ALBERT

Beschreibung: Environmental Science & Technology DOI: 10.1021/es401317c

Beschreibung: The L-band passive and active microwave geophysical model functions (GMFs) of ocean surface winds from the Aquarius data are derived. The matchups of Aquarius data with the Special Sensor Microwave Imager (SSM/I) and National Centers for Environmental Prediction (NCEP) winds were performed and were binned as a function of wind speed and direction. The radar HH GMF is in good agreement with the PALSAR GMF. For wind speeds above 10 $hbox{m}cdothbox{s}^{-1}$ , the L-band ocean backscatter shows positive upwind–crosswind (UC) asymmetry; however, the UC asymmetry becomes negative between about 3 and 8 $hbox{m}cdothbox{s}^{-1}$ . The negative UC (NUC) asymmetry has not been observed in higher frequency (above C-band) GMFs for ASCAT or QuikSCAT. Unexpectedly, the NUC symmetry also appears in the L-band radiometer data. We find direction dependence in the Aquarius $T_{rm BV}$ , $T_{rm BH}$ , and third Stokes data with peak-to-peak modulations increasing from about a few tenths to 2 K in the range of 10–25- $hbox{m}cdothbox{s}^{-1}$ wind speed. The validity of the GMFs is tested through application to wind and salinity retrieval from Aquarius data using the combined active–passive algorithm. Error assessment using the triple collocation analyses of SSM/I, NCEP, and Aquarius winds indicates that the retrieved Aquarius wind speed accuracy is excellent, with a random error of about 0.75 $hbox{m}cdothbox{s}^{-1}$ . The wind direction retrievals also appear reasonable and accurate above 10 $hbox{m}cdothbo- {s}^{-1}$ . The results of the error analysis indicate that the uncertainty of the GMFs for the wind speed correction of vertically polarized brightness temperatures is about 0.14 K for wind speed up to 10 $hbox{m}cdothbox{s}^{-1}$ .

Beschreibung: The local oscillators (LOs) of the Soil Moisture and Ocean Salinity mission payload are used to shift the operating frequency of the 72 receivers to an optimal intermediate frequency needed for the signal processing. The LO temperature variations produce phase errors in the visibility, which result in a blurring of the reconstructed brightness temperature (Tb) image. At the end of the commissioning phase, it was decided to calibrate the LO every 10 min while waiting for a more in-depth analysis. During short periods of time, the LO calibration has been performed every 2 min to assess the impact of a higher calibration rate on the quality of the data. In this paper, by means of a decimation experiment, the relative errors of 6- and 10-min calibration interval data sets are estimated using the 2 min as a reference. A noticeable systematic across- and along-track pattern of amplitude $pm$ 0.3 K is observed for Tb differences between 10 and 2 min, whereas this is reduced between 6 and 2 min. A simulation experiment confirms that the nature of such systematic pattern is due to the visibility phase errors induced by the LO calibration rate. Such pattern is propagated into the sea surface salinity (SSS) retrievals. Overall, the SSS error increase (relative to the 2 min SSS data) is about 0.39 and 0.14 psu for the 10- and 6-min data sets, respectively. This paper shows that a LO calibration rate of at least 6 min would noticeably improve the SSS retrievals.

Beschreibung: Radiometric measurements could provide continuous information about atmospheric conditions. In this paper, a sky status indicator (SSI) is proposed as a real-time recognition criterion for the detection, in particular, of the presence of rain events along the propagation path. The computation of the SSI is based on ground-based brightness temperature measurements, at 23.8 and 31.4 GHz, collected in Cabauw, Netherlands, in 2009 by the ESA Atmospheric Propagation and Profiling System (ATPROP) multichannel radiometer. A validation analysis is carried out between simulated data, which are computed by applying the radiative transfer equation to a database of radiosonde profiles collected in De Bilt, Netherlands, by the Royal Netherlands Meteorological Institute, and two data sets of radiometric observations at two elevation angles ( $theta$ equal to 90 $^{circ}$ and $theta$ equal to 69.6 $^{circ}$ ). The analysis based on SSI probability distribution functions has allowed for calculation of the boundary threshold values that are able to discriminate the status of the sky. Furthermore, performances of the SSI were validated against rainfall measurements collected at the ground by a rain gauge located near the ESA ATPROP multichannel radiometer.

Beschreibung: A new cloud dynamics and radiation database (CDRD) precipitation retrieval algorithm for satellite passive microwave (PMW) radiometer measurements has been developed. It represents a modification to and an improvement upon the conventional cloud radiation database (CRD) algorithms, which have always been prone to ambiguity. This part 2 paper of a series describes the methodology of the algorithm and the modeling verification analysis involved in creating a synthetic CDRD database for the Europe/Mediterranean basin region. This is followed by a proof-of-concept analysis, which demonstrates that the underlying CDRD theory based on use of meteorological parameters for reducing retrieval ambiguity is valid. This paper uses a regional/mesoscale model, applied in cloud resolving model (CRM) mode, to produce a large set of numerical simulations of precipitating storms and extended precipitating systems. The simulations are used for selection of millions of meteorological/microphysical vertical profiles within which surface rainfall is identified. For each of these profiles, top-of-atmosphere brightness temperature (TB) vectors are calculated (the vector dimension associated with the number of relevant cm–mm wavelengths and polarizations), based on an elaborate radiative-transfer equation (RTE) model system (RMS) coupled to the CRM. This entire body of simulation information is organized into the CDRD database, then used as a priori knowledge to guide a physical Bayesian retrieval algorithm in obtaining rainfall and associated precipitation parameters from the PMW satellite observations. We first prove the physical validity of our CRM-RMS simulations, by showing that the simulated TBs are in close agreement with observations. Agreement is demonstrated using dual-channel-frequency TB manifold sections, which quantify the degree of overlap between the simulated and observed TBs extracted from the full manifolds. Nevertheless, the salient result of this paper is a pro- f that the underlying CDRD theory is valid, found by combining subdivisions of the invoked meteorological parameter ranges of values and showing that such meteorological partitioning associates itself with distinct microphysical profiles. It is then shown that these profiles give rise to similar TB vectors, proving the existence of ambiguity in a CRD-type algorithm. Finally, we show that the CDRD methodology provides significant improvements in reducing retrieval ambiguity and retrieval error, especially for land surface backgrounds where contrasts are typically small between the rainfall TB signatures and surface emission signatures.

Beschreibung: The results of remote sensing temperature profiles measurements within a 0–600-m altitude range and total water content measurements during total (Kislovodsk, 2006; Novosibirsk, 2008) and partial (Moscow, 2011) solar eclipses, using microwave radiometers are presented. Initially, continuous data on temperature profiles are obtained at different altitudes before, during, and after total solar eclipses, using two single channel elevation scanning microwave temperature profilers. Terrestrial consequences of solar eclipses (especially total ones) are quite noticeable and important. Solar eclipses support unique, specific conditions, which gives the opportunity for various meteorological research. The most important indicator of thermodynamic processes occurring during solar eclipses is air temperature at different altitudes in the atmospheric boundary layer (ABL). The ABL temperature depends, in general, on the flux of solar radiation and some features of the ground (albedo, absorptivity, and emissivity) and the air (humidity). Temperature profile measurements are accompanied by solar radiation (with net-radiometer) and total water vapor (with microwave radiometers) measurements. The observation results of this paper will contribute detailed model calculations for clarifying meteorological effects of solar eclipses. Observations of the next total solar eclipse over Russia (August 12, 2026) can be used to verify our observational results.

Beschreibung: Snow grain size is the snowpack parameter that most affects the microwave snow emission. The specific surface area (SSA) of snow is a metric that allows rapid and reproducible field measurements and that well represents the grain size. However, this metric cannot be used directly in microwave snow emission models (MSEMs). The aim of this paper is to evaluate the suitability and the adaptations required for using the SSA in two MSEMs, i.e., the Dense Media Radiative Theory-Multilayer model (DMRT-ML) and the Helsinki University of Technology model (HUT n-layer), based on in situ radiometric measurements. Measurements of the SSA, using snow reflectance in the short-wave infrared, were taken at 20 snowpits in various environments (e.g., grass, tundra, and dry fen). The results show that both models required a scaling factor for the SSA values to minimize the root-mean-square error between the measured and simulated brightness temperatures. For DMRT-ML, the need for a scaling factor is likely due to the oversimplified representation of snow as spheres of ice with a uniform radius. We hypothesize that the need for a scaling factor is related to the grain size distribution of snow and the stickiness between grains. For HUT n-layer, using the SSA underestimates the attenuation by snow, particularly for snowpacks with a significant amount of depth hoar. This paper provides a reliable description of the grain size for DMRT-ML, which is of particular interest for the assimilation of satellite passive microwave data in snow models.

Beschreibung: Ice lens formation, which follows rain on snow events or melt-refreeze cycles in winter and spring, is likely to become more frequent as a result of increasing mean winter temperatures at high latitudes. These ice lenses significantly affect the microwave scattering and emission properties, and hence snow brightness temperatures that are widely used to monitor snow cover properties from space. To understand and interpret the spaceborne microwave signal, the modeling of these phenomena needs improvement. This paper shows the effects and sensitivity of ice lenses on simulated brightness temperatures using the microwave emission model of layered snowpacks coupled to a soil emission model at 19 and 37 GHz in both horizontal and vertical polarizations. Results when considering pure ice lenses show an improvement of 20.5 K of the root mean square error between the simulated and measured brightness temperature (Tb) using several in situ data sets acquired during field campaigns across Canada. The modeled Tbs are found to be highly sensitive to the vertical location of ice lenses within the snowpack.

Beschreibung: In recent years, there has been growing interest on the part of the remote sensing community in using the Antarctic area for calibrating and validating data of low-frequency satellite-borne microwave radiometers. In particular, the East Antarctic Plateau appears to be suited for this purpose. The reasons for this interest are the size, structure, spatial homogeneity, and thermal stability of this area. This is particularly interesting for low-frequency microwave radiometers since, due to the low extinction of dry snow, the upper ice-sheet layer is almost transparent and the brightness temperature variability is therefore extremely small. In the context of calibration and validation activities of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite, an experiment called DOMEX-2, which included radiometric L-band measurements, was carried out at the Italian–French base of Concordia located at Dome C in the East Antarctic Plateau from December 2008 to December 2010. Ground measurements (i.e., snow temperature at different depths, snow structure, meteorological data, etc.) were also collected during the experiment. This paper presents information on the experimental campaign, the characteristics of the radiometric measurements, and the main results. A comparison with SMOS data is also presented.

Beschreibung: The 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad 2012) was held at Villa Mondragone, University of Rome "Tor Vergata," near Frascati, Italy, on March 5-9, 2012. The objective of MicroRad 2012 was to provide an open forum to report and discuss recent advances in the field of microwave radiometry, particularly with application to remote sensing of the environment. The meeting was highly successful, with more than 120 attendees representing 20 countries. There were 76 oral presentations and more than 40 posters. From the papers presented at MicroRad 2012 and others submitted specifically for this special issue, 12 were selected for inclusion in the special issue. The papers were carefully peer reviewed with the usual standards of the IEEE TGRS. As is evident from the table of contents, these papers span a broad range of microwave radiometry and remote sensing applications and reflect the interest in MicroRad and the vitality of research in this area.

Beschreibung: Vicarious cold calibration in the frequency range of 85–92 GHz is analyzed. Vicarious cold calibration cannot be applied at these frequencies as easily as at lower frequencies due to greater sensitivity to water vapor and hydrometeor scattering. The effects of that sensitivity are mitigated by selective filtering of the high-frequency brightness temperatures (TBs) to remove those data where large amounts of water vapor and/or hydrometeor scattering are present. Potential filtering algorithms are presented, and the performance of each with respect to vicarious cold calibration TB stability is characterized. A scattering-based precipitation filter that utilizes a combination of both the lower frequencies from 19 to 37 GHz and the frequencies from 85 to 92 GHz is shown to be the most effective and easily implemented filter. For horizontal polarization, the theoretical minimum TB at the higher frequencies occurs at an unphysically high sea surface temperature (SST), which makes the vicarious cold statistic more sensitive to the population of actual SST values as well as the higher amounts of water vapor associated with warm SSTs. The statistic is stabilized in this case by considering the difference between observed and simulated vicarious cold TBs. Intercalibration between two radiometers using the vicarious cold calibration double difference method at high frequencies is shown to be greatly improved when using the precipitation filter.

Beschreibung: After 2.5 years of the Soil Moisture and Ocean Salinity (SMOS) mission, the characterization of residual instrumental systematic errors in the measured brightness temperatures $(T_{B})$ is still rather poor. This, in turn, negatively impacts the sea surface salinity retrievals and, as such, notably limits the mission's success. The error mitigation methodology currently used operationally, the so-called Ocean Target Transformation (OTT), mixes both instrumental and model-induced errors. In this paper, it is proposed to distinguish errors by their type of impact on the $T_{B}$ images: mean brightness level, incidence angle dependence, and azimuth angle dependence. A new approach to characterize the azimuth-dependent errors is proposed. First, a careful data selection strategy is applied. Then, an empirically fitted model, which only accounts for the $T_{B}$ incidence angle dependence, is subtracted from the mean $T_{B}$ images of the selected data sets to estimate the systematic antenna-frame errors. The robustness of this methodology is assessed through the estimated anomaly pattern stability when computed for different geophysical conditions, periods of time, and latitudinal bands. The residual variability ranges from 0.03 K to 0.14 K, whereas the OTT variability is about 0.5 K. The new method is forward model independent and generic. It can therefore be applied to estimate the antenna-frame systematic errors over land and ice. Moreover, it proves to be very effective in separating different sources of error and can therefore be used to further characterize other error components and improve the various SMOS forward model terms.

Beschreibung: Terrain Observation by Progressive Scans (TOPS) synthetic aperture radar (SAR) and spotlight SAR are advanced SAR imaging modes for wide range swath and high resolution. In order to obtain a wider range coverage, azimuth multichannel is introduced in the literature. Since the azimuth bandwidth of beam steering SAR (BS-SAR; spotlight SAR, sliding spotlight SAR, or TOPS SAR) is much greater than that of a stripmap SAR, a signal reconstruction algorithm used for multichannel stripmap SAR may not be effective for multichannel BS-SAR. In this paper, a multichannel full-aperture azimuth processing algorithm is proposed for a BS-SAR. The key of this algorithm lies in the beam and the azimuth bandwidth compressions of multichannel signals in the Doppler–array and slow time–angle planes, respectively. Through compression processing, the beamwidth and the azimuth bandwidth are smaller than the available angle and equivalent pulse repeating frequency , respectively. Then, an improved post-Doppler STAP method is proposed to recover a 2-D spectrum. With the recovered signal, further processing can be utilized to focus the multichannel signal. Simulation and real data results show the effectiveness of the proposed algorithm.

Beschreibung: Remote sensing image fusion can integrate the spatial detail of panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MS) image to produce a fused MS image with high spatial resolution. In this paper, a remote sensing image fusion method is proposed with sparse representations over learned dictionaries. The dictionaries for PAN image and low-resolution MS image are learned from the source images adaptively. Furthermore, a novel strategy is designed to construct the dictionary for unknown high-resolution MS images without training set, which can make our proposed method more practical. The sparse coefficients of the PAN image and low-resolution MS image are sought by the orthogonal matching pursuit algorithm. Then, the fused high-resolution MS image is calculated by combining the obtained sparse coefficients and the dictionary for the high-resolution MS image. By comparing with six well-known methods in terms of several universal quality evaluation indexes with or without references, the simulated and real experimental results on QuickBird and IKONOS images demonstrate the superiority of our method.

Beschreibung: The multichromatic analysis (MCA) uses interferometric pairs of SAR images processed at range subbands and explores the phase trend of each pixel as a function of the different central carrier frequencies to infer absolute optical path difference. This approach allows retrieving unambiguous height information on selected pixels, potentially solving the problem of spatial phase unwrapping, which is instead critical in the standard monochromatic processing. The method, based on concepts originally introduced by Madsen and Zebker, has been developed in previous work both theoretically and through simulations. This paper presents the first MCA experimental validation of the procedure, through application to a wideband SAR single-pass interferometric data set acquired by the AES-1 airborne sensor. An evaluation of the impact of the MCA processing parameters on the height estimation performances is obtained through a parametric analysis. The results confirm the indications derived by the theoretical analysis, demonstrating the feasibility of the MCA absolute phase measurement, provided that a sufficient bandwidth is available.

Beschreibung: This paper proposes a new semisupervised dimension reduction (DR) algorithm based on a discriminative locally enhanced alignment technique. The proposed DR method has two aims: to maximize the distance between different classes according to the separability of pairwise samples and, at the same time, to preserve the intrinsic geometric structure of the data by the use of both labeled and unlabeled samples. Furthermore, two key problems determining the performance of semisupervised methods are discussed in this paper. The first problem is the proper selection of the unlabeled sample set; the second problem is the accurate measurement of the similarity between samples. In this paper, multilevel segmentation results are employed to solve these problems. Experiments with extensive hyperspectral image data sets showed that the proposed algorithm is notably superior to other state-of-the-art dimensionality reduction methods for hyperspectral image classification.

Beschreibung: This paper presents a new framework for the development of generalized composite kernel machines for hyperspectral image classification. We construct a new family of generalized composite kernels which exhibit great flexibility when combining the spectral and the spatial information contained in the hyperspectral data, without any weight parameters. The classifier adopted in this work is the multinomial logistic regression, and the spatial information is modeled from extended multiattribute profiles. In order to illustrate the good performance of the proposed framework, support vector machines are also used for evaluation purposes. Our experimental results with real hyperspectral images collected by the National Aeronautics and Space Administration Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer and the Reflective Optics Spectrographic Imaging System indicate that the proposed framework leads to state-of-the-art classification performance in complex analysis scenarios.

Beschreibung: For typical scanning microwave radiometers, a significant source of calibration error arises from thermal gradients on the hot load. Even when direct or reflected solar illumination is blocked, hot load gradients arise from thermal coupling between the target and the surface facing the target which is heated and cooled as the instrument orbits the earth. For the GlobalL Precipitation Measurement (GPM) Microwave Imager (GMI), a rotating metal annular ring called the “hot load tray” serves to guard the hot load against solar intrusion, and is the surface immediately facing the hot load during the majority of the scan. The planned GMI calibration algorithm corrects for the target gradients induced by thermal coupling between the hot load tray and hot load. The correction uses an empirically derived relationship between the target gradient and the temperature differential between the target and the tray. The correction is derived using target-level and GMI system-level calibration testing. The dual calibration of GMI, in connection with thermal vacuum calibration measurements, is a key aid to determining and correcting the hot load gradients.

Beschreibung: Satellite images have long been used to study surface manifestations of internal waves (IWs). More recently, marine X-band radar data have been employed to retrieve IW packet parameters. Marine radars have the advantage over satellite systems that their high temporal resolution enables the study of the IW evolution. Until today, no method to automatically detect IW surface signatures in marine radar data has been suggested. In this paper, we present a new fully automated tool to retrieve IW signatures from marine radar image sequences. First, after various preprocessing steps, the IW packet velocity is determined using a combination of localized Radon transform and cross-correlation techniques. Temporal averaging of the marine radar data significantly enhances the IW signatures. The knowledge of the IW packet velocity is used to correct for the IW motion, enabling us to extend the averaging period, which further enhances the IW signal. An IW-motion correction is necessary because, otherwise, the IW signal would become smeared if the averaging period were much longer than the time it takes the IW to propagate between radar resolution cells. The IW-enhanced images are then utilized for the IW signature analysis. Here, we identify local backscatter peaks and exploit the marine radar's high temporal resolution to distinguish signal from noise. The resulting series of IW soliton maps provides information on changes in soliton wavelength, velocity, and backscatter intensity. Our marine radar IW signature analysis tool therefore offers a great opportunity of studying the spatiotemporal evolution of IWs as they grow and decay.

Beschreibung: The potential of satellite passive microwave sensors to provide quantitative information about near-source volcanic ash cloud parameters is assessed. To this aim, ground-based microwave weather radar and spaceborne microwave radiometer observations are used together with forward-model simulations. The latter are based on 2-D simulations with the numerical plume model Active Tracer High-Resolution Atmospheric Model (ATHAM), in conjunction with the radiative transfer model Satellite Data Simulator Unit (SDSU) that is based on the deltaEddington approximation and includes Mie scattering. The study area is the Icelandic subglacial volcanic region. The analyzed case study is that of the Grímsvötn eruption in May 2011. ATHAM input parameters are adjusted using available ground data, and sensitivity tests are conducted to investigate the observed brightness temperatures and their variance. The tests are based on the variation of environmental conditions like the terrain emissivity, water vapor, and ice in the volcanic plume. Quantitative correlation analysis between ATHAM/SDSU forward-model columnar content simulations and available microwave radiometric brightness temperature measurements, derived from the Special Sensor Microwave Imager/Sounder (SSMIS), are encouraging in terms of both dynamic range and correlation coefficient. The correlation coefficients are found to vary from $-$ 0.37 to $-$ 0.63 for SSMIS channels from 91 to 183 $pm$ 1 GHz, respectively. The larger sensitivity of the brightness temperature at 183 $pm$ 1 GHz to the columnar content, with respect to other channels, allowed us to consider this channel as the basis for a model-based polynomial relationship of volcanic plume hei- ht as a function of the measured SSMIS brightness temperature.

Beschreibung: Bright curvilinear features arising from the geometry of man-made structures are characteristic of synthetic aperture radar (SAR) images of urban areas, particularly due to double-reflection mechanisms. An approach to urban earthquake damage detection using double-reflection line amplitude change in single-look images has been established in previous literature. Based on this method, this paper introduces an automated tool for fast, unsupervised damage detection in urban areas. Ridge-based curvilinear features are extracted from a preevent SAR image, and double-reflection candidates are selected using prior probability distributions derived from a simple geometrical building model. The candidate features are then used with the ratio of a pair of single preevent and postevent SAR single-look amplitude images to estimate damage levels. The algorithm is very efficient, with overall computational complexity of $O(Nlog k)$ for an $N$ -pixel image containing features of mean length $k$ . The technique is demonstrated using COSMO-SkyMed data covering L'Aquila, Italy, and Port-au-Prince, Haiti.

Beschreibung: It is necessary to measure the sharpness of distributions in many situations. A class of functions is investigated in this paper. First, the relation between this class and sharpness is clarified, and this justifies this class as sharpness measures. Then, we analyze the performance of different sharpness measures and present a guide to select the sharpness measure. In addition, the relation of this class to the sparsity measure is addressed, which leads to a deeper understanding about sparsity. Finally, we show and discuss the application of this class in inverse synthetic aperture radar imaging.

Beschreibung: A detection of radio-frequency interference (RFI) in the space-borne microwave radiometer data is difficult under snow and sea ice-covered conditions. The existing methods such as a spectral difference technique or a principal component analysis (PCA) of RFI indices produce many false RFI signals near the boundary of Greenland and Antarctic ice sheets. In this paper, a double PCA (DPCA) method is developed for RFI detection over Greenland and Antarctic regions. It is shown that the new DPCA method is effective in detecting RFI signals in the C- and X-band radiometer channels of WindSat while removing the false RFI signals over Greenland and Antarctic. It also worked well in other snow-free or snow-rich regions such as winter data over the United States. The proposed DPCA can be applied to satellite radiometer data orbit-by-orbit or granule-by-granule and is thus applicable in an operational environment for fast processing and data dissemination.

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Beschreibung: A super-resolution (SR) method based on compressive sensing (CS), structural self-similarity (SSSIM), and dictionary learning is proposed for reconstructing remote sensing images. This method aims to identify a dictionary that represents high resolution (HR) image patches in a sparse manner. Extra information from similar structures which often exist in remote sensing images can be introduced into the dictionary, thereby enabling an HR image to be reconstructed using the dictionary in the CS framework. We use the K-Singular Value Decomposition method to obtain the dictionary and the orthogonal matching pursuit method to derive sparse representation coefficients. To evaluate the effectiveness of the proposed method, we also define a new SSSIM index, which reflects the extent of SSSIM in an image. The most significant difference between the proposed method and traditional sample-based SR methods is that the proposed method uses only a low-resolution image and its own interpolated image instead of other HR images in a database. We simulate the degradation mechanism of a uniform 2 $times$ 2 blur kernel plus a downsampling by a factor of 2 in our experiments. Comparative experimental results with several image-quality-assessment indexes show that the proposed method performs better in terms of the SR effectivity and time efficiency. In addition, the SSSIM index is strongly positively correlated with the SR quality.

Beschreibung: This paper presents a method and experimental results for near-surface wind sensing using reflected Global Navigation Satellite Systems (GNSS) signals received on a spacecraft. The estimation method proposed involves four steps. First, the bistatic radar cross section (BRCS) of the received signal is estimated from the measurements. Second, the BRCS measurements are calibrated to agree with existing theoretical and empirical wind–wave models. Next, a geometric optics-based scattering model is used to estimate the sea surface slopes, based on the reflection geometry and the measured BRCS. Finally, the surface winds are estimated using an empirically derived function relating the surface mean square slopes to near-surface wind speed. The accuracy of the proposed inversion technique is then tested using a set of 25 space-based GNSS reflection measurements over a range of wind speeds. These measurements were all taken in the proximity of ocean buoys which provided in situ ocean wind speed information. The wind estimates from the buoys were then compared with the wind retrievals made from the measurements and found to be accurate to a root-mean-square error of 1.84 m/s. Additionally, the potential error sources in the measurements are analyzed, including a simulation of the effects of wind direction on the BRCS measurements. This first demonstration of space-based GNSS scatterometry using a small set of sample measurements will hopefully provide a benchmark and example for future experiments.

Beschreibung: There is an error in the above-named article [ibid.,vol. 51, no. 4, pp. 2119??2127, Apr. 2013] regarding the definition and the implementation of equation (3), defining the proposed temporal smoothing index (TSI). The correct formula is provided. These corrections do not change any of the general conclusions of the paper, but some of the comments regarding the interpretation of this table are revised.

Beschreibung: We present a novel method for ground moving target imaging using a synthetic aperture radar system transmitting ultranarrowband continuous waveforms (CW). Our method exploits the high Doppler resolution provided by ultranarrowband CW signals to image both the scene reflectivity and to determine the velocity of multiple moving targets. We develop a new forward model based on the temporal Doppler induced by the movement of antennas and moving targets. The forward model relates reflectivity and velocity information at each location to a correlated received signal. We form the reflectivity images of the moving targets and estimate their motion parameters using a filtered-backprojection (FBP) technique combined with the contrast or gradient optimization method. The method results in focused reflectivity images of moving targets and their velocity estimates, regardless of the target location, speed, and velocity direction. We show that the amplitude and visible edges of the targets can be correctly reconstructed when the correct target velocity estimate is used in the FBP imaging. We present the resolution analysis of the reflectivity images. Extensive numerical simulations demonstrate the performance of our method and validate the theoretical results.

Beschreibung: Environmental Science & Technology DOI: 10.1021/es402249b

Beschreibung: Environmental Science & Technology DOI: 10.1021/es402364w

Beschreibung: Environmental Science & Technology DOI: 10.1021/es401763d

Beschreibung: Environmental Science & Technology DOI: 10.1021/es401837f

Beschreibung: Biochemistry DOI: 10.1021/bi400665t

Beschreibung: Biochemistry DOI: 10.1021/bi400785j

Beschreibung: Biochemistry DOI: 10.1021/bi400770d

Beschreibung: Environmental Science & Technology DOI: 10.1021/es401527q

Beschreibung: Environmental Science & Technology DOI: 10.1021/es402138e

Beschreibung: Environmental Science & Technology DOI: 10.1021/es401932b

Beschreibung: The author has written this short message to introduce himself as the new Editor-in-Chief (EiC) of the IEEE JOURNAL OF OCEANIC ENGINEERING. He took on the role last autumn, following the untimely death of his predecessor, Bill Carey. The new EiC gives an indication of his priorities and plans; as they become fleshed out, he will provide more details in subsequent editorial messages.

Beschreibung: Energy & Fuels DOI: 10.1021/ef4012609

Beschreibung: Energy & Fuels DOI: 10.1021/ef4010658

Beschreibung: Environmental Science & Technology DOI: 10.1021/es402285u

Beschreibung: Energy & Fuels DOI: 10.1021/ef400843c

Beschreibung: Energy & Fuels DOI: 10.1021/ef4013906

Beschreibung: Environmental Science & Technology DOI: 10.1021/es4014807

Beschreibung: This paper presents a novel energy management strategy for a hybridized power source small urban electric vehicle (EV). First, an analysis of load requirements for typical urban driving cycles is presented. Thereafter, the energy and power management issues are addressed for a multisource EV to define an improved management architecture. A dynamically restricted search space strategy coupled with a simulated annealing technique is exploited to accomplish the global optimization of the energy management system (EMS). The control of the dc/dc converter operations based on this EMS is also presented. The multiple sources have been simulated using an overall model implemented in Matlab/Simulink. A reduced-scale prototype has been built to analyze the performance of the energy management strategy. The results obtained show that energy management has been enhanced leading to an increase of the vehicle performance with reduced size embarked sources.

Beschreibung: Prediction intervals (PIs) are a promising tool for quantification of uncertainties associated with point forecasts of wind power. However, construction of PIs using parametric methods is questionable, as forecast errors do not follow a standard distribution. This paper proposes a nonparametric method for construction of reliable PIs for neural network (NN) forecasts. A lower upper bound estimation (LUBE) method is adapted for construction of PIs for wind power generation. A new framework is proposed for synthesizing PIs generated using an ensemble of NN models in the LUBE method. This is done to guard against NN performance instability in generating reliable and informative PIs. A validation set is applied for short listing NNs based on the quality of PIs. Then, PIs constructed using filtered NNs are aggregated to obtain combined PIs. Performance of the proposed method is examined using data sets taken from two wind farms in Australia. Simulation results indicate that the quality of combined PIs is significantly superior to the quality of PIs constructed using NN models ranked and filtered by the validation set.

Beschreibung: This paper presents a supervisory control unit (SCU) combined with short-term ahead wind speed prediction for proper and effective management of the stored energy in a small capacity flywheel energy storage system (FESS) which is used to mitigate the output power fluctuations of an aggregated wind farm. Wind speed prediction is critical for a wind energy conversion system since it may greatly influence the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. In this study, a wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction schemes including data error tolerance and ease in adaptability. The proposed SCU-based control would help to reduce the size of the energy storage system for minimizing wind power fluctuation taking the advantage of prediction scheme. The model for prediction using ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions.

Beschreibung: Due to its reduced communication overhead and robustness to failures, distributed energy management is of paramount importance in smart grids, especially in microgrids, which feature distributed generation (DG) and distributed storage (DS). Distributed economic dispatch for a microgrid with high renewable energy penetration and demand-side management operating in grid-connected mode is considered in this paper. To address the intrinsically stochastic availability of renewable energy sources (RES), a novel power scheduling approach is introduced. The approach involves the actual renewable energy as well as the energy traded with the main grid, so that the supply–demand balance is maintained. The optimal scheduling strategy minimizes the microgrid net cost, which includes DG and DS costs, utility of dispatchable loads, and worst-case transaction cost stemming from the uncertainty in RES. Leveraging the dual decomposition, the optimization problem formulated is solved in a distributed fashion by the local controllers of DG, DS, and dispatchable loads. Numerical results are reported to corroborate the effectiveness of the novel approach.

Beschreibung: The present paper investigates the effect of high penetration of photovoltaic (PV) systems on the small signal stability of a large power system. Reduced system inertia and altered power flow patterns as a result of the addition of the utility scale and residential rooftop PVs that replace a portion of conventional generation resources, may lead to decreased damping of the critical modes of the system. To identify the critical modes of the system and the effect of the high PV penetration on these modes, eigenvalue analysis is carried out on the aforementioned system under various PV penetration levels. To substantiate the results observed from the small signal analysis, transient analysis is carried out on the system under various PV penetration levels. The simulation results effectively identify the impact of high PV penetration on small signal stability of the studied system.

Beschreibung: A speed exclusion zone algorithm to prevent the rotor rotational frequency from exciting the side-side tower mode in a variable-speed wind turbine was designed. The algorithm was first tested on a simple wind turbine model developed in Simulink and then implemented and tested on an experimental test rig. Different speed exclusion zone widths were tested to observe how the performance of the wind turbine is affected. Results obtained from both simulations and experiments showed the effectiveness of the speed exclusion zone algorithm in preventing excitation of tower resonance. Results from different speed exclusion zone widths showed that with a wider exclusion zone, the tower mode is excited less at the expense of a larger power loss.

Beschreibung: A control strategy for the quasi-Z-source inverter (qZSI) with a battery-based photovoltaic (PV) power conversion system is proposed. A battery-assisted qZSI can buck/boost PV panel voltage by introducing shoot-through states, and make full use of PV power by the energy-stored battery paralleled to the quasi-Z-source capacitor. A dynamic small-signal model of the battery-assisted qZSI is established to design a closed-loop controller for regulating shoot-through duty ratio and managing the battery's energy storage. A modified space vector modulation (SVM) technique for the qZSI is applied to achieve low harmonics, high voltage utilization, and high efficiency. A P-Q decoupled grid-tie power injection is fulfilled with the maximum power capture from PV panels and the unity power factor. The validity of the proposed PV system is proved by experimental results, showing an efficient method for the energy-stored PV power generation.

Beschreibung: Doubly-fed induction generator (DFIG)-based wind turbines (WTs) are reported to suffer reliability problems due to the presence of slip-rings, brushes, and the gearbox. These disadvantages encouraged several research groups to investigate the viability of employing single or double-frame brushless cascade DFIGs (BCDFIGs) in grid-connected multimegawatt WTs especially offshore and in solar chimney power plants. In this regard, this paper tackles three main issues. Initially, the expected reduction in gear ratio when BCDFIGs are used instead of DFIGs is examined from a steady state perspective. A reduction would lead to less frequent maintenance and an improved return on investment. Next, a detailed comparison between DFIG-WTs and BCDFIG-WTs under unbalanced grid voltage is presented. Finally, the extent to which a multimegawatt BCDFIG-WT is grid code compliant in terms of fault ride-through capability is studied. This is illustrated by comparing and quantifying the response of a DFIG-WT and a BCDFIG-WT to a severe three-phase voltage dip. Simulation and experimental results indicate promising behavior for BCDFIGs during disturbances.

Beschreibung: We analyze the potential benefits of colocating wind and concentrating solar power (CSP) plants in the southwestern U.S. Using a location in western Texas as a case study, we demonstrate that such a deployment strategy can improve the capacity factor of the combined plant and the associated transmission investment. This is because of two synergies between wind and CSP: 1) the negative correlation between real-time wind and solar resource availability and 2) the use of low-cost high-efficiency thermal energy storage in CSP. The economic tradeoff between transmission and system performance is highly sensitive to CSP and transmission costs. We demonstrate that a number of deployment configurations, which include up to 67% CSP, yield a positive net return on investment.

Beschreibung: Renewable energy resources, especially wind power, are expected to provide a considerable portion of the world energy requirements in the near future. Large-scale wind power penetration impacts the electricity industry in many aspects and raises a number of technical challenges for the electricity network. A day-ahead network-constrained market clearing formulation is proposed which considers demand side resources. The proposed approach can provide flexible load profile and reduce the need for ramp up/down services by the conventional generators. This method can potentially facilitate a large penetration of wind power by shifting the wind power generation from the off-peak periods to the high-peak hours. The validity of the proposed approach has been verified using the IEEE 30 bus and 57 bus test systems.

Beschreibung: The small generation units including cogeneration units and renewables have been widely spread during the last decades. These units raise several questions regarding the power system, e.g., their integration into power system control or their role on the supply-side of smart grids. A multiagent model was established in order to facilitate the investigations of the emerged questions. Several viewpoints are taken into account and built into the model considering technical specifications, proper wind-speed and temperature simulations, constraints of heating service, fuel consumption, legal regulation, outages, and services. A state-based method is elaborated in order to generalize different technologies. The different aspects of operation control are represented by agent strategies. Applying these methods resulted in an easy-to-follow and flexible model. This paper is dealing with the developed multiagent-based model applied to study the distributed generation system from many viewpoints like power system balance, virtual power plant, or smart grid scheduling.

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