Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK

Impact and detectability of hypothetical CCS offshore seep scenarios as an aid to storage assurance and risk assessment

Carbon Capture and Storage has the potential to make a significant contribution to the mitigation of climate change, however there is a regulatory and societal obligation to demonstrate storage robustness and minimal local environmental impact. This requires an understanding of environmental impact potential and detectability of a range of hypothetical leak scenarios. In the absence of a significant body of real-world release experiments this study collates the results of 86 modelled scenarios of offshore marine releases derived from five different model systems. This synthesis demonstrates a consistent generalised relationship between leak rate, detectability and impact potential of a wide range of hypothetical releases from CO2 storage, which can be described by a power law. For example a leak of the order of 1 T per day should be detectable at, at least, 60 m distance with an environmental impact restricted to less than a 15 m radius of the release point. Small releases are likely to require bottom mounted (lander) monitoring to ensure detection. In summary this work, when coupled with a quantification of leakage risk can deliver a first order environmental impact assessment as an aid to the consenting process. Further this work demonstrates that non-catastrophic release events can be detected at thresholds well below levels which would undermine storage performance or significantly impact the environment, given an appropriate monitoring strategy

Optimising environmental monitoring for carbon dioxide sequestered offshore

Carbon Capture and Storage (CCS) provides a mechanism by which CO2 can be removed from the atmosphere and stored in reservoirs. Regulations and stakeholder assurance require monitoring to show storage is robust. The marine environment is heterogeneous and dynamic, and baselines are extremely variable. Hence, distinguishing anomalous CO2 from natural variability is challenging. Monitoring schemes must be designed to identify releases early and with certainty, whilst being cost effective. A key question is how to deploy the smallest number of sensors to ensure effective monitoring? We approached this problem through a 3D hydrodynamic model (FVCOM) coupled to a carbonate system. The unstructured grid resolution ranges from 0.5 km to 3 m and simulates seabed release scenarios ranging from 3 t d−1 to 300 t d−1 using the Goldeneye complex as an exemplar test bed. This configuration allows us to characterise and analyse the fate of CO2 in the water column, with the spatial and temporal CO2 patterns shown to be affected by both tides and seasonal mixing/stratification. A weighted greedy set algorithm is used to identify the positions within the model domain which yield the greatest combined coverage for the smallest number of sampling stations, further limited by selecting only a feasible number of sample sites. The weighted greedy set algorithm incorporates the effect of the variable grid spacing as well as the proximity of the sample locations to the Goldeneye complex. The weighted greedy set can identify releases sooner, with a stronger signal than a regular sampling approach

Uncertainties in steric sea level change estimation during the satellite altimeter era: concepts and practices

This article presents a review of current practice in estimating steric sea level change, focussed on the treatment of uncertainty. Steric sea level change is the contribution to the change in sea level arising from the dependence of density on temperature and salinity. It is a significant component of sea level rise and a reflection of changing ocean heat content. However tracking these steric changes remains still a significant challenge for the scientific community. We review the importance of understanding the uncertainty in estimates of steric sea level change. Relevant concepts of uncertainty are discussed and illustrated with the example of observational uncertainty propagation from a single profile of temperature and salinity measurements to steric height. We summarise and discuss the recent literature on methodologies and techniques used to estimate steric sea level in the context of the treatment of uncertainty. Our conclusions are that progress in quantifying steric sea level uncertainty will benefit from: greater clarity and transparency in published discussions of uncertainty, including exploitation of international standards for quantifying and expressing uncertainty in measurement; and the development of community ‘recipes’ for quantifying the error covariances in observations and from sparse sampling, and for estimating and propagating uncertainty across spatio-temporal scales