Natural disaster accounting bias and its equivalence across genetic resource stocks

Two sources of bias arise in conventional loss predictions in the wake of natural disasters. One source of bias stems from neglect of accounting for animal genetic resource loss. A second source of bias stems from failure to identify, in addition to the direct effects of such loss, the indirect effects arising from implications impacting animal-human interactions. We argue that, in some contexts, the magnitude of bias imputed by neglecting animal genetic resource stocks is substantial. We show, in addition, and contrary to popular belief, that the biases attributable to losses in distinct genetic resource stocks are very likely to be the same. We derive the formal equivalence across the distinct resource stocks by deriving an envelope result in a model that forms the mainstay of enquiry in subsistence farming and we validate the theory, empirically, in a World-Society-for-the-Protection-of-Animals application

Competing for attentional priority: temporary goals versus threats

Numerous studies have shown that attention is biased toward threatening events. More recent evidence has also found attentional biases for stimuli that are relevant to the current and temporary goals of an individual. We examined whether goal-relevant information still evokes an attentional bias when this information competes with threatening events. In three experiments, participants performed a dot probe task combined with a separate task that induced a temporary goal. The results of Experiment 1 showed that attention was oriented to goal-relevant pictures in the dot probe task when these pictures were simultaneously presented with neutral or threatening pictures. Whether goal-relevant pictures themselves were threatening or neutral did not influence the results. Experiment 2 replicated these findings in a sample of highly trait-anxious participants. Experiment 3 showed that attention was automatically deployed to stimuli relevant to a temporary goal even in the presence of stimuli that signal imminent and genuine threat (i.e., a colored patch signaling the presentation of an aversive noise). These findings further corroborate the conclusion that an individual's current and temporary goals guide early attentional processes

Broadly speaking: vocabulary in semantic dementia shifts towards general, semantically diverse words

One of the cardinal features of semantic dementia (SD) is a steady reduction in expressive vocabulary. We investigated the nature of this breakdown by assessing the psycholinguistic characteristics of words produced spontaneously by SD patients during an autobiographical memory interview. Speech was analysed with respect to frequency and imageability, and a recently-developed measure called semantic diversity. This measure quantifies the degree to which a word can be used in a broad range of different linguistic contexts. We used this measure in a formal exploration of the tendency for SD patients to replace specific terms with more vague and general words, on the assumption that more specific words are used in a more constrained set of contexts. Relative to healthy controls, patients were less likely to produce low-frequency, high-imageability words, and more likely to produce highly frequent, abstract words. These changes in the lexical-semantic landscape were related to semantic diversity: the highly frequent and abstract words most prevalent in the patients' speech were also the most semantically diverse. In fact, when the speech samples of healthy controls were artificially engineered such that low semantic diversity words (e.g., garage, spanner) were replaced with broader terms (e.g., place, thing), the characteristics of their speech production came to closely resemble that of SD patients. A similar simulation in which low-frequency words were replaced was less successful in replicating the patient data. These findings indicate systematic biases in the deterioration of lexical-semantic space in SD. As conceptual knowledge degrades, speech increasingly consists of general terms that can be applied in a broad range of linguistic contexts and convey less specific information.

Forecasting by factors, by variables, by both or neither?

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for nowcasting or short-term forecasting, but their relative performance declines as the forecast horizon increases. Forecasts for GDP levels highlight the need for robust strategies, such as intercept corrections or differencing, when location shifts occur as in the recent financial crisis.

Analysis of precipitation climatology simulated by high resolution coupled global models over the South America

The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

Improved evaporative flux partitioning and carbon flux in the land surface model JULES: impact on the simulation of land surface processes in temperate Europe

The primary role of land surface models embedded in climate models is to partition surface available energy into upwards, radiative, sensible and latent heat fluxes. Partitioning of evapotranspiration, ET, is of fundamental importance: as a major component of the total surface latent heat flux, ET affects the simulated surface water balance, and related energy balance, and consequently the feedbacks with the atmosphere. In this context it is also crucial to credibly represent the CO2 exchange between ecosystems and their environment. In this study, JULES, the land surface model used in UK weather and climate models, has been evaluated for temperate Europe. Compared to eddy covariance flux measurements, the CO2 uptake by the ecosystem is underestimated and the ET overestimated. In addition, the contribution to ET from soil and intercepted water evaporation far outweighs the contribution of plant transpiration. To alleviate these biases, adaptations have been implemented in JULES, based on key literature references. These adaptations have improved the simulation of the spatio-temporal variability of the fluxes and the accuracy of the simulated GPP and ET, including its partitioning. This resulted in a shift of the seasonal soil moisture cycle. These adaptations are expected to increase the fidelity of climate simulations over Europe. Finally, the extreme summer of 2003 was used as evaluation benchmark for the use of the model in climate change studies. The improved model captures the impact of the 2003 drought on the carbon assimilation and the water use efficiency of the plants. It, however, underestimates the 2003 GPP anomalies. The simulations showed that a reduction of evaporation from the interception and soil reservoirs, albeit not of transpiration, largely explained the good correlation between the carbon and the water fluxes anomalies that was observed during 2003. This demonstrates the importance of being able to discriminate the response of individual component of the ET flux to environmental forcing.

Comparison of D-region Doppler drift winds measured by the SuperDARN Finland HF radar over an annual cycle using the Kiruna VHF meteor radar

The SuperDARN chain of oblique HF radars has provided an opportunity to generate a unique climatology of horizontal winds near the mesopause at a number of high latitude locations, via the Doppler shifted echoes from sources of ionisation in the D-region. Ablating meteor trails form the bulk of these targets, but other phenomena also contribute to the observations. Due to the poor vertical resolution of the radars, care must be taken to reduce possible biases from sporadic-E layers and Polar Mesospheric Summer echoes that can affect the effective altitude of the geophysical parameters being observed. Second, there is strong theoretical and observational evidence to suggest that the radars are picking up echoes from the backward looking direction that will tend to reduce the measured wind strengths. The effect is strongly frequency dependent, resulting in a 20% reduction at 12 MHz and a 50% reduction at 10 MHz. A comparison of the climatologies observed by the Super-DARN Finland radar between September 1999 and September 2000 and that obtained from the adjacent VHF meteor radar located at Kiruna is also presented. The agreement between the two instruments was very good. Extending the analysis to the SuperDARN Iceland East radar indicated that the principles outlined above could be applied successfully to the rest of the SuperDARN network.

The ability of CMIP5 models to simulate North Atlantic extratropical cyclones

The ability of the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to simulate North Atlantic extratropical cyclones in winter [December–February (DJF)] and summer [June–August (JJA)] is investigated in detail. Cyclones are identified as maxima in T42 vorticity at 850 hPa and their propagation is tracked using an objective feature-tracking algorithm. By comparing the historical CMIP5 simulations (1976–2005) and the ECMWF Interim Re-Analysis (ERA-Interim; 1979–2008), the authors find that systematic biases affect the number and intensity of North Atlantic cyclones in CMIP5 models. In DJF, the North Atlantic storm track tends to be either too zonal or displaced southward, thus leading to too few and weak cyclones over the Norwegian Sea and too many cyclones in central Europe. In JJA, the position of the North Atlantic storm track is generally well captured but some CMIP5 models underestimate the total number of cyclones. The dynamical intensity of cyclones, as measured by either T42 vorticity at 850 hPa or mean sea level pressure, is too weak in both DJF and JJA. The intensity bias has a hemispheric character, and it cannot be simply attributed to the representation of the North Atlantic large- scale atmospheric state. Despite these biases, the representation of Northern Hemisphere (NH) storm tracks has improved since CMIP3 and some CMIP5 models are able of representing well both the number and the intensity of North Atlantic cyclones. In particular, some of the higher-atmospheric-resolution models tend to have a better representation of the tilt of the North Atlantic storm track and of the intensity of cyclones in DJF.

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin.

Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

Vertical distribution and radiative effects of mineral dust and biomass burning aerosol over West Africa during DABEX

This paper presents measurements of the vertical distribution of aerosol extinction coefficient over West Africa during the Dust and Biomass-burning Aerosol Experiment (DABEX)/African Monsoon Multidisciplinary Analysis dry season Special Observing Period Zero (AMMA-SOP0). In situ aircraft measurements from the UK FAAM aircraft have been compared with two ground-based lidars (POLIS and ARM MPL) and an airborne lidar on an ultralight aircraft. In general, mineral dust was observed at low altitudes (up to 2 km), and a mixture of biomass burning aerosol and dust was observed at altitudes of 2–5 km. The study exposes difficulties associated with spatial and temporal variability when intercomparing aircraft and ground measurements. Averaging over many profiles provided a better means of assessing consistent errors and biases associated with in situ sampling instruments and retrievals of lidar ratios. Shortwave radiative transfer calculations and a 3-year simulation with the HadGEM2-A climate model show that the radiative effect of biomass burning aerosol was somewhat sensitive to the vertical distribution of aerosol. In particular, when the observed low-level dust layer was included in the model, the absorption of solar radiation by the biomass burning aerosols increased by 10%. We conclude that this absorption enhancement was caused by the dust reflecting solar radiation up into the biomass burning aerosol layer. This result illustrates that the radiative forcing of anthropogenic absorbing aerosol can be sensitive to the presence of natural aerosol species.

Explicit and implicit subject bias in the ABS journal quality guide

This paper addresses issues raised in two recent papers published in this journal about the UK Association of Business Schools' Journal Quality Guide (ABS Guide). While much of the debate about journal rankings in general, and the ABS Guide in particular, has focused on the construction, power and (mis)use of these rankings, this paper differs in that it explains and provides evidence about explicit and implicit biases in the ABS Guide. In so doing, it poses potentially difficult questions that the editors of the ABS Guide need to address and urgently rectify if the ABS Guide seeks to build and retain legitimacy. In particular, the evidence in this paper shows explicit bias in the ABS Guide against several subject areas, including accounting and finance. It also shows implicit bias against accounting and finance when comparing journal rankings in sub-areas shared between accounting and finance and the broader business management subject areas.

The sensitivity of the tropical circulation and Maritime Continent precipitation to climate model resolution

The dependence of the annual mean tropical precipitation on horizontal resolution is investigated in the atmospheric version of the Hadley Centre General Environment Model (HadGEM1). Reducing the grid spacing from about 350 km to 110 km improves the precipitation distribution in most of the tropics. In particular, characteristic dry biases over South and Southeast Asia including the Maritime Continent as well as wet biases over the western tropical oceans are reduced. The annual-mean precipitation bias is reduced by about one third over the Maritime Continent and the neighbouring ocean basins associated with it via the Walker circulation. Sensitivity experiments show that much of the improvement with resolution in the Maritime Continent region is due to the specification of better resolved surface boundary conditions (land fraction, soil and vegetation parameters) at the higher resolution. It is shown that in particular the formulation of the coastal tiling scheme may cause resolution sensitivity of the mean simulated climate. The improvement in the tropical mean precipitation in this region is not primarily associated with the better representation of orography at the higher resolution, nor with changes in the eddy transport of moisture. Sizeable sensitivity to changes in the surface fields may be one of the reasons for the large variation of the mean tropical precipitation distribution seen across climate models.

Forecasting with difference and trend stationary models

Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.

Serial clustering of extratropical cyclones over the North Atlantic and Europe under recent and future climate conditions

Under particular large-scale atmospheric conditions, several windstorms may affect Europe within a short time period. The occurrence of such cyclone families leads to large socioeconomic impacts and cumulative losses. The serial clustering of windstorms is analyzed for the North Atlantic/western Europe. Clustering is quantified as the dispersion (ratio variance/mean) of cyclone passages over a certain area. Dispersion statistics are derived for three reanalysis data sets and a 20-run European Centre Hamburg Version 5 /Max Planck Institute Version–Ocean Model Version 1 global climate model (ECHAM5/MPI-OM1 GCM) ensemble. The dependence of the seriality on cyclone intensity is analyzed. Confirming previous studies, serial clustering is identified in reanalysis data sets primarily on both flanks and downstream regions of the North Atlantic storm track. This pattern is a robust feature in the reanalysis data sets. For the whole area, extreme cyclones cluster more than nonextreme cyclones. The ECHAM5/MPI-OM1 GCM is generally able to reproduce the spatial patterns of clustering under recent climate conditions, but some biases are identified. Under future climate conditions (A1B scenario), the GCM ensemble indicates that serial clustering may decrease over the North Atlantic storm track area and parts of western Europe. This decrease is associated with an extension of the polar jet toward Europe, which implies a tendency to a more regular occurrence of cyclones over parts of the North Atlantic Basin poleward of 50°N and western Europe. An increase of clustering of cyclones is projected south of Newfoundland. The detected shifts imply a change in the risk of occurrence of cumulative events over Europe under future climate conditions.