Precise quantification of seasonal air-sea exchanges of O2 at the hemispheric scale using data from the ATom, ORCAS, and HIPPO airborne campaigns.
Precise quantification of seasonal air-sea exchanges of O2 at the hemispheric scale using data from the ATom, ORCAS, and HIPPO airborne campaigns.
Abstract:
Atmospheric potential oxygen (APO) is a tracer for the exchange of O2 between the ocean and atmosphere. APO is effectively the concentration of O2 + CO2 which is insensitive to gas exchange between the land and the atmosphere. APO undergoes a regular seasonal cycle in each hemisphere, reflecting the seasonal production and consumption of O2 by the ocean at the hemispheric scale as a result of seasonal marine productivity and ventilation and ocean heating and cooling. Here we provide improved estimates of the hemispheric seasonal ingassing and outgassing of O2 using data from 10 global airborne campaigns: the five HIAPER Pole-to-Pole Observations (HIPPO) campaigns (2009-2011), the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study (2016), and the four Atmospheric Tomography Mission (ATom) campaigns (2016-2018). These flights provide near-global coverage of the troposphere throughout the year and thus allow for high-accuracy quantification of large-scale seasonal air-sea O2 exchanges. We also present a new method to constrain the spatial and temporal bias in the APO inventory due to global atmospheric circulation. In this method, the APO inventory is integrated over each potential temperature surface. We show that by tracking potential temperature surfaces, this method is able to account for mixing by synoptic-scale meridional transport and therefore reduce spatial and temporal biases in atmospheric CO2 and O2 sampling. By using the new method, we quantify seasonal extratropical net productivity in each hemisphere, which provide valuable model constraints. Our preliminary analyses have also shown the surprising results that the amplitude is similar in the northern hemisphere and southern hemisphere, which disagrees with models.