Ability of the land surface model ISBA‐A‐gs to simulate leaf area index at the global scale: Comparison with satellites products

Gibelin, Anne-Laure; Calvet, Jean‐Christophe; Roujean, Jean‐Louis; Jarlan, Lionel; Los, S.O.

doi:10.1029/2005jd006691

Cited by 136 publications

(198 citation statements)

References 71 publications

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“…Over savannah, they are in phase with MODIS whereas CYCLOPES shows a LAI peak one month earlier. This delay between CTESSEL and the satellite products has also been observed by Gibelin et al [2006] who evaluate ISBA-a-gs (from which the photosynthesis and growth modules are taken) at the global scale. The decrease of LAI after the end of the rainy season is quicker for CYCLOPES than for MODIS.…”

Section: Ctessel Against the Satellite-derived Lai And Bias Correctionmentioning

confidence: 90%

“…The photosynthesis parameters of the A-gs module (g c , N a , e, f, etc. ; see Appendix A) are taken from Gibelin et al [2006] who describe the implementation at the global scale of ISBA-A-gs and validate the global simulation from satellite observations. In addition, ECOCLIMAP provides with a climatology of monthly Leaf Area Index that can be used to forced the LAI in CTESSEL by shunting the growth module.…”

Section: Global Net Ecosystem Exchange Data Sets: Sib and Casamentioning

confidence: 99%

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Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa

et al. 2008

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[1] A new version of the land surface model of the European Centre for Medium-Range Weather Forecasts (Carbon-TESSEL, or CTESSEL) includes a vegetation growth model. This study describes a leaf area index (LAI) data assimilation system (LDAS) based on CTESSEL and satellite LAI for operational Net Ecosystem Exchange (NEE) predictions. The LDAS is evaluated over West Africa. A preliminary experiment shows a significant impact of the LAI on the CTESSEL NEE. The LAI is compared to two satellite products: the predicted annual cycle is delayed over the Sahel and savannah, and the LAI values differ from the satellite products. Preliminary to their use in the LDAS, the LAI products are rescaled to the CTESSEL predictions. The LDAS simulations are confronted to measurements of biomass and LAI for a site in Mali. The LAI analysis is shown to improve the predicted biomass and the annual cycles of the water (latent heat flux, or LE) and carbon (NEE) fluxes. Afterward, the LDAS is run over West Africa with the Moderate-Resolution Imaging Spectroradiometer products (2001)(2002)(2003)(2004)(2005). The analysis of LAI shows a limited impact on LE, but it impacts strongly on NEE. Finally, the CTESSEL NEE are compared to two other models' outputs (simple biosphere (SIB) and Carnegie-Ames-Stanford (CASA)). The order of magnitude of the three data sets agrees well, and the shift in annual cycle of CTESSEL is reduced by the LDAS. It is concluded that a LAI data assimilation system is essential for NEE prediction at seasonal and interannual timescales, while a LAI satellite-based climatology may be sufficient for accurate LE predictions.

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Section: Ctessel Against the Satellite-derived Lai And Bias Correctionmentioning

confidence: 90%

Section: Global Net Ecosystem Exchange Data Sets: Sib and Casamentioning

confidence: 99%

Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa

et al. 2008

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“…ISBA-A-gs calculates interactively the leaf biomass and the LAI, using a simple growth model (Calvet et al, 1998). Gibelin et al (2006) and Brut et al (2009) showed that ISBA-A-gs provides reasonable LAI values at regional and global scale under various environmental conditions. The ecosystem respiration (Reco) is described in the model as a basal rate modulated as a function of soil moisture and soil temperature (Albergel et al, 2010b).…”

Section: The Isba-a-gs Model Within Surfexmentioning

confidence: 99%

“…A typical seasonal cycle simulated by ORCHIDEE presents (1) a dormancy phase, (2) a sharp increase of LAI over a few days at the leaf onset, (3) a more gradual growth governed by photosynthesis, until a maximum LAI value has been reached, (4) stable maximum LAI values until the senescence date has been reached, (5) a senescence phase presenting an exponential decline of LAI. The ISBA-A-gs growth model currently used in the SURFEX modelling platform (http://www.cnrm.meteo.fr/surfex/) is described in Gibelin et al (2006). No specific phenology model is used, as the vegetation growth and senescence are entirely driven by photosynthesis.…”

Section: Main Differences Between Isba-a-gs and Orchideementioning

confidence: 99%

“…Over land, SURFEX includes ISBA-A-gs, a CO 2 -responsive LSM (Calvet et al, 1998(Calvet et al, , 2004Gibelin et al, 2006;Calvet et al, 2008) able to simulate the diurnal cycle of carbon and water vapour fluxes, together with LAI and soil moisture. This model accounts for different feedbacks in response to long-term changes in atmospheric concentration of CO 2 , and provides a representation of photosynthesis enhancement and transpiration reduction (fertilization and reduced transpiration effects, respectively).…”

Section: The Isba-a-gs Model Within Surfexmentioning

confidence: 99%

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Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

et al. 2012

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Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994-2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-Ags. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70 %), while providing lower transpiration estimates (−8 %).

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Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

et al. 2017

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Realistic projection of future climate‐carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m−2 yr−1), most models produced higher NPP (309 ± 12 g C m−2 yr−1) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower‐based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m−2 yr−1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.

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Ability of the land surface model ISBA‐A‐gs to simulate leaf area index at the global scale: Comparison with satellites products

Cited by 136 publications

References 71 publications

Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa

Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

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