Articles | Volume 15, issue 2
Geosci. Model Dev., 15, 859–882, 2022
https://doi.org/10.5194/gmd-15-859-2022
Geosci. Model Dev., 15, 859–882, 2022
https://doi.org/10.5194/gmd-15-859-2022
Model description paper
31 Jan 2022
Model description paper | 31 Jan 2022

MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models

Robert Schweppe et al.

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Cited articles

Adams, S. V., Ford, R. W., Hambley, M., Hobson, J. M., Kavčič, I., Maynard, C. M., Melvin, T., Müller, E. H., Mullerworth, S., Porter, A. R., Rezny, M., Shipway, B. J., and Wong, R.: LFRic: Meeting the challenges of scalability and performance portability in Weather and Climate models, J. Parallel Distr. Com., 132, 383–396, https://doi.org/10.1016/j.jpdc.2019.02.007, 2019. a
Andre, B., Kluzek, E., and Sacks, W.: CLM Community Land Model, available at: https://escomp.github.io/ctsm-docs/versions/release-clm5.0/html/index.html (last access: 16 January 2022), 2020. a, b
Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. a, b
Beck, H. E., Dijk, A. I. J. M. v., Roo, A. d., Miralles, D. G., McVicar, T. R., Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of hydrologic model parameters, Water Resour. Res., 52, 3599–3622, https://doi.org/10.1002/2015WR018247, 2016. a, b
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Short summary
The recently released multiscale parameter regionalization (MPR) tool enables environmental modelers to efficiently use extensive datasets for model setups. It flexibly ingests the datasets using user-defined data–parameter relationships and rescales parameter fields to given model resolutions. Modern land surface models especially benefit from MPR through increased transparency and flexibility in modeling decisions. Thus, MPR empowers more sound and robust simulations of the Earth system.