The Impact of GPS Precipitable Water Assimilation on Mesoscale Model Retrievals of Orographic Rainfall during SALPEX'96

Abstract

The potential of GPS precipitable water (PW) to improve mesoscale model retrievals of orographic precipitation is investigated for a prolonged rainfall event observed during the 1996 Southern Alps Experiment (SALPEX'96). The model is the Advanced Regional Prediction System (ARPS), nested within 6-hourly global model analyses. In a set of data assimilation experiments, the analysis nudging technique is used to continuously force the model toward measured values of PW upstream of the mountains. The impact upon subsequent orographic rainfall is examined through comparison with rain gauge observations. It is found that the assimilation of hourly GPS PW gives a statistically significant (at the 3% level) improvement in the retrieved total rainfall on the upwind side of the mountain range, when compared with rainfall from a control simulation that does not involve data assimilation. Best results are obtained when GPS PW data are used along with radiosonde temperature profiles. The model predictions of spillover of rainfall across the main divide were not significantly influenced by the various assimilation strategies. The inclusion of PW leads to an improved simulation of upwind flow blocking and gives better humidity profiles in the lee of the mountains.