Numerical tools to estimate the flux of a gas across the air–water interface and assess the heterogeneity of its forcing functions
- 1MARETEC, Instituto Superior Técnico, Universidade Técnica de Lisboa, Av. Rovisco Pais, 1049-001, Lisbon, Portugal
- 2CIMA – Centre for Marine and Environmental Research, ISE, University of Algarve, Campus de Gambelas, 8005–139 Faro, Portugal
- 3Algae–Marine Plant Ecology, CCMar – Centre of Marine Sciences, University of Algarve, Campus de Gambelas, 8005–139 Faro, Portugal
Abstract. A numerical tool was developed for the estimation of gas fluxes across the air–water interface. The primary objective is to use it to estimate CO2 fluxes. Nevertheless application to other gases is easily accomplished by changing the values of the parameters related to the physical properties of the gases. A user-friendly software was developed allowing to build upon a standard kernel a custom-made gas flux model with the preferred parameterizations. These include single or double layer models; several numerical schemes for the effects of wind in the air-side and water-side transfer velocities; the effects of atmospheric stability, surface roughness and turbulence from current drag with the bottom; and the effects on solubility of water temperature, salinity, air temperature and pressure. An analysis was also developed which decomposes the difference between the fluxes in a reference situation and in alternative situations into its several forcing functions. This analysis relies on the Taylor expansion of the gas flux model, requiring the numerical estimation of partial derivatives by a multivariate version of the collocation polynomial. Both the flux model and the difference decomposition analysis were tested with data taken from surveys done in the lagoon system of Ria Formosa, south Portugal, in which the CO2 fluxes were estimated using the infrared gas analyzer (IRGA) and floating chamber method, whereas the CO2 concentrations were estimated using the IRGA and degasification chamber. Observations and estimations show a remarkable fit.