scholarly journals Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast

2019 ◽  
Vol 11 (17) ◽  
pp. 1964 ◽  
Author(s):  
Jorge Vazquez-Cuervo ◽  
Jose Gomez-Valdes ◽  
Marouan Bouali ◽  
Luis Miranda ◽  
Tom Van der Stocken ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Current System ◽  
California Current ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
California Current System ◽  
The Impact ◽  
Buoy Measurements

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products by comparing with buoy measurements, do not allow for evaluating the impact of mesoscale-to-submesoscale variability. We present the validation of remotely sensed SST and SSS data against the unmanned surface vehicle (USV)—called Saildrone—measurements from the 60 day 2018 Baja California campaign. More specifically, biases and root mean square differences (RMSDs) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero, while MUR showed a bias of 0.3 °C. The OSTIA showed the smallest RMSD of 0.39 °C, while DMI had the largest RMSD of 0.5 °C. An RMSD of 0.4 °C between Saildrone SST and the satellite-derived products could be explained by the diurnal and sub-daily variability in USV SST, which currently cannot be resolved by remote sensing measurements. SSS showed fresh biases of 0.1 PSU for JPLSMAP and 0.2 PSU and 0.3 PSU for RMSS40 and RSS70 respectively. SST and SSS showed peaks in coherence at 100 km, most likely associated with the variability of the California Current System.

scholarly journals Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast

2019 ◽  
Author(s):  
Jorge Vazquez-Cuervo ◽  
Jose Gomez-Valdes ◽  
Marouan Bouali ◽  
Luis Miranda ◽  
Tom Van der Stocken ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Current System ◽  
Local Maximum ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
California Current System ◽  
Daily Variability ◽  
The Impact

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products, using comparisons with buoy measurements, do not allow for evaluating the impact of mesoscale to submesoscale variability. Here we present the validation of remotely-sensed SST and SSS data against the unmanned surface vehicle (USV) – Saildrone – measurements from the Spring 2018 Baja deployment. More specifically, biases and root mean square differences (RMSD) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero while MUR showed a bias of 0.2C. OSTIA showed the smallest RMSD of 0.36C while DMI had the largest RMSD of 0.5C. An RMSD of 0.4C between Saildrone SST and the satellite-derived products could be explained by the daily variability in USV SST which currently cannot be resolved by remote sensing measurements. For SSS, values from the JPLSMAP product showed saltier biases of 0.2 PSU, while RSS40 and RSS70 showed fresh biases of 0.3 PSU. An RMSD of 0.4 PSU could not be explained solely by the daily variability of the USV-derived SSS. Coherences were significant at the longer wavelengths, with a local maximum at 100 km that is most likely associated with the mesoscale turbulence in the California Current System.

scholarly journals Can we use sea surface temperature and productivity proxy records to reconstruct Ekman upwelling?

2019 ◽  
Vol 15 (6) ◽  
pp. 1985-1998
Author(s):  
Anson Cheung ◽  
Baylor Fox-Kemper ◽  
Timothy Herbert
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Current System ◽  
California Current ◽  
Sea Surface ◽  
California Current System ◽  
Proxy Records ◽  
Multiple Variables ◽  
Ekman Upwelling

Abstract. Marine sediments have greatly improved our understanding of the climate system, but their interpretation often assumes that certain climate mechanisms operate consistently over all timescales of interest and that variability at one or a few sample sites is representative of an oceanographic province. In this study, we test these assumptions using modern observations in an idealized manner mimicking paleo-reconstruction to investigate whether sea surface temperature and productivity proxy records in the Southern California Current System can be used to reconstruct Ekman upwelling. The method uses extended empirical orthogonal function (EEOF) analysis of the covariation of alongshore wind stress, chlorophyll, and sea surface temperature as measured by satellites from 2002 to 2009. We find that EEOF1 does not reflect an Ekman upwelling pattern but instead much broader California Current processes. EEOF2 and 3 reflect upwelling patterns, but these patterns are timescale dependent and regional. Thus, the skill of using one site to reconstruct the large-scale dominant patterns is spatially dependent. Lastly, we show that using multiple sites and/or multiple variables generally improves field reconstruction. These results together suggest that caution is needed when attempting to extrapolate mechanisms that may be important on seasonal timescales (e.g., Ekman upwelling) to deeper time but also the advantage of having multiple proxy records.

scholarly journals Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of Retrieval Parameters

2019 ◽  
Vol 11 (7) ◽  
pp. 750 ◽  
Author(s):  
Emmanuel Dinnat ◽  
David Le Vine ◽  
Jacqueline Boutin ◽  
Thomas Meissner ◽  
Gary Lagerloef
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
In Situ Observations ◽  
The Impact

Since 2009, three low frequency microwave sensors have been launched into space with the capability of global monitoring of sea surface salinity (SSS). The European Space Agency’s (ESA’s) Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), onboard the Soil Moisture and Ocean Salinity mission (SMOS), and National Aeronautics and Space Administration’s (NASA’s) Aquarius and Soil Moisture Active Passive mission (SMAP) use L-band radiometry to measure SSS. There are notable differences in the instrumental approaches, as well as in the retrieval algorithms. We compare the salinity retrieved from these three spaceborne sensors to in situ observations from the Argo network of drifting floats, and we analyze some possible causes for the differences. We present comparisons of the long-term global spatial distribution, the temporal variability for a set of regions of interest and statistical distributions. We analyze some of the possible causes for the differences between the various satellite SSS products by reprocessing the retrievals from Aquarius brightness temperatures changing the model for the sea water dielectric constant and the ancillary product for the sea surface temperature. We quantify the impact of these changes on the differences in SSS between Aquarius and SMOS. We also identify the impact of the corrections for atmospheric effects recently modified in the Aquarius SSS retrievals. All three satellites exhibit SSS errors with a strong dependence on sea surface temperature, but this dependence varies significantly with the sensor. We show that these differences are first and foremost due to the dielectric constant model, then to atmospheric corrections and to a lesser extent to the ancillary product of the sea surface temperature.

scholarly journals Can we use sea surface temperature and productivity proxy records to reconstruct Ekman Upwelling?

2019 ◽  
Author(s):  
Anson Cheung ◽  
Baylor Fox-Kemper ◽  
Timothy Herbert
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Current System ◽  
California Current ◽  
Sea Surface ◽  
California Current System ◽  
Proxy Records ◽  
Multiple Variables ◽  
Ekman Upwelling

Abstract. Marine sediments have greatly improved our understanding of the climate system, but their interpretation often assumes that certain climate mechanisms operate consistently over all timescales of interest and that variability at one or few sample sites is representative of an oceanographic province. In this study, we test these assumptions using modern observations in an idealized manner mimicking paleo-reconstruction to investigate whether sea surface temperature and productivity proxy records in the Southern California Current System can be used to reconstruct Ekman upwelling. The method uses Extended Empirical Orthogonal Function (EEOF) analysis of covariation of alongshore windstress, chlorophyll and sea surface temperature as measured by satellites from 2002 to 2009. We find that EEOF1 does not reflect an Ekman upwelling pattern, but instead much broader California Current processes. EEOF2 and 3 reflect upwelling patterns, but these patterns are timescale dependent and are regional. Thus, the skill of using one site to reconstruct the large scale dominant patterns is spatially dependent. Lastly, we show that using multiple sites and/or multiple variables generally improve field reconstruction. These results together suggest caution is needed when attempting to extrapolate mechanisms that may be important on seasonal time scales (e.g. Ekman upwelling) to deeper time, but also the advantage of having multiple proxy records.

scholarly journals Sea Surface Temperature and Wind Stress Curl Variability near a Cape

2012 ◽  
Vol 42 (11) ◽  
pp. 2073-2087 ◽  
Author(s):  
Renato M. Castelao
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Current System ◽  
Empirical Orthogonal Functions ◽  
Sea Surface ◽  
Western Boundary ◽  
Surface Cooling ◽  
Wind Stress Curl ◽  
California Current System

Abstract The coupling between sea surface temperature (SST), SST gradients, and wind stress curl variability near a cape off Brazil is investigated using satellite observations and several different SST high-resolution analyses. The cape is characterized by strong SST fronts year-round, associated with upwelling and advection of warm water offshore in a western boundary current. Observations reveal a strong coupling between crosswind SST gradients and wind stress curl variability, with the predominantly negative crosswind gradients leading to negative, upwelling favorable wind stress curl anomalies. The spatial correlation between empirical orthogonal functions (EOF) of those variables is ~0.6, while the correlation between the EOF amplitude time series of the wind stress curl and crosswind SST gradients is larger than 0.7. The coupling occurs during summer and winter and is strongly modulated by variations in the wind stress directional steadiness. The intensity of the coupling is weaker than around capes on the California Current system, presumably because of higher variability in wind direction off Brazil. During periods of high wind stress directional steadiness off Cape Frio, the coupling is intensified by up to 40%–75%. Wind stress curl is also correlated with SST itself, especially in the vicinity of the cape, although not as strongly as with crosswind SST gradients. The analyses suggest that the observed wind stress curl anomalies can lead to surface cooling of as much as 1°C. If the enhanced upwelling leads to further strengthening of the upwelling front, negative wind stress curl anomalies may be intensified in a positive feedback mechanism.

Meridional Distribution of Surface CO2 along 67°E of the Indian Ocean

2020 ◽  
Author(s):  
Dong-Jin Kang ◽  
Sang-Hwa Choi ◽  
Daeyeon Kim ◽  
Gyeong-Mok Lee
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Seawater ◽  
Surface Salinity ◽  
The North ◽  
The Indian Ocean ◽  
North And South

<p>Surface seawater carbon dioxide was observed from 3 °S to 27 °S along 67 °E of the Indian Ocean in April 2018 and 2019. Partial pressure of CO<sub>2</sub>(pCO<sub>2</sub>) in the surface seawater and the atmosphere were observed every two minutes using an underway CO2 measurement system (General Oceanics Model 8050) installed on R/V Isabu. Surface water temperature and salinity were measured as well. The pCO<sub>2</sub> was measured using Li-7000 NDIR. Standard gases were measured every 8 hours in five classes with concentrations of 0 µatm, 202 µatm, 350 µatm, 447 µatm, and 359.87 µatm. The fCO<sub>2</sub> of atmosphere remained nearly constant at 387 ± 2 µatm, but the surface seawater fCO<sub>2</sub> peaked at about 3 °S and tended to decrease toward the north and south. The distribution of fCO<sub>2</sub> in surface seawater according to latitude tends to be very similar to that of sea surface temperature. In order to investigate the factors that control the distribution of fCO<sub>2</sub> in surface seawater, we analyzed the sea surface temperature, sea surface salinity, and other factors. The effects of salinity are insignificant, and the surface fCO<sub>2</sub> distribution is mainly controlled by sea surface temperature and other factors that can be represented mainly by biological activity and mixing.</p>

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