Intercalibration of Solar Soft X-Ray Broad Band Measurements from SOLRAD 9 through GOES-12

The two-band soft X-ray observations of solar flares made by the Naval Research Laboratory’s (NRL) SOLar RADiation (SOLRAD) satellites and by the Geostationary Orbiting Environmental Satellites (GOES) operated by the National Oceanic and Atmospheric Administration’s (NOAA) Space Weather Prediction Center have produced a nearly continuous record of solar flare observations over a period of more than forty years (1969 – 2011). However, early GOES observations (i.e., GOES-2) and later (GOES-8 and subsequent missions) are not directly comparable due to changes in the conversion of measured currents to integrated fluxes in the two spectral bands that were adopted: 0.05 – 0.3 (or 0.4) nm, which we refer to as XS and 0.1 – 0.8 nm (XL). Furthermore, additional flux adjustments, using overlapping data sets, were imposed to provide consistency of flare-flux levels from mission to mission. This article evaluates the results of these changes and compares experimental GOES-8/GOES-2 results with changes predicted from modeled flare spectra. The factors by which recent GOES observations can be matched to GOES-2 are then optimized by adapting a technique first used to extrapolate GOES X-ray fluxes above saturation using ionospheric VLF radio phase enhancements. A nearly 20% increase in published GOES-8 XL data would be required to match to GOES-2 XL fluxes, which were based on observed flare spectra. On the other hand, a factor of 1.07 would match GOES-8 and later flat-spectrum 0.1 – 0.8 nm fluxes to GOES-2 XL if the latter data were converted to a flat-spectrum basis. Finally, GOES-8 observations are compared to solar soft X-ray estimates made concurrently with other techniques. Published GOES-8 0.1 – 0.8 nm fluxes are found to be 0.59 of the mean of these other determinations. Rescaling GOES to a realistic flare spectrum and removing a 30% downward adjustment applied to the GOES-8 measurements during initial data processing would place GOES-8 and later GOES XL fluxes at 0.94 of this XL mean. GOES-2 on the same scale would lie at about 0.70 of this mean. Significant uncertainties in the absolute levels of broad band soft X-ray fluxes still remain, however.     

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.     

共和盆地黏土矿物与孢粉记录的末次冰消期以来的气候环境相位差

在青藏高原北缘共和盆地达连海钻取了40.92 m沉积柱,其¹⁴C年代有10个控制点,底部年龄最大值为14.5 cal ka BP,沉积柱为末次冰消期以来的湖泊沉积物。在沉积柱中按20 cm/70 a分辨率选出200个样品进行了黏土矿物、粒度、碳酸盐、沉积速率等非生物指标与生物指标的孢粉等多项指标的综合分析。结果表明：末次冰消期以来,达连海沉积柱中非生物指标与生物指标反映的气候和环境变化阶段的显著性不同,反映的气候环境的变化阶段也不尽一致,出现气候环境的相位差。冰消期黏土矿物非生物指标与孢粉生物指标有约1.0~1.2 ka的相位差;早、中全新世黏土矿物反映的气候变化时段较孢粉指标指示的时段滞后约1.0 ka;在晚全新世黏土矿物反映的气候变化较孢粉滞后约0.1 ka。造成黏土矿物和孢粉反映气候环境相位差的原因是孢粉和黏土矿物对气候响应的差异性、黏土矿物和孢粉搬运方式的不同、气候条件及其转换、地貌等多因素的综合影响。     

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.     

基于CiteSpace中国海洋经济研究的知识图谱分析

利用CiteSpace可视化文献分析工具对1982~2013年CNKI总库中文核心期刊以及CSSCI中文社会科学引文数据库中海洋经济研究的3 441篇相关文献进行分析,绘制出研究热点、核心作者群及研究机构的知识结构图谱。结果表明：自中国海洋经济研究会成立以来,中国海洋经济研究主要围绕 “海洋经济”、“海洋产业”、“可持续发展”、“海洋资源”、“海洋开发”、“滨海旅游”等展开;韩增林、张耀光、郑贵斌、殷克东、李靖宇、徐志斌等是主要的发文作者;国家海洋局、中国海洋大学、辽宁师范大学和广东海洋大学为发文较多的机构;《海洋开发与管理》是海洋经济相关研究载文量最多的期刊,《经济地理》、《中国人口·资源与环境》、《地域研究与开发》、《资源科学》等是主要的载文核心期刊。除了传统的海洋经济研究视角下,区域海洋经济差异、海洋产业结构与布局及优化、海洋产业竞争力、海洋产业集群、现代海洋产业、海洋资源开发利用的可持续、人海关系的脆弱性、滨海旅游等的研究外,在新的国际和国内形势下,海洋经济相关理论、战略性新兴海洋产业研究、海洋经济可持续发展研究、及“一路一带”战略对海洋经济相关研究的新要求也是需要重点关注的方面。     

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.     

GPU accelerated marine data visualization method

The study of marine data visualization is of great value. Marine data, due to its large scale, random variation and multiresolution in nature, are hard to be visualized and analyzed. Nowadays, constructing an ocean model and visualizing model results have become some of the most important research topics of ‘Digital Ocean'. In this paper, a spherical ray casting method is developed to improve the traditional ray-casting algorithm and to make efficient use of GPUs. Aiming at the ocean current data, a 3D view-dependent line integral convolution method is used, in which the spatial frequency is adapted according to the distance from a camera. The study is based on a 3D virtual reality and visualization engine, namely the VV-Ocean. Some interactive operations are also provided to highlight the interesting structures and the characteristics of volumetric data. Finally, the marine data gathered in the East China Sea are displayed and analyzed. The results show that the method meets the requirements of real-time and interactive rendering.     

地层证据--对大别造山带汇聚历史的制约

大别造山带的汇聚演化历史一直存在不同的认识,来自扬子陆块和华北陆块显生宙以来的地层记录以及北淮阳地区的地层记录可能为两个陆块的汇聚模式提供制约。通过对扬子陆块与华北陆块显生宙以来岩相古地理进行比较,其中3个阶段相似, 2个阶段差别很大。以浊积岩发育作为俯冲阶段的标志,磨拉石建造出现作为闭合的标志,显生宙以来,大别造山带曾经历了两次俯冲和两次汇聚,俯冲时间分别是晚奥陶世—早志留世和早三叠世,汇聚的时间分别为中 晚泥盆世和中三叠世,早期的汇聚具有软碰撞特征,以上认知得到了北淮阳地区地层、古生物和沉积记录的支持,同时也与大别山造山带榴辉岩的同位素年龄数据基本吻合。高压 超高压变质岩在晚三叠世处于快速折返阶段,早侏罗世以前到达地表,其平均折返隆升速率为39～66mm/a。     

STUDY ON BIOLOGICAL ACTIVITY OF SELENIUM-ENRICHED MUSSEL EXTRACT

ThisworksupportedbytheScienceandTechnologyCommitteeofShandongProvince.Grant(95)50.INTRODUCTIONManyinvestigationsindicatalthatsupplementation0fsuitableseleniumleveIstolowordefidentinseleniumdietcanpreventoccurrenceofvarioustumots(Chen,l990),enhanceorganisminimneability(Wu,l992),maintainthenormalfunCtion0fheart,liv-er,lungandstomach(Schwarzetal,l957),andisgoodpareuti0nsagainstcardiovascularandcerebrovascu1arproblemsinoldpeople.Seleniumisanessentialtraeeelernentfornonnalhumanlife(Balassa…     

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.