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Monitoring of the intertidal and subtidal bathymetry at large spatiotemporal scales using traditional surveying methods is a challenging and costly task. Well established methods of remote sensing and increasing frequency of freely available satellite data enable automated monitoring of intertidal and subtidal bathymetry. A number of methods exist to extract intertidal bathymetry by combining the observed water masks with the water level data simulated by intertidal numerical models and local water level measurements. At the same time, the light attenuation in a water column, observed by optical satellite sensors, can be used to estimate water depth, providing a way to estimate subtidal bathymetry. In this research, we will discuss how these both methods can be combined to generate a consistent intertidal and subtidal bathymetry data. Challenges, such as automated processing at a continental scale (using Google Earth Engine), calibration, and validation of the algorithm will be discussed. This research is used to improve the European Marine Observation and Data Network (EMODnet) bathymetry and is supported by the European Commission and Dutch Ministry of Infrastructure and Water Management. [ABSTRACT FROM AUTHOR]

The increasing sea-level and meteorological changes associated with climate change increase the flood risk in coastal cities and low lying areas. Understanding the magnitude and impact of such changes is vital to design adaptive strategies and create awareness. Such risk predictions are possible with the use of hydrodynamic models that are coupled to climate models. In the context of the CoDEC project (Coastal Dataset for Evaluation of Climate impact), we compute the climate change induced changes on future sea-level, storm-surge, tides and waves, and the associated impacts on coastal flood risk for Europe from present date to 2100. We consider the 4.5 and 8.5 Representative Concentration Pathways (RCP), and produce extreme value statistics representing mid-century and end of century conditions. For the water levels, we use the Global Tide and Surge Model v3.0 (GTSMv3.0), a high resolution hydrodynamic model with global coverage. The model has a coastal resolution of 2.5km globally and 1.25km in Europe, and incorporates dynamically sea-level rise, tides and surge, and therefore calculates the non-linear interactions between them. For the meteorological forcing, we use the global EC-Earth climate model together with a European-wide high resolution climate model from the EURO-CORDEX archive. In order to assess the changes relative to present and past conditions, we perform a reanalysis of extreme sea levels using the newly available high resolution ERA5 forcing. Based on the relative changes, we design a number of indicators that provide useful information about the possible impacts of climate change globally. For Europe, a number of user cases are defined in which different industries use such indicators and global model outputs to downscale and assess impacts at a regional/local scale.We produce output for not only global coastlines at a high resolution, but also at predefined nesting points covering the global ocean which can be used for regional downscaling anywhere in the globe. [ABSTRACT FROM AUTHOR]

As the astronomical forces that drive tides are constant, tides are generally considered to be stationary. However, they can be altered due to various reasons ranging from global change in sea level and ocean stratification to local changes in bathymetry, and river discharge.In this presentation, we will present an analysis of tidal records along the North Sea coasts of The Netherlands. The data are analyzed with a mixed statistical-deterministic modeling approach using a high-resolution hydrodynamic model to remove natural tidal variability, including the nodal cycle, from the observed time series. This offers a methodological advantage compared to a statistical removal of the nodal cycle from observations and also allows for numerical experiments to explore potential causes of the changes.Analysis of M2 amplitude shows considerable inter-annual variability, but virtually no trend prior to 2006-2007 at the Dutch coastal stations. However, from 2007 onwards we observe a relatively strong decline in M2 amplitude at many of the stations. In some stations, we observe a cumulative decline over 2007-2017 of up to 5%. The strongest relative decline occurred at station Petten located at the Holland coast, with a decrease of 0.46 % per year (i.e. 3.2 mm/year). The decline shows a strong spatial coherence, with a gradually decreasing rates of change to the north and south of this station.Finally, we use model experiments and literature to evaluate the various physical mechanisms for their ability to cause the observed changes. [ABSTRACT FROM AUTHOR]

Satellite-based rainfall estimates are a valuable source of information. This is especially the case for regions with low gauge density, such as many regions in sub-Saharan Africa. Satellites do not measure rainfall directly, instead it is derived from other measured variables. This can lead to errors in the position of the rainfall events beside the errors in their intensity. Such errors are particularly critical for localized events such as the convective storms occurring during the monsoon season which produce most of the rainfall in sub-Saharan Africa. We propose a morphing approach to adjust both the intensity and the position of satellite estimates with gauge data. Morphing is a well-known image processing technique that transforms an image into another, using cross-dissolving and warping. Thus, both the intensity and the position are taken into account. Our approach uses an automatic registration, so only the two images are needed as input. There is no need to predefine the rain events, or any other features. The automatic morphing method is applied for a rainfall event during the monsoon season over the Volta Basin region. We gauge-adjust the satellite-based estimates IMERG-early (Integrated Multi-Satellite Retrievals for GPM), using the gauge network from TAHMO (Trans-African Hydro-Meteorological Observatory). The automatic morphing has encouraging results when the precipitation fields are similar enough. [ABSTRACT FROM AUTHOR]

In this study we explore the relationship between time series of gauge precipitation and satellite-based cloud-top temperature (CTT) at different time scales, based on similarity measures of correlation method and dynamic time warping method. The potential and the uncertainty to use CTT time series to generate daily rainfall estimates or rainfall time series are analyzed. Results show their negative correlation increases as with increasing temporal scale, from > -0.4 at daily scale to < -0.75 at monthly scale. In addition, strong similarity of CTT time series at two locations indicates strong similarity of precipitation time series at these two locations at any time scale, with the allowance of an optimal time shift. All the evidences imply high potential of using CTT data to extend rainfall estimation algorithm and parameterization (based on satellite observation, numerical weather model, or stochastic weather generator, etc.,) derived at locations with ground-based rainfall observations to any arbitrary location. [ABSTRACT FROM AUTHOR]

Sea-level rise (SLR) is threatening the low-lying and densely-populated coastal zone. With an increased contribution of the Antarctic ice sheet it is possible that mean sea levels rise well beyond 1 m by 2100. Tidal amplitudes show a strong response to SLR which affect the high and low waters, which can have wide-ranging societal imacts. Any change in tides directly affects flood risk, but can also impact navigation and port operations, functioning of ecosystems in intertidal areas, stratification of shallow seas, and sediment dynamics.Despite the strong response of tides to SLR the assessment of suchs impacts has received relatively little attention in literature. In this contribution, we apply a cutting-edge approach to advance our understanding of how tides along the world's coastline may respond to SLR by 2100. This approach is based on Global Tide and Surge Model (GTSM) version 3.0 (Irazoqui Apecechea, in review). GTSM3.0 has an unprecedented high resolution along the coast (1.25km for Europe), no open boundaries, and has a good performance without data assimilation. We combine GTSM3.0 with probabilistic SLR projections that include an increased contribution from Antarctica (Le Bars et al., 2018). The 50th and 95the SLR projection for RCP8.5 indicate sea levels that are respectively 1.8 m and 2.9 m higher by 2100. Preliminary results show that tidal characteristics can change significantly in response to SLR, especially in shallow seas such as the North Sea and the seas surrounding Indonesia. Changes can be asymmetric, for example, by an increase in the Mean High High Water (MHHW) and no change in the Mean Low Low Water (MLLW). Furthermore, changes are not always proportional to the local SLR, suggesting that changes in tides are sensitive to regional variation of SLR. The effect of coastline recession and retreat of grounding line of ice sheets should be explored further. Our findings show that tides cannot be considered to be constant in time, which suggest that climate impacts studies should address changes in sea level using an integrated approach.References Irazoqui Apecechea, M., Verlaan, M., Williams, J., de Lima Rego, J., Muis, S., van der Pijp, S., Kernkamp H., (2018). GTSM v3.0: A next generation Global Tide and Surge Model. In review Ocean Modelling. Le Bars, D., Drijfhout, S., & de Vries, H. (2017). A high-end sea level rise probabilistic projection including rapid Antarctic ice sheet mass loss. Environmental Research Letters, 12(4), 044013. [ABSTRACT FROM AUTHOR]

Deltares operates two real-time forecasting systems with global coverage: the Global Flood Forecasting and Information System (GLOFFIS) and the Global Storm Surge Information System (GLOSSIS). GLOFFIS produces fluvial flood forecasts with global coverage. The system ingests multiple weather forecasting products including ensemble NWPs. These are used to force multiple hydrological models of various types and spatial resolutions. Data assimilation is applied for selected basins where observations are available in near real time. GLOSSIS continuously provides 10 day water level and storm-surge forecasts using the Global Tide and Surge Model (GTSM). The GTSM is a numerical model based on Delft3D Flexible Mesh (FM), that computes tides and storm surges around the world efficiently and accurately through the use of an unstructured mesh. In GTSM version 3 the coastal resolution is up to about 1km, which is sufficient to capture the local coastal variability in many parts around the world. Both systems are based on the Delft-FEWS forecast production system. Some results are disseminated via www.globalfloodforecast.com. In the presentation, some system characteristics as well as the rationale for forecasting at global scale will be highlighted. Werner, M., Schellekens, J., Gijsbers, P., van Dijk, M., van den Akker, O., and Heynert, K.: The Delft-FEWS flow forecasting system, Environ. Modell. Softw., 40, 65–77, doi:10.1016/j.envsoft.2012.07.010, 2013 [ABSTRACT FROM AUTHOR]