南海季风爆发前后辐射特征分析

利用“2000年南海海气通观测”项目现场观测的辐射资料分析了南海季风爆发前后南海太阳总辐射，海面反射辐射，大气长波辐射，海面长波辐射，净余辐射的日变化和逐日变化规律的实际事实，结果表明，季风爆发前后，云系增多云层增厚，对太阳总辐射，海面反射辐射，海洋和大气长波辐射均有显著的影响，季风爆发期间产生的大浪对海面反射辐射，洋面反射率影响很大，可导致两者的强度急剧增加。     

对近年来主要科技期刊有关GIS论文的统计分析

对近年来国内主要科技期刊上有关 GIS论文进行了统计与分析 ,展示了近年来我国 GIS科学研究的现状和水平 ,揭示了这一学科的应用范围、研究者现状、分布的特点和规律 ,明确了 GIS在国民经济建设中的重要地位。对GIS的发展阶段给予了评价。     

Analysis on statistic characteristics of magnetotelluric signal

For magnetotelluric sounding (MT), many processing methods based on power spectrum have put forward lots of hypotheses, such as MT signals are Gaussian, linear and minimum-phase. If practical signals do not satisfy these requirements, the results will have a few problems as follows. Firstly, when signals are non-linear and non-Gaussian, the information of the earth contained in the MT signals cannot be sufficiently extracted; Secondly, when signals are non-Gaussian and non-minimum phase, the processed results cannot reflect the minimum phase characteristics of the signals. Hence, it is necessary for us to do further research on characteristics of MT signals (YAO, SUN, 1999; LI, CHENG, 2002; Nikias, Petropulu, 1993; ZHANG, 1996). Otherwise, we cannot judge the reliability of the processed results based on power spectrum.     

Modelling of the thermal history of metamorphic zoning in the Connemara region (western Ireland)

The Connemara region of the Irish Caledonides is a classic example of regional-scale metamorphism of low pressure and high temperature. This terrane is considered as part of a fold belt comprising metasedimentary and metavolcanic rocks that are correlated with the Neoproterozoic–Lower Paleozoic Dalradian Supergroup of Scotland. In mid-Ordovician time, the extensive and high-temperature metamorphism was superimposed on the Dalradian rocks resulting in the Connemara zoning. The key feature of the zoning is elevated horizontal thermal gradient of ca. 14 °C/km. Geological data and geochronological evidence point to a causative link between metamorphism and associated magmatic intrusions, and a brief period of development for the metamorphic zoning. Magmatic intrusion into the middle part of continental crust is treated as a most plausible source of heat for metamorphism, and other conjectures as to the origin of the zoning (flow of hot fluid through the permeable rocks, fracture conduit flushed by flowing magma) are believed to be improbable. To examine in sufficient detail the problem of the nature of heat source, a series of appropriate calculations have been performed to reach the best agreement between the observed and simulated spatial distribution of maximum temperatures at different times. The mathematical modelling shows that the temperature–spatial structure of the Connemara zoning is best explained by the model version based on mid-crustal heating above the upper contact of magmatic intrusive body gently curved and tilted at an angle between 20° and 40°, with an initial temperature of the magma appropriate to a basaltic melt. The model estimate of total lifetime of the temperature anomaly in the crust is of the order of 5–6 Ma. In general, this is in rather good agreement with the currently available evidence of geochronological duration of metamorphism and magmatism in Connemara.     

Landslide inventories and their statistical properties

Landslides are generally associated with a trigger, such as an earthquake, a rapid snowmelt or a large storm. The landslide event can include a single landslide or many thousands. The frequency–area (or volume) distribution of a landslide event quanti?es the number of landslides that occur at different sizes. We examine three well‐documented landslide events, from Italy, Guatemala and the USA, each with a different triggering mechanism, and ?nd that the landslide areas for all three are well approximated by the same three‐parameter inverse‐gamma distribution. For small landslide areas this distribution has an exponential ‘roll‐over’ and for medium and large landslide areas decays as a power‐law with exponent ‐2·40. One implication of this landslide distribution is that the mean area of landslides in the distribution is independent of the size of the event. We also introduce a landslide‐event magnitude scale m_L = log(N_LT), with N_LT the total number of landslides associated with a trigger. If a landslide‐event inventory is incomplete (i.e. smaller landslides are not included), the partial inventory can be compared with our landslide probability distribution, and the corresponding landslide‐event magnitude inferred. This technique can be applied to inventories of historical landslides, inferring the total number of landslides that occurred over geologic time, and how many of these have been erased by erosion, vegetation, and human activity. We have also considered three rockfall‐dominated inventories, and ?nd that the frequency–size distributions differ substantially from those associated with other landslide types. We suggest that our proposed frequency–size distribution for landslides (excluding rockfalls) will be useful in quantifying the severity of landslide events and the contribution of landslides to erosion. Copyright © 2004 John Wiley & Sons, Ltd.     

Landslides triggered by the 23 November 2000 rainfall event in the Imperia Province, Western Liguria, Italy

From mid-October to 22 November 2000, the western Liguria Region of Italy experienced prolonged and intense rainfall, with cumulative values exceeding 1000 mm in 45 days. The severe rainfall sequence ended on November 23 with a high-intensity storm that dumped more than 180 mm of rain in 24 h. The high-intensity event caused flooding and triggered more than 1000 soils slips and debris flows and a few large, complex landslides. Slope failures caused three fatalities and severe damage to roads, private homes, and agriculture. Large (1:13,000) and very large (1:5000) scale colour aerial photographs were taken 45 days after the event over the areas most affected by the landslides. Through the interpretation of the 334 photographs covering an area of 500 km², we prepared a landslide inventory map that shows 1204 landslides, for a total landslide area of 1.6 km². We identified the rainfall conditions that triggered landslides in the Armea valley using cumulative- and continuous-rainfall data, combined with detailed information on the time of landslide occurrence. Landslide activity initiated 8 to 10 h after the beginning of the storm, and the most abundant activity occurred in response to rainfall intensities of 8 to 10 mm per hour. For the Ceriana Municipality, an area where the landslides were numerous in November 2000, we also collected information about a historical event that occurred on 8–11 December 1910 and triggered abundant landslides resulting in severe economic damage. A comparison of the damage caused by the historical and the recent landslide events indicated that damage caused by the 1910 historical event was more diffused but less costly than the damage caused by the 2000 event.     

The quality and qualities of population statistics, and the place of the census

Population counts are a key anchor for much of the official statistical system and the benchmark for many commercial and research surveys and analysis. Statistical offices around the world face a wide range of challenges in counting their population, most particularly in the years between censuses, as population flows become much freer and family structures continue to evolve. This paper considers these issues, reviewing how population counts have evolved over time in the UK and other countries. The paper also looks to the future, considering ways in which population count methodology might develop.     

Identifying insect infestation hot spots: an approach using conditional spatial randomization

Epidemic populations of mountain pine beetle highlight the need to understand landscape scale spatial patterns of infestation. The observed infestation patterns were explored using a randomization procedure conditioned on the probability of forest risk to beetle attack. Four randomization algorithms reflecting different representations of the data and beetle processes were investigated. Local test statistics computed from raster representations of surfaces of kernel density estimates of infestation intensity were used to identify locations where infestation values were significantly higher than expected by chance (hot spots). The investigation of landscape characteristics associated with hot spots suggests factors that may contribute to high observed infestations.