A multi-model superensemble algorithm for seasonal climate prediction using DEMETER forecasts

In this paper, a multi-model ensemble approach with statistical correction for seasonal precipitation forecasts using a coupled DEMETER model data set is presented. Despite the continuous improvement of coupled models, they have serious systematic errors in terms of the mean, the annual cycle and the interannual variability; consequently, the predictive skill of extended forecasts remains quite low. One of the approaches to the improvement of seasonal prediction is the empirical weighted multi-model ensemble, or superensemble, combination. In the superensemble approach, the different model forecasts are statistically combined during the training phase using multiple linear regression, with the skill of each ensemble member implicitly factored into the superensemble forecast. The skill of a superensemble relies strongly on the past performance of the individual member models used in its construction. The algorithm proposed here involves empirical orthogonal function (EOF) filtering of the actual data set prior to the construction of a multi-model ensemble or superensemble as an alternative solution for seasonal prediction. This algorithm generates a new data set from the input multi-model data set by finding a consistent spatial pattern between the observed analysis and the individual model forecast. This procedure is a multiple linear regression problem in the EOF space. The newly generated EOF-filtered data set is then used as an input data set for the construction of a multi-model ensemble and superensemble. The skill of forecast anomalies is assessed using statistics of categorical forecast, spatial anomaly correlation and root mean square (RMS) errors. The various verifications show that the unbiased multi-model ensemble of DEMETER forecasts improves the prediction of spatial patterns (i.e. the anomaly correlation), but it shows poor skill in categorical forecast. Due to the removal of seasonal mean biases of the different models, the forecast errors of the bias-corrected multi-model ensemble and superensemble are already quite small. Based on the anomaly correlation and RMS measures, the forecasts produced by the proposed method slightly outperform the other conventional forecasts

Plume motion and large-scale circulation in a cylindrical Rayleigh-B\'enard cell

We used the time correlation of shadowgraph images to determine the angle $\Theta$ of the horizontal component of the plume velocity above (below) the center of the bottom (top) plate of a cylindrical Rayleigh-B\'enard cell of aspect ratio $\Gamma \equiv D/L = 1$ ($D$ is the diameter and $L \simeq 87$ mm the height) in the Rayleigh-number range $7\times 10^7 \leq R \leq 3\times 10^{9}$ for a Prandtl number $\sigma = 6$. We expect that $\Theta$ gives the direction of the large-scale circulation. It oscillates time-periodically. Near the top and bottom plates $\Theta(t)$ has the same frequency but is anti-correlated.Comment: 4 pages, 6 figure

Thermohaline mixing and the photospheric composition of low-mass giant stars

We compute full evolutionary sequences of red giant branch stars close to the luminosity bump by including state of the art composition transport prescriptions for the thermohaline mixing regimes. In particular we adopt a self-consistent double-diffusive convection theory, that allows to handle the instabilities that arise when thermal and composition gradients compete against each other, and a very recent empirically motivated and parameter free asymptotic scaling law for thermohaline composition transport. In agreement with previous works, we find that during the red giant stage, a thermohaline instability sets in shortly after the hydrogen burning shell (HBS) encounters the chemical discontinuity left behind by the first dredge-up. We also find that the thermohaline unstable region, initially appearing at the exterior wing of the HBS, is unable to reach the outer convective envelope, with the consequence that no mixing of elements that produces a non-canonical modification of the stellar surface abundances occurs. Also in agreement with previous works, we find that by artificially increasing the mixing efficiency of thermohaline regions it is possible to connect both unstable regions, thus affecting the photospheric composition. However, we find that in order to reproduce the observed abundances of red giant branch stars close to the luminosity bump, thermohaline mixing efficiency has to be artificially increased by about 4 orders of magnitude from that predicted by recent 3D numerical simulations of thermohaline convection close to astrophysical environments. From this we conclude the chemical abundance anomalies of red giant stars cannot be explained on the basis of thermohaline mixing alone.Comment: 7 pages, 6 figures, accepted for publication in A&

Hydroxyurea therapy for children with sickle cell disease: Describing how caregivers make this decision

Background: Hydroxyurea (HU) is underutilized in children with sickle cell disease (SCD) because caregivers frequently decline HU when it is offered. This study explores what impacts this decision. Results: Caregivers of children with clinically severe SCD whose children were offered HU previously were interviewed. We used a qualitative analytical approach to analyze their telephone interview transcripts. Caregivers who chose HU (n = 9) reported their children had severe SCD, sought detailed information about HU, and accepted HU as a preventative therapy. In contrast, caregivers who did not choose HU (n = 10) did not perceive their children as having severe SCD and did not question their child's provider about HU. Conclusions: This study identifies specific areas that providers should address to when they discuss HU with families so that they can make informed decisions. Our study also uncovered factors that are important to consider when designing future interventions to improve hydroxyurea acceptance and when developing decision-aid tools to assist caregivers of children with SCD who are considering disease modifying therapies

Defining Rules for Kinematic Shapes with Variable Spatial Relations

Designing mechanisms can be a challenging problem, because the underlying kinematics involved are typically not intuitively incorporated into common techniques for design representation. Kinematic shapes and kinematic grammars build on the shape grammar and making grammar formalisms to enable a visually intuitive approach to model and explore mechanisms. With reference to the lower kinematic pairs this paper introduces kinematic shapes. These are connected shapes with parts which have variable spatial relations that account for the relative motion of the parts. The paper considers how such shapes can be defined, the role of elements shared by connected parts, and the motions that result. It also considers how kinematic shape rules can be employed to generate and explore the motion of mechanisms