On the “Cal‐Mode” Correction to TOPEX Satellite Altimetry and Its Effect on the Global Mean Sea Level Time Series

Beckley, B. D.; Callahan, Philip S.; Hancock, D. W.; Mitchum, Gary T.; Ray, Richard D.

doi:10.1002/2017jc013090

Cited by 89 publications

(89 citation statements)

References 49 publications

(87 reference statements)

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“…In addition, between 1993 and 1998, GMSL is known to have been affected by instrumental drift in the TOPEX- A measurement, as quantified by several studies (Watson et al, 2015;Beckley et al, 2017;Dieng et al, 2017). The sea level altimetry community agrees that it is necessary to correct the TOPEX-A record for instrumental drift to improve accuracy and reduce uncertainty in the total sea level record.…”

Section: Climate Scalesmentioning

confidence: 99%

DUACS DT2018: 25 years of reprocessed sea level altimetry products

Taburet¹,

Sánchez-Román²,

Ballarotta³

et al. 2019

Ocean Sci.

299

279

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For more than 20 years, the multi-satellite Data Unification and Altimeter Combination System (DUACS) has been providing near-real-time (NRT) and delayedtime (DT) altimetry products. DUACS datasets range from along-track measurements to multi-mission sea level anomaly (SLA) and absolute dynamic topography (ADT) maps. The DUACS DT2018 ensemble of products is the most recent and major release. For this, 25 years of altimeter data have been reprocessed and are available through the Copernicus Marine Environment Monitoring Service (CMEMS) and the Copernicus Climate Change Service (C3S).Several changes were implemented in DT2018 processing in order to improve the product quality. New altimetry standards and geophysical corrections were used, data selection was refined and optimal interpolation (OI) parameters were reviewed for global and regional map generation. This paper describes the extensive assessment of DT2018 reprocessing. The error budget associated with DT2018 products at global and regional scales was defined and improvements on the previous version were quantified (DT2014;Pujol et al., 2016). DT2018 mesoscale errors were estimated using independent and in situ measurements. They have been reduced by nearly 3 % to 4 % for global and regional products compared to DT2014. This reduction is even greater in coastal areas (up to 10 %) where it is directly linked to the geophysical corrections applied to DT2018 processing. The conclusions are very similar concerning geostrophic currents, for which error was globally reduced by around 5 % and as much as 10 % in coastal areas.

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Section: Climate Scalesmentioning

confidence: 99%

DUACS DT2018: 25 years of reprocessed sea level altimetry products

Taburet¹,

Sánchez-Román²,

Ballarotta³

et al. 2019

Ocean Sci.

299

279

View full text Add to dashboard Cite

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“…For the v2.0 GMSL, the same trend of 3.3 mm yr −1 is found for the 1993-2003 and 2005-2015 altimetry decades, indicating a steady rise of the GMSL. However, several recent studies using different approaches suggest that an instrumental drift has affected the TOPEX-A altimeter measurements during 1993(Valladeau et al, 2012Watson et al, 2015;Dieng et al, 2017;Beckley et al, 2017). The instrumental drift of the TOPEX-A altimeter has long been known (Hayne and Handcock, 1998), leading to the switch early 1999 to the redundant TOPEX-B altimeter.…”

Section: Long-term Gmsl Evolutionmentioning

confidence: 99%

“…Using a sea level budget approach, Dieng et al (2017) also estimated the TOPEX-A drift correction to 1.5 ± 0.5 mm yr −1 for 1993-1998. Another approach was followed by Beckley et al (2017), consisting of suppressing the so-called "internal calibrationmode" range correction, included in the TOPEX-A "net instrument" correction and considered as suspect. Account-ing for the TOPEX-A instrumental correction for the first 6 years of the altimetry dataset, these studies provided a revised GMSL time series that slightly reduces the average GMSL rise over the altimetry era (from 3.3 to 3.0 mm yr −1 ), but shows clear acceleration over 1993-present.…”

Section: Long-term Gmsl Evolutionmentioning

confidence: 99%

An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative

Legeais

Ablain

Zawadzki

et al. 2018

Earth Syst. Sci. Data

183

135

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Abstract. Sea level is a very sensitive index of climate change since it integrates the impacts of ocean warming and ice mass loss from glaciers and the ice sheets. Sea level has been listed as an essential climate variable (ECV) by the Global Climate Observing System (GCOS). During the past 25 years, the sea level ECV has been measured from space by different altimetry missions that have provided global and regional observations of sea level variations. As part of the Climate Change Initiative (CCI) program of the European Space Agency (ESA) (established in 2010), the Sea Level project (SL_cci) aimed to provide an accurate and homogeneous long-term satellite-based sea level record. At the end of the first phase of the project (2010)(2011)(2012)(2013), an initial version (v1.1) of the sea level ECV was made available to users . During the second phase of the project (2014-2017), improved altimeter standards were selected to produce new sea level products (called SL_cci v2.0) based on nine altimeter missions for the period 1993-2015 (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612; Legeais and the ESA SL_cci team, 2016c). Corresponding orbit solutions, geophysical corrections and altimeter standards used in this v2.0 dataset are described in detail in Quartly et al. (2017). The present paper focuses on the description of the SL_cci v2.0 ECV and associated uncertainty and discusses how it has been validated. Various approaches have been used for the quality assessment such as internal validation, comparisons with sea level records from other groups and with in situ measurements, sea level budget closure analyses and comparisons with model outputs. Compared with the previous version of the sea level ECV, we show that use of improved geophysical corrections, careful bias reduction between missions and inclusion of new altimeter missions lead to improved sea level products with reduced uncertainties on different spatial and temporal scales. However, there is still room for improvementPublished by Copernicus Publications. 282J.-F. Legeais et al.: An improved and homogeneous altimeter sea level record from the ESA since the uncertainties remain larger than the GCOS requirements (GCOS, 2011). Perspectives on subsequent evolution are also discussed.

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“…Global mean sea levels have risen~3 mm/year over the last 25 years of satellite observations (Beckley et al, 2017). The observed sea level rise (SLR) has already been linked to increases in nuisance flooding (Ray & Foster, 2016;Sweet & Park, 2014), beach erosion or shoreline retreat (Albert et al, 2016;Wahl & Plant, 2015), and coastal habitat loss (Jankowski et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

et al. 2019

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Rising seas coupled with ever increasing coastal populations present the potential for significant social and economic loss in the 21st century. Relatively short records of the full multidimensional space contributing to total water level coastal flooding events (astronomic tides, sea level anomalies, storm surges, wave run-up, etc.) result in historical observations of only a small fraction of the possible range of conditions that could produce severe flooding. The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential is presented here as a methodology capable of producing new iterations of the sea-state parameters associated with the present-day Pacific Ocean climate to simulate many synthetic extreme compound events. The emulator utilizes weather typing of fundamental climate drivers (sea surface temperatures, sea level pressures, etc.) to reduce complexity and produces new daily synoptic weather chronologies with an auto-regressive logistic model accounting for conditional dependencies on the El Niño Southern Oscillation, the Madden-Julian Oscillation, seasonality, and the prior two days of weather progression. Joint probabilities of sea-state parameters unique to simulated weather patterns are used to create new time series of the hypothetical components contributing to synthetic total water levels (swells from multiple directions coupled with water levels due to wind setup, temperature anomalies, and tides). The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential reveals the importance of considering the multivariate nature of extreme coastal flooding, while progressing the ability to incorporate large-scale climate variability into site specific studies assessing hazards within the context of predicted climate change in the 21st century.Plain Language Summary Predicting extreme coastal flooding is a present-day societal need and will only become more relevant as mean water levels increase due to sea level rise. However, the number of processes contributing to such events is too high for relatively short observational records to have measured all of the constructive combinations of waves, surge, wind, and sea level anomalies. We present a framework designed to create hypothetical combinations of relevant flood hazard potential processes by simulating the climate and weather patterns that drive coastal flooding. Including large-scale oceanic and atmospheric patterns as the drivers of coastal hazards reveals the climate a coastal community is most vulnerable to, which will be increasingly more important to understand as the climate changes during the 21st century.

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On the “Cal‐Mode” Correction to TOPEX Satellite Altimetry and Its Effect on the Global Mean Sea Level Time Series

Cited by 89 publications

References 49 publications

DUACS DT2018: 25 years of reprocessed sea level altimetry products

DUACS DT2018: 25 years of reprocessed sea level altimetry products

An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

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