Estimated energy balance in the jovian upper atmosphere during an auroral heating event

We present an analysis of a series of observations of the auroral/polar regions of Jupiter, carried out between September 8 and 11, 1998, making use of the high-resolution spectrometer, CSHELL, on the NASA InfraRed Telescope Facility (IRTF), Mauna Kea, Hawaii; these observations spanned an “auroral heating event.” This analysis combines the measured line intensities and ion velocities with a one-dimensional model vertical profile of the jovian thermosphere/ionosphere. We compute the model line intensities both assuming local thermodynamic equilibrium (LTE) and, relaxing this condition (non-LTE), through detailed balance calculations, in order to compare with the observations. Taking the model parameters derived, we calculate the changes in heating rate required to account for the modelled temperature profiles that are consistent with the measured line intensities. We compute the electron precipitation rates required to give the modelled ion densities that are consistent with the measured line intensities, and derive the corresponding Pedersen conductivities. We compute the changes in heating due to Joule heating and ion drag derived from the measured ion velocities, and modelled conductivities, making use of ion-neutral coupling coefficients derived from a 3-D global circulation model. Finally, we compute the cooling due to the downward conduction of heat and the radiation-to-space from the molecular ion and hydrocarbons. Comparison of the various heating and cooling terms enables us to investigate the balance of energy inputs into the auroral/polar atmosphere. Increases in Joule heating and ion drag are sufficient to explain the observed heating of the atmosphere; increased particle precipitation makes only a minor heating contribution. But local cooling effects—predominantly radiation-to-space—are shown to be too inefficient to allow the atmosphere to relax back to pre-event thermal conditions. Thus we conclude that this event provides observational, i.e. empirical, evidence that heat must be transported away from the auroral/polar regions by thermally or mechanically driven winds.     

Biomarker responses in Atlantic cod (Gadus morhua) exposed to produced water from a North Sea oil field: laboratory and field assessments

Biological markers of produced water (PW) exposure were studied in Atlantic cod (Gadus morhua) in both laboratory and field experiments, using authentic PW from a North Sea oil field. In the laboratory study, the PW exposure yielded significantly elevated levels of metabolites of polycyclic aromatic hydrocarbons (PAHs) and alkylphenols (APs) in bile even at the lowest exposure dose (0.125% PW). Other biomarkers (hepatic CYP1A induction and DNA adduct formation) responded at 0.25% and 0.5% PW concentrations. In the field study, bile metabolite markers and hepatic CYP1A were clearly increased in fish caged close to the PW outfall. Induction of plasma vitellogenin was not found in laboratory or field exposures, suggesting that the levels of oestrogen agonists (such as APs) might not have been sufficient to elicit induction, under the present conditions. The applicability of the biomarkers for use in water column biomonitoring programs is discussed.     

The distribution and relative toxic potential of organic chemicals in a PCB contaminated bay

For reliable monitoring of environmental improvement, the PCB contaminated bay Orserumsviken on Sweden's Baltic coast was investigated prior to remediation. We examined PCB congener patterns and the relative toxic potential of PCBs in extracts of three matrices: bottom sediment, settling particulate matter and the dissolved phase (obtained from semi-permeable membrane devices). Congener patterns were similar in all matrices. Three fractions were isolated from the extracts: (1) aliphatic and monocyclic aromatic compounds (MAC-fraction), (2) dicyclic aromatic compounds (DAC-fraction), including PCBs, and (3) polycyclic aromatic compounds (PAC-fraction), including PAHs. Total extracts and fractions were injected into newly fertilised rainbow trout eggs. At larval stage, hepatic EROD activities were quantified. Though high, the PCB contamination could explain only an estimated 1-5% of the total EROD induction. The order of EROD induction potential was: total extract > PAC-fraction > DAC-fraction > MAC-fraction in all matrices, suggesting that in Orserumsviken PACs made a larger contribution to the EROD induction potential than PCBs and other DACs.     

Cross-Calibration of SMART-1 XSM with GOES and RHESSI

A number of X-ray instruments have been active in observing the solar coronal X-ray radiation this decade. We have compared XSM observations with simultaneous GOES and RHESSI observations. We present flux calibrations for all instruments and compare XSM and GOES total emission measures (TEM) and temperatures (T).     

Applications of multivariate statistical analysis in remote sensing of agriculture

Rasmussen, Kjeld & Olesen, Henrik Hagen: Applications of multivariate statistical analysis in remote sensing of agriculture. Geografisk Tidsskrift 88:100–107. Copenhagen 1988.

Applications of satellite remote sensing to agriculture involve two main objectives, the identification and mapping of crops, including estimation of acreages, and monitoring of plant growth or production factors, aiming at estimation/prediction of yields.

Deterministic models of the interaction of electromagnetic radiation and plant canopies are used to relate the measured reflected or emitted radiation to crop type and agronomically relevant parameters. The great natural variation of reflectance properties of crops does, however, call for use of a statistical approach. The high dimensionality of the data-sets involved, very often more than ten, requires the use of multivariate techniques.

This paper will deal with the use of multivariate statistical techniques for both crop identification and crop monitoring based on high-resolution satellite remote sensing data, such as those produced by Landsat MSS and -TM and SPOT. Emphasis will be placed upon use of statistical methods in classification and on removal of redundancy in multi-dimensional data-sets. The relative merits of deterministic and statistical methods will be discussed as will the possibilities of incorporating spatial information into statistical methods.     

AGN effect on cooling flow dynamics

We analyzed the feedback of AGN jets on cooling flow clusters using three-dimensional AMR hydrodynamic simulations. We studied the interaction of the jet with the intracluster medium and creation of low X-ray emission cavities (Bubbles) in cluster plasma. The distribution of energy input by the jet into the system was quantified in its different forms, i.e. internal, kinetic and potential. We find that the energy associated with the bubbles, (pV+γ pV/(γ−1)), accounts for less than 10 percent of the jet energy.     

International fisheries regime effectiveness—Activities and resources of key actors in the Southern Ocean

Many contemporary environmental challenges are truly global and span several organizational and geographical borders. Research on international environmental regimes has, over the last couple of decades, identified several important factors that contribute to a more effective governance of global ecological resources, but few studies have addressed the different roles certain influential individual organizations play in determining regime effectiveness. Here we address this question by studying a relatively successful fishery governance system in the Southern Ocean. By drawing on insights from the research fields of common-pool resource management and international environmental regimes, we demonstrate that organizations engaged in certain combinations of activities, and that have access to certain combinations of resources stand out as important for regime effectiveness. In particular, collaboration with other flag states and being politically well-connected stand out as important explanatory factors. However, access to advanced technology, engagement in public campaigns, and being active in the field are other factors that, in different combinations, also seem to explain organizational importance. Furthermore, governmental and non-governmental organizations tend to perform different sets of activities and possess different resources, thereby complementing each other. Also, organizations doing similar things are often of different types with different mandates and objectives. This could contribute to improved adaptability and responsiveness to change at the larger regime level. Finally, we discuss some potential implications of our results for capacity-building in international environmental governance.     

Stochastic rainfall-runoff forecasting: parameter estimation,multi-step prediction,and evaluation of overflow risk

Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date, research has primarily focused on one-step-ahead flow predictions for identifying, estimating, and evaluating greybox models. For control purposes, however, stochastic predictions are required for longer forecast horizons and for the prediction of runoff volumes, rather than flows. This article therefore analyzes the quality of multistep ahead forecasts of runoff volume and considers new estimation methods based on scoring rules for k-step-ahead predictions. The study shows that the score-based methods are, in principle, suitable for the estimation of model parameters and can therefore help the identification of models for cases with noisy in-sewer observations. For the prediction of the overflow risk, no improvement was demonstrated through the application of stochastic forecasts instead of point predictions, although this result is thought to be caused by the notably simplified setup used in this analysis. In conclusion, further research must focus on the development of model structures that allow the proper separation of dry and wet weather uncertainties and simulate runoff uncertainties depending on the rainfall input.