Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource

The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.

Markov models of aging: theory and practice

We review and structure some of the mathematical and statistical models that have been developed over the past half century to grapple with theoretical and experimental questions about the stochastic development of aging over the life course. We suggest that the mathematical models are in large part addressing the problem of partitioning the randomness in aging: How does aging vary between individuals, and within an individual over the lifecourse? How much of the variation is inherently related to some qualities of the individual, and how much is entirely random? How much of the randomness is cumulative, and how much is merely short-term flutter? We propose that recent lines of statistical inquiry in survival analysis could usefully grapple with these questions, all the more so if they were more explicitly linked to the relevant mathematical and biological models of aging. To this end, we describe points of contact among the various lines of mathematical and statistical research. We suggest some directions for future work, including the exploration of information-theoretic measures for evaluating components of stochastic models as the basis for analyzing experiments and anchoring theoretical discussions of aging.

Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures.

Congestion models with consistent conjectures

This paper demonstrates that, in situations in which a cumulative externality exists, the basic nature and extent of resource misallocation may be substantially less than we imagine. This conclusion stems from deriving consistent conjectures in a unified framework in which congestion is present. Experiments support the conclusion that, when numbers of agents are small, when there is little heterogeneity among them, and when they have the opportunity to observe each other during repeated experiment, the market allocation may be efficient

Physically consistent responses of the global atmospheric hydrological cycle in models and observations

Robust and physically understandable responses of the global atmospheric water cycle to a warming climate are presented. By considering interannual responses to changes in surface temperature (T), observations and AMIP5 simulations agree on an increase in column integrated water vapor at the rate 7 %/K (in line with the Clausius­Clapeyron equation) and of precipitation at the rate 2-­3 %/K (in line with energetic constraints). Using simple and complex climate models, we demonstrate that radiative forcing by greenhouse gases is currently suppressing global precipitation (P) at ~ -0.15 %/decade. Along with natural variability, this can explain why observed trends in global P over the period 1988-2008 are close to zero. Regional responses in the global water cycle are strongly constrained by changes in moisture fluxes. Model simulations show an increased moisture flux into the tropical wet region at 900 hPa and an enhanced outflow (of smaller magnitude) at around 600 hPa with warming. Moisture transport explains an increase in P in the wet tropical regions and small or negative changes in the dry regions of the subtropics in CMIP5 simulations of a warming climate. For AMIP5 simulations and satellite observations, the heaviest 5-day rainfall totals increase in intensity at ~15 %/K over the ocean with reductions at all percentiles over land. The climate change response in CMIP5 simulations shows consistent increases in P over ocean and land for the highest intensities, close to the Clausius-Clapeyron scaling of 7 %/K, while P declines for the lowest percentiles, indicating that interannual variability over land may not be a good proxy for climate change. The local changes in precipitation and its extremes are highly dependent upon small shifts in the large-scale atmospheric circulation and regional feedbacks.

Forecasting models of retail rents

The authors model retail rents in the United Kingdom with use of vector-autoregressive and time-series models. Two retail rent series are used, compiled by LaSalle Investment Management and CB Hillier Parker, and the emphasis is on forecasting. The results suggest that the use of the vector-autoregression and time-series models in this paper can pick up important features of the data that are useful for forecasting purposes. The relative forecasting performance of the models appears to be subject to the length of the forecast time-horizon. The results also show that the variables which were appropriate for inclusion in the vector-autoregression systems differ between the two rent series, suggesting that the structure of optimal models for predicting retail rents could be specific to the rent index used. Ex ante forecasts from our time-series suggest that both LaSalle Investment Management and CB Hillier Parker real retail rents will exhibit an annual growth rate above their long-term mean.

Systematic model forecast error in Rossby wave structure

Diabatic processes can alter Rossby wave structure; consequently errors arising from model processes propagate downstream. However, the chaotic spread of forecasts from initial condition uncertainty renders it difficult to trace back from root mean square forecast errors to model errors. Here diagnostics unaffected by phase errors are used, enabling investigation of systematic errors in Rossby waves in winter-season forecasts from three operational centers. Tropopause sharpness adjacent to ridges decreases with forecast lead time. It depends strongly on model resolution, even though models are examined on a common grid. Rossby wave amplitude reduces with lead time up to about five days, consistent with under-representation of diabatic modification and transport of air from the lower troposphere into upper-tropospheric ridges, and with too weak humidity gradients across the tropopause. However, amplitude also decreases when resolution is decreased. Further work is necessary to isolate the contribution from errors in the representation of diabatic processes.

Vertical structure of stratospheric water vapour trends derived from merged satellite data

Stratospheric water vapour is a powerful greenhouse gas. The longest available record from balloon observations over Boulder, Colorado, USA shows increases in stratospheric water vapour concentrations that cannot be fully explained by observed changes in the main drivers, tropical tropopause temperatures and methane. Satellite observations could help resolve the issue, but constructing a reliable long-term data record from individual short satellite records is challenging. Here we present an approach to merge satellite data sets with the help of a chemistry–climate model nudged to observed meteorology. We use the models’ water vapour as a transfer function between data sets that overcomes issues arising from instrument drift and short overlap periods. In the lower stratosphere, our water vapour record extends back to 1988 and water vapour concentrations largely follow tropical tropopause temperatures. Lower and mid-stratospheric long-term trends are negative, and the trends from Boulder are shown not to be globally representative. In the upper stratosphere, our record extends back to 1986 and shows positive long-term trends. The altitudinal differences in the trends are explained by methane oxidation together with a strengthened lower-stratospheric and a weakened upper stratospheric circulation inferred by this analysis. Our results call into question previous estimates of surface radiative forcing based on presumed global long-term increases in water vapour concentrations in the lower stratosphere.

An assessment of the impact of local processes on dust lifting in martian climate models

Simulation of the lifting of dust from the planetary surface is of substantially greater importance on Mars than on Earth, due to the fundamental role that atmospheric dust plays in the former’s climate, yet the dust emission parameterisations used to date in martian global climate models (MGCMs) lag, understandably, behind their terrestrial counterparts in terms of sophistication. Recent developments in estimating surface roughness length over all martian terrains and in modelling atmospheric circulations at regional to local scales (less than O(100 km)) presents an opportunity to formulate an improved wind stress lifting parameterisation. We have upgraded the conventional scheme by including the spatially varying roughness length in the lifting parameterisation in a fully consistent manner (thereby correcting a possible underestimation of the true threshold level for wind stress lifting), and used a modification to account for deviations from neutral stability in the surface layer. Following these improvements, it is found that wind speeds at typical MGCM resolution never reach the lifting threshold at most gridpoints: winds fall particularly short in the southern midlatitudes, where mean roughness is large. Sub-grid scale variability, manifested in both the near-surface wind field and the surface roughness, is then considered, and is found to be a crucial means of bridging the gap between model winds and thresholds. Both forms of small-scale variability contribute to the formation of dust emission ‘hotspots’: areas within the model gridbox with particularly favourable conditions for lifting, namely a smooth surface combined with strong near-surface gusts. Such small-scale emission could in fact be particularly influential on Mars, due both to the intense positive radiative feedbacks that can drive storm growth and a strong hysteresis effect on saltation. By modelling this variability, dust lifting is predicted at the locations at which dust storms are frequently observed, including the flushing storm sources of Chryse and Utopia, and southern midlatitude areas from which larger storms tend to initiate, such as Hellas and Solis Planum. The seasonal cycle of emission, which includes a double-peaked structure in northern autumn and winter, also appears realistic. Significant increases to lifting rates are produced for any sensible choices of parameters controlling the sub-grid distributions used, but results are sensitive to the smallest scale of variability considered, which high-resolution modelling suggests should be O(1 km) or less. Use of such models in future will permit the use of a diagnosed (rather than prescribed) variable gustiness intensity, which should further enhance dust lifting in the southern hemisphere in particular.

Influence of inherent structure shear stress of supercooled liquids on their shear moduli

Configurations of supercooled liquids residing in their local potential minimum (i.e. in their inherent structure, IS) were found to support a non-zero shear stress. This IS stress was attributed to the constraint to the energy minimization imposed by boundary conditions, which keep size and shape of the simulation cell fixed. In this paper we further investigate the influence of these boundary conditions on the IS stress. We investigate its importance for the computation of the low frequency shear modulus of a glass obtaining a consistent picture for the low- and high frequency shear moduli over the full temperature range. Hence, we find that the IS stress corresponds to a non-thermal contribution to the fluctuation term in the Born-Green expression. This leads to an unphysical divergence of the moduli in the low temperature limit if no proper correction for this term is applied. Furthermore, we clarify the IS stress dependence on the system size and put its origin on a more formal basis.

Long-term changes to the frequency of occurrence of British moths are consistent with opposing and synergistic effects of climate and land-use changes

1. Species’ distributions are likely to be affected by a combination of environmental drivers. We used a data set of 11 million species occurrence records over the period 1970–2010 to assess changes in the frequency of occurrence of 673 macro-moth species in Great Britain. Groups of species with different predicted sensitivities showed divergent trends, which we interpret in the context of land-use and climatic changes. 2. A diversity of responses was revealed: 260 moth species declined significantly, whereas 160 increased significantly. Overall, frequencies of occurrence declined, mirroring trends in less species-rich, yet more intensively studied taxa. 3. Geographically widespread species, which were predicted to be more sensitive to land use than to climate change, declined significantly in southern Britain, where the cover of urban and arable land has increased. 4. Moths associated with low nitrogen and open environments (based on their larval host plant characteristics) declined most strongly, which is also consistent with a land-use change explanation. 5. Some moths that reach their northern (leading edge) range limit in southern Britain increased, whereas species restricted to northern Britain (trailing edge) declined significantly, consistent with a climate change explanation. 6. Not all species of a given type behaved similarly, suggesting that complex interactions between species’ attributes and different combinations of environmental drivers determine frequency of occurrence changes. 7. Synthesis and applications. Our findings are consistent with large-scale responses to climatic and land-use changes, with some species increasing and others decreasing. We suggest that land-use change (e.g. habitat loss, nitrogen deposition) and climate change are both major drivers of moth biodiversity change, acting independently and in combination. Importantly, the diverse responses revealed in this species-rich taxon show that multifaceted conservation strategies are needed to minimize negative biodiversity impacts of multiple environmental changes. We suggest that habitat protection, management and ecological restoration can mitigate combined impacts of land-use change and climate change by providing environments that are suitable for existing populations and also enable species to shift their ranges.

On the ability of statistical wind-wave models to capture the variability and long-term trends of the North Atlantic winter wave climate

A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.

Upper-mantle seismic structure beneath SE and Central Brazil from P- and S-wave regional traveltime tomography

We present models for the upper-mantle velocity structure beneath SE and Central Brazil using independent tomographic inversions of P- and S-wave relative arrival-time residuals (including core phases) from teleseismic earthquakes. The events were recorded by a total of 92 stations deployed through different projects, institutions and time periods during the years 1992-2004. Our results show correlations with the main tectonic structures and reveal new anomalies not yet observed in previous works. All interpretations are based on robust anomalies, which appear in the different inversions for P-and S-waves. The resolution is variable through our study volume and has been analyzed through different theoretical test inversions. High-velocity anomalies are observed in the western portion of the Sao Francisco Craton, supporting the hypothesis that this Craton was part of a major Neoproterozoic plate (San Franciscan Plate). Low-velocity anomalies beneath the Tocantins Province (mainly fold belts between the Amazon and Sao Francisco Cratons) are interpreted as due to lithospheric thinning, which is consistent with the good correlation between intraplate seismicity and low-velocity anomalies in this region. Our results show that the basement of the Parana Basin is formed by several blocks, separated by suture zones, according to model of Milani & Ramos. The slab of the Nazca Plate can be observed as a high-velocity anomaly beneath the Parana Basin, between the depths of 700 and 1200 km. Further, we confirm the low-velocity anomaly in the NE area of the Parana Basin which has been interpreted by VanDecar et al. as a fossil conduct of the Tristan da Cunha Plume related to the Parana flood basalt eruptions during the opening of the South Atlantic.

Deep crustal structure of the Parana Basin from receiver functions and Rayleigh-wave dispersion: Evidence for a fragmented cratonic root

The deep crustal structure of the Parana Basin of southern Brazil is investigated by analyzing P- and PP-wave receiver functions at 17 Brazilian Lithosphere Seismic Project stations within the basin. The study area can be described as a typical Paleozoic intracratonic basin that hosts one of the largest Large Igneous Province of the world and makes a unique setting for investigating models of basin subsidence and their interaction with mantle plumes. Our study consists of (1) an analysis of the Moho interaction phases in the receiver functions to obtain the thickness and bulk Vp/Vs ratio of the basin`s underlying crust and (2) a joint inversion with Rayleigh-wave dispersion velocities from an independent tomographic study to delineate the detailed S-wave velocity variation with depth. The results of our analysis reveal that Moho depths and bulk Vp/Vs ratios (including sediments) vary between 41 and 48 km and between 1.70 and 1.76, respectively, with the largest values roughly coinciding with the basin`s axis, and that S-wave velocities in the lower crust are generally below 3.8 km/s. Select sites within the basin, however, show lower crustal S-wave velocities slightly above 3.9 km/s suggestive of underplated mafic material. We show that these observations are consistent with a fragmented cratonic root under the Parana basin that defined a zone of weakness for the initial Paleozoic subsidence of the basin and which allowed localized mafic underplating of the crust along the suture zones by Cenozoic magmatism.

Effects of long-term diabetes on the structure and cell proliferation of the myometrium in the early pregnancy of mice

P>It is known that the development of diabetic complications in human pregnancy is directly related to the severity and the duration of this pathology. In this study, we developed a model of long-term type 1 diabetes to investigate its effects on the cytoarchitecture, extracellular matrix and cell proliferation during the first adaptation phase of the myometrium for pregnancy. A single dose of alloxan was used to induce diabetes in mice prior to pregnancy. To identify the temporal effects of diabetes the mice were divided into two groups: Group D1 (females that became pregnant 90-100 days after alloxan); Group D2 (females that became pregnant 100-110 days after alloxan). Uterine samples were collected after 168 h of pregnancy and processed for light and electron microscopy. In both groups the histomorphometric evaluation showed that diabetes promoted narrowing of the myometrial muscle layers which was correlated with decreased cell proliferation demonstrated by PCNA immunodetection. In D1, diabetes increased the distance between muscle layers and promoted oedema. Contrarily, in D2 the distance between muscle layers decreased and, instead of oedema, there was a markedly deposition of collagen in the myometrium. Ultrastructural analysis showed that diabetes affects the organization of the smooth muscle cells and their myofilaments. Consistently, the immunoreaction for smooth muscle alpha-actin revealed clear disorganization of the contractile apparatus in both diabetic groups. In conclusion, the present model demonstrated that long-term diabetes promotes significant alterations in the myometrium in a time-sensitive manner. Together, these alterations indicate that diabetes impairs the first phenotypic adaptation phase of the pregnant myometrium.