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Volume 9, issue 4
Geosci. Model Dev., 9, 1341–1360, 2016
https://doi.org/10.5194/gmd-9-1341-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 1341–1360, 2016
https://doi.org/10.5194/gmd-9-1341-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 11 Apr 2016

Model description paper | 11 Apr 2016

TerrSysMP–PDAF (version 1.0): a modular high-performance data assimilation framework for an integrated land surface–subsurface model

Wolfgang Kurtz et al.
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Cited articles  
Anderson, J. L.: An ensemble adjustment Kalman filter for data assimilation, Mon. Weather Rev., 129, 2884–2903, https://doi.org/10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2, 2001.
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and Avellano, A.: The data assimilation research testbed: a community facility, B. Am. Meteorol. Soc., 90, 1283–1296, https://doi.org/10.1175/2009bams2618.1, 2009.
Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 29, 872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006.
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This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library. Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP. Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
This paper describes the development of a modular data assimilation (DA) system for the...
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