The contribution of humic substances to the acidity of colored natural waters

An operationally defined carboxyl content of humic substances extracted from rivers, streams, lakes, wetlands, and groundwaters throughout the United States and Canada is reported. Despite the diversity of the samples, only small variations were observed in this humic carboxyl content. The dissociation behavior of two combined fulvic/humic acid extracts was studied and it was found that the dissociation of the humics varied in a predictable manner with pH. Using a carboxyl content of 10 μeq/ mg humic organic carbon, and mass action quotient calculated from sample pH, the ionic balances of three highly colored Nova Scotia rivers were estimated.     

Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.     

Two-dimensional modelling of some CFC replacement compounds

The Cambridge 2-D Eulerian model has been used to study the potential atmospheric distributions and lifetimes of a number of CFC replacement compounds and their degradation products. The study has focused on HFC 134a and HCFCs 123, 141b and 142b and the major products formed by their atmospheric degradation. The loss of these compounds and their products by hydroxyl radical attack, photolysis and in-cloud hydrolysis have been investigated. The study has shown that HCFCs 141b and 142b have sufficiently long lifetimes to enter the stratosphere in significant quantities, where degradation leads to an increase in the total stratospheric chlorine concentration. The study has also highlighted areas where further experimental work would be valuable, in particular characterisation of the product channels for the degradation reactions and determination of the removal rates of the products in the aqueous phase.     

Stochastic perturbation analysis of groundwater flow. Spatially variable soils,semi-infinite domains and large fluctuations

As is well known, a complete stochastic solution of the stochastic differential equation governing saturated groundwater flow leads to an infinite hierarchy of equations in terms of higher-order moments. Perturbation techniques are commonly used to close this hierarchy, using power-series expansions. These methods are applied by truncating the series after a finite number of terms, and products of random gradients of conductivity and head potential are neglected. Uncertainty regarding the number or terms required to yield a sufficiently accurate result is a significant drawback with the application of power series-based perturbation methods for such problems. Low-order series truncation may be incapable of representing fundamental characteristics of flow and can lead to physically unreasonable and inaccurate solutions of the stochastic flow equation. To support this argument, one-dimensional, steady-state, saturated groundwater flow is examined, for the case of a spatially distributed hydraulic conductivity field. An ordinary power-series perturbation method is used to approximate the mean head, using second-order statistics to characterize the conductivity field. Then an interactive perturbation approach is introduced, which yields improved results compared to low-order, power-series perturbation methods for situations where strong interactions exist between terms in such approximations. The interactive perturbation concept is further developed using Feynman-type diagrams and graph theory, which reduce the original stochastic flow problem to a closed set of equations for the mean and the covariance functions. Both theoretical and practical advantages of diagrammatic solutions are discussed; these include the study of bounded domains and large fluctuations.     

Mean wind-direction shear through a forest canopy

The equations of motion applying to the wind field in a forest canopy are simplified to a balance between the shearing stress gradient and either the form-drag of the leaves in the upper dense canopy, or the overall horizontal pressure gradient in the more open space beneath. The equations imply that, in descending through the forest, the stress and wind vectors turn through an angle which depends on the forest characteristics and on the stability and the speed of the airflow above the forest. The turning is roughly confirmed by an overall average measured on a very flat site near Thetford, Norfolk, covered by an extensive uniform pine forest.     

In-flight performance analysis of the CHAMP BlackJack GPS Receiver

JPL's BlackJack receiver currently represents the most widely used geodetic grade GPS receiver for space applications. Using data from the CHAMP science mission, the in-flight performance of the BlackJack receiver has been assessed and the impact of various software updates performed during the 2.5 years since launch is described. Key aspects of the study comprise the channel allocation, anomalous data points, and the noise level of the code and carrier data. In addition, it has been demonstrated that the code measurements collected onboard the CHAMP satellite are notably affected by multipath errors in the aft-looking hemisphere, which can be attributed to cross-talk between the occultation antenna string and the primary precise orbit determination antenna. For carrier smoothed 10 s normal points, the code noise itself varies between a minimum of 5 cm at high elevations and 0.5 m (C/A) to 1.0 m (P₁, P₂) at 10° elevation. Carrier-phase data exhibit representative errors of 0.2 to 2.5 mm. The results of the CHAMP GPS data analysis contribute to a better understanding and possible improvement of the BlackJack receiver and support the design of optimal data editing and weighting strategies in precise orbit determination applications.     

Look out, aurorae about!

Jim Wild recounts the rationale and success of AuroraWatch, a service that alerts you when you might be able to see aurorae.     

GIOVE-A initial signal analysis

In late December 2005 the GIOVE-A test satellite was launched by the European Space Agency (ESA) to secure the frequencies for the Galileo system and to provide a platform for testing the new navigation signals. We performed an initial assessment of these signals using the 30 m deep space antenna of the DLR ground station in Weilheim (Germany). The antenna gain raised the signals above the noise level, thus allowing a detailed analysis even without knowledge of the ranging codes. The present paper covers the analysis of the L1/E1 signals, which includes a discussion of the spectrum, the time domain signal and a decoding of the spreading codes for the Open Service.     

Calculation of the Inverse of the Covariance

In reservoir characterization, the covariance is often used to describe the spatial correlation and variation in rock properties or the uncertainty in rock properties. The inverse of the covariance, on the other hand, is seldom discussed in geostatistics. In this paper, I show that the inverse is required for simulation and estimation of Gaussian random fields, and that it can be identified with the differential operator in regularized inverse theory. Unfortunately, because the covariance matrix for parameters in reservoir models can be extremely large, calculation of the inverse can be a problem. In this paper, I discuss four methods of calculating the inverse of the covariance, two of which are analytical, and two of which are purely numerical. By taking advantage of the assumed stationarity of the covariance, none of the methods require inversion of the full covariance matrix.