Australian blocking impacts on ocean surface waves

Climate Dynamics - We assess the impact of split-flow blocking in the Australian region on global ocean wind waves using 30 years of high-resolution wave data from the CAWCR wave model...     

Climate change at the ecosystem scale: a 50-year record in New Hampshire

Observing the full range of climate change impacts at the local scale is difficult. Predicted rates of change are often small relative to interannual variability, and few locations have sufficiently comprehensive long-term records of environmental variables to enable researchers to observe the fine-scale patterns that may be important to understanding the influence of climate change on biological systems at the taxon, community, and ecosystem levels. We examined a 50-year meteorological and hydrological record from the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, an intensively monitored Long-Term Ecological Research site. Of the examined climate metrics, trends in temperature were the most significant (ranging from 0.7 to 1.3 °C increase over 40–50 year records at 4 temperature stations), while analysis of precipitation and hydrologic data yielded mixed results. Regional records show generally similar trends over the same time period, though longer-term (70–102 year) trends are less dramatic. Taken together, the results from HBEF and the regional records indicate that the climate has warmed detectably over 50 years, with important consequences for hydrological processes. Understanding effects on ecosystems will require a diversity of metrics and concurrent ecological observations at a range of sites, as well as a recognition that ecosystems have existed in a directionally changing climate for decades, and are not necessarily in equilibrium with the current climate.     

The use of the land-sea warming contrast under climate change to improve impact metrics

A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.     

Changes in diatom assemblages since pre-industrial times in 40 reference lakes from the Experimental Lakes Area (northwestern Ontario,Canada)

Diatom assemblages in recent versus pre-industrial sediments were examined in 40 relatively undisturbed lakes from the Experimental Lakes Area (ELA). The ELA region of northwestern Ontario receives low amounts of acidic deposition and the lakes have been minimally disturbed by watershed development or other human activities. Consequently, this region represents an important location to detect possible changes in lakes due to climate change. In over half of the lakes, planktonic taxa (especially Discostella stelligera) increased between 10 and 40% since pre-industrial times. Changes in diatom assemblages are consistent with taxa that would benefit from enhanced stratification and a longer ice-free season. We hypothesized that there should be a relationship between stratification and measured chemical and physical characteristics of the study lakes. Multiple correlation analysis was undertaken to see the relationship between planktonic taxa and D. stelligera since pre-industrial times and the physical and chemical characteristics of the study lakes. Lake depth was consistently identified as an important variable. The timing of the increase in planktonic taxa within cores from these lakes will be needed to rule out other possible regional changes that may also be occurring in the ELA region.     

Mineral Prospectivity Prediction from High-Dimensional Geoscientific Data Using a Similarity-Based Density Estimation Model

Assuming a study region in which each cell has associated with it an N-dimensional vector of values corresponding to N predictor variables, one means of predicting the potential of some cell to host mineralization is to estimate, on the basis of historical data, a probability density function that describes the distribution of vectors for cells known to contain deposits. This density estimate can then be employed to predict the mineralization likelihood of other cells in the study region. However, owing to the curse of dimensionality, estimating densities in high-dimensional input spaces is exceedingly difficult, and conventional statistical approaches often break down. This article describes an alternative approach to estimating densities. Inspired by recent work in the area of similarity-based learning, in which input takes the form of a matrix of pairwise similarities between training points, we show how the density of a set of mineralized training examples can be estimated from a graphical representation of those examples using the notion of eigenvector graph centrality. We also show how the likelihood for a test example can be estimated from these data without having to construct a new graph. Application of the technique to the prediction of gold deposits based on 16 predictor variables shows that its predictive performance far exceeds that of conventional density estimation methods, and is slightly better than the performance of a discriminative approach based on multilayer perceptron neural networks.     

Time-varying transformations for Hill–Clohessy–Wiltshire solutions in elliptic orbits

The relative motion of chief and deputy satellites in close proximity with orbits of arbitrary eccentricity can be approximated by linearized time-periodic equations of motion. The linear time-invariant Hill–Clohessy–Wiltshire equations are typically derived from these equations by assuming the chief satellite is in a circular orbit. Two Lyapunov–Floquet transformations and an integral-preserving transformation are here presented which relate the linearized time-varying equations of relative motion to the Hill–Clohessy–Wiltshire equations in a one-to-one manner through time-varying coordinate transformations. These transformations allow the Hill–Clohessy–Wiltshire equations to describe the linearized relative motion for elliptic chief satellites.     

Atom‐probe analyses of nanodiamonds from Allende

Atom‐probe tomography (APT) is currently the only analytical technique that, due to its spatial resolution and detection efficiency, has the potential to measure the carbon isotope ratios of individual nanodiamonds. We describe three different sample preparation protocols that we developed for the APT analysis of meteoritic nanodiamonds at sub‐nm resolution and present carbon isotope peak ratios of meteoritic and synthetic nanodiamonds. The results demonstrate an instrumental bias associated with APT that needs to be quantified and corrected to obtain accurate isotope ratios. After this correction is applied, this technique should allow determination of the distribution of ¹²C/¹³C ratios in individual diamond grains, solving the decades‐old question of the origin of meteoritic nanodiamonds: what fraction, if any, formed in the solar system and in presolar environments? Furthermore, APT could help us identify the stellar sources of any presolar nanodiamonds that are detected.     

Restriction of parent body heating by metal‐troilite melting: Thermal models for the ordinary chondrites

Ordinary chondrite meteorites contain silicates, Fe,Ni‐metal grains, and troilite (FeS). Conjoined metal‐troilite grains would be the first phase to melt during radiogenic heating in the parent body, if temperatures reached over approximately 910–960 °C (the Fe,Ni‐FeS eutectic). On the basis of two‐pyroxene thermometry of 13 ordinary chondrites, we argue that peak temperatures in some type 6 chondrites exceeded the Fe,Ni‐FeS eutectic and thus conjoined metal‐troilite grains would have begun to melt. Melting reactions consume energy, so thermal models were constructed to investigate the effect of melting on the thermal history of the H, L, and LL parent asteroids. We constrained the models by finding the proportions of conjoined metal‐troilite grains in ordinary chondrites using high‐resolution X‐ray computed tomography. The models show that metal‐troilite melting causes thermal buffering and inhibits the onset of silicate melting. Compared with models that ignore the effect of melting, our models predict longer cooling histories for the asteroids and accretion times that are earlier by 61, 124, or 113 kyr for the H, L, and LL asteroids, respectively. Because the Ni/Fe ratio of the metal and the bulk troilite/metal ratio is higher in L and LL chondrites than H chondrites, thermal buffering has the greatest effect in models for the L and LL chondrite parent bodies, and least effect for the H chondrite parent. Metal‐troilite melting is also relevant to models of primitive achondrite parent bodies, particularly those that underwent only low degrees of silicate partial melting. Thermal models can predict proportions of petrologic types formed within an asteroid, but are systematically different from the statistics of meteorite collections. A sampling bias is interpreted to explain these differences.     

REGIONAL TRENDS IN ELECTORAL SUPPORT IN BRITAIN, 1950–1983*

Analyses of the geography of British elections have typically stressed the continuity in patterns of party support. This paper challenges that conclusion. Employing an alternative method of analysis, it identifies significant regional trends in the Conservative and Labour vote between 1950 and 1983. Pro-Labour trends in Scotland and Northwest England are contrasted with secular changes favoring the Conservatives in non-metropolitan Southern England. These long-term trends have not been associated with growing regional polarization in party support. While the findings are specific to Britain, the method of assessing electoral change might be usefully applied to patterns in other countries.