Fine, R. A., D. A. Willey, and F. J. Millero (2017), Global variability and changes in ocean total alkalinity from Aquarius satellite data, Geophys. Res. Lett., 44, 261–267, doi:10.1002/2016GL071712.
Monitoring changes in the global carbon system, the biogeochemical cycle that dictates how carbon moves around our planet, is an extremely important task. Measuring the oceanographic portion of this cycle is particularly important because the ocean is the largest carbon sink on Earth. Making these measurements, however, is no simple task.
Scientists have historically sampled the ocean’s chemistry by collecting water on exhaustive field campaigns. More recently, autonomous technologies such as gliders and floats have come on-line, providing greater coverage. Now, oceanographers and climatologists have one more tool to add to their quiver: satellites.
Dr. Rana Fine and her group at the University of Miami used data from two satellites to estimate the total alkalinity (TA) of the surface ocean. TA is a metric that describes how well seawater can neutralize acids and is used as a proxy for changes in the ocean’s chemistry. TA measurements can then be used to assess how the ocean’s pH is changing or how much carbon dioxide it can take up. Fine exploited the fact that TA varies linearly with salinity and temperature to explore its spatial and temporal variability on a global scale.
Fine’s team took sea surface salinity (SSS) and temperature (SST) data from NASA’s Aquarius and several NOAA satellites respectively. The Aquarius instrument measures SSS by detecting microwave emissions, a property that varies with salinity, from the surface of the ocean (Fig 1). The SST information comes from the Advanced Very-High-Resolution Radiometers (AVHRRs) that derive temperature from the light reflected off the surface of the ocean. Both systems can capture a complete picture of the Earth’s oceans about twice a day.
For her analysis, Fine used monthly averaged SSS and SST measurements from all of 2014. TA was computed with an equation previously developed by other researchers analyzing thousands of water samples from every ocean basin. This empirical, or experimentally derived, relationship allowed Fine’s group to combine the SSS and SST data with geographic information to estimate the TA over all of Earth’s oceans.
The researchers examined how TA varied in space and time using the satellite measurements. They demonstrated that the annual spatial variability, or how TA changes as a function of location, was highly correlated with the SSS. Figure 2 illustrates this relationship by plotting the estimated TA on top and the SSS on the bottom. Notice how the TA and SSS patterns match up almost perfectly.
To identify long-term temporal trends in TA, Fine compared the 2014 satellite data with information from the World Ocean Database (WOD). WOD is collection of datasets curated by NOAA that includes measurements from many sources. Fine used WOD TA data averaged from between 1975 and 1984 for her study. The group computed the difference between the average TA in 2014 and the WOD data to highlight areas where significant changes have occurred.
The map in Figure 3 shows these differences. Fine highlights eight regions of the ocean where the changes are greater than the error of the TA estimates; meaning the amount the TA has changed cannot be explained only by biases in the measurements. The areas A1-A3, P1, and P2 are subtropical regions that have seen substantial increases in TA. Conversely, the TA in the I1 and P4 regions has decreased.
Fine notes that all these differences between modern and historic measurements are consistent with climate-related changes in ocean SSS. Specifically, that TA has increased in subtropical regions where higher temperatures have lead to increased evaporation. Likewise, TA decreased at higher latitudes due to freshwater run off from melting sea-ice. Furthermore, Fine suggests that the increasing TA in subtropical regions could be reinforcing ocean acidification trends.
Fine and her group have taken an important first step toward establishing a global TA baseline. Such a quantity could be used to evaluate future data and to identify past trends. Doing so on a global scale, however, relies on continued support of organizations like NOAA and NASA. Without the valuable data they provide, we would know precious little about how our Earth works.
Eric is a PhD student at the Scripps Institution of Oceanography. His research in the Jaffe Laboratory for Underwater Imaging focuses on developing methods to quantitatively label image data coming from the Scripps Plankton Camera System. When not science-ing, Eric can be found surfing, canoeing, or trying to learn how to cook.
I am skeptical, did they take the TA measurements from the WOD? Or did they calculate TA from the WOD with the same methods they used for the satellite data? If the two are the same, great! If not, then their comparisons are probably not very accurate.
Hi Brendan, thanks for your comment and close reading!
The researchers did compute the TA in the same way for both types of data. They applied the empirical equation with historic SSS and SST values from the WOD. They also did some detailed error analysis noting the differences between the WOD and satellite measurements of both parameters.