The global positioning system (GPS) differential code biases (DCB) provided by the International GNSS Service (IGS) show solar-cycle-like variation during 2002–2013. This study is to examine whether this variation of the GPS DCBs is associated with ionospheric variability. The GPS observations from low earth orbit (LEO) satellites including CHAMP, GRACE and Jason-1 are used to address this issue. The GPS DCBs estimated from the LEO-based observations at different orbit altitudes show a similar tendency as the IGS DCBs. However, this solar-cycle-like dependency is eliminated when the DCBs of 13 continuously operating GPS satellites are constrained to zero-mean. Our results thus revealed that ionospheric variation is not responsible for the long-term variation of the GPS DCBs. Instead, it is attributed to the GPS satellite replacement with different satellite types and the zero-mean condition imposed on all satellite DCBs. 相似文献
Factors influencing millennial-scale variability in the thermocline depth (vertical mixing) and sea surface salinity (SSS) of the southern Okinawa Trough (OT) during the past 17,300 years were investigated based on foraminifer oxygen isotope records of the surface dweller Globigerinoides ruber sensu stricto and the thermocline dweller Pulleniatina obliquiloculata in the AMS 14C dated OKT-3 core. The thermocline depth is influenced by surface thermal buoyancy (heat) flux, in turn controlled by the annual mean insolation at 30°N and the strength of the East Asian winter monsoon (EAWM). Strong insolation and weak EAWM tend to increase buoyancy gain (decrease buoyancy loss), corresponding to shallow thermocline depths, and vice versa. Regional SSS is influenced by the global ice volume, the Kuroshio Current (KC), and vertical mixing. A deep thermocline coincides with a high SSS because strong vertical mixing brings more, saltier subsurface KC water to the surface, and vice versa. Local SSS (excluding the global ice volume effect) became lower in the northern OT than in the southern OT after ~9.2 ka, implying that Changjiang diluted water had stronger influence in the northern sector. SSS show no major changes during the Bølling/Allerød and Younger Dryas events, probably because the KC disturbed the North Atlantic signals. This argues against earlier interpretations of sea surface temperature records of this core. Wavelet and spectral analyses of the Δδ18OP-G (δ18O of P. obliquiloculata minus G. ruber s.s.) and δ18Olocal records display 1,540-, 1,480-, 1,050-, 860-, 640-, and 630-year periods. These are consistent with published evidence of a pervasive periodicity of 1,500 years in global climate as well as EAWM and KC signatures, and a fundamental solar periodicity of 1,000 years and intermediary derived periodicity of 700 years. 相似文献
Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region. 相似文献
Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVID) was derived, and the global and local Moran’s I of the SVID were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVID values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.
