Submitted as: model description paper 26 May 2021

Submitted as: model description paper | 26 May 2021

Review status: this preprint is currently under review for the journal GMD.

MPR 1.0: A stand-alone Multiscale Parameter Regionalization Tool for Improved Parameter Estimation of Land Surface Models

Robert Schweppe1,2, Stephan Thober1, Matthias Kelbling1, Rohini Kumar1, Sabine Attinger1,2, and Luis Samaniego1 Robert Schweppe et al.
  • 1Helmholtz-Centre for Environmental Research - UFZ, Permoserstraße 15, 04315 Leipzig, Germany
  • 2Institute of Earth and Environmental Science, University of Potsdam - Karl-Liebknecht-Str. 24–25 14476, Potsdam-Golm, Germany

Abstract. Distributed environmental models such as land surface models (LSM) require model parameters in each spatial modelling unit (e.g. grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimen- sionality of parameter space in these models is to use regularization techniques. One such highly efficient technique is the Multiscale Parameter Regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of netCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model mHM ( By using this tool for the generation of continental-scale soil hydraulic param- eters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.

Robert Schweppe et al.

Status: open (until 21 Jul 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Robert Schweppe et al.

Data sets

Workflow to reproduce the figures of the manuscript Robert Schweppe

Model code and software

MPR src code Robert Schweppe, Stephan Thober

Robert Schweppe et al.


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Short summary
The stand-alone Multiscale Parameter Regionalization (MPR) tool enables environmental modellers to efficiently estimate model parameters with high-resolution datasets. It flexibly ingests these datasets by user-defined data-parameter relationships and rescales them to given model resolutions. Especially land-surface models benefit from MPR through increased transparency and flexibility in modelling decisions. Thus, MPR empowers more sound and robust simulations of the Earth system.