Editorial Type:
Article
Article Type:
Research Article

Spatial Optimal Interpolation of Aquarius Sea Surface Salinity: Algorithms and Implementation in the North Atlantic

Oleg Melnichenko International Pacific Research Center, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Peter Hacker Hawaii Institute of Geophysics and Planetology, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Nikolai Maximenko International Pacific Research Center, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Gary Lagerloef Earth and Space Research, Seattle, Washington

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James Potemra Hawaii Institute of Geophysics and Planetology, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Print Publication:
01 Jul 2014
DOI:
https://doi.org/10.1175/JTECH-D-13-00241.1
Page(s):
1583–1600
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Abstract

A method is presented for mapping sea surface salinity (SSS) from Aquarius level-2 along-track data in order to improve the utility of the SSS fields at short length [O(150 km)] and time [O(1 week)] scales. The method is based on optimal interpolation (OI) and derives an SSS estimate at a grid point as a weighted sum of nearby satellite observations. The weights are optimized to minimize the estimation error variance. As an initial demonstration, the method is applied to Aquarius data in the North Atlantic. The key element of the method is that it takes into account the so-called long-wavelength errors (by analogy with altimeter applications), referred to here as interbeam and ascending/descending biases, which appear to correlate over long distances along the satellite tracks. The developed technique also includes filtering of along-track SSS data prior to OI and the use of realistic correlation scales of mesoscale SSS anomalies. All these features are shown to result in more accurate SSS maps, free from spurious structures. A trial SSS analysis is produced in the North Atlantic on a uniform grid with 0.25° resolution and a temporal resolution of one week, encompassing the period from September 2011 through August 2013. A brief statistical description, based on the comparison between SSS maps and concurrent in situ data, is used to demonstrate the utility of the OI analysis and the potential of Aquarius SSS products to document salinity structure at ~150-km length and weekly time scales.

School of Ocean and Earth Science and Technology Contribution Number 9105 and International Pacific Research Center Contribution Number 1052.

Corresponding author address: Oleg Melnichenko, International Pacific Research Center, University of Hawai‘i at Mānoa, POST Bldg., Room 401, 1680 East-West Road, Honolulu, HI 96822. E-mail: oleg@hawaii.edu

Abstract

A method is presented for mapping sea surface salinity (SSS) from Aquarius level-2 along-track data in order to improve the utility of the SSS fields at short length [O(150 km)] and time [O(1 week)] scales. The method is based on optimal interpolation (OI) and derives an SSS estimate at a grid point as a weighted sum of nearby satellite observations. The weights are optimized to minimize the estimation error variance. As an initial demonstration, the method is applied to Aquarius data in the North Atlantic. The key element of the method is that it takes into account the so-called long-wavelength errors (by analogy with altimeter applications), referred to here as interbeam and ascending/descending biases, which appear to correlate over long distances along the satellite tracks. The developed technique also includes filtering of along-track SSS data prior to OI and the use of realistic correlation scales of mesoscale SSS anomalies. All these features are shown to result in more accurate SSS maps, free from spurious structures. A trial SSS analysis is produced in the North Atlantic on a uniform grid with 0.25° resolution and a temporal resolution of one week, encompassing the period from September 2011 through August 2013. A brief statistical description, based on the comparison between SSS maps and concurrent in situ data, is used to demonstrate the utility of the OI analysis and the potential of Aquarius SSS products to document salinity structure at ~150-km length and weekly time scales.

School of Ocean and Earth Science and Technology Contribution Number 9105 and International Pacific Research Center Contribution Number 1052.

Corresponding author address: Oleg Melnichenko, International Pacific Research Center, University of Hawai‘i at Mānoa, POST Bldg., Room 401, 1680 East-West Road, Honolulu, HI 96822. E-mail: oleg@hawaii.edu
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