2016
DOI: 10.1016/j.asr.2016.04.011
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Cross-calibrating ALES Envisat and CryoSat-2 Delay–Doppler: A coastal altimetry study in the Indonesian Seas

Abstract: A regional cross-calibration between the first Delay-Doppler altimetry dataset from Cryosat-2 and a retracked Envisat dataset is here presented, in order to test the benefits of the Delay-Doppler processing and to expand the Envisat time series in the coastal ocean. The Indonesian Seas are chosen for the calibration, since the availability of altimetry data in this region is particularly beneficial due to the lack of in-situ measurements and its importance for global ocean circulation. The Envisat data in the … Show more

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Cited by 45 publications
(36 citation statements)
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“…The rate of sea level rise in this region, derived from altimeter missions over 23 years is higher than the global mean sea level rate about 3.2-3.3 mm/year [13,14]. The positive values of sea level trend in this study are about 2-7 mm/year in agreement with other results in the same areas using altimetry [18][19][20]. The variability of sea level around the Indonesia seas is high mainly due to the effect of ENSO event (El Niño/La Niña).…”
Section: Discussionsupporting
confidence: 82%
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“…The rate of sea level rise in this region, derived from altimeter missions over 23 years is higher than the global mean sea level rate about 3.2-3.3 mm/year [13,14]. The positive values of sea level trend in this study are about 2-7 mm/year in agreement with other results in the same areas using altimetry [18][19][20]. The variability of sea level around the Indonesia seas is high mainly due to the effect of ENSO event (El Niño/La Niña).…”
Section: Discussionsupporting
confidence: 82%
“…For these areas they report sea level trends from 4 to 8 mm/year, based on altimetric measurements during 1993 to 2009. However, in [20], the trends of several seas in the Indonesian region, derived using Cryosat data and retracked Envisat data using ALES, are 2.9 mm/year, 2.9 mm/year, 1.7 mm/year and 3.3 mm/year for Java sea, Flores sea, Banda sea and Ceram sea, respectively, during the period 2002 to 2015.…”
Section: Discussionmentioning
confidence: 99%
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“…red and orange lines in Figure ), so the mean SSH is not well characterized along its ground tracks, and there are still comparatively few satellite passes over each of the Sentinel‐3 ground tracks in the California Current, meaning that SSH anomalies from Sentinel‐3 may have more residual geoid contamination than those from other satellites. Previous studies based on Cryosat‐2 (also a delay‐Doppler altimeter) in the Indonesian seas suggest that the use of a global mean sea surface model to remove the mean SSH along sparsely sampled ground tracks does not amplify the overall spatial variance of SSH within 50‐km × 50‐km test patches (Passaro et al, ). Here, however, we are interested in along‐track data and high‐wavenumber spectra, and therefore, we cannot exclude the possibility of residual geoid contamination in the along‐track means.…”
Section: Methodsmentioning
confidence: 99%
“…Along-strait pressure gradient (∂η) is estimated by subtracting η averaged in the northern Makassar Strait (η Ν ) from η averaged in the southern Makassar Strait (η S ). Satellite altimetry-retrieved η data in the Indonesian seas have been validated and reliably used in previous studies (Lee et al, 2017;Passaro et al, 2016;Xu et al, 2016). The η and τ data have a spatial resolution of 0.25°× 0.25°, while the OLR data have a spatial resolution of 2.5°× 2.5°.…”
Section: 1029/2018jc014729mentioning
confidence: 94%