizable protein (MP) requirements from a moderately high (corn gluten meal) or low (soybean meal) rumen undegradable protein (RUP) fraction on reproductive function around the time of ovulation. We observed that excess dietary RUP enhanced dominant follicle growth and ovulatory parameters, while excess dietary rumen degradable protein (RDP) improved circulating progesterone concentration post ovulation. Based on these data, source of CP when fed to excess may have differential impacts on reproductive function in mature beef cows. However, the mechanisms by which these physiological alterations occur are unknown at this time. Thus, more research is warranted to elucidate how source and amount of CP, when supplemented in low quality forage-based diets, may influence reproductive function in beef cows
Effects of Increasing Supplementation of Rumen Undegradable Protein on Plasma Essential Amino Acid Concentrations in Beef Cows Consuming Low Quality Forage
The effects of pairing a low quality forage with increasing metabolizable protein (MP) supplementation from a moderately abundant rumen undegradable protein (RUP) source (corn gluten meal; 62% RUP) on essential plasma amino acid (AA) concentrations were evaluated in a 60-day trial. Non-pregnant, non-lactating cows (n=24) were offered ad libitum access to cornstalks and fed 1 of 3 isocaloric diets (0.48 NEm/lb) and supplemented primarily with corn gluten meal to provide 100% MP requirements (CON), 125% MP requirements (MP125), or 150% MP requirements (MP150). It was observed that increasing concentrations of MP in the diet from a moderately abundant RUP source increased the percent of essential AA, ketogenic AA, branched-chain AA and urea cycle AA in plasma. Also, as a percent of total AA, glycogenic AA were decreased with increased MP supplementation. Therefore, increasing supplementation of MP can the shift essential AA profiles of beef cows when fed with low quality forage
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