| Abstrakt: |
Dimethyl sulfide (DMS) is a naturally emitted trace gas that can affect the Earth's radiative budget by changing cloud albedo. Most models depend on regional or global distributions of seawater DMS concentrations and sea-air flux parameterizations to estimate its emissions. In this study, we analyze the differences between three estimations of seawater DMS, one of which is an observation-based interpolation method (Hulswar et al., 2022 (hereafter referred to as H22)) and two are proxy-based parameterization methods (Galí et al., 2018a (G18); Wang et al., 2020 (W20)). The interpolation-based method depends on the distribution of observations and the methods used to fill data between observations, while the parameterization-based methods rely on establishing a relationship between DMS and environmental parameters such as chlorophyll a, mixed layer depth, nutrients, sea surface temperature, etc., which can then be used to predict DMS concentrations. On average, the interpolation-based methods show higher DMS values compared to the parameterization-based methods. Even though the interpolation method shows higher values than the parameterization-based methods, it fails to capture mesoscale variability. The regression-based parameterization method (G18) shows the lowest values compared to other estimations, especially in the Southern Ocean, which is the high DMS region in Austral summer. The parameterization-based methods suggest significant positive long-term trends in seawater DMS (6.94 ±1.44 % decade-1 for G18 and 3.53 ±0.53 % decade-1 for W20). Since large differences, often more than 100 %, are observed between the different estimations of seawater DMS, the derived sea-air fluxes and hence the impact of DMS on the radiative budget are very sensitive to the estimate used. [ABSTRACT FROM AUTHOR] |
