Interchannel Error Correlation Associated with AIRS Radiance Observations: Inference and Impact in Data Assimilation

Abstract

The interchannel observation error correlation (IOEC) associated with radiance observations is currently assumed to be zero in meteorological data assimilation systems. This assumption may lead to suboptimal analyses. Here, the IOEC is inferred for the Atmospheric Infrared Radiance Sounder (AIRS) hyperspectral radiance observations using a subset of 123 channels covering the spectral range of 4.1?15.3 ?m. Observed minus calculated radiances are computed for a 1-week period using a 6-h forecast as atmospheric background state. A well-established technique is used to separate the observation and background error components for each individual channel and each channel pair. The large number of collocations combined with the 40-km horizontal spacing between AIRS fields of view allows robust results to be obtained. The resulting background errors are in good agreement with those inferred from the background error matrix used operationally in data assimilation at the Meteorological Service of Canada. The IOEC is in general high among the water vapor?sensing channels in the 6.2?7.2-?m region and among surface-sensitive channels. In contrast, it is negligible for channels within the main carbon dioxide absorption band (13.2?15.4 ?m). The impact of incorporating the IOEC is evaluated from 1D variational retrievals at 381 clear-sky oceanic locations. Temperature increments differ on average by 0.25 K, and ln(q) increments by 0.10, where q is specific humidity. Without IOEC, the weight given to the observations appears to be too high; the assimilation attempts to fit the observations nearly perfectly. The IOEC better constrains the variational assimilation process, and the rate of convergence is systematically faster by a factor of 2.