Eric Dombrowsky

A demonstration of ensemble-based assimilation methods with a layered OGCM from the perspective of operational ocean forecasting systems

A demonstration study of three advanced, sequential data assimilation methods, applied with the nonlinear Miami Isopycnic Coordinate Ocean Model (MICOM), has been performed within the European Commission-funded DIADEM project. The data assimilation techniques considered are the Ensemble Kalman Filter (EnKF), the Ensemble Kalman Smoother (EnKS) and the Singular Evolutive Extended Kalman (SEEK) Filter, which all in different ways resemble the original Kalman Filter. In the EnKF and EnKS an ensemble of model states is integrated forward in time according to the model dynamics, and statistical moments needed at analysis time are calculated from the ensemble of model states. The EnKS, as opposed to the EnKF, update the analysis also backward in time whenever new observations are available, thereby improving the estimated states at the previous analysis times. The SEEK filter reduces the computational burden of the error propagation by representing the errors in a subspace which is initially calculated from a truncated EOF analysis. A hindcast experiment, where sea-level anomaly and sea-surface temperature data are assimilated, has been conducted in the North Atlantic for the time period July until September 1996. In this paper, we describe the implementation of ensemble-based assimilation methods with a common theoretical framework, we present results from hindcast experiments achieved with the EnKF, EnKS and SEEK filter, and we discuss the relative merits of these methods from the perspective of operational marine monitoring and forecasting systems. We found that the three systems have similar performances, and they can be considered feasible technologically for building preoperational prototypes. D 2003 Elsevier Science B.V. All rights reserved.

The GODAE/Mercator-Ocean global ocean forecasting system: results, applications and prospects

The Mercator-Océan eddy permitting (1/4) global ocean forecasting system assimilating satellite altimetry is the French contribution to the GODAE project and to the MERSEA project for operational systems. It has run operationally since October 2005 and is forced with daily surface fluxes from ECMWF operational analyses and forecasts. JASON, ERS and GFO altimetry measurements from AVISO were assimilated from January 2005 up to real time. The simulation results are compared with independent in-situ data of the Atlantic, Pacific and Antarctic Ocean basins in order to provide an estimation of the performance of the system. The results are also compared with the Levitus climatology, and with combinations of in-situ and satellite observations since 2005. In the Atlantic basin, the global system is also compared with Mercator-Ocean regional systems that assimilate SST (Sea Surface Temperature), SLA (Sea Level Anomalies) and in situ (temperature and salinity profiles) near real time observations

Continuous assimilation in an open domain of the northeast Atlantic: 1. Methodology and application to AthenA‐88

A scheme to perform suboptimal intermittent assimilation in an open-ocean, quasi-geostrophic model is presented and applied to the assimilation of altimeter data in a domain of the northeast Atlantic west of Ireland. Both simulated and real altimeter data are used. Three-dimensional (3-D) synoptic observation fields and error variance fields are derived from synoptic dynamic topography anomaly estimates, using an empirical orthogonal mode (EOF) vertical extension technique. The 3-D estimates are suboptimally combined with the time-dependent part of the forecast fields. Suboptimality here means that the combination does not directly use spatial correlations of errors; however, the 3-D synoptic observation estimates used in the combination do contain error spatial statistical information. The resulting fields added to a mean model climatology are used as initial conditions for the model, which is integrated until a new dynamic topography anomaly estimate is available. Locally, the combination is optimal in the sense that it is based on the observational error variances, which reflect the measurement noise and the space-time distribution of data, and that it minimizes the error variance of the results. A similar combination scheme using past as well as future observations is used to update the boundaries during model integration. Simulated surface topography anomaly maps, typical of the northeast Atlantic, are assimilated every 20 days for a 300-day period, with different noise characteristics typical of altimetric sampling errors, in a three-level version of the model. The assimilation fields, especially the vorticity at deeper levels, converge toward the reference fields. The convergence is obtained after O(100 days), regardless of the observational noise levels tested (up to −2 dB). Using a relevant observational error model seems to matter, in particular, the error level should not be underestimated. In the case of an 80-day gap in the data inflow, the model predictability limits the reliability of the forecast beyond 20 days. The scheme makes the model converge back as soon as new observations are entered, with limited convergence loss due to the gap. The case of an unknown model climatology is also studied. Finally, the scheme is applied to Geosat altimeter data, added to the Robinson, Bauer and Schroeder annual climatology, in the AthenA-88 cruise area, which is contained in the model box. The assimilation results compare favorably with hydrographical data from the cruise and help the synoptic interpretation of the observed phenomena.

An introduction to GODAE OceanView

Real-time operational predictions of the major ocean basins which resolve the ocean mesoscale at mid-latitudes have become established in more than a dozen countries over the last 15 years. These predictions depend on the global ocean observing system (particularly satellite altimeters and the Argo profiling float system), high performance computers and sophisticated ocean models and data assimilation systems. They support an expanding range of information services for operations at sea, weather forecasts and protection of the environment. GODAE Oceanview (GOV) assists the groups developing these predictions. This paper provides an introduction to GOV and the papers in this special issue.

Synthesis of new scientific challenges for GODAE OceanView

The marine environment plays an increasingly important role in shaping economies and infrastructures, and touches upon many aspects of our lives, including food supplies, energy resources, national security and recreational activities. Global Ocean Data Assimilation Experiment (GODAE) and GODAE OceanView have provided platforms for international collaboration that significantly contribute to the scientific development and increasing uptake of ocean forecasting products by end users who address societal issues such as those listed above. Many scientific challenges and opportunities remain to be tackled in the ever-changing field of operational oceanography, from the observing system to modelling, data assimilation and product dissemination. This paper provides a brief overview of past achievements in GODAE OceanView, but subsequently concentrates on the future scientific foci of GODAE OceanView and its Task Teams, and provides a vision for the future of ocean forecasting.

Progress in mesoscale variability analysis from satellite altimetry data

Abstract Studies of mesoscale variability resulting from ocean circulation is possible by the use of satellite altimetry. Three approaches are possible, (1) satellite observations on repetitive track, (2) satellite observations at the crossover point of ascending and descending tracks, and (3) satellite measurement of sea level differences. The results concern global statistical parameters (RMS kinetic energy, wave number spectra), or local synoptic maps of dynamic topography. More recently the incorporation of the latter into dynamical models of the mesoscale circulation has been achieved. De Mey and Robinson have shown how the forcing of a mesoscale model by the altimetric height along the boundaries of the model allow to transfer the surface satellite information onto deep circulation pattern. Similarly, Perigaud and Delecluze have indicated how the state of a two layer, wind-forced non linear model of the Somali current can be readjusted by altimetry data. These approaches are means of merging the altimetric information with other data and with a dynamical description of the system. This will likely be the dominant approaches of future oceanographic studies.

Satellite altimetry observations of ocean dynamic topography

Abstract The experience gained by analysing the Seasat altimetric observation of the ocean dynamic topography is getting more valuable as almost 10 years of nearly continuous altimeter data may be obtained by Geosat, ERSI and Topex/Poseidon. Our group worked on all aspects of the question: the accuracy of the measurements and more particularly the improvements of the orbit determination and its error; the extraction of the dynamic topography signal both on the mesoscale and on the large scales and of tides; the analysis of the observations, whether statistically or in the form of synoptic maps, and finally, how to constrain dynamical models from altimetry data. This paper describes these various aspects of our work.