The Early Pleistocene Praetiglian and Ludhamian pollen stages in the North Sea Basin and their relationship to the marine isotope record

In this paper, the currently accepted correlation of the Early Pleistocene Ludhamian stage of England with the Tiglian‐A sub‐stage of the Netherlands is challenged. Recent investigations of Early Pleistocene marine North Sea deposits from a borehole near Noordwijk (the Netherlands) yielded evidence from molluscs, dinoflagellate cysts and sporomorphs for an alternation of warm‐temperate and arctic intervals within the Praetiglian and Tiglian stages. Marine equivalents of the terrestrial‐based pollen sub‐stages Tiglian A and B have been recognised in the upper part of the sequence. A Praetiglian age can be assigned to the lower part of the sequence on the basis of mollusc analysis. Within the Praetiglian, an alternation of warm and cold phases has been recognised from both the dinoflagellate cyst and molluscan records. Three cold phases within the Praetiglian are tentatively correlated with marine isotope stages (MIS) 96–100. The molluscan assemblages provide evidence for climate forcing of the sea level: highest sea levels are reached in the warm‐temperate intervals. Within the Praetiglian, an interval with an acme zone of the dinoflagellate cyst Impagidinium multiplexum, is correlated with the Ludhamian and tentatively linked to MIS 97 and/or MIS 96. The cold molluscan assemblages from the Noordwijk borehole include an acme zone of Megayoldia thraciaeformis, the first and only occurrence of this North Pacific bivalve in the North Sea Basin. Copyright © 2006 John Wiley & Sons, Ltd.     

OSCR wave measurements-some preliminary results

OSCR is an HF radar system that has been developed for high spatial resolution coastal surface current measurement. This paper describes preliminary results that demonstrate that wave measurement can be successfully obtained from suitably processed OSCR data. Comparisons with data from a WAVEC directional buoy are presented and show encouraging agreement. Some of the limitations to the measurement process are discussed and indicate a maximum range of about 20 km. Surface current variability on short time scales presents the most serious obstacle to wave measurement. This appears to be more of a problem when the mean currents are large, in that in these circumstances the data fail initial quality control criteria. However, in lower mean currents, the effect is often still present and leads to errors in long wave measurement     

Application of an improved self-starter to geoacoustic inversion

The self-starter is improved using the operator of the split-step Pade solution. In addition to providing greater stability and being applicable closer to the source, the improved self-starter is an efficient forward model for geoacoustic inversion. It is necessary to solve only O(10) tridiagonal systems of equations to obtain the acoustic field on a vertical array located O(10) wavelengths from a source. This experimental configuration is effective for geoacoustic inverse problems involving unknown parameters deep in the ocean bottom. For problems involving depth-dependent acoustic parameters, the improved self-starter can be used to solve nonlinear inverse problems involving O(10) unknown sediment parameters in less than a minute on the current generation of workstations     

Ice‐cover variability on shallow lakes at high latitudes: model simulations and observations

A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd.     

Infiltration at the Tai rain forest (Ivory Coast): Measurements and modelling

Infiltration experiments have been performed at three sites along a well-known catena under virgin tropical rain forest using a portable sprinkling infiltrometer. Experimentally determined infiltration curves are presented. Infiltration curves are also simulated on the basis of the Mein-Larson equation. The parameters for this model have been obtained from the infiltration curves (saturated conductivity) and simple soil moisture determinations (fillable porosity). The agreement between experimentally determined and modelled infiltration is reasonable, provided (a) saturated conductivity as derived from the experimental data is corrected, (b) a storage parameter, also derived from the experimental data, is added to the Mein-Larson model, and (c) the decline in soil porosity with depth is either small or occurs abruptly at shallow depth. Comparison of observed infiltration rates with rainfall intensity shows that Horton Overland Flow has to occur naturally at least on the middle and lower section of the catena. Despite the fact that most parameters can be estimated in principle from basic soil data, it remains advisable to obtain sprinkling infiltrometer field measurements, because of soil variability due to dynamic surface conditions, macroporosity, air entrapment, and irregularity of the wetting front.