Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System

The Benguela Upwelling System (BUS) on the west coast of southern Africa is one of the global ocean’s most productive upwelling systems supporting a large fishing industry, a fledgling aquaculture sector and offshore mining interests. Despite intensive monitoring and modelling studies, there is no regionally tailored ocean forecasting system that is explicitly developed to deal with the unique ocean dynamics of the Benguela. In this study, the Hybrid Coordinate Ocean Model (HYCOM) is used in conjunction with the Ensemble Optimal Interpolation (EnOI) assimilation scheme to study the impact of assimilating sea surface temperature (SST) and along-track sea level anomalies (SLA) observations on predicted upwelling dynamics in the Benguela. In order to evaluate the predictive skill and impact of data assimilation, three experiments with HYCOMEnOI are evaluated: (1) with no assimilation (HYCOMFREE), (2) only assimilating along-track SLA (HYCOMSLA) and (3) assimilating both SLA and SST (HYCOMSLA+SST). Using MODIS Terra SST as reference, the model SST outputs are evaluated. HYCOMFREE is found to exhibit a warm bias along the coast, HYCOMSLA shows an even greater warm bias while HYCOMSLA+SST conversely shows a much improved SST forecast skill. It is hypothesised that the warm biases could be due to errors in boundary conditions and/or the ERA-interim wind product used to force the model. Furthermore, a comparison of the assimilated SST product (the Operational Sea Surface Temperature and Sea Ice Analysis; OSTIA) with MODIS SST reveals biases in OSTIA up to ±1 ◦C, raising questions over its suitability for assimilation in upwelling regions. Studying the effect of assimilation on SSH, SST and surface currents before and after the assimilation suggests that an increase in SSH from assimilated SLA leads to increased warm SST biases in HYCOMSLA. This is due to an incorrect relationship between SSH and SST in the free-running HYCOM, from which the static ensemble is derived for the EnOI. HYCOMSLA+SST exhibits slightly enhanced SSH increments but the associated increase in SST is significantly reduced by the assimilated SST, resulting in a reduction of the bias with very little impact on the current dynamics. This is reflected in the surface velocitiy increments, which are similar to or worse than that of HYCOMSLA. Investigating the potential of HYCOM-EnOI as an operational forecasting system has revealed that the assimilation of SST and along-track SLA vastly improves modelled SST for the BUS upwelling. Errors in the free-running model, which constitutes the static ensemble, need addressing and comparisons between MODIS and OSTIA SSTs suggests that OSTIA may not be ideally suited for assimilation in the case of coastal upwelling, due to limitations in capturing the dynamics correctly

Scaling Observation Error for Optimal Assimilation of CCI SST Data into a Regional HYCOM EnOI System

South Africa currently possesses no operational ocean forecasting system for the purpose of predicting ocean state variables including temperature,salinity and velocity. Substantial initial efforts towards this goal have been made and resulted in a system using a regional Hybrid Coordinate Ocean Model (HYCOM) along with the Ensemble Optimal Interpolation (EnOI)assimilation scheme. Assimilating only sea surface temperature (SST) observations from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) product into the system resulted in a degraded forecast. Aiming to address this, Climate Change Initiative (CCI) SSTs are assimilated into the system in an effort to improve the forecast skill. Observation errors in the assimilated product are used in the EnOI to determine whether more confidence should be placed in the model or observations in producing the analysis, but overconfidence in observations can shock the model and result in failure. To tweak the impact of the assimilation, a scaling factor is applied in the assimilation code. A scaling factor of 25 was found to produce a favourable result with lowest mean root mean square error (RMSE;1.098C) between the model and observations over time. Postulating the error to be overconfident, a floor value is introduced in order to set a minimum value for the observation error thereby reducing confidence in the observations. These experiments fared less favourably with a floor value of 0.5 and a scaling factor of 15 producing the best mean RMSE (1.118C)

Water Mass Characteristics and Distribution Adjacent to Larsen C Ice Shelf, Antarctica

International audienceThe physical oceanographic environment, water mass characteristics, and distribution in the area adjacent to Larsen C Ice Shelf (LCIS) are investigated using hydrographic data collected during the 2019 Weddell Sea Expedition. The results shed light on the ocean conditions adjacent to a thinning LCIS, on a continental shelf that is a source region for Weddell Sea Deep Water (WSDW), a precursor of the globally important Antarctic Bottom Water. Modified Warm Deep Water (MWDW), a water mass of circumpolar origin, is identified on the continental shelf and is observed to mix with Ice Shelf Water (ISW) and High Salinity Shelf Water (HSSW), both source waters of WSDW. A source water type decomposition analysis reveals high levels of mixing in the area, with much spatial variability. Heat content anomalies indicate an introduction of heat, presumed to be associated with MWDW, into the area via Jason Trough. Furthermore, candidate parent sources for ISW are identified in the region, indicating the potential for a flow of continental shelf waters into the ice shelf cavity; however, the impact on LCIS cannot be surmised from the available observations. ISW and HSSW are observed to make dominant contributions to the densest layers within Jason Trough, where waters are likely en route to feed the deep layers of the Antarctic Slope Current. This cross‐shelf flux of water masses links the region of the Weddell Sea adjacent to northern LCIS to global ocean circulation and Bottom Water characteristics via its contribution to ISW and HSSW, and hence WSDW properties

Sea ice conditions within the Antarctic Marginal Ice Zone in summer 2016, onboard the SA Agulhas II

Our knowledge of sea ice variability, which contributes to the detection of the Antarctic climate change trends, stems primarily from remotely sensed information. However, sea ice in the Southern Ocean is characterized by large variability that remains unresolved and limits our confidence on the remotely sensed products. Therefore, the in situ sea ice observations presented (according to the ASPeCt protocol) provide a greater understanding of the Antarctic sea ice environment - on a local scale - and allows us to evaluate remotely sensed products

The Weddell Sea Expedition 2019: Cruise Scientific Report

Cruise Scientific Report associated with the Weddell Sea Expedition, 2019. Edited by J. A. Dowdeswell (Chief Scientist).This research was funded by the Flotilla Foundation and Marine Archaeology Consultants Switzerland