SUMMARYThe development of an assimilation system for radiance data from the Atmospheric InfraRed Sounder (AIRS) is described, in particular the identification of cloud contamination, bias correction and the characterization of errors in the measured radiances and radiative-transfer model. The results of assimilation experiments are presented. These show that a conservative use of AIRS radiance data (in a system already extensively observed with other satellite data) results in a small, but consistent, improvement in the quality of analyses and forecasts. Larger impacts of AIRS are found in hypothetical experiments that test the use of radiances from only a single sounding instrument. In these, the use of AIRS is found to outperform the use of data either from a single Advanced Microwave Sounding Unit-A (AMSU-A) or from a single High-resolution InfraRed Sounder (HIRS). In this hypothetical context the relative forecast performance of each sensor is found to correlate with the size and vertical scale of increments caused by the assimilation of the radiances.
SUMMARYAircraft and ground-based interferometer measurements are used to investigate the dependence of sea surface emissivity on water temperature and salinity in the infrared spectral region. The effect of dissolved salts is found to be small and in line with previous studies, whereas temperature (often neglected in current emissivity models) has a greater impact. The influence on satellite sea surface temperature (SST) retrievals is found to be significant for high-resolution infrared sounders: neglecting a temperature-dependent emissivity leads to systematic errors in SST of as much as 0.6 K depending on channel frequency.
A scheme for detecting cloud-affected radiances is described. The method is used to determine the probability of cloud-free conditions given the observations and the prior knowledge we have about the atmosphere from a numerical weather prediction (NWP) model. This is achieved using a likelihood method. It combines the strengths of some alternative methods (e.g. comparison of infra-red and microwave channels sounding the lower troposphere and comparison of infra-red window channels with sea surface temperature) in a powerful and flexible method. It is powerful because it uses different types of information simultaneously. It is flexible because it makes no assumption about which instrument is being processed, or what type of prior information ( M , climatology etc.) is used. Therefore, it can readily be extended to new situations and data types (e.g. Advanced TIROS Operational Vertical Sounder (ATOVS)). It is suitable for use on general cloud-detection problems, using combined microwave and infra-red data. It has been tested using TIROS Operational Vertical Sounder (TOVS) radiances. The new method has been compared with an alternative cloud-detection method tailored specifically for TOVS and has been developed to a level of robustness adequate for operational use. The new method gave very similar results to the alternative method, especially over the ocean. The differences that did occur have been investigated by comparing with cloud information derived from the Advanced Very High Resolution Radiometer (AVHRR). Both the alternative method and the new scheme were found to have deficiencies when dealing with very low cloud. Some cloud missed by the existing scheme is identified by the new scheme. Over land, cloud detection is more difficult. The two schemes disagree more often, but validation using AVHRR is also more difficult because of increased surface heterogeneity and more variable emissivity and surface temperature errors. The new method is therefore shown to perform at least as well as an alternative method in operational use, whilst gaining the flexibility required for future systems. The implications for ATOVS are discussed.
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