scholarly journals Satellite Leaf Area Index: Global Scale Analysis of the Tendencies Per Vegetation Type Over the Last 17 Years

2018 ◽  
Vol 10 (3) ◽  
pp. 424 ◽  
Author(s):  
Simon Munier ◽  
Dominique Carrer ◽  
Carole Planque ◽  
Fernando Camacho ◽  
Clément Albergel ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Type ◽  
Global Scale ◽  
Scale Analysis ◽  
Area Index

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

2006 ◽  
Vol 111 (D18) ◽  
Author(s):  
Anne-Laure Gibelin ◽  
Jean-Christophe Calvet ◽  
Jean-Louis Roujean ◽  
Lionel Jarlan ◽  
Sietse O. Los
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Surface Model ◽  
Area Index

scholarly journals Examining the link between vegetation leaf area and land-atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

2020 ◽  
Author(s):  
Anne J. Hoek van Dijke ◽  
Kaniska Mallick ◽  
Martin Schlerf ◽  
Miriam Machwitz ◽  
Martin Herold ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Primary Productivity ◽  
Large Scale ◽  
Vegetation Type ◽  
Carbon Fluxes ◽  
Surface Fluxes ◽  
Energy Fluxes ◽  
Area Index ◽  
Vegetation Control

Abstract. Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve climate models and the extrapolation of ground-based water, energy, and carbon fluxes. We aim to study the large-scale link between vegetation and surface fluxes by combining MODIS leaf area index with flux tower measurements of water (latent heat), energy (sensible heat), and carbon (gross primary productivity and net ecosystem exchange). We show that the correlation between leaf area index and water and energy fluxes depends on vegetation and aridity. In water-limited conditions, the link between vegetation and water and energy fluxes is strong, which is in line with a strong stomatal or vegetation control found in earlier studies. In energy-limited forest we found no vegetation control on water and energy fluxes. In contrast to water and energy fluxes, we found a strong correlation between leaf area index and gross primary productivity that was independent of vegetation type and aridity index. This study provides insight in the large-scale link between vegetation and surface fluxes. The study indicates that for modelling or extrapolating large-scale surface fluxes, LAI can be useful in savanna and grassland, but only of limited use in deciduous broadleaf forest and evergreen needleleaf forest.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (13) ◽  
pp. 5897-5912 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
New Information

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (2) ◽  
pp. 3941-3982 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
Model Aircraft

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements.

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