|
A MAGIS-based Global Sea Level Analysis
3 Major features of the system Taking oceans and atmosphere as its research object, MAGIS is a satellite RS data based GIS software that could implement the management, analysis and representation of multidimensional dynamic data. Its major features are as follows:
TOPEX/POSEIDON (T/P) is the first space mission specifically designed and conducted for studying the circulation of the world oceans. The mission is jointly conducted by the United States National Aeronautics and Space Administration (NASA) and the French space agency, Centre National d’Etudes Spatiales (CNES). It was launched on August 10, 1992 and ended its mission in August 2002. During its operation, T/P covered the global oceans every 10 days, and made observations of the global oceans with unprecedented accuracy required for ocean circulation studies[5]. In the Science Work Flow (SWF) interface of MAGIS, we drag icons that represent data, analysis methods and visualization methods respectively to the right interface, and then draw lines that represents the data flow between icons, as figure 3 shows. Double-clicking the icons could modify the parameters of them. In the present example, we use weekly gridded T/P dataset: maps of Sea Level Anomaly (MSLA) to make a preliminary analysis of the global oceans with MAGIS. The duration of data is from October 1992 to August 2002. As to the analysis methods, we select fundamental statistics, spectrum analysis and harmonic analysis to acquire the characteristics of global sea level variability. After setting the parameters of each icon, we click the “Execute SWF” button on the toolbar, and then MAGIS could do the above works. After the execution, it will turn to the interfaces of results automatically. 4.1 Statistical analysis The outputs of fundamental analysis are fundamental statistics (including minima, maxima, mean, range, variance and standard deviation) and (normalized) anomaly. We save the fundamental statistics results into a file, which we could use to make a plot. The normalized anomaly is set to the input of harmonic analysis. Figure 4 is the mean global sea level anomaly of Oct. 1992 to Aug. 2002. The whole Atlantic, northwest and west parts of Pacific, and the east Indian Ocean have relatively high sea level anomaly.  Fig. 4 Global mean sea level anomaly of Oct. 1992 to Aug. 2002 derived from T/P altimeter 4.2 Spectrum analysis We conduct a spectrum analysis on each of the 360*164 points of global oceans, and use time series plot to show the frequency-amplitude plot at 3°N, 200°E and classed post map to represent the global oceans’ variability period. Figure 5 is the frequency-amplitude plot at 3°N, 200°E. It shows us that the primary energy of sea level anomaly variability concentrates on frequency 1, 0.1 and 0.6 year/cycle, which represent annual variability, 1.2 month variability and semiannual variability respectively.  Fig. 5 Sea level anomaly spectrums at 3°N, 200°E We then use the primary frequency of each point in global oceans to make a 2-D classed post map, as figure 6 shows. About 60% of the global oceans are dominated by annual variability, then 1.2 month variability (25%), and the remaining is seasonal variability and interannual variability. The result is consistent with the fact: the major factors that affect sea level are some marine and atmospheric phenomena like sun radiation, atmospheric motion and ocean currents that have annual features, so the annual variability contributes most to the sea level variability. And secondly, the sea level is also affected by the tides, which has a monthly period. The remaining 15% variability is mainly caused by other marine and atmospheric phenomena like El Nino. |