## 6 Ionospheric Total Electron Content and Disturbance Observations
Considering the effects of tropospheric delay and the ionosphere above spaceborne GNSS-R receivers, [PERSON] et al. [38] proposed an improved method for estimating ionospheric TEC above the ocean, which significantly improved the accuracy of estimating ionospheric TEC. Despite the progress made in the use of L1 data over the past decades, limitations still exist in terms of spatial resolution, update frequency, and accuracy for current TEC maps. L0 data, on the other hand, offers many advantages. A new method for estimating the slant TEC along the path of reflected signals was proposed in the literature [49], using L0-level data collected from the GNSS-R payloads of the Lemur-2 CubeSat satellites of Spire Global Inc. during 2016 and 2017. The results showed that the TEC data obtained by this method was consistent with existing products and could provide nearly \"static\" observations of the ionospheric structure, helping to monitor frequent and intense space weather disturbances in polar regions. This method also improved the ability to observe global ionospheric TEC in the presence of coherent GNSS signal reflections over global oceans and inland water bodies, providing a new data source for data-sparse regions. [PERSON] et al. [114] found that uncertainties in sea surface height were related to ionospheric-model-based group delay altimetry retrieval correction using L0-level data from the Lemur-2 CubeSat satellites of Spire Global Inc., with standard deviations reaching the meter level, demonstrating the great potential of L0-level GNSS-R satellite data for ionospheric research. [PERSON] and [PERSON] [51; 115] proposed an innovative application of spaceborne GNSS-R technology in polar ionospheric research using Spire data, providing a new data source that can help to improve ionospheric monitoring and understanding in high-latitude regions. Ionospheric disturbances significantly affect the propagation of electromagnetic waves. While they have negative impacts on space communication, satellite navigation, and Earth observation technologies, they can also be exploited as a new means of Earth observation. Recent studies have revealed potential associations between seismic activity and ionospheric anomalies [116]. Using GNSS-R technology, positive increments in ionospheric amplitude scintillation in a marine environment were measured, and a small but significant correlation between ionospheric scintillation and earthquake occurrence was explored as a possible precursor to earthquakes [44]. Table 6 summarizes the current methods in the literature for observing ionospheric total electron content and disturbances using spaceborne GNSS-R L1 data and raw IF data, and compares the accuracy of the results for different data types and methods. This section reviews the current status and potential of GNSS-R technology in measuring ionospheric total electron content and disturbances. Currently, the main method for monitoring the ionosphere is to use GNSS-R standard data products, which have limitations in spatial resolution and update frequency. The use of raw IF data from spaceborne GNSS-R has improved the observation of ionospheric TEC and filled data gaps in oceanic and polar regions. In the future, with the development and application of GNSS-R technology, particularly with the launch of single-frequency GNSS-R missions (such as the ESA's PRETTY mission) and more CubeSats and low-cost satellites, new avenues will be provided for high-resolution global ionospheric observation. These observations will greatly enhance our understanding of the impacts of space weather and geophysical phenomena and provide more reliable data support for satellite communication and navigation systems. Additionally, it is expected that artificial intelligence and machine learning algorithms can be explored to extract more useful information from GNSS-R data, thereby improving the monitoring and forecasting of ionospheric disturbances. This can provide valuable information for our observations of the ionosphere.