Estimating the sea-level highstand during the last interglacial: a probabilistic massive ensemble approach

Essential to understanding sea-level change and its causes during the last interglacial is the quantification of uncertainties. In order to estimate the uncertainties, we develop a statistical framework for the comparison of paleao-climatic sea-level index points and GIA model predictions. For the investigation of uncertainties, as well as to generate better model predictions, we implement a massive ensemble approach by applying a data assimilation scheme based on particle filter methods. The different runs are distinguished through varying ice sheet reconstructions based on oxygen-isotope curves and different parameter selections within the GIA model. This framework has several advantages over earlier work, such as the ability to examine either the contribution of individual observations to the results or the probability of specific input parameters. This exploration of input parameters and data leads to a larger range of estimates than previously published work. We illustrate how the assumptions that enter into the statistical analysis, such as the existence of outliers in the observational database or the initial ice volume history, can introduce large variations to the estimate of the maximum highstand. Thus, caution is required to avoid over-interpreting results. We conclude that there are reasonable doubts whether the datasets previously used in statistical analyses are able to tightly constrain the value of maximum highstand during the last interglacial (LIG)

Skilful prediction of cod stocks in the North and Barents Sea a decade in advance

Reliable information about the future state of the ocean and fish stocks is necessary for informed decision-making by fisheries scientists, managers and the industry. However, decadal regional ocean climate and fish stock predictions have until now had low forecast skill. Here, we provide skilful forecasts of the biomass of cod stocks in the North and Barents Seas a decade in advance. We develop a unified dynamical-statistical prediction system wherein statistical models link future stock biomass to dynamical predictions of sea surface temperature, while also considering different fishing mortalities. Our retrospective forecasts provide estimates of past performance of our models and they suggest differences in the source of prediction skill between the two cod stocks. We forecast the continuation of unfavorable oceanic conditions for the North Sea cod in the coming decade, which would inhibit its recovery at present fishing levels, and a decrease in Northeast Arctic cod stock compared to the recent high levels. North Sea cod stock may not recover in the decade 2020-2030 while Northeast Arctic cod biomass is also predicted to decline but will be better able to recover, according to an integration of statistical fisheries models and climate predictionspublishedVersio

Palaeo-sea-level and palaeo-ice-sheet databases: Problems, strategies, and perspectives

Sea-level and ice-sheet databases have driven numerous advances in understanding the Earth system. We describe the challenges and offer best strategies that can be adopted to build self-consistent and standardised databases of geological and geochemical information used to archive palaeo-sea-levels and palaeo-ice-sheets. There are three phases in the development of a database: (i) measurement, (ii) interpretation, and (iii) database creation. Measurement should include the objective description of the position and age of a sample, description of associated geological features, and quantification of uncertainties. Interpretation of the sample may have a subjective component, but it should always include uncertainties and alternative or contrasting interpretations, with any exclusion of existing interpretations requiring a full justification. During the creation of a database, an approach based on accessibility, transparency, trust, availability, continuity, completeness, and communication of content (ATTAC3) must be adopted. It is essential to consider the community that creates and benefits from a database. We conclude that funding agencies should not only consider the creation of original data in specific research-question-oriented projects, but also include the possibility of using part of the funding for IT-related and database creation tasks, which are essential to guarantee accessibility and maintenance of the collected data

Skilful prediction of cod stocks in the North and Barents Sea a decade in advance

Reliable information about the future state of the ocean and fish stocks is necessary for informed decision-making by fisheries scientists, managers and the industry. However, decadal regional ocean climate and fish stock predictions have until now had low forecast skill. Here, we provide skilful forecasts of the biomass of cod stocks in the North and Barents Seas a decade in advance. We develop a unified dynamical-statistical prediction system wherein statistical models link future stock biomass to dynamical predictions of sea surface temperature, while also considering different fishing mortalities. Our retrospective forecasts provide estimates of past performance of our models and they suggest differences in the source of prediction skill between the two cod stocks. We forecast the continuation of unfavorable oceanic conditions for the North Sea cod in the coming decade, which would inhibit its recovery at present fishing levels, and a decrease in Northeast Arctic cod stock compared to the recent high levels. North Sea cod stock may not recover in the decade 2020-2030 while Northeast Arctic cod biomass is also predicted to decline but will be better able to recover, according to an integration of statistical fisheries models and climate prediction