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The effect of sea surface height (SSH) variability is one of the primary factors that limit the accuracy and resolution of altimeter-derived gravity values. We propose a method to estimate the influence of variation of the sea surface height on the accuracy of satellite-derived gravity by simulation technique, with a case study around Indonesian waters. Wederived an Indonesian marine gravity map using the Geosat-geodetic mission (GM). Since most of the area studied is located around coastal and shallow areas, the measurement of SSH of this area is less accurate. To obtain a distribution of SSH variability over the study area, Topex/Poseidon (T/P) data were first processed and assessed. Processing 52 cycles of the Topex/Poseidon data, the root mean square (RMS) of SSH variability for each cycle was found to vary from 1 to 179 cm. Further, for the purpose of estimating the accuracy of altimeter-derived gravity, we derived several levels of Gaussian noise, computed simulation data by adding the Gaussian noise to Geosat data, and determined simulated gravity maps. Based on the distribution of RMS values from T/P data and standard deviation (STD) differences between the simulated and the original gravity maps, we estimated the accuracy of the gravity map. Around Indonesian waters, the accuracy of the gravity map influenced by SSH variation was estimated to be within the range 0.8~93 mgal. 相似文献
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The effect of sea surface height (SSH) variability is one of the primary factors that limit the accuracy and resolution of altimeter-derived gravity values. We propose a method to estimate the influence of variation of the sea surface height on the accuracy of satellite-derived gravity by simulation technique, with a case study around Indonesian waters. Wederived an Indonesian marine gravity map using the Geosat-geodetic mission (GM). Since most of the area studied is located around coastal and shallow areas, the measurement of SSH of this area is less accurate. To obtain a distribution of SSH variability over the study area, Topex/Poseidon (T/P) data were first processed and assessed. Processing 52 cycles of the Topex/Poseidon data, the root mean square (RMS) of SSH variability for each cycle was found to vary from 1 to 179 cm. Further, for the purpose of estimating the accuracy of altimeter-derived gravity, we derived several levels of Gaussian noise, computed simulation data by adding the Gaussian noise to Geosat data, and determined simulated gravity maps. Based on the distribution of RMS values from T/P data and standard deviation (STD) differences between the simulated and the original gravity maps, we estimated the accuracy of the gravity map. Around Indonesian waters, the accuracy of the gravity map influenced by SSH variation was estimated to be within the range 0.8~93 mgal. 相似文献
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The community composition and production of phytoplankton in fish pens of Cape Bolinao, Pangasinan: a field study 总被引：1，自引：0，他引：1
From 1995 up to the present, fish pens proliferated in the municipal waters of Bolinao, northern Philippines. Since then, fish kills and phytoplankton blooms have been recurrent. Have fishpens altered the phytoplankton community composition and production of these waters? The phytoplankton community in Cape Bolinao, Lingayen Gulf is typical of a tropical coastal area where diatoms alternate with dinoflagellates during the dry and wet seasons. In the nutrient-rich fish pens, phytoplankton in this study showed a lower diatom/dinoflagellate ratio and unusually high phytoplankton counts of 10(4) cells/l and even as high as 10(5) cells/l. Correlations between physico-chemical parameters, phytoplankton production and community composition were made in 2001. This paper tried to explain the occurrence of a Cylindrotheca closterium bloom (10(5) cells/l), during the dry season of the same year and a Prorocentrum minimum bloom (4.7 x 10(5) cells/l), which accompanied a massive fish kill during January 2002. 相似文献
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Whether in classical networks such as meteorological networks of in more recent ones of atmospheric chemistry, a wealth of data is at hand. These data have been evaluated in a manner depending on the purpose of the network. However, much more information is hidden in these time series and waits for discovery. Only the imagination of scientists is needed. Four examples are given which lead to new information about the atmospheric aerosol and the behaviour of the atmosphere. These examples are: Atmospheric turbidity from sunshine recordings, Meteorological drainage area from the variance of observations, Location of point sources from air mass trajectories, and Total vertical ozone from turbidity measurements. 相似文献
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