Variance reduced ensemble Kalman filtering

Electrical Engineering, Mathematics and Computer Scienc

OpenDA-NEMO framework for ocean data assimilation

Data assimilation methods provide a means to handle the modeling errors and uncertainties in sophisticated ocean models. In this study, we have created an OpenDA-NEMO framework unlocking the data assimilation tools available in OpenDA for use with NEMO models. This includes data assimilation methods, automatic parallelization, and a recently implemented automatic localization algorithm that removes spurious correlations in the model based on uncertainties in the computed Kalman gain matrix. We have set up a twin experiment where we assimilate sea surface height (SSH) satellite measurements. From the experiments, we can conclude that the OpenDA-NEMO framework performs as expected and that the automatic localization significantly improves the performance of the data assimilation algorithm by successfully removing spurious correlations. Based on these results, it looks promising to extend the framework with new kinds of observations and work on improving the computational speed of the automatic localization technique such that it becomes feasible to include large number of observations.Delft Institute of Applied MathematicsElectrical Engineering, Mathematics and Computer Scienc

Kalman filtering for non-linear chemistry models: Second order experiences

Electrical Engineering, Mathematics and Computer Scienc

Data-assimilation-based parameter estimation of bathymetry and bottom friction coefficient to improve coastal accuracy in a global tide model

Global tide and surge models play a major role in forecasting coastal flooding due to extreme events or climate change. The model performance is strongly affected by parameters such as bathymetry and bottom friction. In this study, we propose a method that estimates bathymetry globally and the bottom friction coefficient in shallow waters for a global tide and surge model (GTSMv4.1). However, the estimation effect is limited by the scarcity of available tide gauges. We propose complementing sparse tide gauges with tide time series generated using FES2014. The FES2014 dataset outperforms the GTSM in most areas and is used as observations for the deep ocean and some coastal areas, such as Hudson Bay and Labrador, where tide gauges are scarce but energy dissipation is large. The experiment is performed with a computation- and memory-efficient iterative parameter estimation scheme (time–POD-based coarse incremental parameter estimation; POD: proper orthogonal decomposition) applied to the Global Tide and Surge Model (GTSMv4.1). Estimation results show that model performance is significantly improved for the deep ocean and shallow waters, especially in the European shelf, directly using the CMEMS tide gauge data in the estimation. The GTSM is also validated by comparing to tide gauges from UHSLC, CMEMS, and some Arctic stations in the year 2014.Mathematical Physic

Secular Trends in Global Tides Derived From Satellite Radar Altimetry

Previous studies have demonstrated that tides are subject to considerable changes on secular time scales. However, these studies rely on sea level observations from tide gauges that are predominantly located in coastal and shelf regions and therefore, the large-scale patterns remain uncertain. Now, for the first time, satellite radar altimetry (TOPEX/Poseidon & Jason series) has been used to study worldwide linear trends in tidal harmonic constants of four major tides (M2, S2, O1, and K1). This study demonstrates both the potential and challenges of using satellite data for the quantification of such long-term changes. Two alternative methods were implemented. In the first method, tidal harmonic constants were estimated for consecutive 4-year periods, from which the linear change was then estimated. In the second method, the estimation of linear trends in the tidal constants of the four tides was integrated in the harmonic analysis. First, both methods were assessed by application to tide gauge data that were sub-sampled to the sampling scheme of the satellites. Thereafter the methods were applied to the real satellite data. Results show both statistically significant decreases and increases in amplitude up to 1 mm/year and significant phase changes up to ∼0.1 deg/year. The level of agreement between altimeter-derived trends and estimates from tide gauge data differs per region and per tide.Physical and Space GeodesyMathematical Physic

Tidal dissipation from free drift sea ice in the Barents Sea assessed using GNSS beacon observations

One of the major challenges facing global hydrodynamic tidal models is the modelling of the interaction between sea ice and tides in high-latitude waters. Recent studies have shown strong seasonal correlation between sea ice and tides. Hence, it is important to accurately model the effect of sea ice in a tidal model. Presence of sea ice leads to a frictional dissipation of tides. Most models either completely ignore sea ice or partly include it by assuming a fixed sea ice cover (landfast ice). However, sea ice can also be drifting and the nature of dissipation between drifting sea ice and tides is partly unknown. We assess the dissipation of tides due to free drift sea ice. In the absence of wind, this is negligible in the deeper and open ocean. For the shallow water regions, however, this dissipation is unknown. Here, we evaluate this dissipation for the Spitzbergen Shelf region using a beacon dataset showing strong free drift subdaily sea ice oscillations and a physics based point ice model. Two analyses were done which compared the model and observed motion. The analyses showed that for winds speeds below 8m/s and with low subdaily signals, the subdaily free drift sea ice motion is strongly connected to the tides and that the frictional dissipation is low. In the context of global tide and storm surge models, the dissipation from free drift sea ice on tides should be evaluated based on the region (deep ocean or shallow water) and existing wind conditions. In the presence of strong winds the dissipation between free drift sea ice and air can be significant on a subdaily scale even if there are no subdaily signals in the wind itself.Mathematical PhysicsPhysical and Space Geodes

Computation-Efficient Parameter Estimation for a High-Resolution Global Tide and Surge Model

In this study, a computation-efficient parameter estimation scheme for high-resolution global tide models is developed. The method is applied to Global Tide and Surge Model with an unstructured grid with a resolution of about 2.5 km in the coastal area and about 4.9 million cells. The estimation algorithm uses an iterative least squares method, known as DUD. We use time-series derived from the FES2014 tidal database in deep water as observations to estimate corrections to the bathymetry. Although the model and estimation algorithm run in parallel, directly applying of DUD would not be affordable computationally. To reduce the computational demand, a coarse-to-fine strategy is proposed by using output from a coarser model to replace the fine model. There are two approaches; One is completely replacing the fine model with a coarser model during calibration (Coarse Calibration) and the second is Coarse Incremental Calibration, that replaces the output increments between the initial model and model with modified parameters by coarser grid model simulations. To further reduce the computation time, the parameter dimension is reduced from O(106) to O(102) based on sensitivity analysis, which greatly reduces the required number of model simulations and storage. In combination, these methods form an efficient optimization strategy. Experiments show that the accuracy of the tidal representation can be improved significantly at affordable cost. Validation for other time-periods and using coastal tide-gauges shows that the accuracy is improved significantly. However, the calibration period of two weeks is short and leads to some over-fitting of the model.Mathematical Physic