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The impact of Global Positioning System data on the prediction of an extratropical cyclone: an observing system simulation experiment
Authors:Y. -H. Kuo   X. Zou  W. Huang
Abstract:In this paper, we report a series of observing system simulation experiments that we conducted to assess the potential impact of Global Positioning System/meteorology (GPS/MET) refractivity data on short-range numerical weather prediction. We first conducted a control experiment using the Penn State/NCAR mesoscale model MM5 at 90-km resolution on an extratropical cyclone known as the ERICA (Experiment on Rapidly Intensifying Cyclones over the Atlantic) IOP 4 storm. The results from the control experiment were then used to simulate GPS/MET refractivity observations with different spatial resolution and measurement characteristics. The simulated refractivity observations were assimilated into an 180-km model during a 6-h period, which was followed by a 48-h forecast integration. Key findings can be summarized as follows:
• The assimilation of refractivity data at the 180-km resolution can recover important atmospheric structures in temperature and moisture fields both in the upper and lower troposphere, and, through the internal model dynamical processes, also the wind fields. The assimilation of refractivity data led to a considerably more accurate prediction of the cyclone.
• Distributing the refractivity randomly in space and applying a line averaging did not alter the results significantly, while reducing the spatial resolution from 180 km to 360 km produced a moderately degraded result. Even at the 360-km resolution, the GPS-type refractivity data still have a notable positive impact on cyclone prediction.
• Restricting the refractivity data to altitude 3 km and above considerably degraded its impact on cyclone prediction. This degradation was greater than the combined effects of distributing the refractivity data randomly, performing line averaging, and reducing the resolution to 360 km.
These results showed that the GPS/MET refractivity data is likely to have a significant impact on short-range operational numerical weather prediction. The random distribution and line averaging associated with the inherent GPS occultation do not pose a problem for effective assimilation. On the other hand, these results also argue that we need to improve the GPS/MET retrieval algorithm in order to recover useful data in the lower troposphere, and to increase the number of low-earth-orbiting satellites carrying GPS receivers in order to increase the density of GPS soundings, so that the potential impact of GPS/MET refractivity data on numerical weather prediction can be fully realized.
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