Jens Schroeter

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Variability of the Antarctic Circumpolar Current derived from GRACE retrievals, model simulations and in-situ measurements

by O. Boebel and Jens Schroeter

The Gravity Recovery and Climate Experiment (GRACE) provides estimates of the Earth's static ... more The Gravity Recovery and Climate Experiment (GRACE) provides estimates of the Earth's static and time-variant gravity field. Solutions from various processing centres (GFZ, CSR, GRGS, JPL etc.) enable us to determine mass redistributions on the globe. Given that land signals are generally large compared to anomalies over the ocean, an assessment of the latter requires a particularly careful filtering of

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Journal of Marine Systems, 2012

A data assimilation (DA) system has been developed for the operational circulation model of the G... more A data assimilation (DA) system has been developed for the operational circulation model of the German Federal Maritime and Hydrographic Agency (BSH) in order to improve the forecast of hydrographic characteristics in the North and Baltic Seas. It is based on the local Singular Evolutive Interpolated Kalman (SEIK) filter algorithm and assimilation of the NOAA AVHRR-derived sea surface temperature (SST). The DA system allows one to improve the agreement of the SST forecast with the satellite observations by 27% on average over the period of October 2007-September 2008. However, a sensitivity analysis of the forecasting system performance shows a significant impact of initial model error statistics on ice fields and bottom temperature. A reinitialisation of model error covariances in accordance with seasonality of the model error statistics was required in order to maintain the predictive skill with respect to these variables. The success of the DA system is quantified by the comparison with independent data from MARNET stations as well as sea ice concentration measurements. In addition, the Maximum Entropy approach is used to assess the system performance and the prior and posterior model error statistics.

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Development of a data assimilation system for BSH operational model of the North and Baltic Seas

… 2010, held 2-7 May …, 2010

Different formulations of SEIK filter have been implemented and validated for NOAA sea surface te... more

On Domain Localization in Ensemble-Based Kalman Filter Algorithms

by Alberta Albertella, Jens Schroeter, Tijana Janjic, and S. Skachko

Monthly Weather Review, 2011

Ensemble Kalman filter methods are typically used in combination with one of two localization tec... more Ensemble Kalman filter methods are typically used in combination with one of two localization techniques. One technique is covariance localization, or direct forecast error localization, in which the ensemble-derived forecast error covariance matrix is Schur multiplied with a chosen correlation matrix. The second way of localization is by domain decomposition. Here, the assimilation is split into local domains in which the assimilation update is performed independently. Domain localization is frequently used in combination with filter algorithms that use the analysis error covariance matrix for the calculation of the gain like the ensemble transform Kalman filter (ETKF) and the singular evolutive interpolated Kalman filter (SEIK). However, since the local assimilations are performed independently, smoothness of the analysis fields across the subdomain boundaries becomes an issue of concern.

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