The Estimated Accuracy Numbers (EAN) are representative of the signature of different error signals on the products, including both uncorrelated (i.e., noise) and correlated (spatial and temporal scale) error signals.
key numbers of the observable wavelengths with the DUACS L3 5Hz and 1Hz products are given in the QUID document.
Uncorrelated errors or measurement noise and mesoscale observability
The noise measurements are mainly induced by instrumental (altimeter) measurement errors. They are quantified by an analysis of the wavenumber spectra of the SLA (figure 1). Indeed, the uncorrelated measurement errors is the noise level estimated as the mean value of energy at high wavenumbers (wavelengths smaller than ~5km). It follows the instrumental white-noise linked to the radar speckle noise. For the conventional radar altimeter measurements, the inhomogeneity of the sea state within the altimeter footprint also induces an error visible as a “hump” in the wavenumber spectra of the SLA. It is also included in the noise measurement for the 1Hz product resolution. The full understanding of this hump of spectral energy (Dibarboure et al, 2014) remains to be achieved. This issue is strongly linked with the development of new retracking, new editing strategy or new technology. For the SAR measurement, part of the high frequency signal is characterized by a correlated signal (figure). This signal still need to be fully explained. At this time, it is considered as an additional unknown signal that is assumed to be a “red noise” error considering the ocean geostrophic signal.
The presence of noise measurement on along-track products limits the observability of the shorter mesoscales. The SLA power spectrum density analysis was used in order to determine the wavelength where signal and error are on the same order of magnitude (figure 1). It represents the minimum wavelength associated with the dynamical structures that altimetry would statistically be able to observe with a signal-to-noise ratio greater than 1. This wavelength has been found to be variable in space and time (Dufau et al., 2016). The mean value for Jason-2 was found to be nearly 65 km. The altimeter observability however varies with the altimeter considered (instrument characteristics and precision), the geographical location (correlation with the significant wave height, rain cells) and period considered (Dufau et al., 2016).
Figure 2: The 1 Hz measurement noise observed along Jason-3 tracks before (top) and after (bottom) along-track filtering processing. Note that the scales are different in each panel; unit : root mean square (cm rms).
Errors at climatic scales
In the framework of the ESA SL-CCI project, the altimeter measurement errors at climatic scales have been estimated using the Topex/Poseidon, Jason-1, Jason-2 and Jason-3 missions. Details on the error budget estimation at climatic scale can be found in Ablain et al.,( 2019) and Guérou et al., (2022). Results are summarized in QUID.
All the parameters/algorithms involved in the altimeter measurement processing can induce errors at climatic scales. However, some parameters contribute more strongly than others. The largest sources of errors for Global Mean Sea Level trend estimation have been identified. They concern i) the radiometer wet tropospheric correction with a drift uncertainty in the range of 0.2~0.3 mm/yr Legeais et al., (2014), ii) the orbit error Couhert et al., (2015) and iii) the altimeter parameters (range, sigma-0, SWH) instabilities Ablain et al., (2012), with additional uncertainty of the order of 0.1 mm/yr over the whole altimeter period, and slightly more over the first decade (1993-2002; Ablain, (2013). Errors of multi-mission calibration (see §Systeme – Homogeneization ans cross-calibration) also contribute to the Global Mean Sea Level (GMSL) trend error of about 0.15 mm/yr over the 1993-2010 period Zawadzki and Ablain, (2016). All sources of errors described above also have an impact at the inter annual time scale (< 5 years) close to 2 mm over a 2-5 years period.
The regional sea level trend uncertainty has an average estimate of 0.83 mm/yr with local values ranging from 0.78 to 1.22 mm/yr depending on the regions. These values are only related to the errors of the altimeter instrumental observing system Prandi et al., (2021). The orbit solution remains the main source of the error Couhert et al., (2015) with large spatial patterns at hemispheric scale. Furthermore, errors are higher during the first decade (1993-2002) where the Earth gravity field models are less accurate. Additional errors are still observed, e.g., for the radiometer-based wet tropospheric correction in tropical areas, other atmospheric corrections in high latitudes, and high frequency corrections in coastal areas.