The Evolution Features of Precipitable Water Vapor Derived from Ground-based GPS During Autumn Rain Weather Process in West China
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Abstract
Based on the principle of deriving precipitable water vapor with ground-based GPS, the estimates of total zenith delay are calculated using ZTD data from the ground-based GPS network in Chengdu Plain during the period of September to November 2007. Precipitable water vapor (PWV) derived from GPS are obtained at 30-minute interval combining meteorological data from automatic weather stations. The autumn rain is classified as showery rain and continuous precipitation in Chengdu Plain, and the relationship between GPS-PWV and autumn rain is analyzed. It shows that precipitation always happens in high value phase of water vapor, so the high precipitable water vapor is necessary for rain in most cases. Precipitation happen when the PWV anomaly is positive, and the PWV anomaly is always higher than 1 when a rainstorm occurs. The variation range of showery in autumn is large. The GPS-PWV always increases 12 hours before the precipitation. When GPS-PWV is higher than the base value of the month or acutely increases in the adjacent time, a shower is likely to occur. High GPS-PWV level and weak updrafts just lead to small rain. But the increasing of precipitable water with strong ascending motion and the decreasing of temperature always causes shower. During continuous precipitation in autumn in Chengdu Plain, the accu-mulation of water vapor is very important, strong precipitation often happens when water vapor rises once again. If the precipitable water vapor maintains the high level, it may rain within 12 hours. If the water vapor falls to the base value of the month then rise to above that within 12 hours, it indicates the beginning of another phase of precipitation. GPS-PWV variation range, extremum level and duration are different in different rain process. These results may be referential for applying precipiatable production derived from ground-based GPS network in precipitation forecast.
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