Multi-Satellite Altimeter Validation along the French Atlantic Coast in the Southern Bay of Biscay from ERS-2 to SARAL

Shipborne GNSS-Determined Sea Surface Heights Using Geoid Model and Realistic Dynamic Topography

With an increasing demand for accurate and reliable estimates of sea surface heights (SSH) from coastal and marine applications, approaches based on GNSS positioning have become favored, to bridge the gap between tide gauge (TG) and altimetry measurements in the coastal zone, and to complement offshore altimetry data. This study developed a complete methodology for jointly deriving and validating shipborne GNSS-determined SSH, using a geoid model and realistic dynamic topography estimates. An approach that combines the properties of hydrodynamic models and TG data was developed to obtain the latter. Tide gauge data allow estimating the spatiotemporal bias of a hydrodynamic model and, thus, linking it to the used vertical datums (e.g., a novel geoid-based Baltic Sea Chart Datum 2000). However, TG data may be erroneous and represent different conditions than offshore locations. The qualities of spatiotemporal bias are, hence, used to constrain TG data errors. Furthermore, a rigid system of four GNSS antennas was used to ensure SSH accuracy. Besides eliminating the vessel’s attitude effect on measurement data, the rigid system also provides a means for internal validation, suggesting a 4.1 cm height determination accuracy in terms of standard deviation. The methodology also involves eliminating the effect of sea state conditions via a low-pass filter and empirical estimation of vessel sailing-related corrections, such as the squat effect. The different data validation (e.g., examination of residual values and intersection analyses) results, ranging from 1.8 cm to 5.5 cm in terms of standard deviation, indicate an SSH determination accuracy of around 5 cm.

Evaluation of Real-Time PPP-Based Tide Measurement Using IGS Real-Time Service

Tide data plays a key role in many marine scientific research fields such as seafloor topography measurement and navigation safety. To obtain reliable tide data, various methods have been proposed, e.g., tide station measurement, satellite altimeter measurement, and differential global positioning system (GPS) buoy measurement. However, these methods suffer from the limitation that continuous observations at different areas might not be always available. In order to provide high-precision as well as continuous real-time tide data, we propose a method based on real-time precise point positioning (RT-PPP) by using International GNSS Service (IGS) real-time service (RTS) products. Firstly, compared with the IGS final products, the accuracy of the RTS satellite orbit and clock is evaluated. Secondly, the positioning performance of RT-PPP is compared with the IGS ultra-fast products. Finally, a robust Vondrak filter is proposed to eliminate the influence of high-frequency noise and errors and to obtain tide results. Experimental results show that three-dimensional (3D) accuracy of the RTS orbit is better than 0.05 m, and also has 0.22 ns less clock bias. An improvement of 60% is achieved for positioning accuracy using RTS products compared to IGS ultra-fast products. Compared with the post-processing PPP method, the double difference (DD) method and tide gauge data, the root mean square (RMS) values of RT-PPP tide are 0.090, 0.194 and 0.167 m, respectively.

Robust, Long-term Lake Level Change from Multiple Satellite Altimeters in Tibet: Observing the Rapid Rise of Ngangzi Co over a New Wetland

Satellite altimetry has been successfully applied to monitoring water level variation of global lakes. However, it is still difficult to retrieve accurate and continuous observations for most Tibetan lakes, due to their high altitude and rough terrain. Aiming to generate long-term and accurate lake level time series for the Tibetan lakes using multi-altimeters, we present a robust strategy including atmosphere delay corrections, waveform retracking, outlier removal and inter-satellite bias adjustment. Apparent biases in dry troposphere corrections from different altimeter products are found, and such correctios must be recalculated using the same surface pressure model. A parameter is defined to evaluate the performance of the retracking algorithm. The ICE retracker outperforms the 20% and 50% threshold retrackers in the case of Ngangzi Co, where a new wetland has been established. A two-step algorithm is proposed for outlier removal. Two methods are adopted to estimate inter-satellite bias for different cases of with and without overlap. Finally, a 25-year-long lake level time series of Ngangzi Co are constructed using the TOPEX/Poseidon-family altimeter data from October 1992 to December 2017, resulting in an accuracy of ~17 cm for TOPEX/Poseidon and ~10 cm for Jason-1/2/3. The accuracy of retrieved lake levels is on the order of decimeter. Because of no gauge data available, ICESat and SARAL data with the accuracy better than 7 cm are used for validation. A correlation more than 0.9 can be observed between the mean lake levels from TOPEX/Poseidon-family satellites, ICESat and SARAL. Compared to the previous studies and other available altimeter-derived lake level databases, our result is the most robust and has resulted in the maximum number of continuous samples. The time series indicates that the lake level of Ngangzi Co increased by ~8 m over 1998–2017 and changed with different rates in the past 25 years (-0.39 m/yr in 1992–1997, 1.03 m/yr in 1998–2002 and 0.32 m/yr in 2003–2014). These findings will enhance the understanding of water budget and the effect of climate change.

Influence of recent climatic events on the surface water storage of the Tonle Sap Lake

Lakes and reservoirs have been identified as sentinels of climate change. Tonle Sap is the largest lake in both the Mekong Basin and Southeast Asia and because of the importance of its ecosystem, it is has been described as the "heart of the lower Mekong". Its seasonal cycle depends on the annual flood pulse governed by the flow of the Mekong River. This study provides an impact analysis of recent climatic events from El Niño 1997/1998 to El Niño 2015/2016 on surface storage variations in the Tonle Sap watershed determined by combining remotely sensed observations, multispectral images and radar altimetry from 1993 to 2017. The Lake's surface water volume variations are highly correlated with rainy season rainfall in the whole Mekong River Basin (R = 0.84) at interannual time-scale. Extreme droughts and floods can be observed when precipitation deficit and excess is recorded in both the Tonle Sap watershed and the Mekong River Basin during moderate to very strong El Niño/La Niña events (R = -0.70) enhanced by the Pacific Decadal Oscillation (R = -0.68). Indian and Western North Pacific Monsoons were identified as having almost equal influence. Below normal vegetation activity was observed during the first semester of 2016 due to the extreme drought in 2015.