A methodology for precise determination of the fundamental geodetic parameter w0, the potential value of the Gauss–Listing geoid, as well as its time derivative 0, is presented. The method is based on: (1) ellipsoidal harmonic expansion of the external gravitational field of the Earth
to degree/order 360/360 (130 321 coefficients; http://www.uni-stuttgard.de/gi/research/ index.html projects) with respect
to the International Reference Ellipsoid WGD2000, at the GPS positioned stations; and (2) ellipsoidal free-air gravity reduction
of degree/order 360/360, based on orthometric heights of the GPS-positioned stations. The method has been numerically tested
for the data of three GPS campaigns of the Baltic Sea Level project (epochs 1990.8,1993.4 and 1997.4). New w0 and 0 values (w0=62 636 855.75 ± 0.21 m2/s2, 0=−0.0099±0.00079 m2/s2 per year, w0/&γmacr;=6 379 781.502 m,0/&γmacr;=1.0 mm/year, and &γmacr;= −9.81802523 m2/s2) for the test region (Baltic Sea) were obtained. As by-products of the main study, the following were also determined: (1)
the high-resolution sea surface topography map for the Baltic Sea; (2) the most accurate regional geoid amongst four different
regional Gauss–Listing geoids currently proposed for the Baltic Sea; and (3) the difference between the national height datums
of countries around the Baltic Sea.
Received: 14 August 2000 / Accepted: 19 June 2001 相似文献
Asian monsoon have multiple forms of variations such as seasonal variation, intra-seasonal variation, interannual variation,
etc. The interannual variations have not only yearly variations but also variations among several years. In general, the yearly
variations are described with winter temperature and summer precipitation, and the variations among several years are reflected
by circulation of ENSO events. In this study, at first, we analyze the relationship between land cover and interannual monsoon
variations represented by precipitation changes using Singular Value Decomposition method based on the time series precipitation
data and 8km NOAA AVHRR NDVI data covering 1982 to 1993 in east Asia. Furthermore, after confirmation and reclassification
of ENSO events which are recognized as the strong signal of several year monsoon variation, using the same time series NDVI
data during 1982 to 1993 in east Asia, we make a Principle Component Analysis and analyzed the correlation of the 7th component
eigenvectors and Southern Oscillation Index (SOI) that indicates the characteristic of ENSO events, and summed up the temporal-spatial
distribution features of east Asian land cover’s inter-annual variations that are being driven by changes of ENSO events. 相似文献
Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.
The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.
The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes. 相似文献
Seasonal forecasts have potential value as tools for the management of risks due to inter-annual climate variability and iterative adaptation to climate change. Despite their potential, forecasts are not widely used, in part due to poor performance and lack of relevance to specific users’ decision problems, and in part due to a variety of economic and behavioural factors. In this paper a theoretical model of perceived forecast value is proposed and applied to a stylized portfolio-type decision problem with wide applicability to actual forecast users, with a view to obtaining a more complete picture of the determinants of perceived value. The effects of user wealth, risk aversion, and perceived forecast trustworthiness, and presentational parameters, such as the position of forecast parameter categories, and the size of probability categories, on perceived value is investigated. Analysis of the model provides several strong qualitative predictions of how perceived forecast value depends on these factors. These predictions may be used to generate empirical hypotheses which offer the chance of evaluating the model's assumptions, and suggest several means of improving understanding of perceived value based on qualitative features of the results. 相似文献