Publications and Presentations

Presentations

PDAF has been presented at different conferences. Here are slides from some of these presentations:

​The Parallel Data Assimilation Framework PDAF for scalable sequential data assimilation,
Workshop on Programming Environments for Data Assimilation: Software and Applications, Deltares, Delft, Netherlands, January 31, 2011.

​Scalable sequential data assimilation with the Parallel Data Assimilation Framework PDAF,
2010 Ocean Sciences Meeting, Portland, Oregon, February 20-26, 2010.

​Sequential data assimilation on high-performance computers with the Parallel Data Assimilation Framework,
13th ECMWF Workshop on High Performance Computing in Meteorology, Reading, UK, November 3-7, 2008.

​PDAF - The Parallel Data Assimilation Framework: Experiences with Kalman Filtering,
11th ECMWF Workshop on Use of High Performance Computing in Meteorology, Reading, UK, October 25-29, 2004.

Publications about PDAF

Nerger, L., Hiller, W. (2013). Software for Ensemble-based Data Assimilation Systems - Implementation Strategies and Scalability. Computers and Geosciences, 55, 110-118. ​doi:10.1016/j.cageo.2012.03.026

Nerger, L., Hiller, W., Schröter, J.(2005). PDAF - The Parallel Data Assimilation Framework: Experiences with Kalman Filtering, Use of high performance computing in meteorology : proceedings of the Eleventh ECMWF Workshop on the Use of High Performance Computing in Meteorology, Reading, UK, 25 - 29 October 2004 / Eds.: Walter Zwieflhofer; George Mozdzynski, Singapore: World Scientific, 63-83.

Publications involving PDAF

in press

Kirchgessner, P., Nerger, L., Bunse-Gerstner, A. (2014) On the choice of an optimal localization radius in ensemble Kalman filter methods. Monthly Weather Review

Nerger, L., Schulte, S., Bunse-Gerstner, A. (2013) On the influence of model nonlinearity and localization on ensemble Kalman smoothing. Quarterly Journal of the Royal Meteorological Society, in press, ​doi:10.1002/qj.2293

2014

Losa, S.N., Danilov, S., Schröter, J., Janjic, T., Nerger, L., Janssen, F. (2014). Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Part 2. Sensitivity of the forecast's skill to the prior model error statistics. Journal of Marine Systems, 129, 259-270 ​doi:10.1016/j.jmarsys.2013.06.011

2013

Fournier, A., Nerger, L., Aubert, J. (2013). An ensemble Kalman filter for the time-dependent analysis of the geomagnetic field. Geochemistry, Geophysics, Geosystems, 14, 4035-4043 ​doi:10.1002/ggge.20252

2012

Nerger, L., Janjić, T., Schröter, J., Hiller, W. (2012). A unification of ensemble square root Kalman filters. Monthly Weather Review, 140, 2335-2345. ​doi:10.1175/MWR-D-11-00102.1

Nerger, L., Janjić, T., Schröter, J., Hiller, W. (2012). A regulated localization scheme for ensemble-based Kalman filters. Quarterly Journal of the Royal Meteorological Society, 138, 802-812. ​doi:10.1002/qj.945.

Janjić, T., Schröter, J., Savcenko, R., Bosch, W., Albertella, A., Rummel, R., Klatt, O. (2012). Impact of combining GRACE and GOCE gravity data on ocean circulation estimates. Ocean Science, 8, 65-79 ​doi:10.5194/os-8-65-2012.

Janjić, T., Schröter, J., Albertella, A., Bosch, W., Rummel, R., Savcenko, R., Schwabe, J., Scheinert, M. (2012). Assimilation of geodetic dynamic ocean topography using ensemble based Kalman filter. Journal of Geodynamics, 59-60, pp. 92-98 ​doi:10.5194/os-8-65-2012.

Losa, S.N., Danilov, S., Schröter, J., Nerger, L., Massmann, S., Janssen, F. (2012). Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data. Journal of Marine Systems, 105-108, pp. 152-162. ​doi:10.1016/j.jmarsys.2012.07.008

2011

Janjić, T., Nerger, L., Albertella, A., Schröter, J., Skachko, S. (2011). On domain localization in ensemble based Kalman filter algorithms. Monthly Weather Review, 139, 2046-2060 ​doi:10.1175/2011MWR3552.1.

2009

Rollenhagen, K., Timmermann, R., Janjic, T., Schröter, J., Danilov, S.(2009). Assimilation of sea ice motion in a Finite Element Sea Ice Model, Journal of Geophysical Research, 114, C05007, ​doi:10.1029/2008JC005067.

2008

Skachko, S., Danilov, S., Janjic, T., Schröter, J., Sidorenko, D., Savcenko, R., Bosch, W.(2008). Sequential assimilation of multi-mission dynamical topography into a global finite-element ocean model, Ocean Science, 4, 307-318, ​doi:10.5194/os-4-307-2008.

Nerger, L., Gregg, W. W.(2008). Improving Assimilation of SeaWiFS Data by the Application of Bias Correction with a Local SEIK Filter, Journal of Marine Systems, 73 (2008) 87-102, ​doi:10.1016/j.jmarsys.2007.09.007.

2007

Nerger, L., Gregg, W. W.(2007). Assimilation of SeaWiFS data into a global ocean-biogeochemical model using a local SEIK Filter, Journal of Marine Systems, 68, 237-254, ​doi:10.1016/j.jmarsys.2006.11.009.

Nerger, L., Danilov, S., Kivman, G., Hiller, W., Schröter, J.(2007). Data assimilation with the Ensemble Kalman Filter and the SEIK filter applied to a finite element model of the North Atlantic, Journal of Marine Systems, 65(1/4), 288-298., ​doi:10.1016/j.jmarsys.2005.06.009.

2006

Nerger, L., Danilov, S., Hiller, W., Schröter, J.(2006). Using sea-level data to constrain a finite-element primitive-equation ocean model with a local SEIK filter, Ocean Dynamics, 56(5/6), 634-649., ​doi:10.1007/s10236-006-0083-0.

2005

Nerger, L., Hiller, W., Schröter, J.(2005). A Comparison of Error Subspace Kalman Filters, Tellus series A-Dynamic Meteorology and Oceanography, 57A(5), 715-735, ​doi:10.1111/j.1600-0870.2005.00141.x.

2004

Nerger, L.(2004). Parallel Filter Algorithms for Data Assimilation in Oceanography, PhD Thesis, University of Bremen, 2004 (​Reports on Polar and Marine Research, 487, 174 pp.)