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.

Data sets

SoilGrids1km - Global Soil Information Based on Automated Mapping T. Hengl, J. M. de Jesus, R. A. MacMillan, N. H. Batjes, G. B. M. Heuvelink, E. Ribeiro, et al. https://doi.org/10.1371/journal.pone.0105992

SoilGrids250m: Global gridded soil information based on machine learning T. Hengl, J. Mendes de Jesus, G. B. M. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda, A. Blagotić, W. Shangguan, M. N. Wright, X. Geng, B. Bauer-Marschallinger, M. A. Guevara, R. Vargas, R. A. MacMillan, N. H. Batjes, J. G. B. Leenaars, E. Ribeiro, I. Wheeler, S. Mantel, and B. Kempen, https://doi.org/10.1371/journal.pone.0169748

New generation of hydraulic pedotransfer functions for Europe B. Tóth, M. Weynants, A. Nemes, A. Makó,G. Bilas, and G. Tóth https://doi.org/10.1111/ejss.12192

ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000--2001 M. Friedl, A. Strahler, and J. Hodges https://doi.org/10.3334/ORNLDAAC/968

NLDAS Primary Forcing Data L4 Hourly 0.125 x 0.125 degree Y. Xia and NCEP/EMC https://doi.org/10.5067/6j5lhhohzhn4

IFS Documentation CY46R1 ECMWF https://doi.org/10.24381/cds.bd0915c6

Model code and software

Multiscale Parameter Regionalization tool -MPR v. 1.0 Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego https://doi.org/10.5281/zenodo.4650513

marshallward/f90nml Marshall Ward, HoWol76, Reno, James Penn, Daniel S. Katz, jenssss, Huziy Oleksandr, Martin Dix, Dalon Work, naught101, Andrew Kiss, barpaum, Maik Riechert, Michael Lamparski, Pascal Hebbeker, and Warrick Ball https://doi.org/10.5281/zenodo.4768748

FORD Christopher MacMackin https://doi.org/10.5281/zenodo.1422473

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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.