研究目的
Investigating the effectiveness of Principle Component Analysis (PCA) method in data set preparation for SCAT sigma0s for wind fields retrieving.
研究成果
The PCA method proposed is effective in improving processing speed for wind fields while the discarding operation needed further improvement. The research has opened a new way of scatterometer data analysis, which could be applied in data space analysis in further research as well.
研究不足
The discarding operation needed further improvement which is main reason of WVCs could not be resolved.
1：Experimental Design and Method Selection:
PCA method was applied for getting data sets containing principle information instead of averaging for wind fields retrieving. Two ways of applying PCA were adopted.
2：Sample Selection and Data Sources:
Simulated data for SCAT from uniform and wind fields from ECMWF were used.
3：List of Experimental Equipment and Materials:
NSCAT-4 model was applied for simulating sigma0s.
4：0s. Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: PCA was applied to common setting of WVCs and to the scenario of large number of sigma0s in a WVC.
5：Data Analysis Methods:
MLE (maximum likelihood estimation) was conducted on WVCs (wind vector cells).
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