Abstract

AbstractThe differences between brightness temperature observations and simulated observations based on numerical weather predictions, i.e., O‐B, for Advanced Technology Microwave Sounder (ATMS) temperature sounding channels exhibit a clear striping pattern [Bormann et al., 2013]. We propose to first use the principal component analysis to isolate scan‐dependent features such as the cross‐track striping from the atmospheric signal and then to use an Ensemble Empirical Mode Decomposition (EEMD) to extract the striping noise in ATMS Earth scene brightness temperature observations for both temperature and water vapor sounding channels. It is shown that the Principal Component (PC) coefficient of the first PC mode, which mainly describes a scan‐dependent feature of cross‐track radiometer measurements, captures the striping noise. The EEMD is then applied to the PC coefficient to extract the first three high‐frequency intrinsic mode functions (IMFs), which are denoted as the PC1/IMF3 noise. When the PC1/IMF3 noise is removed from the data, the striping noise is imperceptible in the global distribution of O‐B for ATMS temperature sounding channels 1–16. Using the same method, it is demonstrated that the striping noise is also present in ATMS water vapor sounding channels 17–22. The magnitude of the ATMS striping noise is about ±0.3 K for the temperature sounding channels and ±1.0 K for the moisture sounding channels. The same technique is also applied to Advanced Microwave Sounding Unit‐A (AMSU‐A), AMSU‐B, and Microwave Humidity Sounder (MHS). The striping noise is undetectable for AMSU‐A but present in AMSU‐B and MHS data.

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