**1. Introduction**

Satellite altimeter occupies the radar technology at vertical incidence. It measures the twoway travel time of pulses, which corresponds to the distance between the satellite and the ocean surface. The time between the transmission of the pulses to the reception of the reflected echoes is proportional to the satellite's orbital height. Through the magnitude and shape of

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

the echoes (or waveform), geophysical information about the ocean surfaces (i.e., sea level, wave height, and wind speed) can be retrieved (**Figure 1**).

**Figure 1** shows the altimetric waveforms over the open and coastal oceans. The waveform shape over the open ocean (**Figure 1a**) follows the Brown [10] model. It features a sharp increase of leading edge, following a decreasing plateau. From the shape, several ocean parameters can be deduced. The parameter of wind speed can be deduced from the waveform amplitude, the sea level from the mid-point of leading edge, and the significant wave height from the slope of leading edge. Satellite instrumentation parameters can also be deduced: thermal noise and antenna mispointing angle (based on the slope of trailing edge). In **Figure 1b**, the land impact is clearly seen in the waveform, which features high amplitude on the waveform trailing edge. In case of corrupted waveforms, the processor tracker on-board of the satellite cannot properly determine the ocean parameters. Therefore, an efficient signal post-processing called as "the retracking" should be performed on the ground to optimize the accuracy of the estimation [8]. This is because the leading edge of waveform deviates from the on-board tracking gate [8],

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the…

http://dx.doi.org/10.5772/intechopen.74399

47

Waveform retracking can be conducted based on the physical (e.g., MLE4, OCE3, and Red3) or empirical (e.g., Ice1 and Offset Centre of Gravity (OCOG)) retrackers. The former fits the waveforms to an ocean surface model (e.g., [10]) to retrieve the optimized parameters (e.g., [10–13, 14]), and the latter retrieves the parameters based on the empirical assumption about

Due to the low quality of altimeter geophysical retrieval over coastal oceans, data are usually systematically flagged and rejected. The coastal water is poorly observed, particularly within ~10 km of the shoreline [17, 18]. The no data gaps over coastal regions have been improved with the advanced altimetric technology such as AltiKa and Sentinel 3A altimetry mission. The AltiKa satellite operates with a Ka-band (~35.8 GHz) frequency signal. It produces a finer spatial resolution when compared to Ku-band (~13.5 GHz). With the smaller size footprint (~8 km in diameter compared to 20 km for Jason-2 and 15 km for Envisat) [19] and higher spatial resolution along the satellite track (40 Hz, compared to 20 Hz for Jason-2), the AltiKa can bring measurements closer to the coastline and produces excellent data coverage (~99%) [20, 21].

This chapter provides a necessary step to derive accurate sea level anomaly (SLA) from AltiKa satellite altimetry. The framework developed in this chapter should enable the derivation of accurate sea levels over the Southeast Asia regions. The launched of the AltiKa satellite mission promises a significant refinement of coastal altimetry, with advanced instruments, an improved retracking algorithm, and geophysical corrections [7, 19, 20, 22, 23]. The validation and calibration of the satellite mission are compulsory to find the level of confidence on the data quality before it can be used in any applications. Global calibrations for AltiKa have been conducted by Centre National d'Etudes Spatiales (CNES), Indian Space Research Organization (ISRO), and many other researchers (e.g., [5, 19, 20, 24, 25]). However, limited research focuses on the regional validation over the Southeast Asia (e.g., [24, 26–29]). The regional validation is important because the ocean characteristics of the region are significantly different than the other oceans, such as the Pacific and Atlantic Ocean. It is characterized by marginal and semi-closed oceans that contain many small islands and a broad range of topographic features, thus producing complicated waveform patterns when they enter the altimeter footprints. Therefore, this study is conducted to quantify the quality of sea levels

thus reducing the accuracy of measurements.

derived from the AltiKa over the Southeast Asia region.

the signals (e.g., [15, 16]).

There are two types of radar altimetry: pulse-limited and beam-limited. The pulse-limited altimeter dictates the shape of returning signals by the length (width) of the pulse; meanwhile, the beam-limited dictates the shape of returning signals by the width of the beam (cf. [1]). The technology of pulse-limited altimeter has been used over the past 30 years, on-board of various altimetry missions such as ERS series, Jason series, and SARAL/AltiKa. Contrary, the beam-limited altimeter is considered as an advanced technology, which carries delay-Doppler altimeter instrument on-board of Cryosat-2 and Sentinel 3A satellites. With the advanced technology, the improvement can be seen in terms of the along-track spatial resolution, the noise ratio, and the sensitivity rate to the sea states [1].

The altimetry data have been beneficial for measuring ocean geophysical parameters, particularly the sea levels. They have been embedded in several ocean modeling systems such as the Australian national coastal modeling hindcast/forecast systems (e.g., BLUElink), and Regional Ocean Modeling System in Alaska, the United States of America. The altimetry can provide highly accurate sea level measurement (in cm level) over the open ocean due to proper modeling of ocean state qualities (e.g., tides) and accurate measurement of atmospheric refractions [2]. The altimetry is capable of providing accurate information of ocean properties up to 4 cm in height measurements [3, 4] and 2–3 cm in mean sea level variations [5].

However, in coastal regions, altimetry and its applications face many challenges (e.g., [2, 6–9]) due to various reasons. The accuracy of measurements decreases abruptly as the altimeter approaches the coast, where the sea conditions can diverge drastically over time and space. In addition, the altimetric waveforms within a footprint are usually corrupted by land, resulting in complicated ocean signals.

**Figure 1.** Examples of returned waveforms. (a) Brown-shaped waveform over homogeneous ocean surface. (b) Nonbrown waveform over complex coastal area.

**Figure 1** shows the altimetric waveforms over the open and coastal oceans. The waveform shape over the open ocean (**Figure 1a**) follows the Brown [10] model. It features a sharp increase of leading edge, following a decreasing plateau. From the shape, several ocean parameters can be deduced. The parameter of wind speed can be deduced from the waveform amplitude, the sea level from the mid-point of leading edge, and the significant wave height from the slope of leading edge. Satellite instrumentation parameters can also be deduced: thermal noise and antenna mispointing angle (based on the slope of trailing edge). In **Figure 1b**, the land impact is clearly seen in the waveform, which features high amplitude on the waveform trailing edge. In case of corrupted waveforms, the processor tracker on-board of the satellite cannot properly determine the ocean parameters. Therefore, an efficient signal post-processing called as "the retracking" should be performed on the ground to optimize the accuracy of the estimation [8]. This is because the leading edge of waveform deviates from the on-board tracking gate [8], thus reducing the accuracy of measurements.

the echoes (or waveform), geophysical information about the ocean surfaces (i.e., sea level,

There are two types of radar altimetry: pulse-limited and beam-limited. The pulse-limited altimeter dictates the shape of returning signals by the length (width) of the pulse; meanwhile, the beam-limited dictates the shape of returning signals by the width of the beam (cf. [1]). The technology of pulse-limited altimeter has been used over the past 30 years, on-board of various altimetry missions such as ERS series, Jason series, and SARAL/AltiKa. Contrary, the beam-limited altimeter is considered as an advanced technology, which carries delay-Doppler altimeter instrument on-board of Cryosat-2 and Sentinel 3A satellites. With the advanced technology, the improvement can be seen in terms of the along-track spatial resolu-

The altimetry data have been beneficial for measuring ocean geophysical parameters, particularly the sea levels. They have been embedded in several ocean modeling systems such as the Australian national coastal modeling hindcast/forecast systems (e.g., BLUElink), and Regional Ocean Modeling System in Alaska, the United States of America. The altimetry can provide highly accurate sea level measurement (in cm level) over the open ocean due to proper modeling of ocean state qualities (e.g., tides) and accurate measurement of atmospheric refractions [2]. The altimetry is capable of providing accurate information of ocean properties up to 4 cm

However, in coastal regions, altimetry and its applications face many challenges (e.g., [2, 6–9]) due to various reasons. The accuracy of measurements decreases abruptly as the altimeter approaches the coast, where the sea conditions can diverge drastically over time and space. In addition, the altimetric waveforms within a footprint are usually corrupted by land, resulting

**Figure 1.** Examples of returned waveforms. (a) Brown-shaped waveform over homogeneous ocean surface. (b) Non-

wave height, and wind speed) can be retrieved (**Figure 1**).

46 Multi-purposeful Application of Geospatial Data

tion, the noise ratio, and the sensitivity rate to the sea states [1].

in height measurements [3, 4] and 2–3 cm in mean sea level variations [5].

in complicated ocean signals.

brown waveform over complex coastal area.

Waveform retracking can be conducted based on the physical (e.g., MLE4, OCE3, and Red3) or empirical (e.g., Ice1 and Offset Centre of Gravity (OCOG)) retrackers. The former fits the waveforms to an ocean surface model (e.g., [10]) to retrieve the optimized parameters (e.g., [10–13, 14]), and the latter retrieves the parameters based on the empirical assumption about the signals (e.g., [15, 16]).

Due to the low quality of altimeter geophysical retrieval over coastal oceans, data are usually systematically flagged and rejected. The coastal water is poorly observed, particularly within ~10 km of the shoreline [17, 18]. The no data gaps over coastal regions have been improved with the advanced altimetric technology such as AltiKa and Sentinel 3A altimetry mission. The AltiKa satellite operates with a Ka-band (~35.8 GHz) frequency signal. It produces a finer spatial resolution when compared to Ku-band (~13.5 GHz). With the smaller size footprint (~8 km in diameter compared to 20 km for Jason-2 and 15 km for Envisat) [19] and higher spatial resolution along the satellite track (40 Hz, compared to 20 Hz for Jason-2), the AltiKa can bring measurements closer to the coastline and produces excellent data coverage (~99%) [20, 21].

This chapter provides a necessary step to derive accurate sea level anomaly (SLA) from AltiKa satellite altimetry. The framework developed in this chapter should enable the derivation of accurate sea levels over the Southeast Asia regions. The launched of the AltiKa satellite mission promises a significant refinement of coastal altimetry, with advanced instruments, an improved retracking algorithm, and geophysical corrections [7, 19, 20, 22, 23]. The validation and calibration of the satellite mission are compulsory to find the level of confidence on the data quality before it can be used in any applications. Global calibrations for AltiKa have been conducted by Centre National d'Etudes Spatiales (CNES), Indian Space Research Organization (ISRO), and many other researchers (e.g., [5, 19, 20, 24, 25]). However, limited research focuses on the regional validation over the Southeast Asia (e.g., [24, 26–29]). The regional validation is important because the ocean characteristics of the region are significantly different than the other oceans, such as the Pacific and Atlantic Ocean. It is characterized by marginal and semi-closed oceans that contain many small islands and a broad range of topographic features, thus producing complicated waveform patterns when they enter the altimeter footprints. Therefore, this study is conducted to quantify the quality of sea levels derived from the AltiKa over the Southeast Asia region.

This chapter presents the quality assessment, and the validation of AltiKa sea levels against tide gauges over the Southeast Asia coastal region. The quality assessment identifies how close the data can get to the coastline and how much data can be recovered through three retracking algorithms (i.e., MLE-4, Ice-1, and Ice-2) [30–32] Southeast. It is noted that the three retracking algorithms are the standard retrackers available from the Sensor Geophysical Data Records (SGDR). The assessments are conducted by computing: (1) the percentage of data availability over the Southeast coastal region; (2) the minimum distance of the AltiKa retracked sea level data to the coastline; and (3) the root mean square (RMS) error and temporal correlation of the retracked sea levels with tide gauges.

Section 2 presents the data description and processing procedures involved in the quality assessment and validation; Section 3 reports on the data qualitative assessment, which includes both the percentage of data availability and the minimum distance of sea level to the coastline; Section 4 reports on the validation of retracked sea levels against the tide gauge; and Section 5 concludes the chapter.
