Estimating surface CO2 fluxes from space-borne dry air mole fraction observations using an Ensemble Kalman filter

We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Understanding African easterly waves: a moist singular vector approach

Moist singular vectors (MSV) have been applied successfully to predicting mid-latitude storms growing in association with latent heat of condensation. Tropical cyclone sensitivity has also been assessed. Extending this approach to more general tropical weather systems here, MSVs are evaluated for understanding and predicting African easterly waves, given the importance of moist processes in their development. First results, without initial moisture perturbations, suggest MSVs may be used advantageously. Perturbations bear similar structural and energy profiles to previous idealised non-linear studies and observations. Strong sensitivities prevail in the metrics and trajectories chosen, and benefits of initial moisture perturbations should be appraised. Copyright © 2009 Royal Meteorological Society

Health Benefits of Organic Food: effects of the environment

Public concern over impacts of chemicals in plant and animal production on health and the environment has led to increased demand for organic produce, which is usually promoted and often perceived as containing fewer contaminants, more nutrients, and being positive for the environment. These benefits are difficult to quantify, and potential environmental impacts on such benefits have not been widely studied. This book addresses these key points, examining factors such as the role of certain nutrients in prevention and promotion of chronic disease, potential health benefits of bioactive compounds in plants, the prevalence of food-borne pesticides and pathogens and how both local and global environmental factors may affect any differences between organic and conventionally produced food. This book is an essential resource for researchers and students in human health and nutrition, environmental science, agriculture and organic farming. Main Contents 1. Organic farming and food systems: definitions and key characteristics. 2. The health benefits of n-3 fatty acids and their concentrations in organic and conventional animal-derived foods. 3. Environmental impacts on n-3 content of foods from ruminant animals. 4. Health benefits and selenium content of organic vs conventional foods. 5. Environmental impacts concerning the selenium content of foods. 6. Contaminants in organic and conventional food: the missing link between contaminant levels and health effects. 7. Mycotoxins in organic and conventional foods and effects of the environment. 8. Human pathogens in organic and conventional foods and effects of the environment. 9. What does consumer science tell us about organic foods? 10. The beneficial effects of dietary flavonoids: sources, bioavailability and biological functions. 11. Environmental regulation of flavonoid biosynthesis. 12. Nitrates in the human diet. 13. Impacts of environment and management on nitrate in vegetables and water. 14. Effects of the environment on the nutritional quality and safety of organically produced foods: Round-up and summary.

A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems

The extent to which the four-dimensional variational data assimilation (4DVAR) is able to use information about the time evolution of the atmosphere to infer the vertical spatial structure of baroclinic weather systems is investigated. The singular value decomposition (SVD) of the 4DVAR observability matrix is introduced as a novel technique to examine the spatial structure of analysis increments. Specific results are illustrated using 4DVAR analyses and SVD within an idealized 2D Eady model setting. Three different aspects are investigated. The first aspect considers correcting errors that result in normal-mode growth or decay. The results show that 4DVAR performs well at correcting growing errors but not decaying errors. Although it is possible for 4DVAR to correct decaying errors, the assimilation of observations can be detrimental to a forecast because 4DVAR is likely to add growing errors instead of correcting decaying errors. The second aspect shows that the singular values of the observability matrix are a useful tool to identify the optimal spatial and temporal locations for the observations. The results show that the ability to extract the time-evolution information can be maximized by placing the observations far apart in time. The third aspect considers correcting errors that result in nonmodal rapid growth. 4DVAR is able to use the model dynamics to infer some of the vertical structure. However, the specification of the case-dependent background error variances plays a crucial role.

A singular vector perspective of 4D-Var: Filtering and interpolation

Four-dimensional variational data assimilation (4D-Var) combines the information from a time sequence of observations with the model dynamics and a background state to produce an analysis. In this paper, a new mathematical insight into the behaviour of 4D-Var is gained from an extension of concepts that are used to assess the qualitative information content of observations in satellite retrievals. It is shown that the 4D-Var analysis increments can be written as a linear combination of the singular vectors of a matrix which is a function of both the observational and the forecast model systems. This formulation is used to consider the filtering and interpolating aspects of 4D-Var using idealized case-studies based on a simple model of baroclinic instability. The results of the 4D-Var case-studies exhibit the reconstruction of the state in unobserved regions as a consequence of the interpolation of observations through time. The results also exhibit the filtering of components with small spatial scales that correspond to noise, and the filtering of structures in unobserved regions. The singular vector perspective gives a very clear view of this filtering and interpolating by the 4D-Var algorithm and shows that the appropriate specification of the a priori statistics is vital to extract the largest possible amount of useful information from the observations. Copyright © 2005 Royal Meteorological Society

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Understanding the alphaviruses: Recent research on important emerging pathogens and progress towards their control

The alphaviruses were amongst the first arboviruses to be isolated, characterized and assigned a taxonomic status. They are globally very widespread, infecting a large variety of terrestrial animals, insects and even fish, and circulate both in the sylvatic and urban/peri-urban environment, causing considerable human morbidity and mortality. Nevertheless, despite their obvious importance as pathogens, there are currently no effective antiviral drugs with which to treat humans or animals infected by any of these viruses. The EU-supported project—VIZIER (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 Project: 2004-511960) was instigated with an ultimate view of contributing to the development of antiviral therapies for RNA viruses, including the alphaviruses [Coutard, B., Gorbalenya, A.E., Snijder, E.J., Leontovich, A.M., Poupon, A., De Lamballerie, X., Charrel, R., Gould, E.A., Gunther, S., Norder, H., Klempa, B., Bourhy, H., Rohayemj, J., L’hermite, E., Nordlund, P., Stuart, D.I., Owens, R.J., Grimes, J.M., Tuckerm, P.A., Bolognesi, M., Mattevi, A., Coll, M., Jones, T.A., Åqvist, J., Unger, T., Hilgenfeld, R., Bricogne, G., Neyts, J., La Colla, P., Puerstinger, G., Gonzalez, J.P., Leroy, E., Cambillau, C., Romette, J.L., Canard, B., 2008. The VIZIER project: preparedness against pathogenic RNA viruses. Antiviral Res. 78, 37–46]. This review highlights some of the major features of alphaviruses that have been investigated during recent years. After describing their classification, epidemiology and evolutionary history and the expanding geographic distribution of Chikungunya virus, we review progress in understanding the structure and function of alphavirus replicative enzymes achieved under the VIZIER programme and the development of new disease control strategies.

Plant pathogens as suppressors of host defense

This chapter reviews our current knowledge about mechanisms of suppression developed by pathogens to avoid host defense responses. In general, plants perceive pathogens by diverse pathogen- or microbe- or even damage-associated molecular patterns (PAMPs, MAMPs, DAMPs) and induce a variety of defense mechanisms referred to as horizontal or basal resistance, nowadays designated PAMP-triggered immunity (PTI). In addition, plants can also recognize specific pathogen-derived effectors and have derived a highly specific defense response termed effector-triggered immunity (ETI), classically called R gene-mediated, specific or vertical resistance. Both PTI and ETI are responses to potential dangers and have common components. Fungal, oomycete, and bacterial pathogens have evolved various effector-based mechanisms of suppression that interfere with such components. Plants strongly depend on RNA gene silencing to interfere with viral pathogens. Plant viruses counteract this response by encoding suppressor proteins of RNA silencing.

CD8+ T-cells mediate immunopathology in tick-borne encephalitis

Epidemics of tick-borne encephalitis involving thousands of humans occur annually in the forested regions of Europe and Asia. Despite the importance of this disease, the underlying basis for the development of encephalitis remains undefined. Here, we prove the key role of CD8(+) T-cells in the immunopathology of tick-borne encephalitis, as demonstrated by prolonged survival of SCID or CD8(-/-) mice, following infection, when compared with immunocompetent mice or mice with adoptively transferred CD8(+) T-cells. The results imply that tick-borne encephalitis is an immunopathological disease and that the inflammatory reaction significantly contributes to the fatal outcome of the infection. (C) 2008 Elsevier Inc. All rights reserved.

Mutations in the NS2B and NS3 genes affect mouse neuroinvasiveness of a Western European field strain of tick-borne encephalitis virus

An attenuated strain (263) of the tick-borne encephalitis virus, isolated from field ticks, was either serially subcultured, 5 times in mice, or at 40 degrees C in PS cells, producing 2 independent strains, 263-m5 and 263-TR with identical genomes; both strains exhibited increased plaque size, neuroinvasiveness and temperature-resistance. Sequencing revealed two unique amino acid substitutions, one mapping close to the catalytic site of the viral protease. These observations imply that virus adaptation from ticks to mammals occurs by selection of pre-existing virulent variants from the quasispecies population rather than by the emergence of new random mutations. The significance of these observations is discussed. (c) 2008 Elsevier Inc. All rights reserved.

The population dynamical consequences of density-dependence in fungal plant pathogens

Almost all stages of a plant pathogen life cycle are potentially density dependent. At small scales and short time spans appropriate to a single-pathogen individual, density dependence can be extremely strong, mediated both by simple resource use, changes in the host due to defence reactions and signals between fungal individuals. In most cases, the consequences are a rise in reproductive rate as the pathogen becomes rarer, and consequently stabilisation of the population dynamics; however, at very low density reproduction may become inefficient, either because it is co-operative or because heterothallic fungi do not form sexual spores. The consequence will be historically determined distributions. On a medium scale, appropriate for example to several generations of a host plant, the factors already mentioned remain important but specialist natural enemies may also start to affect the dynamics detectably. This could in theory lead to complex (e.g. chaotic) dynamics, but in practice heterogeneity of habitat and host is likely to smooth the extreme relationships and make for more stable, though still very variable, dynamics. On longer temporal and longer spatial scales evolutionary responses by both host and pathogen are likely to become important, producing patterns which ultimately depend on the strength of interactions at smaller scales.