**2. Data description and processing procedures**

The experimental region encompasses the Southeast Asia, which comprises of the Andaman Sea, the Strait of Malacca, the Gulf of Thailand, the South China Sea, and the Sulu Sea (**Figure 2**). It covers an area of about 20°N–5°S and 95°E–126°E.

The data utilized in this study are acquired from several agencies. The altimeter data are available at the Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) ftp site (ftp://avisoftp.cnes.fr). SGDR product, which comprises of 40 Hz of data from cycles 1 to 19 (April 2013–December 2014), are utilized. Hourly tide gauge measurements are supplied by the Department of Survey and Mapping Malaysia (DSMM) and the University of Hawaii Sea Level Centre (UHSLC); https://uhslc.soest.hawaii.edu). There are six tide gauge stations used in this study, which are Geting, Langkawi, Bintulu, Lubang, Ko Taphao Noi, and Vung Tau (**Figure 2**). The hourly tide gauge data are acquired from March 2013 to December 2014.

where *H* is satellite altitude, *Robs* is the observed range, *Rretracked* is the range corrections from the retracking algorithm (i.e., MLE-4, Ice-1 and Ice-2), *Rdry* and *Rwet* are dry and wet tropospheric corrections, *Riono* is ionospheric correction, *Rssb* is sea state bias correction, *mssh* is mean sea surface height, *hot* is ocean tides, *hsolid* is solid earth tides, *hpole* is pole tides, *hload* is tidal loading, *hiny* is inverse barometer height correction, and *hhf* is high frequency fluctuations. The correction of *Rdry* and *Rwet* are based on the European Centre for Medium-Range Weather Forecasts, *Riono* is from the Global Ionospheric Map, *Rssb* is from the Hybrid sea state bias [34], and *hot* is from the FES2012 model. Due to limited number of data samples (~1.5 years) used in this study, the global FES2012 tidal model is used rather than a coastal tidal model such as the pointwise tide model (e.g., [35]). The use of pointwise tide modeling for resolving tidal signals requires at least 3 years of datasets to ensure that the individual constituents are separated due to the Rayleigh criterion [36]). It is noted that the use of the global tidal model to resolve coastal tidal signals may produce inaccurate results because tidal signals in the coastal regions are more

**Figure 2.** The region of the study area. Red marks indicate the tide gauge stations and green lines indicate the AltiKa

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

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

49

ground passes. The blue lines are the AltiKa ground passes used for validation with tide gauge.

The tide gauge data is processed to extract a non-tidal sea level time series, so that the physical contents are comparable to the satellite altimetry. The sea level measured by the tide gauge is different from the sea level measured by the satellite altimeter. The tide gauge measures the

complex than in the deep ocean.

For altimeter data, two processing steps are involved in the derivation of sea level: (1) by applying the range correction and (2) by correcting the impact of atmosphere and ocean geophysical. The range corrections are obtained from MLE-4, Ice-1, and Ice-2 retracking algorithms. The MLE-4 and Ice-2 algorithms are based on the theoretical model of scattering surface of Brown [10], and Ice-1 is the empirical method of the OCOG [15]. The geophysical amendments correct the SLAs by isolating the ocean dynamic height contributors of ocean tides, atmospheric refraction, and atmospheric pressure loading such as sea state bias (SSB) and inverse barometer.

The SLA from AltiKa is derived from Eq. (1) [33];

$$\text{SLA} = H - \left(R\_{\text{obs}} - R\_{\text{netrad}d} - \Delta R\_{\text{net}} - \Delta R\_{\text{dry}} - \Delta R\_{\text{ins}} - \Delta R\_{\text{asb}} - \text{massh}\right) - h\_{\text{at}} - h\_{\text{soil}} - h\_{\text{fuel}} - h\_{\text{ing}} - h\_{\text{ft}} \tag{1}$$

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the… http://dx.doi.org/10.5772/intechopen.74399 49

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

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

The experimental region encompasses the Southeast Asia, which comprises of the Andaman Sea, the Strait of Malacca, the Gulf of Thailand, the South China Sea, and the Sulu Sea (**Figure 2**).

The data utilized in this study are acquired from several agencies. The altimeter data are available at the Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) ftp site (ftp://avisoftp.cnes.fr). SGDR product, which comprises of 40 Hz of data from cycles 1 to 19 (April 2013–December 2014), are utilized. Hourly tide gauge measurements are supplied by the Department of Survey and Mapping Malaysia (DSMM) and the University of Hawaii Sea Level Centre (UHSLC); https://uhslc.soest.hawaii.edu). There are six tide gauge stations used in this study, which are Geting, Langkawi, Bintulu, Lubang, Ko Taphao Noi, and Vung Tau (**Figure 2**). The hourly tide gauge data are acquired from March

For altimeter data, two processing steps are involved in the derivation of sea level: (1) by applying the range correction and (2) by correcting the impact of atmosphere and ocean geophysical. The range corrections are obtained from MLE-4, Ice-1, and Ice-2 retracking algorithms. The MLE-4 and Ice-2 algorithms are based on the theoretical model of scattering surface of Brown [10], and Ice-1 is the empirical method of the OCOG [15]. The geophysical amendments correct the SLAs by isolating the ocean dynamic height contributors of ocean tides, atmospheric refraction, and atmospheric pressure loading such as sea state bias (SSB)

*SLA* = *H* − (*Robs* − *Rretracked* − ∆*Rwet* − ∆*Rdry* − ∆*Riono* − ∆*Rssb* − *mssh*) − *hot* − *hsolid* − *hpole* − *hload* − *hiny* − *hhf* (1)

retracked sea levels with tide gauges.

48 Multi-purposeful Application of Geospatial Data

Section 5 concludes the chapter.

2013 to December 2014.

and inverse barometer.

**2. Data description and processing procedures**

It covers an area of about 20°N–5°S and 95°E–126°E.

The SLA from AltiKa is derived from Eq. (1) [33];

**Figure 2.** The region of the study area. Red marks indicate the tide gauge stations and green lines indicate the AltiKa ground passes. The blue lines are the AltiKa ground passes used for validation with tide gauge.

where *H* is satellite altitude, *Robs* is the observed range, *Rretracked* is the range corrections from the retracking algorithm (i.e., MLE-4, Ice-1 and Ice-2), *Rdry* and *Rwet* are dry and wet tropospheric corrections, *Riono* is ionospheric correction, *Rssb* is sea state bias correction, *mssh* is mean sea surface height, *hot* is ocean tides, *hsolid* is solid earth tides, *hpole* is pole tides, *hload* is tidal loading, *hiny* is inverse barometer height correction, and *hhf* is high frequency fluctuations. The correction of *Rdry* and *Rwet* are based on the European Centre for Medium-Range Weather Forecasts, *Riono* is from the Global Ionospheric Map, *Rssb* is from the Hybrid sea state bias [34], and *hot* is from the FES2012 model. Due to limited number of data samples (~1.5 years) used in this study, the global FES2012 tidal model is used rather than a coastal tidal model such as the pointwise tide model (e.g., [35]). The use of pointwise tide modeling for resolving tidal signals requires at least 3 years of datasets to ensure that the individual constituents are separated due to the Rayleigh criterion [36]). It is noted that the use of the global tidal model to resolve coastal tidal signals may produce inaccurate results because tidal signals in the coastal regions are more complex than in the deep ocean.

The tide gauge data is processed to extract a non-tidal sea level time series, so that the physical contents are comparable to the satellite altimetry. The sea level measured by the tide gauge is different from the sea level measured by the satellite altimeter. The tide gauge measures the changes in sea level over time relative to a datum, which is mean sea surface height (MSSH). Meanwhile, the altimeter measures the sea level above the reference ellipsoid.

The tide gauge is designed to estimate tides. In order to find the non-tidal sea level, highfrequency tidal effects on the tide gauge data need to be removed. Tidal signals from the tide gauge are removed using a harmonic analysis method [37, 38]. Harmonic analysis is a mathematical process which separates the observed tide into basic harmonic constituents. This method can determine the amplitude and phase of tidal constituents from a long-time series observation. It models the tidal signals as the sum of a finite set of sinusoids at specific frequencies related to astronomical parameters. If the amplitude and phase of each constituent is known, it can be removed from the sea level measurement [37].
