scholarly journals Optimization of Terrestrial Ecosystem Model Parameters Using Atmospheric CO2 Concentration Data With the Global Carbon Assimilation System (GCAS)

2017 ◽  
Vol 122 (12) ◽  
pp. 3218-3237 ◽  
Author(s):  
Zhuoqi Chen ◽  
Jing M. Chen ◽  
Shupeng Zhang ◽  
Xiaogu Zheng ◽  
Weiming Ju ◽  
...  
Keyword(s):  
Carbon Assimilation ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Ecosystem Model ◽  
Atmospheric Co2 ◽  
Model Parameters ◽  
Concentration Data ◽  
Terrestrial Ecosystem Model ◽  
Global Carbon ◽  
Assimilation System

scholarly journals A Global Carbon Assimilation System using a modified EnKF assimilation method

2014 ◽  
Vol 7 (5) ◽  
pp. 6519-6547
Author(s):  
S. Zhang ◽  
X. Zheng ◽  
Z. Chen ◽  
B. Dan ◽  
J. M. Chen ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Carbon Assimilation ◽  
Terrestrial Ecosystem ◽  
Carbon Fluxes ◽  
Ecosystem Model ◽  
Atmospheric Co2 ◽  
Forecast Errors ◽  
Global Carbon ◽  
Assimilation System

Abstract. A Global Carbon Assimilation System based on Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 abundance data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is based on the ensemble Kalman filter (EnKF), but with several new developments, including using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is tested in observing system simulation experiments and then used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

scholarly journals A global carbon assimilation system using a modified ensemble Kalman filter

2015 ◽  
Vol 8 (3) ◽  
pp. 805-816 ◽  
Author(s):  
S. Zhang ◽  
X. Zheng ◽  
J. M. Chen ◽  
Z. Chen ◽  
B. Dan ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Carbon Assimilation ◽  
Terrestrial Ecosystem ◽  
Carbon Fluxes ◽  
Ecosystem Model ◽  
Atmospheric Co2 ◽  
Forecast Errors ◽  
Global Carbon ◽  
Assimilation System

Abstract. A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO2 concentration in state vectors, using the ensemble Kalman filter (EnKF) with 1-week assimilation windows, using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results show that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

scholarly journals Optimization of the seasonal cycles of simulated CO<sub>2</sub> flux by fitting simulated atmospheric CO<sub>2</sub> to observed vertical profiles

2009 ◽  
Vol 6 (3) ◽  
pp. 5933-5957 ◽  
Author(s):  
Y. Nakatsuka ◽  
S. Maksyutov
Keyword(s):  
Net Primary Productivity ◽  
Transport Model ◽  
Vertical Mixing ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Model Parameters ◽  
Seasonal Cycles ◽  
Concentration Data ◽  
Near Surface ◽  
Terrestrial Ecosystem Model

Abstract. An inverse of a combination of atmospheric transport and flux models was used to optimize model parameters of the Carnegie-Ames-Stanford Approach (CASA) terrestrial ecosystem model. The method employed in the present study is based on minimizing an appropriate cost function (i.e. the weighted differences between the simulated and observed seasonal cycles of CO2 concentrations). We tried to reduce impacts that the inaccuracy of a vertical mixing in a transport model has on the simulated amplitudes of seasonal cycles of carbon flux by using airborne observations of CO2 vertical profile aggregated to a partial column. Effect of the vertical mixing on optimized NEP was evaluated by carrying out 2 sets of inverse calculations: one with partial-column concentration data from 15 locations and another with near-surface CO2 concentration data from the same 15 locations. We found that the values of simulated growing season net flux (GSNF) and net primary productivity (NPP) are affected by the rate of vertical mixing in a transport model used in the optimization. Optimized GSNF and NPP are higher when optimized with partial column data as compared to the case with near-surface data only due to the weak vertical mixing in the transport model used in this study.

scholarly journals Climate and atmospheric drivers of historical terrestrial carbon uptake in the province of British Columbia, Canada

2014 ◽  
Vol 11 (3) ◽  
pp. 635-649 ◽  
Author(s):  
Y. Peng ◽  
V. K. Arora ◽  
W. A. Kurz ◽  
R. A. Hember ◽  
B. J. Hawkins ◽  
...  
Keyword(s):  
British Columbia ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Ecosystem Model ◽  
Carbon Uptake ◽  
Stem Wood ◽  
Terrestrial Ecosystem Model ◽  
Changing Climate ◽  
Model Response ◽  
Two Factors

Abstract. The impacts of climate change and increasing atmospheric CO2 concentration on the terrestrial uptake of carbon dioxide since 1860 in the Canadian province of British Columbia are estimated using the process-based Canadian Terrestrial Ecosystem Model (CTEM). Model simulations show that these two factors yield an enhanced carbon uptake of around 44 gC m−2 yr−1 (or equivalently 63 gC m−2 yr−1 over the province's forested area), during the 1980s and 1990s, and continuing into the 2000s. About three-quarters of the simulated sink enhancement in our study compared to pre-industrial conditions is attributed to changing climate, and the rest is attributed to increase in CO2 concentration. The model response to changing climate and increasing CO2 is corroborated by comparing simulated stem wood growth rates with ground-based measurements from inventory plots in coastal British Columbia. The simulated sink is not an estimate of the net carbon balance because the effects of harvesting, insect disturbances and land-use change are not considered.

scholarly journals Regional CO<sub>2</sub> fluxes from 2010 to 2015 inferred from GOSAT XCO<sub>2</sub> retrievals using a new version of the Global Carbon Assimilation System

2021 ◽  
Vol 21 (3) ◽  
pp. 1963-1985
Author(s):  
Fei Jiang ◽  
Hengmao Wang ◽  
Jing M. Chen ◽  
Weimin Ju ◽  
Xiangjun Tian ◽  
...  
Keyword(s):  
Carbon Assimilation ◽  
Carbon Fluxes ◽  
Atmospheric Co2 ◽  
Interannual Variations ◽  
Carbon Sinks ◽  
Area Index ◽  
Spatial Coverage ◽  
The Impact ◽  
Global Carbon ◽  
Assimilation System

Abstract. Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) could help to improve carbon flux estimation due to their good spatial coverage. In this study, in order to assimilate the GOSAT (Greenhouse Gases Observing Satellite) XCO2 retrievals, the Global Carbon Assimilation System (GCAS) is upgraded with new assimilation algorithms, procedures, a localization scheme, and a higher assimilation parameter resolution. This upgraded system is referred to as GCASv2. Based on this new system, the global terrestrial ecosystem (BIO) and ocean (OCN) carbon fluxes from 1 May 2009 to 31 December 2015 are constrained using the GOSAT ACOS (Atmospheric CO2 Observations from Space) XCO2 retrievals (Version 7.3). The posterior carbon fluxes from 2010 to 2015 are independently evaluated using CO2 observations from 52 surface flask sites. The results show that the posterior carbon fluxes could significantly improve the modeling of atmospheric CO2 concentrations, with global mean bias decreases from a prior value of 1.6 ± 1.8 ppm to −0.5 ± 1.8 ppm. The uncertainty reduction (UR) of the global BIO flux is 17 %, and the highest monthly regional UR could reach 51 %. Globally, the mean annual BIO and OCN carbon sinks and their interannual variations inferred in this study are very close to the estimates of CarbonTracker 2017 (CT2017) during the study period, and the inferred mean atmospheric CO2 growth rate and its interannual changes are also very close to the observations. Regionally, over the northern lands, the strongest carbon sinks are seen in temperate North America, followed by Europe, boreal Asia, and temperate Asia; in the tropics, there are strong sinks in tropical South America and tropical Asia, but a very weak sink in Africa. This pattern is significantly different from the estimates of CT2017, but the estimated carbon sinks for each continent and some key regions like boreal Asia and the Amazon are comparable or within the range of previous bottom-up estimates. The inversion also changes the interannual variations in carbon fluxes in most TransCom land regions, which have a better relationship with the changes in severe drought area (SDA) or leaf area index (LAI), or are more consistent with previous estimates for the impact of drought. These results suggest that the GCASv2 system works well with the GOSAT XCO2 retrievals and shows good performance with respect to estimating the surface carbon fluxes; meanwhile, our results also indicate that the GOSAT XCO2 retrievals could help to better understand the interannual variations in regional carbon fluxes.

scholarly journals Accounting for Carbon and Nitrogen interactions in the Global Terrestrial Ecosystem Model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production

2018 ◽  
Author(s):  
Nicolas Vuichard ◽  
Palmira Messina ◽  
Sebastiaan Luyssaert ◽  
Bertrand Guenet ◽  
Sönke Zaehle ◽  
...  
Keyword(s):  
Primary Production ◽  
Gross Primary Production ◽  
Essential Element ◽  
Co2 Enrichment ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Atmospheric Co2 ◽  
Functional Responses ◽  
Terrestrial Ecosystem Model ◽  
Recent Developments

Abstract. Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric [CO2] increase. This study presents the evaluation – focussing on gross primary production (GPP) – of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version. We quantify the model skills at 78 Fluxnet sites by simulating the observed mean seasonal cycle, daily mean flux variations, and annual mean average GPP flux for grasslands and forests. Accounting for carbon-nitrogen interactions does not substantially change the main skills of ORCHIDEE, except for the site-to-site annual mean GPP variations, for which the version with carbon-nitrogen interactions is in better agreement to observations. However, the simulated GPP response to idealized [CO2] enrichment simulations is highly sensitive to whether or not carbon-nitrogen interactions are accounted for. Doubling of the atmospheric [CO2] induces an increase of the GPP, but the site-averaged GPP response to CO2 increase projected by the model version with carbon-nitrogen interactions is half of the increase projected by the version without carbon-nitrogen interactions. This model's differentiated response has important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon-nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows good agreement with the observation-based MTE-GPP product for present-day conditions. An attribution experiment making use of this new version of ORCHIDEE for the time period 1860–2016 suggests that global GPP has increased by 50 %, the main driver being the enrichment of land in reactive nitrogen (through deposition and fertilization), followed by the [CO2] increase. Based on our factorial experiment and sensitivity analysis, we conclude that if carbon-nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agrees with current understanding of photosynthesis than when the carbon-nitrogen interactions are not accounted for, and that carbon-nitrogen interactions are essential in understanding global terrestrial ecosystem productivity.

scholarly journals Reduction of Global Plant Production due to Droughts from 2001 to 2010: An Analysis with a Process-Based Global Terrestrial Ecosystem Model

2015 ◽  
Vol 19 (16) ◽  
pp. 1-21 ◽  
Author(s):  
Chang Liao ◽  
Qianlai Zhuang
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Plant Production ◽  
Model Parameters ◽  
Drought Impact ◽  
Terrestrial Ecosystem Model

Abstract Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.

scholarly journals Optimization of the seasonal cycles of simulated CO<sub>2</sub> flux by fitting simulated atmospheric CO<sub>2</sub> to observed vertical profiles

2009 ◽  
Vol 6 (12) ◽  
pp. 2733-2741 ◽  
Author(s):  
Y. Nakatsuka ◽  
S. Maksyutov
Keyword(s):  
Net Primary Productivity ◽  
Transport Model ◽  
Vegetation Type ◽  
Vertical Mixing ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Seasonal Cycles ◽  
Concentration Data ◽  
Near Surface ◽  
Terrestrial Ecosystem Model

Abstract. An inverse of a combination of atmospheric transport and flux models was used to optimize the Carnegie-Ames-Stanford Approach (CASA) terrestrial ecosystem model properties such as light use efficiency and temperature dependence of the heterotrophic respiration separately for each vegetation type. The method employed in the present study is based on minimizing the differences between the simulated and observed seasonal cycles of CO2 concentrations. In order to compensate for possible vertical mixing biases in a transport model we use airborne observations of CO2 vertical profile aggregated to a partial column instead of surface observations used predominantly in other parameter optimization studies. Effect of the vertical mixing on optimized net ecosystem production (NEP) was evaluated by carrying out 2 sets of inverse calculations: one with partial-column concentration data from 15 locations and another with near-surface CO2 concentration data from the same locations. We confirmed that the simulated growing season net flux (GSNF) and net primary productivity (NPP) are about 14% higher for northern extra-tropical land when optimized with partial column data as compared to the case with near-surface data.

scholarly journals Limiting the parameter space in the Carbon Cycle Data Assimilation System (CCDAS)

2014 ◽  
Vol 7 (4) ◽  
pp. 1609-1619 ◽  
Author(s):  
S. Kemp ◽  
M. Scholze ◽  
T. Ziehn ◽  
T. Kaminski
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Parameter Space ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Transformation Method ◽  
Terrestrial Ecosystem Model ◽  
Parameter Values ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Terrestrial ecosystem models are employed to calculate the sources and sinks of carbon dioxide between land and atmosphere. These models may be heavily parameterised. Where reliable estimates are unavailable for a parameter, it remains highly uncertain; uncertainty of parameters can substantially contribute to overall model output uncertainty. This paper builds on the work of the terrestrial Carbon Cycle Data Assimilation System (CCDAS), which, here, assimilates atmospheric CO2 concentrations to optimise 19 parameters of the underlying terrestrial ecosystem model (Biosphere Energy Transfer and Hydrology scheme, BETHY). Previous experiments have shown that the identified minimum may contain non-physical parameter values. One way to combat this problem is to use constrained optimisation and so avoid the optimiser searching non-physical regions. Another technique is to use penalty terms in the cost function, which are added when the optimisation searches outside of a specified region. The use of parameter transformations is a further method of avoiding this problem, where the optimisation is carried out in a transformed parameter space, thus ensuring that the optimal parameters at the minimum are in the physical domain. We compare these different methods of achieving meaningful parameter values, finding that the parameter transformation method shows consistent results and that the other two provide no useful results.

scholarly journals Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production

2019 ◽  
Vol 12 (11) ◽  
pp. 4751-4779 ◽  
Author(s):  
Nicolas Vuichard ◽  
Palmira Messina ◽  
Sebastiaan Luyssaert ◽  
Bertrand Guenet ◽  
Sönke Zaehle ◽  
...  
Keyword(s):  
Primary Production ◽  
Gross Primary Production ◽  
Essential Element ◽  
Co2 Enrichment ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Atmospheric Co2 ◽  
Functional Responses ◽  
Terrestrial Ecosystem Model ◽  
Recent Developments

Abstract. Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric [CO2] increase. This study presents the evaluation – focussing on gross primary production (GPP) – of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version. We quantify the model skills at 78 FLUXNET sites by simulating the observed mean seasonal cycle, daily mean flux variations, and annual mean average GPP flux for grasslands and forests. Accounting for carbon–nitrogen interactions does not substantially change the main skills of ORCHIDEE, except for the site-to-site annual mean GPP variations, for which the version with carbon–nitrogen interactions is in better agreement with observations. However, the simulated GPP response to idealised [CO2] enrichment simulations is highly sensitive to whether or not carbon–nitrogen interactions are accounted for. Doubling of the atmospheric [CO2] induces an increase in the GPP, but the site-averaged GPP response to a CO2 increase projected by the model version with carbon–nitrogen interactions is half of the increase projected by the version without carbon–nitrogen interactions. This model's differentiated response has important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon–nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows good agreement with the observation-based MTE-GPP (model tree ensemble gross primary production) product for present-day conditions. An attribution experiment making use of this new version of ORCHIDEE for the time period 1860–2016 suggests that global GPP has increased by 50 %, the main driver being the enrichment of land in reactive nitrogen (through deposition and fertilisation), followed by the [CO2] increase. Based on our factorial experiment and sensitivity analysis, we conclude that if carbon–nitrogen interactions are accounted for, the functional responses of ORCHIDEE r4999 better agree with the current understanding of photosynthesis than when the carbon–nitrogen interactions are not accounted for and that carbon–nitrogen interactions are essential in understanding global terrestrial ecosystem productivity.

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