Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year
    4.890
  • CiteScore value: 4.49 CiteScore
    4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 51 Scimago H
    index 51
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.
Related authors  
Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277-301, https://doi.org/10.5194/hess-23-277-2019,https://doi.org/10.5194/hess-23-277-2019, 2019
Short summary
Is high-resolution inverse characterization of heterogeneous river bed hydraulic conductivities needed and possible?
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3795-3813, https://doi.org/10.5194/hess-17-3795-2013,https://doi.org/10.5194/hess-17-3795-2013, 2013
Related subject area  
Climate and Earth System Modeling
The Brazilian Earth System Model ocean–atmosphere (BESM-OA) version 2.5: evaluation of its CMIP5 historical simulation
Sandro F. Veiga, Paulo Nobre, Emanuel Giarolla, Vinicius Capistrano, Manoel Baptista Jr., André L. Marquez, Silvio Nilo Figueroa, José Paulo Bonatti, Paulo Kubota, and Carlos A. Nobre
Geosci. Model Dev., 12, 1613-1642, https://doi.org/10.5194/gmd-12-1613-2019,https://doi.org/10.5194/gmd-12-1613-2019, 2019
Short summary
The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6
Tongwen Wu, Yixiong Lu, Yongjie Fang, Xiaoge Xin, Laurent Li, Weiping Li, Weihua Jie, Jie Zhang, Yiming Liu, Li Zhang, Fang Zhang, Yanwu Zhang, Fanghua Wu, Jianglong Li, Min Chu, Zaizhi Wang, Xueli Shi, Xiangwen Liu, Min Wei, Anning Huang, Yaocun Zhang, and Xiaohong Liu
Geosci. Model Dev., 12, 1573-1600, https://doi.org/10.5194/gmd-12-1573-2019,https://doi.org/10.5194/gmd-12-1573-2019, 2019
Short summary
Fldgen v1.0: an emulator with internal variability and space–time correlation for Earth system models
Robert Link, Abigail Snyder, Cary Lynch, Corinne Hartin, Ben Kravitz, and Ben Bond-Lamberty
Geosci. Model Dev., 12, 1477-1489, https://doi.org/10.5194/gmd-12-1477-2019,https://doi.org/10.5194/gmd-12-1477-2019, 2019
Short summary
Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century
Matthew J. Gidden, Keywan Riahi, Steven J. Smith, Shinichiro Fujimori, Gunnar Luderer, Elmar Kriegler, Detlef P. van Vuuren, Maarten van den Berg, Leyang Feng, David Klein, Katherine Calvin, Jonathan C. Doelman, Stefan Frank, Oliver Fricko, Mathijs Harmsen, Tomoko Hasegawa, Petr Havlik, Jérôme Hilaire, Rachel Hoesly, Jill Horing, Alexander Popp, Elke Stehfest, and Kiyoshi Takahashi
Geosci. Model Dev., 12, 1443-1475, https://doi.org/10.5194/gmd-12-1443-2019,https://doi.org/10.5194/gmd-12-1443-2019, 2019
Short summary
HOMMEXX 1.0: a performance-portable atmospheric dynamical core for the Energy Exascale Earth System Model
Luca Bertagna, Michael Deakin, Oksana Guba, Daniel Sunderland, Andrew M. Bradley, Irina K. Tezaur, Mark A. Taylor, and Andrew G. Salinger
Geosci. Model Dev., 12, 1423-1441, https://doi.org/10.5194/gmd-12-1423-2019,https://doi.org/10.5194/gmd-12-1423-2019, 2019
Short summary
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.
Ashby, S. and Falgout, R.: A parallel multigrid preconditioned conjugate gradient algorithm for groundwater flow simulations, Nucl. Sci. Eng., 124, 145–159, 1996.
Bailey, R. T. and Baù, D.: Estimating geostatistical parameters and spatially-variable hydraulic conductivity within a catchment system using an ensemble smoother, Hydrol. Earth Syst. Sci., 16, 287–304, https://doi.org/10.5194/hess-16-287-2012, 2012.
Publications Copernicus
Download
Short summary
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...
Citation