Journal article
Comparison of Distributional Statistics of Aquarius and Argo Sea Surface Salinity Measurements
Journal of atmospheric and oceanic technology, Vol.33(1), pp.103-118
01/01/2016
DOI: 10.1175/JTECH-D-15-0068.1
Abstract
Abstract Salinity is an indicator of the interaction between ocean circulation and the global water cycle, which in turn affects the regulation of the earth’s climate. To thoroughly understand sea surface salinity’s connection to processes that define the hydrological cycle, such as surface forcing and ocean mixing, there is need for proper validation of remotely sensed salinity products with independent measurements, beyond central tendencies, across the entire distribution of salinity. Because of its fine spatial and temporal coverage, Aquarius presents an ideal measurement system for fully characterizing the distribution and properties of sea surface salinity. Using the first 33 months of Aquarius, version 3.0, level 2 sea surface salinity data, both central tendencies and distributional quantile characteristics across time and space are investigated, and a statistical validation of Aquarius measurements with Argo in situ observations is conducted. Several aspects are considered, including regional characteristics and temporal agreement, as well as seasonal differences by ocean basin and hemisphere. Regional studies examine the time and space scales of variability through time series comparisons and an analysis of quantile properties. Results indicate that there are significant differences between the tails of their respective distributions, especially the lower tail. The Aquarius data show longer, fatter lower tails, indicating higher probability to sample low-salinity events. There is also evidence of differences in measurement variation between Aquarius and Argo. These results are seen across seasons, ocean basins, hemispheres, and regions.
Details
- Title: Subtitle
- Comparison of Distributional Statistics of Aquarius and Argo Sea Surface Salinity Measurements
- Creators
- Elizabeth Mannshardt - Department of Statistics, North Carolina State University, Raleigh, North CarolinaKatarina Sucic - Department of Statistics, North Carolina State University, Raleigh, North CarolinaMontserrat Fuentes - Department of Statistics, North Carolina State University, Raleigh, North CarolinaFrederick M Bingham - Center for Marine Science, University of North Carolina at Wilmington, Wilmington, North Carolina
- Resource Type
- Journal article
- Publication Details
- Journal of atmospheric and oceanic technology, Vol.33(1), pp.103-118
- DOI
- 10.1175/JTECH-D-15-0068.1
- ISSN
- 0739-0572
- eISSN
- 1520-0426
- Language
- English
- Date published
- 01/01/2016
- Academic Unit
- Biostatistics; Statistics and Actuarial Science; President
- Record Identifier
- 9984065887402771
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