Evaluation of sea-surface salinity observed by Aquarius

Abstract

Sea-surface salinity (SSS) observed by Aquarius was compared with global observations from Argo floats and offshore moored buoys to evaluate the quality of satellite SSS data and to assess error structures. Aquarius products retrieved by different algorithms (Aquarius Official Release version 3.0 [V3.0], Combined Active-Passive [CAP] algorithm version 3.0, and Remote Sensing Systems test bed algorithm version 3) were compared. The Aquarius SSS was in good agreement with in situ salinity measurements for all three products. Root-mean-square (rms) differences of the salinity residual, with respect to Argo salinity, ranged from 0.41 to 0.52 psu. These three Aquarius products exhibit high SSS deviation from Argo salinity under lower sea-surface temperature conditions (<10 C) due to lower sensitivity of microwave emissivity to SSS. The CAP product deviates under strong wind conditions (>10 m s 21 ), probably due to model bias and uncertainty associated with sea-surface roughness. Furthermore, significant SSS differences between ascending (south-to-north) and descending (north-to-south) paths were detected. The monthly averaged Aquarius SSS (1 3 1 grid) was also compared with outputs from the ocean data optimal interpolation (OI) system operated by the Japan Agency for Marine-Earth Science Technology (JAMSTEC) and the ocean data assimilation system used by the Meteorological Research Institute, Japan Meteorological Agency (MRI/JMA). Negative bias, attributed to near-surface salinity stratification by precipitation, was detected in tropical regions. For 40 S-40 N, rms difference, with respect to JAMSTEC OI, is 0.27 psu for the V3.0, while the CAP product rms difference is only 0.22 psu, which is close to the Aquarius mission goal.

Subfootprint Variability of Sea Surface Salinity Observed during the SPURS-1 and SPURS-2 Field Campaigns

“…To mimic the validation process for the Aquarius and SMAP satellites (e.g. [5][6][7]), for each 7-day block, I picked out a random in situ measurement, and compared it to the weighted mean computed from all the available measurements. The result, Figure 6, shows points clustered around the one-to-one line with an RMS difference of 0.068.…”

“…[4]) which are commonly used for this purpose are derived from measurements at an average scale of 1 measurement per 3 • ×3 • square per 10 days. For the most part, validation of satellite SSS has been done comparing values to individual in situ measurements such as Argo floats [5][6][7]. Floats come to the surface in relatively random locations, and, if close enough in space and time, can be matched up with satellite samples [8].…”

“…The satellite estimate of an SSS snapshot at point E is equivalent to averaging the SSS over a region, the central part of which we will call the 'footprint'. in situ measurements such as Argo floats [5][6][7]. Floats come to the surface in relatively random locations, and, if close enough in space and time, can be matched up with satellite samples [8].…”

Mechanisms of Long‐Term Variability and Recent Trend of Salinity Along 137°E

“…For example, using sea surface height (SSH) observations by satellite altimetry since 1992, many previous studies (e.g., Fu et al, 2010;Kobashi & Kawamura, 2002;Qiu & Chen, 2010) have revealed eddyrich oceans over the world and their spatial and temporal variability, and it has become possible in recent years to investigate long-term sea surface height variability (e.g., Han et al, 2014;Lee, 2004;Lee & McPhaden, 2008). In the 2010s, satellite observations of sea surface salinity (SSS) have enabled the global mapping of SSS (e.g., Abe & Ebuchi, 2014;Le Vine et al, 2007). In addition to such surface monitoring by satellites, the subsurface ocean has also been monitored in real time by the Argo network consisting of more than 3,000 profiling floats over the global ocean (e.g., Riser et al, 2016;Roemmich et al, 2001).…”

Responses to Reviewer #1

“…In contrast, in the SCM of the western basin associated with low values of NO − 3 norm , the Chl a : b bp ratio showed values < 300 mg m −2 . This ratio is a proxy of the Chl a : POC ratio (Behrenfeld et al, 2015;Álvarez et al, 2016;Westberry et al, 2016) and constitutes an optical index of photoacclimation Siegel et al, 2005) or of the phytoplankton communities (Cetinić et al, 2012(Cetinić et al, , 2015. Hence, in both the western and eastern basins, the high values of the Chl a : b bp ratio occurring in the SCM, associated with very low-light conditions, could be attributed to either photoacclimation of phytoplankton cells to low-light intensity.…”