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

被引:50
|
作者
Bacour, C. [1 ]
Maignan, F. [2 ]
MacBean, N. [3 ]
Porcar-Castell, A. [4 ]
Flexas, J. [5 ]
Frankenberg, C. [6 ,7 ]
Peylin, P. [2 ]
Chevallier, F. [2 ]
Vuichard, N. [2 ]
Bastrikov, V [2 ]
机构
[1] NOVELTIS, Labege, France
[2] Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA, Gif Sur Yvette, France
[3] Indiana Univ, Dept Geog, Bloomington, IN 47405 USA
[4] Univ Helsinki, Inst Atmospher & Earth Syst Res Forest Sci, Opt Photosynth Lab, Helsinki, Finland
[5] Univ Iles Balears, Res Grp Plant Biol Mediterranean Condit, Inst Invest Agroambientales & Econ Agua, Palma De Mallorca, Spain
[6] CALTECH, Div Geol & Planetary Sci, Pasadena, CA 91125 USA
[7] CALTECH, Jet Prop Lab, Pasadena, CA USA
基金
芬兰科学院; 欧盟地平线“2020”;
关键词
solar-induced fluorescence; gross primary productivity; terrestrial biosphere model; data assimilation; SIF modeling; INDUCED CHLOROPHYLL FLUORESCENCE; LAND-SURFACE MODEL; SUN-INDUCED FLUORESCENCE; NET ECOSYSTEM EXCHANGE; MULTIPLE DATA STREAMS; CARBON-CYCLE; CONSISTENT ASSIMILATION; PHOTOSYNTHETIC CAPACITY; STOMATAL CONDUCTANCE; BIOCHEMICAL-MODEL;
D O I
10.1029/2019JG005040
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Over the last few years, solar-induced chlorophyll fluorescence (SIF) observations from space have emerged as a promising resource for evaluating the spatio-temporal distribution of gross primary productivity (GPP) simulated by global terrestrial biosphere models. SIF can be used to improve GPP simulations by optimizing critical model parameters through statistical Bayesian data assimilation techniques. A prerequisite is the availability of a functional link between GPP and SIF in terrestrial biosphere models. Here we present the development of a mechanistic SIF observation operator in the ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems) terrestrial biosphere model. It simulates the regulation of photosystem II fluorescence quantum yield at the leaf level thanks to a novel parameterization of non-photochemical quenching as a function of temperature, photosynthetically active radiation, and normalized quantum yield of photochemistry. It emulates the radiative transfer of chlorophyll fluorescence to the top of the canopy using a parametric simplification of the SCOPE (Soil Canopy Observation Photosynthesis Energy) model. We assimilate two years of monthly OCO-2 (Orbiting Carbon Observatory-2) SIF product at 0.5 degrees (2015-2016) to optimize ORCHIDEE photosynthesis and phenological parameters over an ensemble of grid points for all plant functional types. The impact on the simulated GPP is considerable with a large decrease of the global scale budget by 28 GtC/year over the period 1990-2009. The optimized GPP budget (134/136 GtC/year over 1990-2009/2001-2009) remarkably agrees with independent GPP estimates, FLUXSAT (137 GtC/year over 2001-2009) in particular and FLUXCOM (121 GtC/year over 1990-2009). Our results also suggest a biome dependency of the SIF-GPP relationship that needs to be improved for some plant functional types.
引用
收藏
页码:3281 / 3306
页数:26
相关论文
共 37 条
  • [11] Mango-GPP: A Process-Based Model for Simulating Gross Primary Productivity of Mangrove Ecosystems
    Tang, Yuqi
    Li, Tingting
    Yang, Xiu-Qun
    Chao, Qingchen
    Wang, Chunlin
    Lai, Derrick Y. F.
    Liu, Jiangong
    Zhu, Xudong
    Zhao, Xiaosong
    Fan, Xingwang
    Zhang, Yiping
    Hu, Qiwen
    Qin, Zhangcai
    JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2023, 15 (12)
  • [12] Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3
    Ni, J
    Sykes, MT
    Prentice, IC
    Cramer, W
    GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2000, 9 (06): : 463 - 479
  • [13] Tracking Gross Primary Productivity Using Satellite Solar Induced Fluorescence: Insights Across Agricultural Ecosystems of India
    Behera, Subhrasita
    Dutta, Debsunder
    JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 2024, 129 (05)
  • [14] Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy
    Chen, Ruonan
    Liu, Liangyun
    Liu, Xinjie
    Liu, Zhunqiao
    Gu, Lianhong
    Rascher, Uwe
    REMOTE SENSING OF ENVIRONMENT, 2024, 300
  • [15] Integrating multi-source datasets in exploring the covariation of gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) at an Indian tropical forest flux site
    Hari, Manoj
    Kutty, Govindan
    Tyagi, Bhishma
    ENVIRONMENTAL EARTH SCIENCES, 2024, 83 (08)
  • [16] Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China
    Peijuan Wang
    Donghui Xie
    Yuyu Zhou
    Youhao E
    Qijiang Zhu
    Environmental Earth Sciences, 2014, 71 : 647 - 658
  • [17] Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China
    Wang, Peijuan
    Xie, Donghui
    Zhou, Yuyu
    Youhao E
    Zhu, Qijiang
    ENVIRONMENTAL EARTH SCIENCES, 2014, 71 (02) : 647 - 658
  • [18] Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States
    Li, Zhengpeng
    Liu, Shuguang
    Tan, Zhengxi
    Bliss, Norman B.
    Young, Claudia J.
    West, Tristram O.
    Ogle, Stephen M.
    ECOLOGICAL MODELLING, 2014, 277 : 1 - 12
  • [19] Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations
    Liu, Dan
    Cai, Wenwen
    Xia, Jiangzhou
    Dong, Wenjie
    Zhou, Guangsheng
    Chen, Yang
    Zhang, Haicheng
    Yuan, Wenping
    PLOS ONE, 2014, 9 (11):
  • [20] Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence
    Alemohammad, Seyed Hamed
    Fang, Bin
    Konings, Alexandra G.
    Aires, Filipe
    Green, Julia K.
    Kolassa, Jana
    Miralles, Diego
    Prigent, Catherine
    Gentine, Pierre
    BIOGEOSCIENCES, 2017, 14 (18) : 4101 - 4124