【摘要】：壓強(qiáng)是地基GPS反演水汽時(shí)的一個(gè)關(guān)鍵參數(shù),而實(shí)測(cè)壓強(qiáng)值或NWM提供的參考?jí)簭?qiáng)值經(jīng)常無(wú)法得到,這時(shí)一般采用經(jīng)驗(yàn)?zāi)Ｐ虶PT系列模型進(jìn)行壓強(qiáng)計(jì)算,但是GPT系列模型精度較低,特別是在南極等地區(qū),影響水汽的精度。本文引入時(shí)間序列分析的方法,基于ECMWF提供的全球高時(shí)空分辨率的高精度壓強(qiáng)序列進(jìn)行ARIMA模型的建模及預(yù)測(cè),結(jié)果表明,3天以內(nèi)精度均在2hPa以內(nèi),5天以內(nèi)精度在5hPa以內(nèi),短期預(yù)報(bào)滿足精度要求,可以作為一種有效的壓強(qiáng)計(jì)算方法用于水汽反演中。
[Abstract]:Pressure is a key parameter in water vapor inversion by ground-based GPS, but the measured pressure value or the reference pressure value provided by NWM can not be obtained. At this time, the empirical model GPT series model is generally used to calculate the pressure, but the accuracy of GPT series model is low, especially in Antarctica and other areas, which affects the accuracy of water vapor. In this paper, the method of time series analysis is introduced to model and predict the ARIMA model based on the high precision pressure series with high temporal and spatial resolution provided by ECMWF. The results show that the accuracy within 3 days is less than 2hPa and the accuracy within 5 days is less than 5hPa. Short-term prediction meets the accuracy requirements, and can be used as an effective pressure calculation method in water vapor inversion.
【作者單位】： 武漢大學(xué)測(cè)繪學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(41174012;41274022) 國(guó)家863計(jì)劃資助項(xiàng)目(2013AA122502) 教育部新世紀(jì)優(yōu)秀人才支持計(jì)劃資助項(xiàng)目(NCET-12-0428)~~
【分類(lèi)號(hào)】：P228.4

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