Laurent Bertino

An Iterative EnKF for Strongly Nonlinear Systems

AbstractThe study considers an iterative formulation of the ensemble Kalman filter (EnKF) for strongly nonlinear systems in the perfect-model framework. In the first part, a scheme is introduced that is similar to the ensemble randomized maximal likelihood (EnRML) filter by Gu and Oliver. The two new elements in the scheme are the use of the ensemble square root filter instead of the traditional (perturbed observations) EnKF and rescaling of the ensemble anomalies with the ensemble transform matrix from the previous iteration instead of estimating sensitivities between the ensemble observations and ensemble anomalies at the start of the assimilation cycle by linear regression. A simple modification turns the scheme into an ensemble formulation of the iterative extended Kalman filter. The two versions of the algorithm are referred to as the iterative EnKF (IEnKF) and the iterative extended Kalman filter (IEKF).In the second part, the performance of the IEnKF and IEKF is tested in five numerical experiments...

The TOPAZ monitoring and prediction system for the Atlantic and Arctic Oceans

Ocean data assimilation systems allow the combination of remote sensing and in-situ ocean observations with primitive equation ocean general circulation models (OGCM). They thus provide initial conditions for short-term ocean currents forecasts (ten days to one month) and boundary conditions for nested high-resolution models of coastal seas and can be operated in hindcast to reproduce past events over long periods. At a time when offshore activities are moving toward deeper waters and ice-covered seas, accurate monitoring and forecasting of the environment (particularly ocean currents and seaice) cannot be neglected. This paper presents the TOPAZ system, being the Arctic component of the MERSEA integrated system and one of the contributors to the GODAE international initiative. The system is based on the latest scientific developments in terms of ocean modelling with the Hybrid Coordinate Ocean Model (HYCOM) and data assimilation with the Ensemble Kalman Filter (EnKF). Validation results of the system and applications in nested regional models are presented.

GEROS-ISS: GNSS REflectometry, Radio Occultation, and Scatterometry Onboard the International Space Station

GEROS-ISS stands for GNSS REflectometry, radio occultation, and scatterometry onboard the International Space Station (ISS). It is a scientific experiment, successfully proposed to the European Space Agency in 2011. The experiment as the name indicates will be conducted on the ISS. The main focus of GEROS-ISS is the dedicated use of signals from the currently available Global Navigation Satellite Systems (GNSS) in L-band for remote sensing of the Earth with a focus to study climate change. Prime mission objectives are the determination of the altimetric sea surface height of the oceans and of the ocean surface mean square slope, which is related to sea roughness and wind speed. These geophysical parameters are derived using reflected GNSS signals (GNSS reflectometry, GNSS-R). Secondary mission goals include atmosphere/ionosphere sounding using refracted GNSS signals (radio occultation, GNSS-RO) and remote sensing of land surfaces using GNSS-R. The GEROS-ISS mission objectives and its design, the current status, and ongoing activities are reviewed and selected scientific and technical results of the GEROS-ISS preparation phase are described.

Ensemble Optimal Interpolation: multivariate properties in the Gulf of Mexico

High-resolution models can reproduce mesoscale dynamics and the variability in the Gulf of Mexico (GOM), but cannot provide accurate locations of currents without data assimilation (DA). We use the computationally cheap Ensemble Optimal Interpolation (EnOI) in conjunction with the HYCOM model for assimilating altimetry data. The covariance matrix extracted from a historical ensemble, is 3-dimensional and multivariate. This study shows that the multivariate correlations with Sea Level Anomaly are coherent with the known dynamics of the area at two locations: the central part of the GOM, and the upper slope of the northern shelf. The correlations in the first location are suitable for an eddy forecasting system, but the correlations in the second location show some limitations due to seasonal variability. The multivariate relationships between variables are reasonably linear, as assumed by the EnOI. Our DA set-up produces little noise that is dampened within two days, when the model is pulled strongly towards observations. Part of it is caused by density perturbations in the isopycnal layers, or artificial caballing. The DA system is demonstrated for a realistic case of Loop Current eddy shedding, namely Eddy Yankee (2006).

Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments

Building the capacity for monitoring and forecasting marine biogeochemistry and ecosystem dynamics is a scientific challenge of strategic importance in the context of rapid environmental change and growing public awareness of its potential impacts on marine ecosystems and resources. National Operational Oceanography centres have started to take up this challenge by integrating biogeochemistry in operational systems. Ongoing activities are illustrated in this paper by presenting examples of (pre-)operational biogeochemical systems active in Europe and North America for global to regional applications. First-order principles underlying biogeochemical modelling are briefly introduced along with the description of biogeochemical components implemented in these systems. Applications are illustrated with examples from the fields of hindcasting and monitoring ocean primary production, the assessment of the ocean carbon cycle and the management of living resources. Despite significant progress over the past 5 years in integrating biogeochemistry into (pre-)operational data-assimilation systems, a sustained research effort is still needed to assess these systems and their products with respect to their usefulness to the management of marine systems.

Status and future of global and regional ocean prediction systems

Operational evolution of global and regional ocean forecasting systems has been extremely significant in recent years. Global Ocean Data Assimilation Experiment (GODAE) Oceanview supports the national research groups providing them with coordination and sharing expertise among the partners. Several systems have been set up and developed pre-operationally, and the majority of these are now fully operational; at the present time, they provide medium- and long-term forecasts of the most relevant ocean physical variables. These systems are based on ocean general circulation models and data-assimilation techniques that are able to correct the model with the information inferred from different types of observations. A few systems also incorporate a biogeochemical component coupled with the physical system, while others are based on coupled ocean–wave–ice–atmosphere models. The products are routinely validated with observations in order to assess their quality. Data and product implementation and organization, as well as service, for users have been well tried and tested, and most of the products are now available to users. The interaction with different users is an important factor in the development process. This paper provides a synthetic overview of the GODAE OceanView prediction systems.

Parameterization of an Iceberg Drift Model in the Barents Sea

Abstract The problem of parameter estimation is examined for an iceberg drift model of the Barents Sea. The model is forced by atmospheric reanalysis data from ECMWF and ocean and sea ice variables from the Hybrid Coordinate Ocean Model (HYCOM). The model is compared with four observed iceberg trajectories from April to July 1990. The first part of the study focuses on the forces that have the strongest impact on the iceberg trajectories, namely, the oceanic, atmospheric, and Coriolis forces. The oceanic and atmospheric form drag coefficients are optimized for three different iceberg geometries. As the iceberg mass increases, the optimal form drag coefficients increase linearly. A simple balance between the drag forces and the Coriolis force explains this behavior. The ratio between the oceanic and atmospheric form drag coefficients is similar in all experiments, although there are large uncertainties on the iceberg geometries. Two iceberg trajectory simulations have precisions better than 20 km during tw...

Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: a twin experiment

Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method for performing seasonal-to-decadal prediction and secondly, reassess the use of sea surface temperature (SST) for initialisation of these forecasts. We use the Norwegian Climate Prediction Model (NorCPM), which is based on the Norwegian Earth System Model (NorESM) and uses the deterministic ensemble Kalman filter to assimilate observations. NorESM is a fully coupled system based on the Community Earth System Model version 1, which includes an ocean, an atmosphere, a sea ice and a land model. A numerically efficient coarse resolution version of NorESM is used. We employ a twin experiment methodology to provide an upper estimate of predictability in our model framework (i.e. without considering model bias) of NorCPM that assimilates synthetic monthly SST data (EnKF-SST). The accuracy of EnKF-SST is compared to an unconstrained ensemble run (FREE) and ensemble predictions made with near perfect (i.e. microscopic SST perturbation) initial conditions (PERFECT). We perform 10 cycles, each consisting of a 10-yr assimilation phase, followed by a 10-yr prediction. The results indicate that EnKF-SST improves sea level, ice concentration, 2 m atmospheric temperature, precipitation and 3-D hydrography compared to FREE. Improvements for the hydrography are largest near the surface and are retained for longer periods at depth. Benefits in salinity are retained for longer periods compared to temperature. Near-surface improvements are largest in the tropics, while improvements at intermediate depths are found in regions of large-scale currents, regions of deep convection, and at the Mediterranean Sea outflow. However, the benefits are often small compared to PERFECT, in particular, at depth suggesting that more observations should be assimilated in addition to SST. The EnKF-SST system is also tested for standard ocean circulation indices and demonstrates decadal predictability for Atlantic overturning and sub-polar gyre circulations, and heat content in the Nordic Seas. The system beats persistence forecast and shows skill for heat content in the Nordic Seas that is close to PERFECT.

Status and future of data assimilation in operational oceanography

The GODAE OceanView systems use various data assimilation algorithms, including 3DVar, EnOI, EnKF and the SEEK filter with a fixed basis, using different time windows. The main outputs of the operational data assimilation systems, the increments, have been compared for February 2014 in various regions. The eddy-permitting systems’ increments are similar in a number of the regions, indicating similar forecast errors are being corrected, while the eddy-resolving systems represent smaller-scale structures in the mid-latitude regions investigated and appear to have smaller biases. Monthly average temperature increments show significant SST biases, particularly in the systems which assimilate swath satellite SST data, indicating systematic errors in the surface heat fluxes and the way in which they are propagated vertically by the ocean models. On-going developments to the data assimilation systems include improvements to the specification of error covariances, improving assimilation of data near the equator, and understanding the effect of assimilation on the Atlantic Meridional Overturning Circulation. Longer term developments are expected to include the implementation of more advanced algorithms to make use of flow-dependent error covariance information. Assimilation of new data sources over the coming years, such as wide-swath altimetry, is also expected to improve the accuracy of ocean state estimates and forecasts provided by the GODAE OceanView systems.

Forecasting search areas using ensemble ocean circulation modeling

We investigate trajectory forecasting as an application of ocean circulation ensemble modeling. The ensemble simulations are performed weekly, starting with assimilation of data for various variables from multiple sensors on a range of observational platforms. The ensemble is constructed from 100 members, and member no. 1 is designed as a standard (deterministic) simulation, providing us with a benchmark for the study. We demonstrate the value of the ensemble approach by validating simulated trajectories using data from ocean surface drifting buoys. We find that the ensemble average trajectories are generally closer to the observed trajectories than the corresponding results from a deterministic forecast. We also investigate an alternative model in which velocity perturbations are added to the deterministic results and ensemble mean results, by a first-order stochastic process. The parameters of the stochastic model are tuned to match the dispersion of the ensemble approach. Search areas from the stochastic model give a higher hit ratio of the observations than the results based on the ensemble. However, we find that this is a consequence of a positive skew of the area distribution of the convex hulls of the ensemble trajectory end points.