Abstract

Spaceborne radar altimeters record echo waveforms over all Earth surfaces, but their interpretation and quantitative exploitation over the Arctic Ocean is particularly challenging. Radar returns may be from all ocean, all sea ice, or a mixture of the two, so the first task is the determination of which surface and then an interpretation of the signal to give range. Subsequently, corrections have to be applied for various surface and atmospheric effects before making a comparison with a reference level. This paper discusses the drivers for improved altimetry in the Arctic and then reviews the various approaches that have been used to achieve the initial classification and subsequent retracking over these diverse surfaces, showing examples from both LRM (low resolution mode) and SAR (synthetic aperture radar) altimeters. The review then discusses the issues concerning corrections, including the choices between using other remote-sensing measurements and using those from models or climatology. The paper finishes with some perspectives on future developments, incorporating secondary frequency, interferometric SAR and opportunities for fusion with measurements from laser altimetry or from the SMOS salinity sensor, and provides a full list of relevant abbreviations.

Highlights

  • Within the Arctic Ocean, radar altimetry is used to monitor both the sea level and the freeboard of sea ice, i.e., how far the ice surface is above the surrounding water level

  • This paper has provided a review of the technical aspects of radar altimetry over the Arctic for both sea level and sea-ice studies and complements the scientific review provided by Johannessen and Andersen [1]

  • It has shown how the surface type affects the shape and strength of the return waveforms, both for low-resolution measurement (LRM) and Synthetic Aperture Radar (SAR) altimeters. It has covered the challenges of robustly classifying the waveforms and developing retracking approaches for deriving the height of the reflecting surface, especially with spurious extra signals due to off-nadir bright targets

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Summary

Introduction

Within the Arctic Ocean, radar altimetry is used to monitor both the sea level and the freeboard of sea ice, i.e., how far the ice surface is above the surrounding water level. The sea level is a measure of the amount of water within a basin, but assuming the geostrophic approximation to be valid, its spatial derivative is an indicator of surface currents. Arctic Ocean altimetry helps provide a number of measures for monitoring the environment, both for short-term responses to force and to understand the effects of climate change. This paper provides a review of the methodological techniques required to obtain useful environmental information from altimeters, giving an overview of the choice of approaches available to interested users. This paper does not explore the scientific results achieved because there has been a good recent summary of those by Johannessen and Andersen [1]

Scientific and Operational Requirements
Relevant Altimeter Datasets
Waveform Discrimination
LRM Altimeters
Classical Techniques
Statistical Techniques
SAR Altimeters
Power-Based Methods
RIP and Waveform Shape-Based Methods
Validation of Discrimination
Validation with Optical Sensors
Validation with SAR
Validation Through Dedicated Aircraft Campaigns
Waveform Retracking
Waveform Retracking for Ice Floes
LRM Retracking for Ice Floes
Empirical SAR Waveform Retracking for Ice Floes
Physical SAR waveform Retracking for Ice Floes
LRM Model for Leads
SAR Retracking for Leads
Unified Models for Physical Retracking
Quality Control
Snagging Effect Within Altimeter Data
Azimuth Ambiguity Effect Within SAR Data
Ensuring Consistency in Space and Time
Determining Sea Level
Atmospheric Corrections
Tides and Mean Sea Surface
Amplitude and Scale Length of Corrections
Interpolating Sea Level Anomaly and Calculating Freeboard
Freeboard to Thickness Conversions
Impact of Snow on Sea-Ice Freeboard and Thickness Retrievals
Comparison With In Situ and Airborne Measurements
Sea Level and Currents
Freeboard and Sea-Ice Thickness
Freeboard
Validation of Algorithms
Future Prospects
Improvements in Processing
New Missions with New Capabilities
Utilising Data Fusion Techniques
Enhanced in Situ Observations
Findings
Conclusions
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