Analysis of drought areas in northern Algeria using Markov chains

Journal of Earth System Science - The present work studies the trends in drought in northern Algeria. This region was marked by a severe, wide-ranging and persistent drought due to its...     

The radio counterpart of the likely TeV binary HESS J0632+057

The few known γ-ray binary systems are all associated with variable radio and X-ray emission. The TeV source HESS J0632+057, apparently associated with the Be star MWC 148, is plausibly a new member of this class. Following the identification of a variable X-ray counterpart to the TeV source we conducted Giant Metrewave Radio Telescope (GMRT) and Very Large Array (VLA) observations in 2008 June–September to search for the radio counterpart of this object. A point-like radio source at the position of the star is detected in both 1280-MHz GMRT and 5-GHz VLA observations, with an average spectral index, α, of ∼0.6. In the VLA data there is significant flux variability on ∼month time-scales around the mean flux density of ≈0.3 mJy. These radio properties (and the overall spectral energy distribution) are consistent with an interpretation of HESS J0632+057 as a lower power analogue of the established γ-ray binary systems.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

Meteorological inventory of rain-on-snow events in the Canadian Arctic Archipelago and satellite detection assessment using passive microwave data

The spatial and temporal distributions of rain-on-snow (ROS) events across the Canadian Arctic Archipelago (CAA) remain poorly understood owing to their sporadic nature in time and space. This situation motivated the development of remote sensing detection algorithms. This paper uses a large meteorological dataset across the CAA to adapt an existing ROS-detection algorithm developed in a previous study by our group. Results highlight the spatial distribution and evolution of ROS occurrences reported since 1985 at 14 weather stations across the CAA. Results show that >600 ROS events were inventoried since 1985, for which >70% were classified as pure rain (liquid form) and 30% as mixed precipitation (solid/liquid). Of the pure rain events, 75% occurred during spring, 14% during fall, 8% during summer and <1% during winter. Such events can have significant impacts on ungulate grazing conditions through the creation of ice layers, causing serious problems for caribou calf survival, especially during the migration period. This paper introduces an adaptation for larger scale Arctic application of a detection algorithm (sensitivity analysis on the detection threshold) with an error of ~5%. The validation, however, remains limited due to a short study period and limited number of sites.     

High albedos of low inclination Classical Kuiper belt objects

We present observations of thermal emission from fifteen transneptunian objects (TNOs) made using the Spitzer Space Telescope. Thirteen of the targets are members of the Classical population: six dynamically hot Classicals, five dynamically cold Classicals, and two dynamically cold inner Classical Kuiper belt objects (KBOs). We fit our observations using thermal models to determine the sizes and albedos of our targets finding that the cold Classical KBOs have distinctly higher visual albedos than the hot Classicals and other TNO dynamical classes. The cold Classicals are known to be distinct from other TNOs in terms of their color distribution, size distribution, and binarity fraction. The Classical objects in our sample all have red colors yet they show a diversity of albedos which suggests that there is not a simple relationship between albedo and color. As a consequence of high albedos, the mass estimate of the cold Classical Kuiper belt is reduced from approximately 0.01 M_⊕ to approximately 0.001 M_⊕. Our results also increase significantly the sample of small Classical KBOs with known albedos and sizes from 21 to 32 such objects.     

Combination of Spectral and Textural Features in the MSG Satellite Remote Sensing Images for Classifying Rainy Area into Different Classes

The rainfall intensity classification technique using spectral and textural features from MSG/SEVIRI (Meteosat Second Generation/Spinning Enhanced Visible and Infrared) satellite data is proposed in this paper. The study is carried out over north of Algeria. The developed method is based on the artificial neural multilayer perceptron network (MLP). Two MLP algorithms are used: the MLP-S based only on spectral parameters and the MLP-ST that use both spectral and textural features. The MLP model is created with three layers (input, hidden, and output) that consist of 6 output neurons in the output layer that represent the 6 rain intensities classes: very high, moderate to high, moderate, light to moderate, light and no rain and 10 spectral input neurons for the MLP-S and 15 input neurons for MLP-ST, which as ten spectral features that were calculated from MSG thermal infrared brilliance temperature and brilliance temperature difference and as five textural features, and The rainfall intensity areas classified by the proposed technique are validated against ground-based radar data. The rainfall rates used in the training set are derived from Setif radar measurements (Algeria). The results obtained after applying this method show that the introduction of textural parameters as additional information works in improving the classification of different rainfall intensities pixels in the MSG/SEVIRI imagery compared to the techniques based only on spectral information. These results are compared with results obtained with the probability of rainfall intensity (PRI). This comparison revealed a clear outperformance of the MLP algorithms over the PRI algorithms. Best results are provided by the MLP-ST algorithm. The combination of spectral and textural features in the MSG–SEVIRI imagery is important and for the classification of the rainfall intensities to different classes.     

Trace metal enrichments in Lake Tanganyika sediments: Controls on trace metal burial in lacustrine systems

We investigate the distributions of several key diagenetic reactants (C, S, Fe) and redox-sensitive trace metals (Mo, Cd, Re, U) in sediments from Lake Tanganyika, East Africa. This study includes modern sediments from a chemocline transect, which spans oxygenated shallow waters to sulfidic conditions at depth, as well as ancient sediments from a longer core (∼2 m) taken at ∼900 m water depth. Modern sediments from depths spanning ∼70-335 m are generally characterized by increasing enrichments of C, S, Mo, Cd, and U with increasing water depth but static Fe distributions. It appears that the sedimentary enrichments of these elements are, to varying degrees, influenced by a combination of organic carbon cycling and sulfur cycling. These modern lake characteristics contrast with a period of high total organic carbon (C_org), total sulfur (S_Tot), and trace metal concentrations observed in the 900 m core, a period which follows the most recent deglaciation (∼18-11 ky). This interval is followed abruptly by an interval (∼11-6 ky) that is characterized by lower C, S, U, and Mo. Consistent with other work we suspect that the low concentrations of S, Mo, and U may indicate a period of intense lake mixing, during which time the lake may have been less productive and less reducing as compared to the present. An alternative, but not mutually exclusive, hypothesis is that changes in the lake’s chemical inventory, driven by significant hydrological changes, could be influencing the distribution of sedimentary trace elements through time.