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Calibration of radio interferometric observations becomes increasingly difficult towards lower frequencies. Below ?300 MHz, spatially variant refractions and propagation delays of radio waves traveling through the ionosphere cause phase rotations that can vary significantly with time, viewing direction and antenna location. In this article we present a description and first results of SPAM (Source Peeling and Atmospheric Modeling), a new calibration method that attempts to iteratively solve and correct for ionospheric phase errors. To model the ionosphere, we construct a time-variant, 2-dimensional phase screen at fixed height above the Earth’s surface. Spatial variations are described by a truncated set of discrete Karhunen-Loève base functions, optimized for an assumed power-law spectral density of free electrons density fluctuations, and a given configuration of calibrator sources and antenna locations. The model is constrained using antenna-based gain phases from individual self-calibrations on the available bright sources in the field-of-view. Application of SPAM on three test cases, a simulated visibility data set and two selected 74 MHz VLA data sets, yields significant improvements in image background noise (5–75 percent reduction) and source peak fluxes (up to 25 percent increase) as compared to the existing self-calibration and field-based calibration methods, which indicates a significant improvement in ionospheric phase calibration accuracy., Electrical Engineering, Mathematics and Computer Science

Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods., Electrical Engineering, Mathematics and Computer Science

Radio astronomical observations at low frequencies (< 250 MHz), can be severely distorted by fluctuations in electron density in the ionosphere. The free electrons cause a phase change of electromagnetic waves traveling through the ionosphere. This effect increases for lower frequencies. For this reason observations at low frequencies have been limited to short baselines and hence poor angular resolution. Most radio astronomical observations today are done at higher frequencies. The lower frequency bands however contain signals that are of great scientific value. Due to the expansion of the universe signals from distant objects are redshifted, i.e. shifted to lower frequencies. The more distant an observed object is the further we look back in time. An important period in the history of the universe is the ”Epoch of Reionization” (EoR). A few hundred thousand years after the Big Bang the universe has cooled enough to allow the formation of neutral hydrogren and helium. When the universe was a few hundred million years old the EoR started and the almost completely neutral gas was ionized again. Probably the only method to trace the neutral gas in this period is through the 1420 MHz spectral line of neutral hydrogen. For the EoR this line is redshifted to somewhere probably 100 and 200 MHz. Recently it has in principle become possible to observe with high resolution at low frequencies because the ever increasing computing power of digital data processing devices has made it possible to correct for the effect of the ionosphere. Determining the necessary corrections to the effect of the ionosphere is calles ionospheric calibration. The reason that ionospheric calibration is difficult is that the gain is direction dependent and rapidly varying over time. This greatly increases the number of degrees of freedom which causes two problems. First, the estimation of a large number of parameters is computationally costly. Second, the more parameters need to be estimated, the la, Microelectronics & Computer Engineering, Electrical Engineering, Mathematics and Computer Science

Calibration of radio interferometric observations becomes increasingly difficult towards lower frequencies. Below ?300 MHz, spatially variant refractions and propagation delays of radio waves traveling through the ionosphere cause phase rotations that can vary significantly with time, viewing direction and antenna location. In this article we present a description and first results of SPAM (Source Peeling and Atmospheric Modeling), a new calibration method that attempts to iteratively solve and correct for ionospheric phase errors. To model the ionosphere, we construct a time-variant, 2-dimensional phase screen at fixed height above the Earth’s surface. Spatial variations are described by a truncated set of discrete Karhunen-Loève base functions, optimized for an assumed power-law spectral density of free electrons density fluctuations, and a given configuration of calibrator sources and antenna locations. The model is constrained using antenna-based gain phases from individual self-calibrations on the available bright sources in the field-of-view. Application of SPAM on three test cases, a simulated visibility data set and two selected 74 MHz VLA data sets, yields significant improvements in image background noise (5–75 percent reduction) and source peak fluxes (up to 25 percent increase) as compared to the existing self-calibration and field-based calibration methods, which indicates a significant improvement in ionospheric phase calibration accuracy., Electrical Engineering, Mathematics and Computer Science

Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods., Electrical Engineering, Mathematics and Computer Science

The Low Frequency Array (LOFAR) is a radio telescope currently being designed. Its targeted observational frequency window lies in the range of 10–250 MHz. In frequency bands in which there is interference, the sensitivity of LOFAR can be enhanced by interference mitigation techniques. In this paper we demonstrate spatial filtering capabilities at the LOFAR initial test station (ITS) and relate it to the LOFAR radio frequency interference mitigation strategy. We show that in frequency ranges which are occupied with moderate?intensity man?made radio signals, the strongest observed astronomical sky sources can be recovered by spatial filtering. We also show that under certain conditions, intermodulation products of point?like interfering sources remain point sources. This means that intermodulation product filtering can be done in the same way as for “direct” interference. We further discuss some of the ITS system properties such as cross?talk and sky noise limited observations. Finally, we demonstrate the use of several beam former types for ITS., Electrical Engineering, Electrical Engineering, Mathematics and Computer Science

The Low Frequency Array (LOFAR) is a radio telescope currently being designed. Its targeted observational frequency window lies in the range of 10–250 MHz. In frequency bands in which there is interference, the sensitivity of LOFAR can be enhanced by interference mitigation techniques. In this paper we demonstrate spatial filtering capabilities at the LOFAR initial test station (ITS) and relate it to the LOFAR radio frequency interference mitigation strategy. We show that in frequency ranges which are occupied with moderate?intensity man?made radio signals, the strongest observed astronomical sky sources can be recovered by spatial filtering. We also show that under certain conditions, intermodulation products of point?like interfering sources remain point sources. This means that intermodulation product filtering can be done in the same way as for “direct” interference. We further discuss some of the ITS system properties such as cross?talk and sky noise limited observations. Finally, we demonstrate the use of several beam former types for ITS., Electrical Engineering, Electrical Engineering, Mathematics and Computer Science