Uncertainties in projecting climate-change impacts in marine ecosystems

Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability uncertainty, (iii) parametric uncertainty, and (iv) scenario uncertainty. For each uncertainty type, we then examine the current state-of-the-art in assessing and quantifying its relative importance. We consider whether the marine scientific community has addressed these types of uncertainty sufficiently and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization uncertainty is rarely treated explicitly and reducing this type of uncertainty may deliver gains on the seasonal-to-decadal time-scale. We conclude that all parts of marine science could benefit from a greater exchange of ideas, particularly concerning such a universal problem such as the treatment of uncertainty. Finally, marine science should strive to reach the point where scenario uncertainty is the dominant uncertainty in our projections.

Sedimentary archives of climate and sea-level changes during the Holocene in the Rhone prodelta (NW Mediterranean Sea)

A 7.38 m-long sediment core was collected from the eastern part of the Rhone prodelta (NW Mediterranean) at 67 m water depth. A multi-proxy study (sedimentary facies, benthic foraminifera and ostracods, clay mineralogy, and major elements from XRF) provides a multi-decadal to century-scale record of climate and sea-level changes during the Holocene. The early Holocene is marked by alternative silt and clay layers interpreted as distal tempestites deposited in a context of rising sea level. This interval contains shallow infra-littoral benthic meiofauna (e.g. Pontocythere elongata, Elphidium spp., Quinqueloculina lata) and formed between ca. 20 and 50 m water depth. The middle Holocene (ca. 8.3 to 4.5 ka cal. BP), is characterized, at the core site, by a period of sediment starvation (accumulation rate of ca. 0.01 cm yr−1) resulting from the maximum landward shift of the shoreline and the Rhone outlet(s). From a sequence stratigraphic point of view, this condensed interval, about 35 cm-thick, is a Maximum Flooding Surface that can be identified on seismic profiles as the transition between delta retrogradation and delta progradation. It is marked by very distinct changes in all proxy records. Following the stabilization of the global sea level, the late Holocene is marked by the establishment of prodeltaic conditions at the core site, as shown by the lithofacies and by the presence of benthic meiofauna typical of the modern Rhone prodelta (e.g. Valvulineria bradyana, Cassidulina carinata, Bulimina marginata). Several periods of increased fluvial discharge are also emphasized by the presence of species commonly found in brackish and shallow water environments (e.g. Leptocythere). Some of these periods correspond to the multi-decadal to centennial late Holocene humid periods recognized in Europe (i.e. the 2.8 ka event and the Little Ice Age). Two other periods of increased runoffs at ca. 1.3 and 1.1 ka cal. BP are recognized, and are likely to reflect periods of regional climate deterioration that are observed in the Rhone watershed.

Wave climate in the Arctic 1992-2014: seasonality and trends

Over the past decade, the diminishing Arctic sea ice has impacted the wave field, which depends on the ice-free ocean and wind. This study characterizes the wave climate in the Arctic spanning 1992–2014 from a merged altimeter data set and a wave hindcast that uses CFSR winds and ice concentrations from satellites as input. The model performs well, verified by the altimeters, and is relatively consistent for climate studies. The wave seasonality and extremes are linked to the ice coverage, wind strength, and wind direction, creating distinct features in the wind seas and swells. The altimeters and model show that the reduction of sea ice coverage causes increasing wave heights instead of the wind. However, trends are convoluted by interannual climate oscillations like the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation. In the Nordic Greenland Sea the NAO influences the decreasing wind speeds and wave heights. Swells are becoming more prevalent and wind-sea steepness is declining. The satellite data show the sea ice minimum occurs later in fall when the wind speeds increase. This creates more favorable conditions for wave development. Therefore we expect the ice freeze-up in fall to be the most critical season in the Arctic and small changes in ice cover, wind speeds, and wave heights can have large impacts to the evolution of the sea ice throughout the year. It is inconclusive how important wave–ice processes are within the climate system, but selected events suggest the importance of waves within the marginal ice zone.

Developing European operational oceanography for Blue Growth, climate change adaptation and mitigation, and ecosystem-based management

Operational approaches have been more and more widely developed and used for providing marine data and information services for different socio-economic sectors of the Blue Growth and to advance knowledge about the marine environment. The objective of operational oceanographic research is to develop and improve the efficiency, timeliness, robustness and product quality of this approach. This white paper aims to address key scientific challenges and research priorities for the development of operational oceanography in Europe for the next 5-10 years. Knowledge gaps and deficiencies are identified in relation to common scientific challenges in four EuroGOOS knowledge areas: European Ocean Observations, Modelling and Forecasting Technology, Coastal Operational Oceanography and Operational Ecology. The areas "European Ocean Observations" and "Modelling and Forecasting Technology" focus on the further advancement of the basic instruments and capacities for European operational oceanography, while "Coastal Operational Oceanography" and "Operational Ecology" aim at developing new operational approaches for the corresponding knowledge areas.