52 resultados para panel data with spatial effects


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It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques.

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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.

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he construction market around the world has witnessed the growing eminence of construction professional services (CPSs), such as urban planning, architecture, engineering, and consultancy, while the traditional contracting sector remains strong. Nowadays, it is not uncommon to see a design firm taking over the work of a traditional main contractor, or vice versa, of overseeing the delivery of a project. Although the two sectors of contracting and CPS share the same purpose of materializing the built environment, they are as different as they are interrelated. Much has been mentioned about the nexus between the two but little has been done to articulate it using empirical evidence. This study examined the nexus between contracting and CPS businesses by offering and testing lead-lag effects between the two sectors in the international market. A longitudinal panel data composed of 23 top international contractors and CPS firms was adopted. Surprisingly, results of the panel data analyses show that CPS business does not have a significant positive causal effect on contracting as a downstream business, and vice versa. CPS and contracting subsidiaries, although within the same company, do not necessarily form a consortium to undertake the same project; rather, they often collaborate with other CPS or contracting counterparts to undertake projects. This paper provides valuable insights into the sophisticated nexus between contracting and CPS in the international construction market. It will support business executives’ rational decision making for selecting proper contracting or CPS allies, or a proper mergers and acquisitions strategy in the international market. The paper also provides a fresh perspective through which researchers can better investigate the diversification strategies adopted by international contracting and CPS firms.

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In this paper we address two topical questions: How do the quality of governance and agricultural intensification impact on spatial expansion of agriculture? Which aspects of governance are more likely to ensure that agricultural intensification allows sparing land for nature? Using data from the Food and Agriculture Organization, the World Bank, the World Database on Protected Areas, and the Yale Center for Environmental Law and Policy, we estimate a panel data model for six South American countries and quantify the effects of major determinants of agricultural land expansion, including various dimensions of governance, over the period 1970–2006. The results indicate that the effect of agricultural intensification on agricultural expansion is conditional on the quality and type of governance. When considering conventional aspects of governance, agricultural intensification leads to an expansion of agricultural area when governance scores are high. When looking specifically at environmental aspects of governance, intensification leads to a spatial contraction of agriculture when governance scores are high, signaling a sustainable intensification process.

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Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

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The polynyas of the Laptev Sea are regions of particular interest due to the strong formation of Arctic sea-ice. In order to simulate the polynya dynamics and to quantify ice production, we apply the Finite Element Sea-Ice Ocean Model FESOM. In previous simulations FESOM has been forced with daily atmospheric NCEP (National Centers for Environmental Prediction) 1. For the periods 1 April to 9 May 2008 and 1 January to 8 February 2009 we examine the impact of different forcing data: daily and 6-hourly NCEP reanalyses 1 (1.875° x 1.875°), 6-hourly NCEP reanalyses 2 (1.875° x 1.875°), 6-hourly analyses from the GME (Global Model of the German Weather Service) (0.5° x 0.5°) and high-resolution hourly COSMO (Consortium for Small-Scale Modeling) data (5 km x 5 km). In all FESOM simulations, except for those with 6-hourly and daily NCEP 1 data, the openings and closings of polynyas are simulated in principle agreement with satellite products. Over the fast-ice area the wind fields of all atmospheric data are similar and close to in situ measurements. Over the polynya areas, however, there are strong differences between the forcing data with respect to air temperature and turbulent heat flux. These differences have a strong impact on sea-ice production rates. Depending on the forcing fields polynya ice production ranges from 1.4 km3 to 7.8 km3 during 1 April to 9 May 2011 and from 25.7 km3 to 66.2 km3 during 1 January to 8 February 2009. Therefore, atmospheric forcing data with high spatial and temporal resolution which account for the presence of the polynyas are needed to reduce the uncertainty in quantifying ice production in polynyas.

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Field observations of new particle formation and the subsequent particle growth are typically only possible at a fixed measurement location, and hence do not follow the temporal evolution of an air parcel in a Lagrangian sense. Standard analysis for determining formation and growth rates requires that the time-dependent formation rate and growth rate of the particles are spatially invariant; air parcel advection means that the observed temporal evolution of the particle size distribution at a fixed measurement location may not represent the true evolution if there are spatial variations in the formation and growth rates. Here we present a zero-dimensional aerosol box model coupled with one-dimensional atmospheric flow to describe the impact of advection on the evolution of simulated new particle formation events. Wind speed, particle formation rates and growth rates are input parameters that can vary as a function of time and location, using wind speed to connect location to time. The output simulates measurements at a fixed location; formation and growth rates of the particle mode can then be calculated from the simulated observations at a stationary point for different scenarios and be compared with the ‘true’ input parameters. Hence, we can investigate how spatial variations in the formation and growth rates of new particles would appear in observations of particle number size distributions at a fixed measurement site. We show that the particle size distribution and growth rate at a fixed location is dependent on the formation and growth parameters upwind, even if local conditions do not vary. We also show that different input parameters used may result in very similar simulated measurements. Erroneous interpretation of observations in terms of particle formation and growth rates, and the time span and areal extent of new particle formation, is possible if the spatial effects are not accounted for.