Terrestrial Biosphere

2010 ◽  
pp. 345-365
Author(s):  
Zoltán Somogyi ◽  
György Borka ◽  
Katalin Lovas ◽  
József Zsembeli
Keyword(s):  
Terrestrial Biosphere

scholarly journals Carbon balance of the terrestrial biosphere in the Twentieth Century: Analyses of CO2, climate and land use effects with four process-based ecosystem models

2001 ◽  
Vol 15 (1) ◽  
pp. 183-206 ◽  
Author(s):  
A. D. McGuire ◽  
S. Sitch ◽  
J. S. Clein ◽  
R. Dargaville ◽  
G. Esser ◽  
...  
Keyword(s):  
Land Use ◽  
Twentieth Century ◽  
Carbon Balance ◽  
Ecosystem Models ◽  
Terrestrial Biosphere ◽  
Land Use Effects

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 Constraining a land surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System

2016 ◽  
Author(s):  
G. J. Schürmann ◽  
T. Kaminski ◽  
C. Köstler ◽  
N. Carvalhais ◽  
M. Voßbeck ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Land Surface ◽  
Data Stream ◽  
Atmospheric Co2 ◽  
Surface Model ◽  
Terrestrial Biosphere ◽  
Multiple Observations ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the land surface scheme of the MPI-Earth System Model v1 (JSBACH). The simulated terrestrial biosphere processes (phenology and carbon balance) were constrained by observations of the fraction of photosynthetically active radiation (TIP-FAPAR product) and by observations of atmospheric CO2 at a global set of monitoring stations for the years 2005–2009. The system successfully, and computationally efficiently, improved average foliar area and northern extra-tropical seasonality of foliar area when constrained by TIP-FAPAR. Global net and gross carbon fluxes were improved when constrained by atmospheric CO2, although the system tended to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, therefore overall increasing the appropriateness of the resultant parameter values and biosphere dynamics. Our study thus highlights the role of the TIP-FAPAR product in stabilising the underdetermined atmospheric inversion problem and demonstrates the value of multiple-data stream assimilation for the simulation of terrestrial biosphere dynamics. The constraint on regional gross and net CO2 flux patterns is limited through the parametrisation of the biosphere model. We expect improvement on that aspect through a refined initialisation strategy and inclusion of further biosphere observations as constraints.

scholarly journals Deglacial carbon cycle changes observed in a compilation of 127 benthic <i>δ</i><sup>13</sup>C time series (20–6 ka)

2018 ◽  
Vol 14 (8) ◽  
pp. 1229-1252 ◽  
Author(s):  
Carlye D. Peterson ◽  
Lorraine E. Lisiecki
Keyword(s):  
Time Series ◽  
Carbon Cycle ◽  
Carbon Storage ◽  
Large Scale ◽  
Deep Ocean ◽  
Atmospheric Co2 ◽  
Last Deglaciation ◽  
Terrestrial Biosphere ◽  
Spatial Coverage ◽  
Ocean Carbon

Abstract. We present a compilation of 127 time series δ13C records from Cibicides wuellerstorfi spanning the last deglaciation (20–6 ka) which is well-suited for reconstructing large-scale carbon cycle changes, especially for comparison with isotope-enabled carbon cycle models. The age models for the δ13C records are derived from regional planktic radiocarbon compilations (Stern and Lisiecki, 2014). The δ13C records were stacked in nine different regions and then combined using volume-weighted averages to create intermediate, deep, and global δ13C stacks. These benthic δ13C stacks are used to reconstruct changes in the size of the terrestrial biosphere and deep ocean carbon storage. The timing of change in global mean δ13C is interpreted to indicate terrestrial biosphere expansion from 19–6 ka. The δ13C gradient between the intermediate and deep ocean, which we interpret as a proxy for deep ocean carbon storage, matches the pattern of atmospheric CO2 change observed in ice core records. The presence of signals associated with the terrestrial biosphere and atmospheric CO2 indicates that the compiled δ13C records have sufficient spatial coverage and time resolution to accurately reconstruct large-scale carbon cycle changes during the glacial termination.

scholarly journals The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs

2013 ◽  
Vol 10 (6) ◽  
pp. 4137-4177 ◽  
Author(s):  
R. Pavlick ◽  
D. T. Drewry ◽  
K. Bohn ◽  
B. Reu ◽  
A. Kleidon
Keyword(s):  
Functional Diversity ◽  
Land Surface ◽  
Grid Cell ◽  
Surface Fluxes ◽  
Growth Strategies ◽  
Vegetation Model ◽  
Terrestrial Biosphere ◽  
Dynamic Global Vegetation Model ◽  
Trade Offs ◽  
Global Vegetation

Abstract. Terrestrial biosphere models typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical plant functional types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) as a new approach to terrestrial biosphere modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly generated plant growth strategies, each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a strategy is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other strategies. The biogeochemical fluxes and land surface properties of the individual strategies are aggregated to the grid-cell scale using a mass-based weighting scheme. We evaluate the simulated global biogeochemical patterns against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favourably with other state-of-the-art global vegetation models. We also evaluate the simulated patterns of functional diversity and the sensitivity of the JeDi-DGVM modelling approach to the number of sampled strategies. Altogether, the results demonstrate the parsimonious and flexible nature of a functional trade-off approach to global vegetation modelling, i.e. it can provide more types of testable outputs than standard PFT-based approaches and with fewer inputs. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.

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 A novel bias correction methodology for climate impact simulations

2015 ◽  
Vol 6 (2) ◽  
pp. 1999-2042 ◽  
Author(s):  
S. Sippel ◽  
F. E. L. Otto ◽  
M. Forkel ◽  
M. R. Allen ◽  
B. P. Guillod ◽  
...  
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Terrestrial Ecosystem ◽  
Climate Impact ◽  
Correlation Structure ◽  
Terrestrial Biosphere ◽  
Terrestrial Ecosystem Model ◽  
Multivariate Correlation ◽  
Impact Simulations

Abstract. Understanding, quantifying and attributing the impacts of extreme weather and climate events in the terrestrial biosphere is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. In this study, we introduce a novel, resampling-based bias correction scheme that fully preserves the physical consistency and multivariate correlation structure of the model output. This procedure strongly improves the representation of climatic extremes and variability in a large regional climate model ensemble (HadRM3P, climateprediction.net/weatherathome), which is illustrated for summer extremes in temperature and rainfall over Central Europe. Moreover, we simulate biosphere–atmosphere fluxes of carbon and water using a terrestrial ecosystem model (LPJmL) driven by the bias corrected climate forcing. The resampling-based bias correction yields strongly improved statistical distributions of carbon and water fluxes, including the extremes. Our results thus highlight the importance to carefully consider statistical moments beyond the mean for climate impact simulations. In conclusion, the present study introduces an approach to alleviate climate model biases in a physically consistent way and demonstrates that this yields strongly improved simulations of climate extremes and associated impacts in the terrestrial biosphere. A wider uptake of our methodology by the climate and impact modelling community therefore seems desirable for accurately quantifying past, current and future extremes.

scholarly journals Photosynthetic capacity exhibits diurnal variation, implications for terrestrial biosphere models and gas exchange measurements

2020 ◽  
Author(s):  
Joseph Stinziano ◽  
Marissa Harjoe ◽  
Cassaundra Roback ◽  
Nellie Toliver ◽  
Alistair Rogers ◽  
...  
Keyword(s):  
Gas Exchange ◽  
Diurnal Variation ◽  
Photosynthetic Capacity ◽  
Terrestrial Biosphere
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