The redshift dependence of spectral index in powerful radio galaxies

We present and discuss in this paper the rest frame radio spectra (1–25 GHz) of a sample of fourteen radio galaxies atz >2 from the newly defined MRC/1Jy complete sample of 558 radio sources. These galaxies are among the most powerful radio sources known and range in luminosity from 1028-1028·8 watt Hz-1 at 1 GHz. We find that the median rest frame spectral index of this sample of galaxies atz >2 is significantly steeper than that of a matched luminosity sample of 3CRR galaxies which are at a much lower redshift (0.85 <z < 1.7). This indicates that spectral index correlates primarily with redshift, at least in the luminosity range considered here. The difference between the distributions of rest frame spectral curvatures for the two samples does not appear to be statistically significant. We suggest a new explanation for the steeper spectra of radio galaxies at high redshift involving steeper electron energy spectra at injection. Electron energy spectra are expected to steepen in a first-order Fermi acceleration process, at both non-relativistic and relativistic shock fronts, as the upstream fluid velocity decreases. This may well be the case at high redshifts: the hotter and denser circum-galactic medium at high redshifts could result in slower speeds for the hotspot and the jet material behind it. The smaller sizes of radio sources at higher redshifts provide support to this scenario. Since deceased.     

Application of solar max ACRIM data to analysis of solar-driven climatic variability on Earth

Climatic change caused by solar variability has been proposed for at least a century, but could not be assessed reliably in the past because the uncertainty in solar irradiance measured from the Earth's surface is too large. Now satellite measurements by such instruments as the Active Cavity Radiometer Irradiance Monitor (ACRIM) permit a preliminary assessment. The satellite data exhibit irradiance variations over a spectrum of shorter timescales, but the first 5-yr overall trend indicates slightly decreasing luminosity. The global temperature response to monthly-mean ACRIM-measured fluctuations from 1980–1984 was computed from the NYU 1D transient climate model - which includes thermal inertia effects of the world oceans - starting from an assumed pre-existing steady state, and the results compared with observations of recent global temperature trends. The modeled surface temperature evolution exhibited a complex history-dependent behavior whose fluctuations were an order of magnitude smaller than observed, primarily owing to oceanic thermal damping. Thus solar variability appears unlikely to have been an important factor in global-scale climate change over this period. The possibility of using the measurements to develop simple correlations for irradiance with longer term solar activity observable from the surface, and therefore to analyze historical effects, was considered, but is not supported by the satellite data. However, we have used a model of solar irradiance variation with time (Schatten, 1988), covering the period 1976–1997 in order to assess our model's response to forcing whose fluctuation timescale is comparable to the thermal relaxation time of the upper ocean. Continuous monitoring of solar flux by space-based instruments over timescales of 20 yr or more, comparable to timescales for thermal relaxation of the oceans, and of the solar cycle itself, is probably needed to resolve issues of long-term solar variation effects on climate.Presently at Lamont-Doherty Geological Observatory of Columbia University, Palisades, NY 10964.     

Evaluating flood retarding structures

An empirical relation between volume and peak of runoff (VPR) was utilized to determine peak discharge reduction effectiveness of flood retarding structures. The effectiveness was evaluated by comparing the predam VPR relation with and a pre and post dam channel length frequency distribution (CLFD) for the point of interest. The procedure involved well related hydrologic and geomorphic variables and thus could be a practical prediction tool.     

Weathering potential index for rocks based on density and porosity measurements

Rock samples belonging to ten lithological types under different stages of weathering, were collected from different stratigraphical horizons at Bhagalpur. Their densities and porosities were determined experimentally and the data obtained were fitted empirically in a linear equation for each lithological type. The slopes of the curves, which were negative in each case, showed that the increase in porosity for the same decrease in density were in the order, white sandstone > ferruginous sandstone > white claystone > porphyritic gneiss > quartzite > pegmatite > amphibolite ≅ biotite gnejss > basalt ≅ dolerite. A new weathering potential index based on the density-porosity data was proposed and the values for a specific stage of weathering for all the lithological types studied fall within the same range.     

Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces

Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relations among rainfall intensity, slope, and sediment transport were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF-THEN format. The commonly used weighted average method was employed for the defuzzification procedure.The sediment load predicted by the fuzzy model was in satisfactory agreement with the measured sediment load data. Predicting the mean sediment loads from experimental runs, the performance of the fuzzy model was compared with that of the artificial neural networks (ANNs) and the physics-based models. The results of showed revealed that the fuzzy model performed better under very high rainfall intensities over different slopes and over very steep slopes under different rainfall intensities. This is closely related to the selection of the shape and frequency of the fuzzy membership functions in the fuzzy model.     

Rain rate measurements over global oceans from IRS-P4 MSMR

In this paper rain estimation capability of MSMR is explored. MSMR brightness temperature data of six channels corresponding to three frequencies of 10, 18 and 21 GHz are colocated with the TRMM Microwave Imager (TMI) derived rain rates to find a new empirical algorithm for rain rate by multiple regression. Multiple correlation analysis involving various combinations of channels in linear and non-linear forms and rain rate from TMI is carried out, and thus the best possible algorithm for rain rate measurement was identified which involved V and H polarized brightness temperature measurements at 10 and 18 GHz channels. This algorithm explained about 82 per cent correlation (r) with rain rate, and 1.61 mm h^-1 of error of estimation. Further, this algorithm is used for generating global average rain rate map for two contrasting months of August (2000) and January (2001) of northern and southern hemispheric summers, respectively. MSMR derived monthly averaged rain rates are compared with similar estimates from TRMM Precipitation Radar (PR), and it was found that MSMR derived rain rates match well, quantitatively and qualitatively, with that from PR.     

A geomorphologic kinematic‐wave (GKW) model for estimation of floods from small alpine watersheds

A geomorphologic kinematic‐wave (GKW) model was developed for simulation of extreme floods from small alpine catchments. The GKW model couples the kinematic‐wave theory and the geomorphologic representation of the catchment based on the Horton–Strahler ordering scheme. The model was tested on two small alpine catchments in Switzerland, and the agreement between simulated and observed floods was good. Care must however be taken with the computation of slope and roughness parameters. Copyright © 1999 John Wiley & Sons, Ltd.     

Unmelted cosmic metal particles in the Indian Ocean

Fe‐Ni metal is a common constituent of most meteorites and is an indicator of the thermal history of the respective meteorites, it is a diagnostic tool to distinguish between groups/subgroups of meteorites. In spite of over a million micrometeorites collected from various domains, reports of pure metallic particles among micrometeorites have been extremely rare. We report here the finding of a variety of cosmic metal particles such as kamacite, plessite, taenite, and Fe‐Ni beads from deep‐sea sediments of the Indian Ocean, a majority of which have entered the Earth unaffected by frictional heating during atmospheric entry. Such particles are known as components of meteorites but have never been found as individual entities. Their compositions suggest precursors from a variety of meteorite groups, thus providing an insight into the metal fluxes on the Earth. Some particles have undergone heating and oxidation to different levels during entry developing features similar to I‐type cosmic spherules, suggesting atmospheric processing of individual kamacites/taenite grains as another hitherto unknown source for the I‐type spherules. The particles have undergone postdepositional aqueous alteration transforming finally into the serpentine mineral cronstedtite. Aqueous alteration products of kamacite reflect the local microenvironment, therefore they have the potential to provide information on the composition of water in the solar nebula, on the parent bodies or on surfaces of planetary bodies. Our observations suggest it would take sustained burial in water for tens of thousands of years under cold conditions for kamacites to alter to cronstedtite.