Verification of the mixed layer depth in the OceanMAPS operational forecast model for Austral autumn

Abstract

Abstract. The ocean mixed layer depth is an important parameter describing the exchange of fluxes between the atmosphere and ocean. In ocean modelling a key factor in the accurate representation of the mixed layer is the parameterization of vertical mixing. An ideal opportunity to investigate the impact of different mixing schemes was provided when the Australian Bureau of Meteorology upgraded its operational ocean forecasting model, OceanMAPS to version 3.0. In terms of the mixed layer, the main difference between the old and new model versions was a change of vertical mixing scheme from that of Chen et al. (1994) to the General Ocean Turbulence Model. The model estimates of the mixed layer depth were compared with those derived from Argo observations. Both versions of the model exhibited a deep bias in tropical latitudes and a shallow bias in the Southern Ocean, consistent with previous studies. The bias, however, was greatly reduced in version 3.0, and variance between model runs decreased. Additionally, model skill against climatology also improved significantly. Further analysis discounted changes to model resolution outside of the Australian region having a significant impact on these results, leaving the change in vertical mixing scheme as the main factor in the assessed improvements to mixed layer depth representation.

Including the invisible: Deep depth-integrated chlorophyll estimates from remote sensing may assist in identifying biologically important areas in oligotrophic coastal margins

“…Here, we define the mixed layer depth as the first depth at which either the potential temperature differed by 0.2 °C from the reference potential temperature or the potential density exceeded the reference potential density by 0.03 kg m -3 (de Boyer Montégut et al, 2004;Boettger et al, 2018). Samples taken at 10 m depth were used as reference values (Boettger et al, 2018).…”

Synergies in Operational Oceanography: The Intrinsic Need for Sustained Ocean Observations

“…This has been a very active field of research in the atmospheric verification community, especially for precipitation forecasts, with many new spatial methods developed (Gilleland et al, 2009). Operational oceanography with external metrics tends to focus more on specific phenomena potentially over all oceans (e.g., focusing on mixed layer assessment; Boettger et al, 2018), but emphasis can also be on the forecast capability of an early warning system, such as river flooding (Taylor et al, 2011), or it can be dedicated to a specific region with the use of spatial-and object-based methods applied to high-resolution ocean forecasts verification to make the most of both sparse in situ ocean observations and remotely sensed observations (such as high frequency radar, satellite sensors). As model resolution increases, verification methods must therefore diversify, with a need for observations of synoptic mesoscale to submesoscale ocean features.…”