Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4233-2023
https://doi.org/10.5194/gmd-16-4233-2023
Development and technical paper
 | 
27 Jul 2023
Development and technical paper |  | 27 Jul 2023

Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses

Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines

Related authors

Water and energy budgets over hydrological basins on short and long timescales
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023,https://doi.org/10.5194/hess-27-1723-2023, 2023
Short summary

Related subject area

Climate and Earth system modeling
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025,https://doi.org/10.5194/gmd-18-2443-2025, 2025
Short summary
TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025,https://doi.org/10.5194/gmd-18-2427-2025, 2025
Short summary
The ensemble consistency test: from CESM to MPAS and beyond
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025,https://doi.org/10.5194/gmd-18-2349-2025, 2025
Short summary
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025,https://doi.org/10.5194/gmd-18-2161-2025, 2025
Short summary
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025,https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary

Cited articles

Balmaseda, M. A., Mogensen, K., and Weaver, A. T.: Evaluation of the ECMWF ocean reanalysis system ORAS4, Q. J. Roy. Meteor. Soc., 139, 1132–1161, 2013. a
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001. a, b
Bocquet, M. and Sakov, P.: An iterative ensemble Kalman smoother, Q. J. Roy. Meteor. Soc., 140, 1521–1535, https://doi.org/10.1002/qj.2236, 2014. a, b
Buizza, R., Poli, P., Rixen, M., Alonso-Balmaseda, M., Bosilovich, M. G., Brönnimann, S., Compo, G. P., Dee, D. P., Desiato, F., Doutriaux-Boucher, M., Fujiwara, M., Kaiser-Weiss, A. K., Kobayashi, S., Liu, Z., Masina, S., Mathieu, P.-P., Rayner, N., Richter, C., Seneviratne, S. I., Simmons, A. J., Thépaut, J.-N., Auger, J. D., Bechtold, M., Berntell, E., Dong, B., Kozubek, M., Sharif, K., Thomas, C., Schimanke, S., Storto, A., Tuma, M., Välisuo, I., and Vaselali, A.: Advancing Global and Regional Reanalyses, B. Am. Meteorol. Soc., 99, ES139–ES144, https://doi.org/10.1175/BAMS-D-17-0312.1, 2018. a
Burgers, G., Van Leeuwen, P. J., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, 1998. a
Download
Short summary
Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Share