On the retrieval of sea-ice thickness using SMOS polarization differences

Mukesh Gupta,Carolina Gabarro,Justino Martinez,Antonio Turiel,Marcos Portabella

doi:10.1017/jog.2019.26

Abstract

ABSTRACTArctic sea ice is going through a dramatic change in its extent and volume at an unprecedented rate. Sea-ice thickness (SIT) is a controlling geophysical variable that needs to be understood with greater accuracy. For the first time, a SIT-retrieval method that exclusively uses only airborne SIT data for training the empirical algorithm to retrieve SIT from Soil Moisture Ocean Salinity (SMOS) brightness temperature (TB) at different polarization is presented. A large amount of airborne SIT data has been used from various field campaigns in the Arctic conducted by different countries during 2011–15. The algorithm attempts to circumvent the issue related to discrimination between TB signatures of thin SIT versus low sea-ice concentration. The computed SIT has a rms error of 0.10 m, which seems reasonably good (as compared to the existing algorithms) for analysis at the used 25 km grid. This new SIT retrieval product is designed for direct operational application in ice prediction/climate models.

Highlights

Sea-ice thickness (SIT) is one of the essential climate variables that critically contributes to the characterization of Earth’s climate (WMO, 2018)
The use of thin SIT data from EM bird (EMB) with accuracy 0.10 m and thick SIT data from Operation IceBridge (OIB) with accuracy 0.40 m allows a reliable retrieval of SIT using Soil Moisture Ocean Salinity (SMOS) TB (Fig. 2)
The Barcelona Expert Center (BEC) algorithm overcomes many difficulties that previous SIT products did not consider. These are summarized as follows: (1) For the first time, only airborne data are used for algorithm training to retrieve the SIT from polarization difference (PD) of SMOS TB

Summary

Introduction

Sea-ice thickness (SIT) is one of the essential climate variables that critically contributes to the characterization of Earth’s climate (WMO, 2018). SIT is used in estimating the sea-ice volume, high-latitude heat-budget, ship navigation, global ocean circulation of the Earth system (Vinnikov and others, 1999; Maksym, 2019) and SIT data assimilation in regional ice prediction and global climate models (Chen and others, 2017). The volume of sea ice is inaccurately estimated due to uncertainty in SIT and its distribution caused by non-uniform, anisotropic and heterogeneous nature of the surface and bottom of sea ice. Many regional and global climate models use the thermodynamic model of sea-ice growth. The problem of remotesensing retrieval of SIT and its adequate use in various regional ice prediction and global climate models is still a topic of active research

Methods

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Discussion

Conclusion