Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6 % of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanket-bog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland, Wales and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre-Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland, and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

A joint state and parameter estimation scheme for nonlinear dynamical systems

We present a novel algorithm for concurrent model state and parameter estimation in nonlinear dynamical systems. The new scheme uses ideas from three dimensional variational data assimilation (3D-Var) and the extended Kalman filter (EKF) together with the technique of state augmentation to estimate uncertain model parameters alongside the model state variables in a sequential filtering system. The method is relatively simple to implement and computationally inexpensive to run for large systems with relatively few parameters. We demonstrate the efficacy of the method via a series of identical twin experiments with three simple dynamical system models. The scheme is able to recover the parameter values to a good level of accuracy, even when observational data are noisy. We expect this new technique to be easily transferable to much larger models.

Southern Ocean isopycnal mixing and ventilation changes driven by winds

Observed and predicted changes in the strength of the westerly winds blowing over the Southern Ocean have motivated a number of studies of the response of the Antarctic Circumpolar Current and Southern Ocean Meridional Overturning Circulation (MOC) to wind perturbations and led to the discovery of the``eddy-compensation" regime, wherein the MOC becomes insensitive to wind changes. In addition to the MOC, tracer transport also depends on mixing processes. Here we show, in a high-resolution process model, that isopycnal mixing by mesoscale eddies is strongly dependent on the wind strength. This dependence can be explained by mixing-length theory and is driven by increases in eddy kinetic energy; the mixing length does not change strongly in our simulation. Simulation of a passive ventilation tracer (analogous to CFCs or anthropogenic CO$_2$) demonstrates that variations in tracer uptake across experiments are dominated by changes in isopycnal mixing, rather than changes in the MOC. We argue that, to properly understand tracer uptake under different wind-forcing scenarios, the sensitivity of isopycnal mixing to winds must be accounted for.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6% of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanketbog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts that large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland,Wales, and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre- Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model

Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean–sea ice model. The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover. Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.

Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates.

The role of CO2 and dynamic vegetation on the impact of temperate land use change in the HadCM3 coupled climate model

Human induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2 yet present day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modelling the impact of LUC needs to accurately simulate CO2 driven changes in precipitation and snowfall, and incorporate accurate, dynamic vegetation distribution.

A low mortality, high morbidity reduced intensity status epilepticus (RISE) model of epilepsy and epileptogenesis in the rat

Animal models of acquired epilepsies aim to provide researchers with tools for use in understanding the processes underlying the acquisition, development and establishment of the disorder. Typically, following a systemic or local insult, vulnerable brain regions undergo a process leading to the development, over time, of spontaneous recurrent seizures. Many such models make use of a period of intense seizure activity or status epilepticus, and this may be associated with high mortality and/or global damage to large areas of the brain. These undesirable elements have driven improvements in the design of chronic epilepsy models, for example the lithium-pilocarpine epileptogenesis model. Here, we present an optimised model of chronic epilepsy that reduces mortality to 1% whilst retaining features of high epileptogenicity and development of spontaneous seizures. Using local field potential recordings from hippocampus in vitro as a probe, we show that the model does not result in significant loss of neuronal network function in area CA3 and, instead, subtle alterations in network dynamics appear during a process of epileptogenesis, which eventually leads to a chronic seizure state. The model’s features of very low mortality and high morbidity in the absence of global neuronal damage offer the chance to explore the processes underlying epileptogenesis in detail, in a population of animals not defined by their resistance to seizures, whilst acknowledging and being driven by the 3Rs (Replacement, Refinement and Reduction of animal use in scientific procedures) principles.

Evaluation of moisture sources for the Central European summer flood of May/June 2013 based on regional climate model simulations

Heavy precipitation affected Central Europe in May/June 2013, triggering damaging floods both on the Danube and the Elbe rivers. Based on a modelling approach with COSMO-CLM, moisture fluxes, backward trajectories, cyclone tracks and precipitation fields are evaluated for the relevant time period 30 May–2 June 2013. We identify potential moisture sources and quantify their contribution to the flood event focusing on the Danube basin through sensitivity experiments: Control simulations are performed with undisturbed ERA-Interim boundary conditions, while multiple sensitivity experiments are driven with modified evaporation characteristics over selected marine and land areas. Two relevant cyclones are identified both in reanalysis and in our simulations, which moved counter-clockwise in a retrograde path from Southeastern Europe over Eastern Europe towards the northern slopes of the Alps. The control simulations represent the synoptic evolution of the event reasonably well. The evolution of the precipitation event in the control simulations shows some differences in terms of its spatial and temporal characteristics compared to observations. The main precipitation event can be separated into two phases concerning the moisture sources. Our modelling results provide evidence that the two main sources contributing to the event were the continental evapotranspiration (moisture recycling; both phases) and the North Atlantic Ocean (first phase only). The Mediterranean Sea played only a minor role as a moisture source. This study confirms the importance of continental moisture recycling for heavy precipitation events over Central Europe during the summer half year.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multi-model study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3)

The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant–Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant–Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

The Bone Formation Capabilities of the Anorganic Bone Matrix-Synthetic Cell-Binding Peptide 15 Grafts in an Animal Periodontal Model: A Histologic and Histomorphometric Study in Dogs

Background: The aim of this study is to verify the regenerative potential of particulate anorganic bone matrix synthetic peptide-15 (ABM-P-15) in class III furcation defects associated or not with expanded polytetrafluoroethylene membranes. Methods: Class III furcation defects were produced in the mandibular premolars (P2, P3, and P4) of six dogs and filled with impression material. The membranes and the bone grafts were inserted into P3 and P4, which were randomized to form the test and control groups, respectively; P2 was the negative control group. The animals were sacrificed 3 months post-treatment. Results: Histologically, the complete closure of class III furcation defects was not observed in any of the groups. Partial periodontal regeneration with similar morphologic characteristics among the groups was observed, however, through the formation of new cementum, periodontal ligament, and bone above the notch. Histologic analysis showed granules from the bone graft surrounded by immature bone matrix and encircled by newly formed tissue in the test group. The new bone formation area found in the negative control group was 2.28 +/- 2.49 mm(2) and in the test group it was 6.52 +/- 5.69 mm(2), which showed statistically significant differences for these groups considering this parameter (Friedman test P <0.05). There was no statistically significant difference among the negative control, control, and test groups for the other parameters. Conclusions: The regenerative potential of ABM-P-15 was demonstrated through new bone formation circumscribing and above the graft particles. The new bone also was accompanied by the formation of new cementum and periodontal ligament fibers. J Periodontol 2010;81:594-603.

A METHOD FOR THE STUDY OF ACCRETION DISK EMISSION IN CATACLYSMIC VARIABLES. I. THE MODEL

We have developed a spectrum synthesis method for modeling the ultraviolet (UV) emission from the accretion disk from cataclysmic variables (CVs). The disk is separated into concentric rings, with an internal structure from the Wade & Hubeny disk-atmosphere models. For each ring, a wind atmosphere is calculated in the comoving frame with a vertical velocity structure obtained from a solution of the Euler equation. Using simple assumptions, regarding rotation and the wind streamlines, these one-dimensional models are combined into a single 2.5-dimensional model for which we compute synthetic spectra. We find that the resulting line and continuum behavior as a function of the orbital inclination is consistent with the observations, and verify that the accretion rate affects the wind temperature, leading to corresponding trends in the intensity of UV lines. In general, we also find that the primary mass has a strong effect on the P Cygni absorption profiles, the synthetic emission line profiles are strongly sensitive to the wind temperature structure, and an increase in the mass-loss rate enhances the resonance line intensities. Synthetic spectra were compared with UV data for two high orbital inclination nova-like CVs-RW Tri and V347 Pup. We needed to include disk regions with arbitrary enhanced mass loss to reproduce reasonably well widths and line profiles. This fact and a lack of flux in some high ionization lines may be the signature of the presence of density-enhanced regions in the wind, or alternatively, may result from inadequacies in some of our simplifying assumptions.

CMB and LSS constraints on a single-field model of inflation

A new inflationary scenario whose exponential potential V (Phi) has a quadratic dependence on the field Phi in addition to the standard linear term is confronted with the five-year observations of the Wilkinson-Microwave Anisotropy Probe and the Sloan Digital Sky Survey data. The number of e-folds (N), the ratio of tensor-to-scalar perturbations (r), the spectral scalar index of the primordial power spectrum (n(s)) and its running (dn(s)/d ln k) depend on the dimensionless parameter a multiplying the quadratic term in the potential. In the limit a. 0 all the results of the exponential potential are fully recovered. For values of alpha not equal 0, we find that the model predictions are in good agreement with the current observations of the Cosmic Microwave Background (CMB) anisotropies and Large-Scale Structure (LSS) in the Universe. Copyright (C) EPLA, 2008.

A simplified approach for Chaplygin-type cosmologies

A new class of accelerating cosmological models driven by a one-parameter version of the general Chaplygin-type equation of state is proposed. The simplified version is naturally obtained from causality considerations with basis on the adiabatic sound speed vs plus the observed accelerating stage of the universe. We show that very stringent constraints on the unique free parameter a describing the simplified Chaplygin model can be obtained from a joint analysis involving the latest SNe type la data and the recent Sloan Digital Sky Survey measurement of baryon acoustic oscillations (BAO). In our analysis we have considered separately the SNe type la gold sample measured by [A.G. Riess et al.. Astrophys. J. 607 (2004) 665] and the supernova legacy survey (SNLS) from [P. Astier et al., Astron. Astrophys. 447 (2006) 31]. At 95.4% (c.l.), we find for BAO + gold sample, 0.91 <= alpha <= 1.0 and Omega(m) = 0.28(-0.048)(+0.043) while BAO + SNLS analysis provides 0.94 <= alpha <= 1.0 and Omega(m) = 0.27(-0.045)(+0.048). (C) 2008 Elsevier B.V. All rights reserved.