Changes between Version 233 and Version 234 of PublicationsandPresentations
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- Aug 15, 2023, 4:43:42 PM (15 months ago)
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PublicationsandPresentations
v233 v234 97 97 98 98 Shu, Q., F. Qiao, J. Liu, Z. Song, Z. Chen, J. Zhao, X. Yin, Y. Song. (2021) Arctic sea ice concentration and thickness data assimilation in 99 the FIO-ESM climate forecast system, Acta Oceanol. Sin., 40, 65–75 [https://doi.org/ 0.1007/s13131-021-1768-4 doi:0.1007/s13131-021-1768-4]99 the FIO-ESM climate forecast system, Acta Oceanol. Sin., 40, 65–75 [https://doi.org/10.1007/s13131-021-1768-4 doi:10.1007/s13131-021-1768-4] 100 100 101 101 Luo, H., Q. Yang, L. Mu, X. Tian-Kunze, L. Nerger, M. Mazloff, L. Kaleschke, D. Chen. (2021) DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations, Journal of Glaciology, 67, 1235-1240 [https://doi.org/10.1017/jog.2021.57 doi:10.1017/jog.2021.57] … … 173 173 Journal of Geophysical Research: Biogeosciences, 123 (2018) 2839-2862 [https://doi.org/10.1029/2016JG003753 doi:10.1029/2016JG003753] 174 174 175 Liu, Y, W. Fu (2018). Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea. Ocean Science 14(2018) 525-541 [https://doi.org/10.5194/os-14-525-2018 ] (The paper doesn't mention PDAF, but the author's confirmed that PDAF with offline-coupling to NEMO was used)176 177 Bocher, M., A. Fournier, N. Coltice (2018). Ensemble Kalman filter for the reconstruction of the Earth's mantle circulation. Nonlin. Proc. Geophys., 25 (2018) 99-123 [https://doi.org/10.5194/npg-25-99-2018 ]175 Liu, Y, W. Fu (2018). Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea. Ocean Science 14(2018) 525-541 [https://doi.org/10.5194/os-14-525-2018 doi:10.5194/os-14-525-2018] (The paper doesn't mention PDAF, but the author's confirmed that PDAF with offline-coupling to NEMO was used) 176 177 Bocher, M., A. Fournier, N. Coltice (2018). Ensemble Kalman filter for the reconstruction of the Earth's mantle circulation. Nonlin. Proc. Geophys., 25 (2018) 99-123 [https://doi.org/10.5194/npg-25-99-2018 doi:10.5194/npg-25-99-2018] 178 178 179 179 Zhang, H., W. Kurtz, S. Kollet, H. Vereecken, H.-J. Hendricks Franssen (2018). Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model. Advances in Water Resources, 111 (2018) 224-238 [http://doi.org/10.1016/j.advwatres.2017.11.003] … … 213 213 Korthe, S., J. Tödter, B. Ahrens. (2016) Strategies for soil initialization of regional decadal climate predictions. Meteorologisch Zeitschrift, 25 (2016) 775-794 [https://doi.org/10.1127/metz/2016/0729] 214 214 215 Nerger, L., Losa, S. N., Brüning T., Janssen F. (2016) The HBM-PDAF assimilation system for operational forecasts in the North and Baltic Seas, in Operational Oceanography for Sustainable Blue Growth. Proceedings of the Seventh EuroGOOS International Confer -ence. 28-30 October 2014, Lisbon, Portugal / Eds. E. Buch, Y. Antoniou, D. Eparkhina, G. Nolan. ISBN 978-2-9601883-1-8215 Nerger, L., Losa, S. N., Brüning T., Janssen F. (2016) The HBM-PDAF assimilation system for operational forecasts in the North and Baltic Seas, in Operational Oceanography for Sustainable Blue Growth. Proceedings of the Seventh EuroGOOS International Conference. 28-30 October 2014, Lisbon, Portugal / Eds. E. Buch, Y. Antoniou, D. Eparkhina, G. Nolan. ISBN 978-2-9601883-1-8 216 216 217 217 Yang, Q., Losch, M., Losa, S., Jung, T., Nerger, L., Lavergne, T. (2016) Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation. The Cryosphere, 10, 761-774, 2016 [http://dx.doi.org/10.5194/tc-10-761-2016 doi:10.5194/tc-10-761-2016]) … … 253 253 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 [http://dx.doi.org/doi:10.5194/os-8-65-2012 doi:10.5194/os-8-65-2012]. 254 254 255 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 [http://dx.doi.org/doi:10. 5194/os-8-65-2012 doi:10.5194/os-8-65-2012].255 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 [http://dx.doi.org/doi:10.1016/j.jog.2011.07.001 doi:10.1016/j.jog.2011.07.001]. 256 256 257 257 Saynisch, J., Thomas, M. (2012). Ensemble Kalman‐Filtering of Earth rotation observations with aglobal ocean model. Journal of Geodynamics, 62, 24‐29 [http://dx.doi.org/10.1016/j.jog.2011.10.003 doi:10.1016/j.jog.2011.10.003]