LPJmL4 - A dynamic global vegetation model with managed land - Part 2: Model evaluation

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Sibyll Schaphoff - , Potsdam Institute for Climate Impact Research (Autor:in)
  • Matthias Forkel - , Juniorprofessur für Umweltfernerkundung, Technische Universitat Wien (Autor:in)
  • Christoph Müller - , Potsdam Institute for Climate Impact Research (Autor:in)
  • Jürgen Knauer - , Max Planck Institute for Biogeochemistry (Autor:in)
  • Werner Von Bloh - , Potsdam Institute for Climate Impact Research (Autor:in)
  • Dieter Gerten - , Potsdam Institute for Climate Impact Research, Humboldt-Universität zu Berlin (Autor:in)
  • Jonas Jägermeyr - , Potsdam Institute for Climate Impact Research (Autor:in)
  • Wolfgang Lucht - , Potsdam Institute for Climate Impact Research, Humboldt-Universität zu Berlin (Autor:in)
  • Anja Rammig - , Technische Universität München (Autor:in)
  • Kirsten Thonicke - , Potsdam Institute for Climate Impact Research (Autor:in)
  • Katharina Waha - , Potsdam Institute for Climate Impact Research, Commonwealth Scientific & Industrial Research Organisation (CSIRO) (Autor:in)

Abstract

The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through <a hrefCombining double low line"https://gitlab.pik-potsdam.de/lpjml/LPJmL" targetCombining double low linehttps://gitlab.pik-potsdam.de/lpjml/LPJmL</a>. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.

Details

OriginalspracheEnglisch
Seiten (von - bis)1377-1403
Seitenumfang27
FachzeitschriftGeoscientific model development
Jahrgang11
Ausgabenummer4
PublikationsstatusVeröffentlicht - 12 Apr. 2018
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0003-0363-9697/work/142252084