Menu

Javascript is not activated in your browser. This website needs javascript activated to work properly.
You are here

Effect of climate dataset selection on simulations of terrestrial GPP: Highest uncertainty for tropical regions

Author:
  • Zhendong Wu
  • Niklas Boke Olén
  • Rasmus Fensholt
  • Jonas Ardö
  • Lars Eklundh
  • Veiko Lehsten
Publishing year: 2018-06-21
Language: English
Pages:
Publication/Series: PLoS ONE
Volume: 13
Issue: 6
Document type: Journal article
Publisher: Public Library of Science

Abstract english

Biogeochemical models use meteorological forcing data derived with different approaches(e.g. based on interpolation or reanalysis of observation data or a hybrid hereof) to simulateecosystem processes such as gross primary productivity (GPP). This study assesses theimpact of different widely used climate datasets on simulated gross primary productivity andevaluates the suitability of them for reproducing the global and regional carbon cycle asmapped from independent GPP data. We simulate GPP with the biogeochemical modelLPJ-GUESS using six historical climate datasets (CRU, CRUNCEP, ECMWF, NCEP,PRINCETON, and WFDEI). The simulated GPP is evaluated using an observation-basedGPP product derived from eddy covariance measurements in combination with remotelysensed data. Our results show that all datasets tested produce relatively similar GPP simulationsat a global scale, corresponding fairly well to the observation-based data with a differencebetween simulations and observations ranging from -50 to 60 g m-2 yr-1. However, allsimulations also show a strong underestimation of GPP (ranging from -533 to -870 g m-2 yr-1)and low temporal agreement (r < 0.4) with observations over tropical areas. As the shortwaveradiation for tropical areas was found to have the highest uncertainty in the analyzed historicalclimate datasets, we test whether simulation results could be improved by a correction ofthe tested shortwave radiation for tropical areas using a new radiation product from the InternationalSatellite Cloud Climatology Project (ISCCP). A large improvement (up to 48%) insimulated GPP magnitude was observed with bias corrected shortwave radiation, as well asan increase in spatio-temporal agreement between the simulated GPP and observationbasedGPP. This study conducts a spatial inter-comparison and quantification of the performancesof climate datasets and can thereby facilitate the selection of climate forcing dataover any given study area for modelling purposes.

Keywords

  • Physical Geography
  • Climate datasets selection
  • Global carbon cycle
  • Ecosystem modelling
  • GPP
  • LPJ-GUESS
  • Eddy covariance flux
  • ISCCP

Other

Published
  • ISSN: 1932-6203
E-mail: lars [dot] eklundh [at] nateko [dot] lu [dot] se

Professor

Dept of Physical Geography and Ecosystem Science

+46 46 222 96 55

454

16

Teaching staff

Dept of Physical Geography and Ecosystem Science

16

Department of Physical Geography and Ecosystem Science
Lund University
Sölvegatan 12
S-223 62 Lund
Sweden

Processing of personal data

Accessibility statement