PRELIMINARY STUDY ON APPLYING GPS OBSERVATIONS TO MESOSCALE NUMERICAL WEATHER PREDICTION MODEL
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Abstract
Water vapor is a critical atmospheric variable for the description of the state and evolution of many physical processes. Lack of precise and continuous water vapor dat a is one of the majorerror sources in NWP. The Global Positioning System (GPS) can monitor the precipitable water (PW) continuously at low cost. The GPS data has been used to improve NWP in recent years. Based on the GPS precipit able water data at 11 sites of GPS net-works in Yangt zedelta, The experiments on initial humidity fields reanalysis and Nudging assimulation were conducted to investigate the improvement of MM5 simulation on railf all event from 23 to 24 July 2002. The results show that initial humidity fields reanalyzed by using GPSPW can obviously improve its capability in revea-ling the water vapor distribution, which can result in decreasing water vapor error in initial fields of MM5. It also can restrain PW prediction bias during the earlier period of model int egration and improving the 6h accumulated precipitation prediction. Nudging assimulation of GPSPW data can improve precipitation prediction slightly with different effectsat different precipitation thresholds, and increasing nudging gain coefficient play a little role in improving precipitation prediction. On the whole, the results which are obtained by the reanalysis are better than by the nudging assimulation. It's also found that the reanalysis influences the results of 6h accumu-lated precipitation on amount and occurring time through changing the non-convective precipitation prediction mainly. The precipitat ion prediction improved by the nudging assimulation are substantially associated with convective precipitation change.
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