Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models

Jorge Vazquez-Cuervo,Dustin Carroll,Hong Zhang,Jose Gomez-Valdes,Dimitris Menemenlis,Michael Steele,Chelle Gentemann,Marouan Bouali,Wenqing Tang

doi:10.3390/rs13050831

Abstract

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

Highlights

The Arctic is one of the most critical areas for both climate and biodiversity [1,2]
The magnitude of the freshening depends on the Soil Moisture Active Passive (SMAP) product; with regard to the models, the LLC270 shows little or no freshening, while the higher resolution LLC4320 shows similar freshening as the SMAP products
Two 2019 Saildrone deployments in the Bering, Chukchi, and Beaufort Seas off the Alaskan coast allowed for direct comparisons between the sea-surface salinity (SSS) derived from the onboard

Summary

Introduction

The Arctic is one of the most critical areas for both climate and biodiversity [1,2]. It is one of the most under sampled, due to the difficulty of environmental conditions and seasonality of sea-ice cover. One example is the Yukon River estuary, where changes in stratification are governed by river runoff, sea-ice melt, and precipitation. Part of this paper’s focus is to examine how well SMAP and model-derived SSS can detect the low-SSS signal from the Y-K Delta shelf, where low- salinity water exits from the Yukon and other rivers, with secondary inputs from sea-ice melt and net precipitation minus evaporation. Our analysis should be taken as a preliminary step in the comparison of observations and models to encourage future research and applications in this region

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Conclusion