Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.

Investigating subtypes of reward processing deficits as trait markers for depression

Background: Anhedonia, the loss of pleasure in usually enjoyable activities, is a central feature of major depressive disorder (MDD). The aim of the present study was to examine whether young people at a familial risk of depression display signs of anticipatory, motivational or consummatory anhedonia, which would indicate that these deficits may be trait markers for MDD. Methods: The study was completed by 22 participants with a family history of depression (FH+) and 21 controls (HC). Anticipatory anhedonia was assessed by asking participants to rate their anticipated liking of pleasant and unpleasant foods which they imagined tasting when cued with images of the foods. Motivational anhedonia was measured by requiring participants to perform key presses to obtain pleasant chocolate taste rewards or to avoid unpleasant apple tastes. Additionally, physical consummatory anhedonia was examined by instructing participants to rate the pleasantness of the acquired tastes. Moreover, social consummatory anhedonia was investigated by asking participants to make preference-based choices between neutral facial expressions, genuine smiles, and polite smiles. Results: It was found that the FH+ group’s anticipated liking of unpleasant foods was significantly lower than that of the control group. By contrast, no group differences in the pleasantness ratings of the actually experienced tastes or in the amount of performed key presses were observed. However, controls preferred genuine smiles over neutral expressions more often than they preferred polite smiles over neutral expressions, while this pattern was not seen in the FH+ group. Conclusion: These findings suggest that FH+ individuals demonstrate an altered anticipatory response to negative stimuli and show signs of social consummatory anhedonia, which may be trait markers for depression.

Thermal aspects of satellite downscaling

The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales down with dimension. However, these two terms do not necessarily scale in the same way, and so the thermal balance may alter and the temperature of subsystems may reach undesired levels. This paper focuses on low-Earth-orbit satellites. We constructed a generalized lumped thermal model that combines a generalized low-Earth-orbit satellite configuration with scaling trends in subsystem heat dissipation and thermal connectivity. Using satellite mass as a scaling parameter, we show that subsystems do not become thermally critical by scaling mass alone.

Aspects of particle filtering in high-dimensional spaces

Nonlinear data assimilation is high on the agenda in all fields of the geosciences as with ever increasing model resolution and inclusion of more physical (biological etc.) processes, and more complex observation operators the data-assimilation problem becomes more and more nonlinear. The suitability of particle filters to solve the nonlinear data assimilation problem in high-dimensional geophysical problems will be discussed. Several existing and new schemes will be presented and it is shown that at least one of them, the Equivalent-Weights Particle Filter, does indeed beat the curse of dimensionality and provides a way forward to solve the problem of nonlinear data assimilation in high-dimensional systems.