根据全球导航卫星系统测量评估尼日利亚上空大气水蒸气含量变化的影响

IF 0.3 Q4 REMOTE SENSING
O. A. Isioye, L. Combrinck, J. Botai, M. Moses
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引用次数: 1

摘要

本研究分析了2013年至2014年从尼日利亚地面全球导航卫星系统(GNSS)站获取的可降水量变化的气象影响;这些测量代表了对尼日利亚上空GNSS PWV分布和变异性的最重要探测。在这项研究中,全球导航卫星系统PWV每日估计数分为月度和季节平均数;对全球导航卫星系统PWV的月度和季节估计值的变化进行了表征,并将其与被视为良好气候变化指标的不同天气事件相关联。结果表明,PWV含量的时空变化在很大程度上受纬度、地形特征、季节和大陆气团的影响。我们的研究表明,GNSS PWV、相对湿度、降雨量和云量估计之间存在非常强烈的季节性相互作用。此外,全球导航卫星系统PWV和总电子含量估计值显示出相反的关系;GNSS PWV与TEC之间的半日关系强于季节关系。GNSS PWV、温度和风速之间的季节关系似乎较弱,而GNSS PWW、太阳黑子数和太阳总辐射估计之间存在非常强的相互作用。我们的结果证实,GNSS PWV是天气预报/监测的良好指标,如果在更长的时间范围内可用,则适合气候监测。最后,我们建议在尼日利亚加密全球导航卫星系统网络,因为这将能够对PWV进行3D分析,从而提供长期气候学所需的更多关于全球导航卫星网PWV时间序列的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the impact of variations in atmospheric water vapour content over Nigeria from GNSS measurements
This study analyses the meteorological impact of the variability of precipitable water vapour (PWV) retrieved from ground-based global navigation satellite system (GNSS) stations over Nigeria from 2013 to 2014; these measurements represent the foremost probe of GNSS PWV distribution and variability over Nigeria. In this study, GNSS PWV daily estimates were grouped into monthly and seasonal averages; the variations in the monthly and seasonal estimates of GNSS PWV were characterized and correlated with different weather events that are regarded as good climate change indicators. The results revealed that the spatiotemporal changes in PWV content are largely subjugated by the effects of latitude, topographical features, the seasons and the continental air masses. Our study shows that there is a very strong seasonal interplay among the GNSS PWV, relative humidity, rainfall and cloud estimates. In addition, GNSS PWV and total electron content (TEC) estimates show an opposite relationship; the semi-diurnal relationship between GNSS PWV and TEC is stronger than the seasonal relationship. The seasonal relation among GNSS PWV, temperature and wind speed appears weak, while very strong interplay exists among the GNSS PWV, sun spot number and total solar radiation estimates. Our results confirm that GNSS PWV is a good pointer for weather forecasting/monitoring and fit for climate monitoring if available on a longer time scale. Finally, we recommend the densification of the GNSS network in Nigeria, as this will enable 3D profiling of PWV, thereby providing more information on GNSS PWV time series, which is needed for long-term climatology.
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