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Title: A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Journal Article · · Geoscientific Model Development (Online)
 [1];  [2];  [1];  [1];  [3];  [4];  [1];  [1];  [1];  [1];  [1];  [2]
  1. Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France)
  2. Noveltis, Ramonville-Saint-Agne (France)
  3. Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France); Univ. of Melbourne, VIC, Melbourne (Australia)
  4. Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France); IMASL-CONICET/Univ. Nacional de San Luis, San Luis (Argentina)
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Here, large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO2, using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr-1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.

Research Organization:
Oregon State Univ., Corvallis, OR (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
FG02-04ER63917; FG02-04ER63911
OSTI ID:
1361538
Journal Information:
Geoscientific Model Development (Online), Vol. 9, Issue 9; ISSN 1991-9603
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 61 works
Citation information provided by
Web of Science

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Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion journal February 2020
Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination journal October 2018
Three decades of simulated global terrestrial carbon fluxes from a data assimilation system confronted with different periods of observations journal January 2019
Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model journal January 2019
Constraining estimates of terrestrial carbon uptake: new opportunities using long‐term satellite observations and data assimilation journal August 2019
Consistent assimilation of multiple data streams in a carbon cycle data assimilation system journal January 2016
Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model journal June 2018
Improving Estimates of Gross Primary Productivity by Assimilating Solar‐Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process‐Based SIF Model journal November 2019
Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems journal January 2017
Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model journal May 2019
Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects journal February 2019
Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation journal November 2018
Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb) journal January 2018
Utilisation des traits fonctionnels au sein d'un modèle global de végétation : analyse de trois approches complémentaires axées sur les écosystèmes forestiers text January 2016
Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH journal January 2019
Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data journal January 2018
Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates journal January 2018
Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: model description and information content journal January 2018
Data Assimilation using an Ensemble of Models: A hierarchical approach journal February 2017
Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems journal January 2017
Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles posted_content January 2018
Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles journal January 2018

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