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Presenter: Oreste Reale

Seminar Title: Improving forecast skill by assimilation of quality-controlled AIRS temperature retrievals under partially cloudy conditions.

The NASA Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite is now recognized as an important contributor towards the improvement of weather forecasts. However, at this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid-lower tropospheric sounding AIRS channels are assimilated primarily under completely clear-sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS-derived information.

In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud-contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. A set of Observing System Experiments (OSE) is designed. Three 31-day assimilation experiments, starting at 00z 1 January 2003, have been performed with the GEOS-5 DAS run at a spatial horizontal resolution of 1x1. In all three experiments conventional and satellite observations used operationally at NCEP at that time are assimilated, with the exclusion of AIRS data in the first run, which we define CNTRL. AIRS temperature profiles with medium quality control, and the same AIRS data only above 200 hPa (so as to assess the significance of withdrawing tropospheric temperature information derived under cloudy conditions) are assimilated in the experiments named AIRS and CUTF respectively. From the three sets of analyses, three corresponding sets of 27 five-day forecasts (CNTRL, AIRS and CUTF) are produced and verified against operational NCEP analyses.

500 hPa geopotential height anomaly correlation (AC) in the northern hemisphere extratropics, for the 3 sets of 27 5-day forecasts, show a significant impact of AIRS throughout the integration, whereas the CUTF AC is virtually identical to that of the CNTRL, thus suggesting that most of the impact during boreal winter originates from AIRS data within the troposphere.

Cases are selected based upon daily variations of AC5, in order to investigate the dynamical response of the forecast model to different analyses. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover (selected from the cases in which the corresponding forecast is better than the CNTRL) result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS-induced anomaly propagates through the model's dynamics producing improved 5-day forecasts.

The few cases in which AIRS AC5 is smaller than the CNTRL are associated with highly asymmetric data sampling over dynamically active regions. We select one particularly interesting case, in which AIRS coverage only exists on the eastern side of one intense double cutoff low, creating an imbalance that propagates in the Hovmoller as an unrealistic stationary wave. This spurious stationary wave disrupts the quality of the forecast over most of the northern hemisphere.

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