WAVEFORM CLASSIFICATION AND RETRACKING OF JASON-2 AND JASON-3 IN HALMAHERA SEA

The accuracy of sea surface heights (SSHs) estimation from satellite altimeters is strongly influenced by the microwave reflected signals (or waveforms). Waveforms in open oceans generally have ideal shapes following the Brown (1977) model. However, in coastal and shallow waters, the signals are disturbed by lands, thus resulting in complicated waveforms (non-Brown). Non-Brown waveforms produce inaccurate SSH estimations; therefore, specialized protocols such as waveform classification and retracking are crucial when attempting to produce accurate estimations. In this study, waveforms of Jason-2 and Jason-3 satellite altimeters in the Halmahera were classified and retracked using several algorithms, such as Offset Centre of Gravity (OCOG), Ice, Threshold, and Improved Threshold. The results showed that waveforms in the Halmahera Sea had ten generic classes with dominant class of the Browns. The validation results showed that all retrackers (except OCOG) had the value of correlations exceeding 0.75, and Root Mean Square Error (RMSE) smaller than 25 cm at a distance of 5-20 km from the land. The Threshold 10% was the most common retracker that appeared with the highest improvement percentage (IMP), meanwhile the Ice retracker consistently produced the best correlation (0.86) and the lowest RMSE (16cm). The retracking results showed that waveform retracking generally can improve SSH estimation accuracy from ocean (standard) retracker.

Detecting Lake Level Change From 1992 to 2019 of Zhari Namco in Tibet Using Altimetry Data of TOPEX/Poseidon and Jason-1/2/3 Missions

Zhari Namco, a large lake in the Tibetan Plateau (TP), is sensitive to climate and environmental change. However, it is difficult to retrieve accurate and continuous lake levels for Zhari Namco. A robust strategy, including atmospheric delay correction, waveform retracking, outlier deletion, and inter-satellite adjustment, is proposed to generate a long-term series of lake levels for Zhari Namco through multi-altimeter data. Apparent biases are found in troposphere delay correction from different altimeter products and adjusted using an identical model. The threshold (20%) algorithm is employed for waveform retracking. The two-step method combining a sliding median filter and 2σ criterion is used to eliminate outliers. Tandem mission data of altimeters are used to estimate inter-satellite bias. Finally, a 27-year-long lake level time series of Zhari Namco are constructed using the TOPEX/Poseidon-Jason1/2/3 (T/P-Jason1/2/3) altimeter data from 1992 to 2019, resulting in an accuracy of 10.1 cm for T/P-Jason1/2/3. Temperature, precipitation, lake area, equivalent water height, and in situ gauge data are used for validation. The correlation coefficient more than 0.90 can be observed between this result and in situ gauge data. Compared with previous studies and existing database products, our method yields sequences with the best observational quality and the longest continuous monitoring in Zhari Namco. The time series indicates that the lake level in Zhari Namco has increased by ∼ 5.7 m, with an overall trend of 0.14 ± 0.01 m/yr, showing a fluctuating rate (1992–1999: −0.25 ± 0.05 m/yr, 2000–2008: 0.26 ± 0.04 m/yr, 2009–2016: −0.05 ± 0.03 m/yr, 2017–2019: 1.34 ± 0.34 m/yr). These findings will enhance the understanding of water budget and the effect of climate change in the TP.

Defining a retracking manifold within a radargram stack to improve satellite altimetric water level over coastal seas: A feasibility study

<p>Single-waveform retracking for satellite altimetry applications over coastal zones has reached its limits, obtaining decimeter-level accuracy. The existing retracking methods find a retracker offset in a waveform by analyzing the variation in backscattered power along the bin coordinate. This makes the retracking procedure strongly dependent on noise in backscattered power. Moreover, the success of such methods is only guaranteed for certain waveform types requiring cumbersome pre-processing steps including waveform classification. </p><p>With the launch of the operational Sentinel-3 series of the European Copernicus programme, the algorithms to obtain highly precise water level estimates over inland waters and coastal seas need to become more robust, efficient and fit for automated use. Therefore, the main objective of this study is to demonstrate the potential of developing a next-level retracking algorithm and, consequently, improve altimetric water level determination over coastal regions. To this end, neighboring waveforms are collected into a (single-pass) radargram and, then, such radargrams are stacked over time. These so-called (multi-pass) radargram stacks contain, unlike single waveforms, the full information on spatio-temporal variation of backscattered power over water surfaces.</p><p>The radargram stack eases the recognition of patterns like retracking gate, shoreline, tides, etc. Instead of a retracking gate as a point in the 1D waveform, in a 3D radargram stack a surface referred to as retracking manifold is to be determined.</p><p>The potential of our new approach will be demonstrated using Sentinel 3B data, pass number 655, over the Cuxhaven tide gauge station at the Wadden Sea.</p><p>The idea of waveform retracking by analyzing its spatio-temporal behavior in a 3D data structure opens new pathways for achieving robust and more accurate water level estimates from operational missions, e.g. Sentinel 3, and from future missions, e.g. SWOT, over inland waters and coastal seas.</p>

Coastal Waveform Retracking in the Slick-Rich Sulawesi Sea of Indonesia, Based on Variable Footprint Size with Homogeneous Sea Surface Roughness

Waveforms of radar altimeters are often corrupted due to heterogeneous sea surface roughness within footprints, such as slicks. In past studies, subwaveform retrackers such as the adaptive leading edge subwaveform retracker (ALES) which use only a section of the waveform have been proposed. However, it is difficult to choose a reasonable estimation window from an individual waveform. In the present study, a post-processed subwaveform retracker is proposed which identifies the waveforms of surrounding along-track points. The size of the estimation window is variable and is determined to keep the sea surface roughness within the corresponding footprint homogeneous. The method was applied to seven years of 20 Hz Jason-2 altimeter data over the slick-rich Sulawesi Sea of Indonesia and compared with ALES and sensor geophysical data record (SGDR) products. The standard deviation of the sea surface dynamic heights was around 0.13 m, even without spatial smoothing or some geophysical corrections. This is only 75% and 25% of the ALES and SGDR results, respectively. Moreover, all retrievals of the range, SWH, and sigma0 include less outliers than the other products. These results indicate that the variable estimation windows determined in the present study can adapt well to the variation of sea surface roughness.

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.