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Because of limited high-quality satellite and in situ observations, less attention has been given to the trends in Arctic sea ice thickness and therefore sea ice volume than to the trends in sea ice extent. This study evaluates the spatial and temporal variability in Arctic sea ice thickness using the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Additionally, the Community Earth System Model Large Ensemble Project (LENS) is used to quantify the forced response and internal variability in the model. A dipole spatial pattern of sea ice thickness variability is shown in both PIOMAS and LENS with opposite signs of polarity between the East Siberian Sea and near the Fram Strait. As future sea ice thins, this dipole structure of variability is reduced, and the largest interannual variability is found only along the northern Greenland coastline. Under a high-emissions scenario (RCP8.5) projection, average September sea ice thickness falls below 0.5 m by the end of the twenty-first century. However, a regional analysis shows internal variability contributes to an uncertainty of 10 to 20 years for the timing of the first September sea ice thickness less than 0.5 m in the marginal seas.

Managing dynamic information in large multi-site, multi-species, and multi-discipline consortia is a challenging task for data management applications. Often in academic research studies the goals for informatics teams are to build applications that provide extract-transform-load (ETL) functionality to archive and catalog source data that has been collected by the research teams. In consortia that cross species and methodological or scientific domains, building interfaces which supply data in a usable fashion and make intuitive sense to scientists from dramatically different backgrounds increases the complexity for developers. Further, reusing source data from outside one’s scientific domain is fraught with ambiguities in understanding the data types, analysis methodologies, and how to combine the data with those from other research teams. We report on the design, implementation, and performance of a semantic data management application to support the NIMH funded Conte Center at the University of California, Irvine. The Center is testing a theory of the consequences of “fragmented” (unpredictable, high entropy) early-life experiences on adolescent cognitive and emotional outcomes in both humans and rodents. It employs cross-species neuroimaging, epigenomic, molecular, and neuroanatomical approaches in humans and rodents to assess the potential consequences of fragmented unpredictable experience on brain structure and circuitry. To address this multi-technology, multi-species approach, the system uses semantic web techniques based on the Neuroimaging Data Model (NIDM) to facilitate data ETL functionality. We find this approach enables a low-cost, easy to maintain, and semantically meaningful information management system, enabling the diverse research teams to access and use the data.

Vulnerability to emotional disorders including depression derives from interactions between genes and environment, especially during sensitive developmental periods. Across evolution, maternal care is a key source of environmental sensory signals to the developing brain, and a vast body of work has linked quantitative and qualitative aspects of maternal care to emotional outcome in children and animals. However, the fundamental properties of maternal signals, that promote advantageous vs pathological outcomes in the offspring, are unknown and have been a topic of intense study. We studied emotional outcomes of adolescent rats reared under routine or impoverished environments, and used mathematical approaches to analyze the nurturing behaviors of the dams. Unexpectedly, whereas the quantity and typical qualities of maternal care behaviors were indistinguishable in the two environments, their patterns and rhythms differed drastically and influenced emotional outcomes. Specifically, unpredictable, fragmented maternal care patterns translated into high-entropy rates of sensory signals to the offspring in the impoverished cages. During adolescence, these offspring had significant reductions in sucrose preference and in peer-play, two independent measures of the ability to experience pleasure. This adolescent anhedonia, often a harbinger of later depression, was not accompanied by measures of anxiety or helplessness. Dopaminergic pleasure circuits underlying anhedonia are engaged by predictable sequences of events, and predictable sensory signals during neonatal periods may be critical for their maturation. Conversely, unpredictability maternal-derived signals may disrupt these developmental processes, provoking anhedonia. In sum, high-entropy and fragmented patterns of maternal-derived sensory input to the developing brain predicts, and might promote, the development of anhedonia in rodents, with potential clinical implications.

Different approaches to obtaining uncertainty estimates of the North Atlantic Oscillation (NAO) are explored. The resulting estimates are used to enhance the understanding of spatial variability of the NAO over different time periods. Among the parametric and nonparametric approaches investigated in this study, the bootstrap is nonparametric and not confined to the assumption of normally distributed data. It gives physically plausible uncertainty estimates. The NAO uncertainty estimates depend on sample sizes with greater sampling variability as sample size is smaller. The NAO uncertainty varies with time but common features include that the most uncertain values are centered between the centers of action of theNAOand are asymmetric in the zonal direction (more uncertainty in the eastward direction or downstream). The bootstrap can also be used to provide direct measures of uncertainty regarding the location of the NAO action centers. The uncertainty of the location of the NAO action centers not only helps assess the shift in the NAO but also provides evidence of more than two action centers. The methods reported on here could in principle be applied to any EOF-derived climate pattern. © 2014 American Meteorological Society.

The wintertime NAO is traditionally defined as the first Empirical Orthogonal Function of monthly sea level pressure (SLP) anomalies for all winters and therefore remains fixed in space. The associated NAO index represents the projection of SLP onto the fixed NAO pattern. The NAO index is positive when the pressure contrast between the two centers of action is particularly strong; it is negative when the contrast is weak. This index represents an incomplete description of the wintertime NAO as the pattern is found to shift location on decadal timescales. This study investigates the movement of the centers of action (or nodes) of the NAO for winter in 20-yr running windows starting in 1871. A new climate index, the Angle index, is introduced. It is a measure of the asymmetry in location of the two nodes of the NAO defined in the partially overlapping 20-yr windows. The Angle index has a value of zero only when both nodes are located on the same meridian. It increases in positive value as the curve connecting the nodes tilts more to the northeast; it becomes negative when the tilt is to the northwest. The Angle index complements the smooth NAO index, which is the traditional NAO index averaged over the 20-yr window, especially when the Angle index is strongly negative as occurred during the Arctic warming of the early to mid 20th century. Regression analysis shows that the Angle index provides additional information about climate variability beyond that provided by the smooth NAO index.

A data set of Intertropical Convergence Zone (ITCZ) extent and location in the eastern Pacific, 90°W–180°W, 0°N–25°N, is used to examine the diurnal cycle of cloudiness over the ocean. The data set was generated using a statistical model which utilizes 30 year, 3-hourly infrared (IR) satellite data from 1980 to 2009. The ITCZ envelope of convection has a significant diurnal cycle across the whole domain, and the area of cloudiness “pulses” in extent, peaking in the afternoon. The diurnal cycle of brightness temperatures within the ITCZ changes from east to west, but generally there are two minima in mean IR, implying cold cloud is at a peak: one in the morning, 0600–0900 LST, and another in the afternoon, 1300–1600 LST. Decomposition of cloud top temperatures show that high cloud is at a maximum in the early morning and midlevel cloud peaks in the afternoon. Low cloud is at a maximum in the late evening (2200–0000 LST) and is immediately followed by increases in high cloud, suggesting that the deepest convective systems grow rapidly, within a few hours overnight. There are seasonal changes in the diurnal cycle of cloud top temperature, and it is suggested that colder mean temperatures are more likely in the afternoon when the ITCZ is more extensive. This is shown via seasonal changes and also by comparing El Niño years, when ITCZ is more present, to La Niña years.

Proposes a multi-dimensional curriculum that formed the basis for the Canadian National Core French Study. (Author/VWL)