Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

By Shilong Piao, Stephen Sitch, Philippe Ciais, Pierre Friedlingstein, P. Peylin, Xuhui Wang, Anders Ahlström, A. Anav, J. Canadell, N. Cong and 17 more. Global Change Biology, 2013

758 citations recorded by the source corpus.

Subfields: Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/25d6a09987512e4c4c2e092729abbde6108b3a14

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Citations in the corpus

Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? (2014, background): “Recent model evaluations against experimental data from free air CO2 enrichment (FACE) experiments have shown that terrestrial carbon cycle models generally overestimate the response of gross primary productivity (GPP) to CO2 fertilization (Piao et al., 2013).”
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence (2014, methodology): “We have compared our SIF-based crop GPP estimates with the GPP predicted by ensembles of state-of-the-art data-driven (9) and process-based (28, 29) biogeochemistry models (see SI Appendix, Model-Based GPP Data).”
Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa (2013, neutral): “LPJ-GUESS has been evaluated extensively and exhibits comparable skill to other approaches and models in reproducing observed temporal and spatial variation in large-scale vegetation patterns, productivity and ecosystem–atmosphere carbon exchange (Piao et al., 2013).”
Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study (2015, background): “Moreover, many ESMs poorly simulate key metrics of the present-day terrestrial C cycle such as vegetation and soil C, plant productivity, and C turnover rates, among others (Anav et al 2013, Piao et al 2013, Todd-Brown et al 2013, Carvalhais et al 2014).”
Effect of increasing CO2 on the terrestrial carbon cycle (2014, background): “The median global CO2 effect simulated by the TRENDY models over the 1990–2007 time period is −2.6 ± 1.0.”
Mapping Photosynthesis Solely from Solar-Induced Chlorophyll Fluorescence: A Global, Fine-Resolution Dataset of Gross Primary Production Derived from OCO-2 (2019, methodology): “77 TRENDY [59] 105 BNU-ESM [57] 133 Average from multiple models [60]”
Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms (2016, methodology): “The ML upscaled outputs are also increasingly used to evaluate process-based land surface models (e.g., Anav et al., 2013; Bonan et al., 2011; Ichii et al., 2009; Piao et al., 2013).”
Detection and attribution of vegetation greening trend in China over the last 30 years (2015, methodology): “For example, only two of the five models consider the effect of nitrogen deposition, although there is increasing evidence that nitrogen limitation strongly decreases the CO 2 fertilization effect (Hickler et al., 2008; Norby et al., 2010; Piao et al., 2013 ).”