Impacts of the 2012‐2015 Californian Drought on Carbon, Water and Energy Fluxes in Californian Sierras: Results from an Imaging Spectrometry‐Constrained Terrestrial Biosphere Model

2021 ◽  
Author(s):  
S. Alexander Antonarakis ◽  
Stacy A. Bogan ◽  
Michael L. Goulden ◽  
Paul R. Moorcroft
Keyword(s):  
Energy Fluxes ◽  
Terrestrial Biosphere ◽  
Imaging Spectrometry ◽  
Biosphere Model

scholarly journals Optimizing Phenology Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Net CO2 Flux Inter-Annual Variability

2021 ◽  
Author(s):  
Kashif Mahmud ◽  
Joel Biederman ◽  
Russ Scott ◽  
Marcy Litvak ◽  
Thomas Kolb ◽  
...  
Keyword(s):  
Co2 Flux ◽  
Terrestrial Biosphere ◽  
Annual Variability ◽  
Biosphere Model

scholarly journals Using satellite data to improve the leaf phenology of a global terrestrial biosphere model

2015 ◽  
Vol 12 (23) ◽  
pp. 7185-7208 ◽  
Author(s):  
N. MacBean ◽  
F. Maignan ◽  
P. Peylin ◽  
C. Bacour ◽  
F.-M. Bréon ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Biosphere ◽  
Modis Ndvi ◽  
Growing Season Length ◽  
Median Correlation ◽  
Temperate Deciduous ◽  
Correct Representation ◽  
Biosphere Model ◽  
Deciduous Plant

Abstract. Correct representation of seasonal leaf dynamics is crucial for terrestrial biosphere models (TBMs), but many such models cannot accurately reproduce observations of leaf onset and senescence. Here we optimised the phenology-related parameters of the ORCHIDEE TBM using satellite-derived Normalized Difference Vegetation Index data (MODIS NDVI v5) that are linearly related to the model fAPAR. We found the misfit between the observations and the model decreased after optimisation for all boreal and temperate deciduous plant functional types, primarily due to an earlier onset of leaf senescence. The model bias was only partially reduced for tropical deciduous trees and no improvement was seen for natural C4 grasses. Spatial validation demonstrated the generality of the posterior parameters for use in global simulations, with an increase in global median correlation of 0.56 to 0.67. The simulated global mean annual gross primary productivity (GPP) decreased by ~ 10 PgC yr−1 over the 1990–2010 period due to the substantially shortened growing season length (GSL – by up to 30 days in the Northern Hemisphere), thus reducing the positive bias and improving the seasonal dynamics of ORCHIDEE compared to independent data-based estimates. Finally, the optimisations led to changes in the strength and location of the trends in the simulated vegetation productivity as represented by the GSL and mean annual fraction of absorbed photosynthetically active radiation (fAPAR), suggesting care should be taken when using un-calibrated models in attribution studies. We suggest that the framework presented here can be applied for improving the phenology of all global TBMs.

scholarly journals Improving Estimates of Gross Primary Productivity by Assimilating Solar‐Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process‐Based SIF Model

2019 ◽  
Vol 124 (11) ◽  
pp. 3281-3306 ◽  
Author(s):  
C. Bacour ◽  
F. Maignan ◽  
N. MacBean ◽  
A. Porcar‐Castell ◽  
J. Flexas ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Terrestrial Biosphere ◽  
Satellite Retrievals ◽  
Biosphere Model

scholarly journals Terrestrial biosphere model performance for inter-annual variability of land-atmosphere CO2 exchange

2012 ◽  
Vol 18 (6) ◽  
pp. 1971-1987 ◽  
Author(s):  
T.F. Keenan ◽  
Ian Baker ◽  
Alan Barr ◽  
Philippe Ciais ◽  
Ken Davis ◽  
...  
Keyword(s):  
Model Performance ◽  
Co2 Exchange ◽  
Terrestrial Biosphere ◽  
Annual Variability ◽  
Biosphere Model

Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide

2017 ◽  
Vol 203 ◽  
pp. 109-124 ◽  
Author(s):  
T. Kaminski ◽  
M. Scholze ◽  
M. Vossbeck ◽  
W. Knorr ◽  
M. Buchwitz ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Remotely Sensed ◽  
Terrestrial Biosphere ◽  
Atmospheric Carbon ◽  
Biosphere Model
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