Regional sea level changes due to global warming will be one of the main problems during the second half of this century. Of particular importance are projections of the changes in the extreme sea level events. The values of these extremes will be determined by the slowly varying global mean sea level (at the moment about 3 mm/year) and the changes in the variability around this mean. The latter contribution is mainly due to changes in ocean circulation and involves what is called the dynamic sea level. One needs a strongly eddying ocean model to capture these sea level extremes, and an ensemble of simulations with such a model to distinguish the global warming forced signal from the one due to internal ocean variability. The aim of the eSALSA project is to provide the changes in statistics of the extreme sea level events by performing a 16-member ensemble simulation with the high-resolution Parallel Ocean Program (POP) model. So far, we have only performed one full simulation over the years 2000-2100 with a specific greenhouse gas forcing. The main result is the change (between the period 2081-2100 and 2001-2020) in the extreme monthly sea level that is expected to occur only once every 10 years (10-year return time). This change is shown in the figure below; for example near the Netherlands such extremes will increase by about 20-30 cm.

We propose to investigate a major problem occurring in the mouth-bar area of the Yangtze Estuary and in the Ems Estuary (Wadden Sea), viz. the increased sediment concentrations and enhanced deposition of this material in waterways after engineering works. Specific objectives are 1. to identify sources, physical-chemical attributes and flocculation characteristics of fine sediment and to assess their influence on estuarine turbidity dynamics; 2. to quantify similarities and differences, regarding along-channel flow and sediment patterns, in a turbidity zone that is characterised by either multiple channels or by a single channel; 3. to investigate the role of time-varying mixing conditions, wind and channel-flat feedbacks on along-channel and across-channel trapping of sediment, evolution of the mouth-bar area and sediment accumulation in the waterways; 4. to propose methods to reduce deposition of sediment in navigation channels. An integrated approach will be adopted of analysing field data, and developing and analysing process-based models. Available data of the Ems Estuary will be used, whilst also new data will be collected in the Yangtze Estuary. Two closely linked subprojects are proposed. The first project (PhD at UU) focuses on modelling along-channel distributions of fine sediment in a tidal network, and comparing results with field data. Both a semi-analytical and numerical model will be used to perform a sensitivity study to changes in depth and mixing conditions resulting from interventions. Results will be unravelled in terms of physical mechanisms. The second project (PhD at ECNU) focuses on the collection and analysis of available and new field data, and investigates the physical-chemical properties of fine sediments in water and bed load samples. The results will be incorporated in a model to examine the effect of floc size and its rapid settling on both across-channel and along-channel patterns of sediment transport and accumulation under varying external conditions.

Channel-shoal patterns on ebb-tidal deltas often migrate, deform and disappear in repetitive cycles of decadal timescales. These dynamic patterns strongly affect the navigability of shipping routes and influence the safety of the nearby barrier islands. Furthermore, human interventions in backbarrier basins have resulted in unforeseen changes in the channel-shoal dynamics on ebb-tidal deltas. In this project we will unravel the physical mechanisms causing the cyclic dynamics of ebb-tidal deltas. Specific research objectives are to 1. quantify the characteristics of cyclic features on ebb-tidal deltas as a function of tide and wave conditions and geometry of the inlet system; 2. explain the formation of these cyclic features on ebb-tidal deltas; 3. assess the interaction between the processes in the backbarrier area and on the ebb-tidal delta. We will accomplish these objectives by applying an innovative combination of techniques. Firstly, we will use historic field data of ebb-tidal deltas worldwide to identity relationships between cyclic channel-shoal patterns and external forcing and geometry of the inlet system. Secondly, we will develop an idealised model, in which ebb-tidal deltas occur as morphodynamic equilibrium solutions. With this tool we will verify our key hypothesis that cyclic patterns on ebb-tidal deltas emerge as inherent instabilities of these equilibrium solutions if waves are obliquely incident to the coast. Finally, we will conduct experiments with a state-of-the-art numerical morphodynamic model to integrate results and to address our last objective. This study will contribute to development of more effective management strategies of tidal inlet systems.

The worldwide shrinking of glaciers and ice sheets represents the largest contribution to current sea level rise. Melting at the glacier-atmosphere interface dominates this mass loss, and will likely do so for centuries to come. To quantify present and predict future melt rates requires the use of high-resolution, state-of-the-art regional atmospheric climate models for Antarctica and Greenland, and distributed surface energy balance (SEB) models for smaller ice caps and mountain glaciers. These models invariably require in situ SEB measurements for evaluation and tuning, which makes dedicated meteorological measurements using automatic weather stations (AWS) invaluable for glacier mass balance research. To that end, UU/IMAU has successfully operated a network of AWS on glaciers in the Alps, Norway, Iceland, Svalbard, Greenland and Antarctica (17 currently operational) since the early 1990s, in close collaboration with international partners. These AWS are specifically designed to close the SEB and quantify melt rate. However, the current AWS design is powered by a relatively large number of lithium batteries and has intricate external wiring, rendering it prone to damage and incompatible with ever-stricter international transportation rules for lithium batteries. Moreover, with this high level of international collaboration, a continuously changing group of researchers and technicians should be able to swiftly deploy and maintain our AWS. In order to overcome these problems, a radically different AWS design is proposed here, the intelligent Weather Station for polar use (iWS). iWS uses ultra-low power consumption sensors and electronics (including datalogger), enabling the full integration of electronics and all but two of the AWS sensors in a single unit (wind speed and radiation remain external). In combination with wireless internal and external data communication, this eliminates the need for vulnerable (external) cables and connectors, and greatly facilitates/shortens AWS installation, maintenance and repair visits. With power consumption reduced by over 95%, only three lithium batteries are required to power an iWs: this saves the environment, enhances transport safety/flexibility and reduces costs. Depending on whether the surface is ablating ice or accumulating snow, an independent, locally powered ultrasonic height sensor or snow thermistor string is installed next to the iWS, which communicate their data wirelessly to the iWS unit through Bluetooth. In melt areas over grounded ice, the iWS is combined with WiSe, a system of up to 32 wireless sensors that transmit englacial temperature and water pressure data through a maximum of 2400 m thick ice. We plan a four-year development, test and transition period (2012-2015) at eight AWS locations. After that, iWS is envisaged to replace all current UU/IMAU AWS.

An abrupt shutdown of the warm Gulfstream could induce abrupt transitions elsewhere, such as an intensification of El Niño and an accelerated permafrost thawing. The research team will study and quantify the risk of such cascading behavior and the expected climate response, to identify dangerous climatic change under global warming.