Abstract—

One of the options for the practical application of GNSS technology, in addition to geodetic and navigation needs, is remote sensing of the atmosphere by radio signals from navigation satellites in order to improve the quality and detail of weather forecasts. The propagation of a radio signal from GNSS satellites to a ground receiving device (GNSS receiver) through a neutral atmosphere is accompanied by a decrease in the phase velocity of the radio waves (additional atmospheric delays). This is due to the presence of nitrogen, oxygen, carbon dioxide, and water vapor molecules in the atmosphere. Therefore, measurements of the additional delay of the radio signal in the atmosphere (tropospheric delay) provide information on the integral properties of the atmosphere along the propagation path of the radio signal. As a result of the primary processing of the GNSS measurement results, the distances from the observation station to GNSS satellites are determined. Secondary processing of GNSS measurements consists in solving a navigation problem and provides information on the location of the station. In order to obtain meteorological information, it is necessary to develop special methods of secondary data processing based on solving inverse problems. The combination of primary and secondary data (processing) along with meteorological information makes it possible to obtain a global model of the atmosphere in near-real time. The efficiency of this approach, the complete automation, and the absence of consumables during remote sensing provide opportunities for the widespread implementation of operational monitoring of the state of the atmosphere in order to improve the data’s detail and accuracy of regional short-term weather forecasts. Currently, due to cross-border cooperation with European countries in conducting joint GNSS observations in the UA-EUPOS/ZAKPOS network of stations, we are able to have an accurate, dense, and continuous sampling of tropospheric delay values, which allows us to determine and predict the dynamics of atmospheric changes in real time. The main goal of the work is to study the spatio-temporal instability of the atmosphere over an area covered by active reference stations. The results of the study can be used to improve the quality of weather prediction.

中文翻译：

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基于实时GNSS数据处理的地球大气时空不稳定性调查与分析

摘要-

除大地测量和导航需求外，GNSS技术实际应用的一种选择是通过导航卫星的无线电信号对大气进行遥感，以提高天气预报的质量和细节。从GNSS卫星到中立大气层的GNSS卫星到地面接收设备（GNSS接收器）的无线电信号传播伴随着无线电波相速度的下降（​​额外的大气延迟）。这是由于大气中存在氮，氧，二氧化碳和水蒸气分子。因此，对大气中无线电信号的附加延迟（对流层延迟）的测量提供了有关沿无线电信号传播路径的大气整体特性的信息。作为GNSS测量结果的主要处理的结果，确定了从观测站到GNSS卫星的距离。GNSS测量的二次处理在于解决导航问题并提供有关电台位置的信息。为了获得气象信息，有必要在解决逆问题的基础上开发特殊的二次数据处理方法。一次和二次数据（处理）与气象信息的结合使得可以近乎实时地获得大气的全球模型。这种方法的效率，完全的自动化，而且遥感过程中没有消耗品，这为广泛实施大气状况运行监测提供了机会，以改善数据的详细信息和区域短期天气预报的准确性。当前，由于与欧洲国家进行跨境合作，在UA-EUPOS / ZAKPOS台站网络中进行了GNSS联合观测，因此我们能够对流层延迟值进行准确，密集和连续的采样，这使我们能够确定并实时预测大气变化的动态。这项工作的主要目的是研究活跃基准站所覆盖区域的大气时空不稳定性。研究结果可用于改善天气预报的质量。