Assimilation of Infrared Radiances in the Context of Observing System Simulation Experiments

• Published in: Journal of applied meteorology and climatology Vol. 52; no. 4; pp. 1031 - 1045
• Main Authors: Heilliette, Sylvain, Rochon, Yves J., Garand, Louis, Kaminski, Jacek W.
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.04.2013
• Subjects: Atmospheric Infrared Sounder; Atmospheric sounding; Atmospheric windows; Atmospherics; Bias; Channels; Cloud detection; Clouds; Contamination; Data assimilation; Data collection; Data types; Earth, ocean, space; Exact sciences and technology; Experiments; External geophysics; Forecasting models; Geophysics. Techniques, methods, instrumentation and models; Infrared interferometers; Infrared radiation; Instruments; Meteorology; Meteors; Noise levels; Perturbation; Quality assurance; Quality control; Radiance; Radiation; Radiative transfer. Solar radiation; Response functions; Satellites; Simulation; Soundings; Standard deviation; Studies; Water vapor; Water vapour; Weather; Weather forecasting; Measurement technique; Space remote sensing; Satellite observation; Infrared atmospheric sounding interferometer; Advanced infrared sounder; Data assimilation; radiance
• ISSN: 1558-8424; 1558-8432
• DOI: 10.1175/JAMC-D-12-0124.1

The Observing System Simulation Experiment (OSSE) capability developed at Environment Canada allows simulation of all observation types currently used operationally as well as future data types. Its infrastructure, based on the operational global data assimilation system used at the Canadian Meteorological Centre, was recently enhanced to conduct data assimilation experiments for two future satellite missions. This study presents a subcomponent of that system, focusing on the assimilation of infrared radiances from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) instruments. The goal is to realistically simulate the radiance observations and to reproduce statistical characteristics of these data seen in the real system, notably background and analysis departures. Care is taken to emulate the operational quality control procedures leading to the assimilation of clear radiances, which implies radiance simulation for all-sky conditions. It is found that the standard deviation of the Gaussian random perturbation applied to the simulated observations should be close to that of the radiometric noise level for sounding channels in the 13.0–14.5-μm region but that it should be significantly higher for water vapor channels in the 5.5–6.7-μm region. The study also allows evaluation of residual biases linked to cloud contamination. For atmospheric window channels, that bias can reach −0.4 K. It reduces rapidly with peak height of the channel response function. This suggests that improvements are needed in low-cloud detection. The realism of the OSSE is further demonstrated through the shown impact consistency of AIRS and IASI radiance assimilation in forecasts up to 5 days from the separate use of simulated and real observations.