Antarctic Ice-sheet Freeze-thaw Detection Based On Active And Passive Microwave Remote Sensing

Antarctic ice-sheet contributes significantly to the global heat budget by controlling the exchange of heat, moisture, and momentum at the surface-atmosphere interface, which directly influences the global atmospheric circulation and climate change. Ice-sheet melt will cause snow humidity increase, which will accelerate the disintegration and movement of ice sheet. As a result, detecting Antarctic ice-sheet melt is essential for global climate change research.Microwave remote sensing is an all-weather technology, which has strong penetration capability and it is sensitive to dielectric properties. All these advantages make it an important frontier of earth observing. Furthermore, microwave brightness temperature and microwave backscatter coefficient are so sensitive to the water content variation that, with the onset and end of snowmelt, brightness temperature and backscatter coefficient experience dramatic variation. On the basis of snow microwave characteristics, I provide a review on the principle of detecting snowmelt with passive microwave remote sensing data and active microwave remote sensing data, and then introduced some passive microwave algorithms and active microwave algorithms for Antarctic ice-sheet melt monitoring and for long-time series melting result derivation, at the same time, the synergy of microwave radiometer and scatterometer was researched for ice-sheet melt monitoring, and the specific contents are as follows:(1) The problems of the current XPGR algorithm and the simple physical model algorithm for the ice-sheet melt detection of microwave radiometer are analyzed, in order to solve the problems, the improved radiometer simple physical model, XPGR combined with wavelet transform algorithm and radiometer simple physical model combined with wavelet transform algorithm are proposed to improves the computational efficiency, usability and operability of detecting the ice-sheet melt detection. The algorithms do not rely on the actual melt information and can automatically select many samples. The ground verification is done based on the automatic weather station data. The results show that the methods can be effectively used for the detection of Antarctic ice-sheet melt.(2) On the basis of the simple snowmelt physical model for microwave scatterometer, a new automatic threshold segmentation algorithm of Antarctic ice-sheet freeze-thaw detection was proposed, which did not depend on the field observations. That was the histogram for the data of the physical model by the use of generalized Gaussian model to automatically get Antarctic melt distribution. The algorithm improves the computational efficiency, usability and operability of the freeze-thaw detection because the algorithm does not rely on the actual melt information and can automatically select more samples. In addition, in according to the characteristic of backscattering coefficient having dramatic changes with the event of melt or freeze and the characteristic of wavelet transform edge extraction, wavelet edge detection for Antarctic ice-sheet freeze-thaw detection algorithm is proposed. Moreover, the backscattering coefficient is not stable in the melt state, and the mathematical morphology can filer the signal with the edge preserved. So the mathematical morphology combined with wavelet transform algorithm was proposed, and these algorithms can automatically detect the Antarctic ice-sheet melt, which provide methodological support and supplement for the global ice-sheet freeze-thaw detection.(3) Passive and active microwave measurements have been used in various studies to detect melt based on their sensitivity to liquid water present in snow. The scatterometer is more sensitive to surface melt than passive microwave observations. The radiometer is more reliable than active microwave. In order to effectively carry on the ice-sheet freeze-thaw detection, the active and passive microwave sensors are efficiently combined based on the sensitivity and the high spatial resolution of the scatterometer and the reliability of the radiometer, two new Antarctic freeze-thaw synergistic detection methods were proposed. One was based on the high sensitivity of the scatterometer and the high reliability of the radiometer by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic melt onset date, melt duration and melt end date. The other was based on the high spatial resolution of the scatterometer and the reliability of the radiometer through the physical models of the active and passive microwave data sets. Both new algorithms make use of the advantages of active and passive microwave sensors. The results show that the algorithms improve the detection accuracy of melt onset date, melt duration, melt end date and melt distribution.(4) The spatial distribution of melt areas shows that the majority of melt areas are located on the edge of Antarctic ice shelf region. It is affected by land cover type, surface elevation and geographic location. The temporal distribution of melt areas shows that the Antarctic ice sheet melt varies with years with some rule. The melt areas in1991are1518750km2,and its areas are largest. The melt areas in1999are565000km2,and its areas are smallest. In addition, the Antarctic ice sheet melt varies with seasons. It is particularly acute in summer, peaking at December and January, staying low in March.