We present a new model of the magnetic eld at the core{mantle boundary for the interval 1590{1990. The model, called gufm1, is based on a massive new compilation of historical observations of the magnetic eld. The greater part of the new dataset originates from unpublished observations taken by mariners engaged in merchant and naval shipping. Considerable attention is given to both correction of data for possible mislocation (originating from poor knowledge of longitude) and to proper allocation of error in the data. We adopt a stochastic model for uncorrected positional errors that properly accounts for the nature of the noise process based on a Brownian motion model. The variability of navigational errors as a function of the duration of the voyages that we have analysed is consistent with this model. For the period before 1800, more than 83 000 individual observations of magnetic declination were recorded at more than 64 000 locations; more than 8000 new observations are for the 17th century alone. The time-dependent eld model that we construct from the dataset is parametrized spatially in terms of spherical harmonics and temporally in B-splines, using a total of 36 512 parameters. The model has improved the resolution of the core eld, and represents the longest continuous model of the eld available. However, full exploitation of the database may demand a new modelling methodology.

We present a comprehensive review of historical geomagnetic data collected over the last 2 decades by many workers, culminating in the largest such compilation in the world. It spans over 4 centuries, from 1510 to 1930 inclusive, and consists of 151,560 declinations, 19,525 inclinations, and 16,219 intensities. The greater part of the new data set comprises unpublished observations recorded by mariners engaged in merchant and naval shipping across the world's oceans. Earlier published compilations and printed accounts of voyages have also been included, in particular when their original sources were inaccessible, missing, or no longer extant. The current effort has brought together an unprecedented number of early observations of the Earth's magnetic field, in standardized format, of potential use in many areas of geophysical research.

Frequency-dependent peak-delay times and coda quality factors have been used jointly to separate seismic absorption from scattering quantitatively in Earth media at regional and continental scale; to this end, we measure and map these two quantities at Mount St. Helens volcano. The results show that we can locate and characterize volcanic and geological structures using their unique contribution to seismic attenuation. At 3 Hz a single high-scattering and high-absorption anomaly outlines the debris flows that followed the 1980 explosive eruption, as deduced by comparison with remote sensing imagery. The flows overlay a NNW-SSE interface, separating rocks of significant varying properties down to 2-4 km, and coinciding with the St.Helens Seismic Zone. High-scattering and high-absorption anomalies corresponding to known locations of magma emplacement follow this signature under the volcano, showing the important interconnections between its feed-

No abstract

The susceptibility of the English and Welsh fish farming and fisheries industry to emergent diseases is assessed using a stochastic simulation model. The model dynamics operate on a network comprising directed transport and river contacts, as well as undirected local and fomite transmissions. The directed connections cause outward transmission risk to be geographically more confined than inward risk. We consider reactive, proactive, and hybrid methods of control which correspond to a mixture of policy and the ease of disease detection. An explicit investigation of the impact of laboratory capacity is made. General quantified guidelines are derived to mitigate future epidemics.

S U M M A R YThe technique of bootstrapped discrete scale invariance allows multiple time-series of different observables to be normalized in terms of observed and predicted characteristic timescales. A case study is presented using the SINT2000 time-series of virtual axial dipole moment, which spans the past 2 Myr. It is shown that this sequence not only bears a clear signature of a preferred timescale of about 55.6 Ka, but additionally predicts similar features (of shorter and longer duration) that are actually observed on the timescales of historical secular variation and dipole reversals, respectively. In turn, the latter two empirical sources both predict the characteristic timescale found in the dipole intensity sequence. These communal scaling characteristics suggest that a single underlying process could be driving dynamo fluctuations across all three observed timescales, from years to millions of years.

S U M M A R YThe geodynamo exhibits a bewildering gamut of time-dependent fluctuations, on timescales from years to at least hundreds of millions of years. No framework yet exists that comprises all and relates each to all others in a quantitative sense. The technique of bootstrapped discrete scale invariance quantifies characteristic timescales of a process, based upon log-periodic fits of modulated power-law scaling of size-ranked event durations. Four independent geomagnetic data sets are analysed therewith, each spanning different timescales: the sequence of 332 known dipole reversal intervals (0-161 Ma); dipole intensity fluctuations (0-2 Ma); archeomagnetic secular variation (5000 B.C.-1950 A.D.); and historical secular variation (1590-1990 A.D.).Six major characteristic timescales are empirically attested: circa 1.43 Ma, 56 Ka, and 763, 106, 21 and 3 yr. Moreover, all detected wavelengths and phases of the detected scaling signatures are highly similar, suggesting that a single process underlies all. This hypothesis is reinforced by extrapolating the log-periodic scaling signal of any particular data set to higher timescales than observed, through which predictions are obtained for characteristic scales attested elsewhere. Not only do many confirm one another, they also predict the typical duration of superchrons and geomagnetic jerks. A universal scaling bridge describes the complete range of geodynamo fluctuation timescales with a single power law.

River water temperature is a hydrological feature primarily controlled by topographical, meteorological, climatological, and anthropogenic factors. For Britain, the study of freshwater temperatures has focussed mainly on observations made in England and Wales; similar comprehensive data sets for Scotland are currently unavailable. Here we present a model for the whole of mainland Britain over three recent decades (1982–2011) that incorporates geographical extrapolation to Scotland. The model estimates daily mean freshwater temperature for every river segment and for any day in the studied period, based upon physico-geographical features, daily mean air and sea temperatures, and available freshwater temperature measurements. We also extrapolate the model temporally to predict future warming of Britain’s rivers given current observed trends. Our results highlight the spatial and temporal diversity of British freshwater temperatures and warming rates. Over the studied period, Britain’s rivers had a mean temperature of 9.84°C and experienced a mean warming of +0.22°C per decade, with lower rates for segments near lakes and in coastal regions. Model results indicate April as the fastest-warming month (+0.63°C per decade on average), and show that most rivers spend on average ever more days of the year at temperatures exceeding 10°C, a critical threshold for several fish pathogens. Our results also identify exceptional warming in parts of the Scottish Highlands (in April and September) and pervasive cooling episodes, in December throughout Britain and in July in the southwest of England (in Wales, Cornwall, Devon, and Dorset). This regional heterogeneity in rates of change has ramifications for current and future water quality, aquatic ecosystems, as well as for the spread of waterborne diseases.