Radio-frequency interference（RFI） detection for low-frequency microwave measurements is an important step before these data are applied to geophysical parameter retrieval or data assimilation. There are several robu...Radio-frequency interference（RFI） detection for low-frequency microwave measurements is an important step before these data are applied to geophysical parameter retrieval or data assimilation. There are several robust techniques to identify the RFI signals, such as the mean/standard deviation method and the normalized principal component analysis method. However, verification of these existing detection methods remains an open issue in the absence of a reliable validation data-set of the ‘true＇ RFI signals. In this paper, a cross-validation scheme using two independent RFI detection methods is proposed to derive the thresholds for identifying the RFI-contaminated data for the Advanced Microwave Scanning Radiometer for Earth Observing System（AMSR-E）. It is shown that the new scheme is effective in the quantitative classification of the RFI signals in the AMSR-E C-and X-band channels over the continents. Strong RFI signals are found to be populated over cities of the United States at AMSR-E C-band, while RFIs at X-band are mainly observed over Europe and Japan.展开更多
基金supported by the Special Fund for Meteorological Research in the Public Interest of China(Project No.GYHY201406008)the National Natural Science Foundation of China[grant number 91337218]
文摘Radio-frequency interference（RFI） detection for low-frequency microwave measurements is an important step before these data are applied to geophysical parameter retrieval or data assimilation. There are several robust techniques to identify the RFI signals, such as the mean/standard deviation method and the normalized principal component analysis method. However, verification of these existing detection methods remains an open issue in the absence of a reliable validation data-set of the ‘true＇ RFI signals. In this paper, a cross-validation scheme using two independent RFI detection methods is proposed to derive the thresholds for identifying the RFI-contaminated data for the Advanced Microwave Scanning Radiometer for Earth Observing System（AMSR-E）. It is shown that the new scheme is effective in the quantitative classification of the RFI signals in the AMSR-E C-and X-band channels over the continents. Strong RFI signals are found to be populated over cities of the United States at AMSR-E C-band, while RFIs at X-band are mainly observed over Europe and Japan.
