Preprints
https://doi.org/10.5194/gmd-2022-291
https://doi.org/10.5194/gmd-2022-291
Submitted as: model description paper
 | 
05 Jan 2023
Submitted as: model description paper |  | 05 Jan 2023
Status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

LandInG 1.0: A toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources

Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff

Abstract. We present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEM) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology and crop growth model LPJmL (Lund-Potsdam-Jena with managed Land).

The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent, so that users can make their own decisions on how to resolve these, should they not be content with the default assumptions made here.

As an example, we use the toolbox to create input datasets at 5 and 30 arc minutes spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent or similar. Also, new data sources or new versions of existing data become available continuously and the toolbox approach allows for incorporating new data to stay up-to-date.

Sebastian Ostberg et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on gmd-2022-291', Jinfeng Chang, 24 Jan 2023
  • RC1: 'Comment on gmd-2022-291', Jinfeng Chang, 24 Jan 2023
  • RC2: 'Comment on gmd-2022-291', Anonymous Referee #2, 09 Feb 2023
  • RC3: 'Comment on gmd-2022-291', Anonymous Referee #3, 17 Feb 2023
  • AC1: 'Response to referee comments on gmd-2022-291', Sebastian Ostberg, 31 Mar 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on gmd-2022-291', Jinfeng Chang, 24 Jan 2023
  • RC1: 'Comment on gmd-2022-291', Jinfeng Chang, 24 Jan 2023
  • RC2: 'Comment on gmd-2022-291', Anonymous Referee #2, 09 Feb 2023
  • RC3: 'Comment on gmd-2022-291', Anonymous Referee #3, 17 Feb 2023
  • AC1: 'Response to referee comments on gmd-2022-291', Sebastian Ostberg, 31 Mar 2023

Sebastian Ostberg et al.

Model code and software

Code for LandInG v.1.0 sample application at 5 arc-minute and 30 arc-minute resolution Ostberg, Sebastian https://doi.org/10.5281/zenodo.7371650

Sebastian Ostberg et al.

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Short summary
We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent, so that users can make their own decisions on how to resolve these, should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.