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首页> 外文期刊>Acta Meteorologica Sinica >Preliminary Study on the Application of GPS Observations to a Mesoscale Numerical Model
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Preliminary Study on the Application of GPS Observations to a Mesoscale Numerical Model

机译：GPS观测在中尺度数值模型中的应用初步研究

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摘要

Based on observations from 11 stations inside the GPS (global positioning system) observation network, study is performed both on adjustment of the MM5 initial humidity field by means of, and nudging assimilations of, G-PW (short for GPS-sensed atmospheric precipitable water) for a rainfall event happening in the Yangtze delta during June 23-24, 2002. Results show that adjusting the initial moisture field through G-PW will enhance pronouncedly the ability of the initial field to depict vapor distribution, thereby harnessing errors of atmospheric PW prediction at an early stage of model integration to improve more markedly the prediction of 6-h rainfall and, in contrast, nudging assimilations of G-PW show insignificant amelioration of model prediction, with less effect on the result by using a bigger nudging coefficient. On the whole, compared to successive nudging assimilations of G-PW into the MM5, greater amelioration occurs in 6-h rainfall prediction from the G-PW adjusted initial moisture field. Also, evidence suggests that the improvement of 6-h rainfall prediction with G-PW in correcting the initial humidity field is realized mainly through the amelioration of the ability of grid-scale rainfall prediction while the nudging scheme achieves the improvement largely by bettering sub-grid scale rainfall prediction.
机译：基于GPS（全球定位系统）观测网络内部11个站的观测结果，研究了通过G-PW（GPS感知的大气可沉淀水的简称）对MM5初始湿度场的调整以及对N-P的同化作用。 ）针对2002年6月23日至24日发生在长江三角洲的降雨事件。结果表明，通过G-PW调整初始湿度场将显着增强初始场描述蒸汽分布的能力，从而利用大气PW的误差在模型集成的早期进行预测可以显着改善6小时降雨的预测，相反，G-PW的微调同化对模型预测的改善不明显，而通过使用更大的微调系数对结果的影响较小。总体而言，与将G-PW连续推入MM5中相比，根据G-PW调整后的初始湿度场，在6小时降雨预报中会出现更大的改善。此外，有证据表明，G-PW在校正初始湿度场方面对6小时降雨预报的改进主要是通过改善网格尺度降雨预报的能力而实现的，而通过微调方案，通过改善子预报来改善6小时降雨预报的效果在很大程度上得到了改善。网格规模降雨预报。

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