An Analytical Model For Threshold Crossing Rates Of Concentration Fluctuations In Dispersing Plumes

A simple analytical model is developed for the meanupcrossing rate of plume concentration fluctuations assuming that thisprocess can be well approximated by a lognormal process. The resultingexpression requires only the specification of the in-plume fluctuationintensity and in-plume Taylor micro-time scale and, hence, does notexplicitly involve the joint probability density function of theconcentration and its derivative. The analytical model provides agood fit to some field measurements of the mean upcrossing rate ina dispersing plume.     

Middle Miocene thermal metamorphism due to the infiltration of high-temperature fluid in the Sanbagawa metamorphic belt,southwest Japan

 The Middle Miocene Tobe hornfels in the Sanbagawa metamorphic belt, western Shikoku, southwest Japan, is characterized by an abnormally steep metamorphic gradient compared with other hornfelses associated with intrusive bodies. The basic hornfels, originally Sanbagawa greenschist rocks, is divided into the following three metamorphic zones: plagioclase, hornblende, and orthopyroxene. The plagioclase zone is defined by the appearance of calcic plagioclase, the hornblende zone by the assemblage of hornblende+calcic plagioclase+quartz, and the orthopyroxene zone is characterized by the assemblage of orthopyroxene + clinopyroxene + plagioclase + quartz. Calcic amphibole compositions change from actinolite to hornblende as a result of the continuous reactions during prograde metamorphism. Petrographical and thermometric studies indicate a metamorphic temperature range of 300–475°C for the plagioclase zone, 475–680°C for the hornblende zone, and 680–730°C for the orthopyroxene zone. The temperature gradient based on petrological studies is approximately 5°C/m, which is unusually high. Geological and petrological studies demonstrate that the hornfelses were formed by the focusing of high-temperature fluids through zones of relatively high fracture permeability. The steep thermal gradient in the Tobe hornfels body is consistent with a large fluid flux, greater than 8.3 × 10^–7 m³ m^–2S^–1, over the relatively short duration of metamorphism, approximately 100 years. Received: 10 October 1995 / Accepted: 28 May 1996     

Study on uncertainty of inversion and resolution limit in the presence of noise

This study analyzed the uncertainty of inversion and the resolution limit in the presence of noise by means of statistical experiments. The exhaustive method is adopted to obtain the global optimal solution in each experiment. We found that even with small level of noise, solutions fluctuate in a large range for the thin bed. The distribution of solutions in the presence of noise is closely related to the spread of the cost function in the absence of noise. As a result, the area of a certain neighborhood around the true solution on the spread of the cost function in the absence of noise is used to evaluate the uncertainty of inversion and the resolution limit in the presence of noise. In the case that the SNR (signal-to-noise ratio) is 5 in this study, solutions focus around the true solution with a very small uncertainty only when the bed thickness is greater than the reciprocal of the double predominant frequency of the convoluting wavelet.     

An inter-comparison of tidal solutions computed with a range of unstructured grid models of the Irish and Celtic Sea Regions

Three finite element codes, namely TELEMAC, ADCIRC and QUODDY, are used to compute the spatial distributions of the M₂, M₄ and M₆ components of the tide in the sea region off the west coast of Britain. This region is chosen because there is an accurate topographic dataset in the area and detailed open boundary M₂ tidal forcing for driving the model. In addition, accurate solutions (based upon comparisons with extensive observations) using uniform grid finite difference models forced with these open boundary data exist for comparison purposes. By using boundary forcing, bottom topography and bottom drag coefficients identical to those used in an earlier finite difference model, there is no danger of comparing finite element solutions for “untuned unoptimised solutions” with those from a “tuned optimised solution”. In addition, by placing the open boundary in all finite element calculations at the same location as that used in a previous finite difference model and using the same M₂ tidal boundary forcing and water depths, a like with like comparison of solutions derived with the various finite element models was possible. In addition, this open boundary was well removed from the shallow water region, namely the eastern Irish Sea where the higher harmonics were generated. Since these are not included in the open boundary, forcing their generation was determined by physical processes within the models. Consequently, an inter-comparison of these higher harmonics generated by the various finite element codes gives some indication of the degree of variability in the solution particularly in coastal regions from one finite element model to another. Initial calculations using high-resolution near-shore topography in the eastern Irish Sea and including “wetting and drying” showed that M₂ tidal amplitudes and phases in the region computed with TELEMAC were in good agreement with observations. The ADCIRC code gave amplitudes about 30 cm lower and phases about 8° higher. For the M₄ tide, in the eastern Irish Sea amplitudes computed with TELEMAC were about 4 cm higher than ADCIRC on average, with phase differences of order 5°. For the M₆ component, amplitudes and phases showed significant small-scale variability in the eastern Irish Sea, and no clear bias between the models could be found. Although setting a minimum water depth of 5 m in the near-shore region, hence removing wetting and drying, reduced the small-scale variability in the models, the differences in M₂ and M₄ tide between models remained. For M₆, a significant reduction in variability occurred in the eastern Irish Sea when a minimum 5-m water depth was specified. In this case, TELEMAC gave amplitudes that were 1 cm higher and phases 30° lower than ADCIRC on average. For QUODDY in the eastern Irish Sea, average M₂ tidal amplitudes were about 10 cm higher and phase 8° higher than those computed with TELEMAC. For M₄, amplitudes were approximately 2 cm higher with phases of order 15° higher in the northern part of the region and 15° lower in the southern part. For M₆ in the north of the region, amplitudes were 2 cm higher and about 2 cm lower in the south. Very rapid M₆ tidal-phase changes occurred in the near-shore regions. The lessons learned from this model inter-comparison study are summarised in the final section of the paper. In addition, the problems of performing a detailed model–model inter-comparison are discussed, as are the enormous difficulties of conducting a true model skill assessment that would require detailed measurements of tidal boundary forcing, near-shore topography and precise knowledge of bed types and bed forms. Such data are at present not available.     

Amplitudes of long-period PcP and the core-mantle boundary

The amplitudes of the core reflection PcP are sensitive to the wave velocities and densities in the neighborhood of the core-mantle boundary (CMB). We study the amplitude ratio of the long-period phases PcP and P from two South American deep-focus earthquakes with favorable fault-plane solution, depth and magnitude, as recorded by WWNSS and CSN stations in North America.Comparison is made with long-period PcP/P amplitude ratios, derived from theoretical seismograms for a variety of CMB models. Models from previous studies, which were mainly derived from short-period PcP observations and which are characterized by discrete layers above the CMB, are almost all inconsistent with the long-period data. The data also discriminate against low nonzero S velocities below the CMB. Simple first-order-discontinuity models of the CMB, for instance according to the Jeffreys-Bullen earth model or according to recent models based mainly on free oscillations, explain the data reasonably well.Model improvements are attempted by varying the P-velocity gradient above the CMB. The best amplitude fit is obtained for a rather strong decrease in P velocity with depth in this zone which, however, gives no acceptable traveltime fit for PcP. The scatter in body-wave amplitudes is considerable even for long-period waves and may prevent the correct assessment of that part of the amplitude variation of a phase with distance that is due to the variation of velocities and densities with depth alone.     

Reconstruction of cropland spatial patterns and its spatiotemporal changes over the 20th century on the Songnen Plain,Northeast China

We initially estimated the cropland area at county level using local historical documents for the Songnen Plain (SNP) in the 1910s and 1930s. We then allocated this cropland area to grid cells with a size of 1 km × 1 km, using a range of cultivation possibilities from high to low; this was based on topography and minimum distances to rivers, settlements, and traffic lines. Cropland areas for the 1950s were obtained from the Land Use Map of Northeast China, and map vectorization was performed with ArcGIS technology. Cropland areas for the 1970s, 1980s, 1990s, 2000s, and 2010s were retrieved from Landsat images. We found that the cropland areas were 4.92 × 10⁴ km² and 7.60 × 10⁴ km², accounting for 22.8% and 35.2% of the total area of the SNP in the 1910s and 1930s, respectively, which increased to 13.14 × 10⁴ km², accounting for 60.9% in the 2010s. The cropland increased at a rate of 1.18 × 10⁴ km² per decade from the 1910s to 1970s while it was merely 0.285 × 10⁴ km² per decade from the 1970s to 2010s. From the 1910s to 1930s, new cultivation mainly occurred in the central SNP while, from the 1930s to 1970s, it was mainly over the western and northern parts. This spatially explicit reconstruction could be offered as primary data for studying the effects of changes in human-induced land cover based on climate change over the last century.