Abstract

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 (2010–2013), an initial version (v1.1) of the sea level ECV was made available to users (Ablain et al., 2015). 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 improvement since the uncertainties remain larger than the GCOS requirements (GCOS, 2011). Perspectives on subsequent evolution are also discussed.

Highlights

  • Present-day global mean sea level (GMSL) rise primarily reflects the amount of heat added to the ocean, as well as land ice melt in response to anthropogenic global warming (e.g. IPCC, 2013; von Schuckmann et al, 2016)

  • Compared with the previous version of the sea level essential climate variables” (ECVs), 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

  • This paper describes the sea level CCI project (SL_cci) v2.0 ECV and presents some validation results obtained through different approaches

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Summary

Introduction

Present-day global mean sea level (GMSL) rise primarily reflects the amount of heat added to the ocean, as well as land ice melt in response to anthropogenic global warming (e.g. IPCC, 2013; von Schuckmann et al, 2016). The Global Climate Observing System (GCOS) defined a list of key parameters of the Earth system, or “essential climate variables” (ECVs) that need to be accurately monitored in order to meet the needs of the climate change community (Bojinski et al, 2014) To respond to this need for climate-quality satellite data, the European Space Agency (ESA) developed the “Climate Change Initiative” (CCI) program. They correspond to the error levels to be met by the sea level record on different spatial and temporal scales (e.g. long-term evolution and inter-annual and annual signals) These requirements have been considered as a reference within the CCI program and especially when assessing the quality of the SL_cci ECV. The paper finishes with the discussion of perspectives on evolution of the sea level products

Input data and altimeter standards
Long-term GMSL evolution
Inter-annual signals
Seasonal cycle
Regional sea level trends
Mesoscale signals
Sea level budget closure and comparison with model outputs
Comparison with ocean reanalyses
Comparison with the TOPAZ and NorESM models in the Arctic region
Validation based on the GECCO model of the University of Hamburg
Regional sea level validation: agreement with ocean model outputs
MSL error characterization and uncertainties
Findings
Conclusions and perspectives
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