Persistence of Planetary Waves in the Lower Ionosphere

The transient planetary waves in the atmosphere and ionosphere seem to occur in the form of bursts of a couple of waves with limited persistence. To study persistence of planetary wave events in the lower ionosphere, data from two radio paths from Central Europe are used, Luxembourg – Panská Ves (f = 6.09 MHz, f _eq = 2.1-2.2 MHz) and Deutschlandfunk – Panská Ves (f = 1539 kHz, f _eq = 650-700 kHz). The absorption along the former radio paths is formed very predominantly at altitudes of about 90-100 km, whereas the latter absorption is formed mostly at altitudes of about 85-90 km. The persistence of planetary wave type oscillations is studied in three period bands centred at 5, 10 and 16 days. Waves with period T near 5 days reveal a typical persistence of wave events around 5 cycles. Waves with T = 10 days are less persistent with a typical persistence of 3-4 cycles. The typical persistence of waves T = 16 days is no more than 3 cycles. In terms of number of cycles, the persistence of oscillations evidently decreases with increasing period. On the other hand, in terms of number of days, the persistence seems rather to increase with increasing period.     

The value of ocean reflections of GPS signals to enhance satellite altimetry: data distribution and error analysis

The time and space distribution of general reflection altimetry from two satellites (senders and receivers) via the the oceans surface is examined with specific reference to GPS senders and two current receiving satellites. While a considerable enhancement of conventional altimeter coverage is possible in all configurations if the reflection signals can be used, repeating passes of these (with GPS senders) having reasonably small cycle times (days to tens of days) occur only if the receiving orbit is nearly polar. Results of an analysis of the fundamental geometry show that over a large range of reflection angles the error of recovered sea heights depends almost entirely on the errors in the delay signal and the radial error of the receiving satellite (using current estimates of GPS orbit accuracies). The most critical element is the precision of the delay measurement. Both it and the accuracy of the receiving orbit should be below the decimeter level for the technique to achieve its full potential.     

Geostatistical analysis of arsenic concentration in groundwater in Bangladesh using disjunctive kriging

The National Hydrochemical Survey of Bangladesh sampled the water from 3,534 tube wells for arsenic throughout most of Bangladesh. It showed that 27% of the shallow tube wells (less than 150 m deep) and 1% of the deep tube wells (more than 150 m deep) exceeded the Bangladesh standard for arsenic in drinking water (50 µg L^–1). Statistical analyses revealed the main characteristics of the arsenic distribution. Concentrations ranged from less than the detection limit (0.5 µg L^–1), to as much as 1,600 µg L^–1, though with a very skewed distribution, and with spatial dependence extending to some 180 km. Disjunctive kriging was used to estimate concentrations of arsenic in the shallow ground water and to map the probability that the national limit for arsenic in drinking water was exceeded for most of the country (the Chittagong Hill Tracts and the southern coastal region were excluded). A clear regional pattern was identified, with large probabilities in the south of the country and small probabilities in much of the north including the Pleistocene Tracts. Using these probabilities, it was estimated that approximately 35 million people are exposed to arsenic concentrations in groundwater exceeding 50 µg L^–1 and 57 million people are exposed to concentrations exceeding 10 µg L^–1 (the WHO guideline value).     

Seasonal Dynamics in Dissolved Organic Carbon Concentrations in a Coastal Water-Table Aquifer at the Forest-Marsh Interface

The seasonal dynamics of dissolved organic carbon (DOC) in a subterranean estuary were examined in a coastal water-table aquifer extending across a forest-marsh interface into an adjacent tidal creek that leads to North Inlet (SC). The aquifer is characterized by groundwater flow from the forest recharge area towards the creek. DOC concentrations range from 50 to 140 mg L^-1 in the shallow portions of the aquifer below the forest and undergo seasonal changes that are inversely related to temperature and precipitation conditions. Markedly lower DOC concentrations (<10 mg L^-1) in the deep portion of the aquifer are consistent with the loss of a large fraction of the original DOC along the groundwater flow paths. Mass balance estimates indicate that over 60% of the DOC losses are due to sorption reactions whereas the rest appear to be caused by heterotrophic decay. Groundwater DOC discharge from the forest, which occurs in a restricted zone of the high marsh, is 5.5 mg carbon m^-2 d^-1 and accounts for a minor component of the annual carbon export from North Inlet. In contrast, moderately saline (2–12 ppt) ground waters below the marsh display elevated DOC concentrations (20 mg L^-1) that appear to be the result of mixing of fresh ground waters and surface seawater during tidal seepage and concentration during evapotranspiration. The flux of DOC associated with the discharge of these saline ground waters is 600 mg carbon m^-2 d^-1, which represents a significant fraction of the annual DOC budget for North Inlet.     

Determination of Soil Parameters via the Solution of Inverse Problems in Infiltration

In this paper, we propose an efficient method for the identification of soil parameters in unsaturated porous media, using measurements from infiltration experiments. The infiltration is governed by Richard's nonlinear equation expressed in terms of effective saturation. The soil retention and hydraulic permeability functions are expressed using the Van Genuchten-Mualem ansatz in terms of the soil parameters. The mathematical algorithm is based on a transformation of Richard's equation to a system of ordinary differential equations completed by the governing equation for the movement of the wetness front. This system can be efficiently solved by specialized packages for the solution of stiff systems of ODE. The unknown parameters are determined using the optimization approach of minimizing a cost functional for the discrepancy between the model output and the measurements. The gradient and Hessian of the solution with respect to soil parameter vector are determined using automatic differentiation. Several numerical experiments are included.     

Optimum estimation in a growth curve model with a priori unknown variance components in geodetic networks

Summary Time varying coordinates of points of a geodetic network are indirectly measured by a group of measurement devices with different characteristics of accuracy in several epochs. The design of the measurement is the same in all epochs. The ratio of the characteristics of accuracy is a priori unknown. The aim is to determine an estimator of the parameters of functions modelling changes of the coordinates, confidence regions of these functions and to construct a procedure for testing linear hypotheses on time varying coordinates of a geodetic network. As the characteristics of accuracy are a priori unknown, the problem of their estimation has to be solved simultaneously. The research of rules of recent crustal movements leads to studying the mentioned model.     

The inclusion of surface synoptic data in very short range predictions of convective events

Summary Predictor vectors, including upper air as well as surface data, were used for categorical forecasting convective events over a subregion of the Czech territory, and the effect of including surface variables in the predictor vector was examined. While upper air data were considered as Perfect Prognosis, the surface data were successively included according to the time of their origin. The forecasting technique was based on linear multiple regression with learning, and the accuracy of the forecast was measured by the Critical Success Index. The input data from the three May-September periods in 1989–91 were used, and the first year served as the learning set. The aerological data from TEMP 12 UTC, simulating Perfect Prognosis, were the source of the upper air predictors. The performance of all, upper air, surface and combined, predictors were evaluated and compared. It turned out that the improvement of prediction accuracy due to the inclusion of surface variables was not negligible. Significant improvements were made in the forecasts of thunderstorm occurrence between 18 and 24 UTC.