Boron incorporation into mullite

Summary Boron-doped mullites were synthesized using aluminium nitrate-nonahydrate, tetraethoxysilane and boric acid in a sol–gel process with subsequent annealing at 950 and 1300 °C for five hours. Two different bulk compositions with constant Al₂O₃ contents (60 and 70 mol%, respectively) and varying SiO₂ plus B₂O₃ contents were investigated. X-ray powder diffraction analyses yielded a linear decrease of the lattice parameters with increasing bulk B₂O₃ content, which was interpreted as to be due to boron incorporation. Related to the increasing boron content, corresponding infrared spectra revealed a slight and continuous shift for most of the absorption bands. These data show that mullite is able to incorporate large amounts of boron into its structure (up to about 20 mol% B₂O₃ depending on the bulk composition of the starting materials). Infrared analyses suggest that boron is incorporated into the mullite structure in form of planar three-fold coordinated BO₃ groups. Author’s address: A. Beran, Institut für Mineralogie und Kristallographie, Universit?t Wien-Geozentrum, Althanstra?e 14, 1090 Wien, Austria     

A gridded monthly upper-air data set from 1918 to 1957

Significant efforts have been devoted in recent years towards extending observation-based three-dimensional atmospheric data sets back in time. Such data sets form an important basis for a better understanding of the climate system. Here we present a new monthly three-dimensional global data set that is based on historical upper-air data and surface data. We use statistical reconstruction techniques, calibrated using ERA-40 data, to obtain gridded data from the numerous, but scattered and heterogeneous historical upper-air observations. In contrast to previous work, in which we used hemispheric principal components on both the predictor and the predictand side to reconstruct spatially complete fields back to 1880, we restrict the procedure to places and times where upper-air observations are available. Each grid column (consisting of four variables at six levels) is then reconstructed independently using only predictor variables in the vicinity (i.e., only local stationarity is required rather than stationary large-scale patterns). The product, termed REC2, is a gridded, global monthly data set of geopotential height, temperature, and u and v wind from 850 to 100?hPa back to 1918. The data set is sparse (i.e., many grid cells are empty), but provides an alternative to large-scale reconstructions as it allows for non-stationary teleconnections. We show the results of several validation experiments, compare our new data set with a number of existing data sets, and demonstrate that it is suitable for analysing large-scale climate variability on interannual time-scales.     

A multi-data set comparison of the vertical structure of temperature variability and change over the Arctic during the past 100?years

We compare the daily, interannual, and decadal variability and trends in the thermal structure of the Arctic troposphere using eight observation-based, vertically resolved data sets, four of which have data prior to 1948. Comparisons on the daily scale between historical reanalysis data and historical upper-air observations were performed for Svalbard for the cold winters 1911/1912 and 1988/1989, the warm winters 1944/1945 and 2005/2006, and the International Geophysical Year 1957/1958. Excellent agreement is found at mid-tropospheric levels. Near the ground and at the tropopause level, however, systematic differences are identified. On the interannual time scale, the correlations between all data sets are high, but there are systematic biases in terms of absolute values as well as discrepancies in the magnitude of the variability. The causes of these differences are discussed. While none of the data sets individually may be suitable for trend analysis, consistent features can be identified from analyzing all data sets together. To illustrate this, we examine trends and 20-year averages for those regions and seasons that exhibit large sea-ice changes and have enough data for comparison. In the summertime Pacific Arctic and the autumn eastern Canadian Arctic, the lower tropospheric temperature anomalies for the recent two decades are higher than in any previous 20-year period. In contrast, mid-tropospheric temperatures of the European Arctic in the wintertime of the 1920s and 1930s may have reached values as high as those of the late 20th and early 21st centuries.     

A reconstructed dynamic Indian monsoon index extended back to 1880

The authors present a reconstruction of summer (June–July–August) mean dynamic Indian monsoon index (DIMI) back to 1880 based on a large number of historical surface observation data as well as information from the upper air data. The reconstruction shows a satisfying skill in terms of both the value of reduction of error and an evaluation against other independent monsoon indices. The skill of reconstruction increases over time with more predictor data (in particular upper-level data) becoming available. A comparison with the observed all Indian summer monsoon rainfall index (AIRI) shows a high consistence in both inter-decadal and inter-annual variability. The reconstruction shows stronger than normal monsoon during the 1880s, 1915–1925 (around 1920) and 1930–1945 (around 1940) as the AIRI. The El Nino/Southern Oscillation (ENSO)—monsoon relationship is reasonably captured in the reconstruction. Powers concentrating within quasi-biennial band stand out in the reconstruction as well as in the AIRI. A comparison of the reconstruction against an atmospheric general circulation model simulation with specified SST and external forcing agents spanning 1901–1999 indicates a slightly higher reproducibility of monsoon circulation than monsoon rainfall in terms of interannual variability. The relationship between the Asian continent warming and the ENSO–monsoon connection is also discussed by using the new dynamic index.     

Oceanic low-angle monopulse radar tracking errors

Radar systems often experience difficulties when tracking low-altitude targets over the ocean because of multipath effects. Whenever the radar cannot resolve the target from its image, it will track a false target position which can move far above or below the actual position. In this paper, mathematical models are utilized to quantitatively determine the degradation in tracking ability of a monopulse radar due to multipath. The model incorporates provisions for the antenna sum and difference patterns, including sidelobes, and for the antenna polarization. Divergence factors are utilized to account for the curvature of the earth's lossy surface. More accurate calculations of the phase length of the direct and reflected rays using the spherical earth model are included. Smooth and rough surface models are used to model the prevailing sea state. The smooth surface model determines both stable and unstable equilibrium directions toward which the target position is indicated. The rough surface model defines a band of maximum error in the indicated position, as a function of the surface waveheight, and it includes both the rough specular and the rough diffuse reflection term.