From site-level to global simulation: Reconciling carbon, water and energy fluxes over different spatial scales using a process-based ecophysiological land-surface model
被引:13
|
作者:
Alton, Paul B.
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h-index: 0
机构:
Swansea Univ, Dept Geog, Swansea SA2 8PP, W Glam, WalesSwansea Univ, Dept Geog, Swansea SA2 8PP, W Glam, Wales
Alton, Paul B.
[1
]
机构:
[1] Swansea Univ, Dept Geog, Swansea SA2 8PP, W Glam, Wales
Carbon cycle;
Water cycle;
Land-surface modelling;
Spatial scaling;
Moderate resolution imaging spectroradiometer (MODIS);
FLUXNET;
NET PRIMARY PRODUCTION;
AREA INDEX PRODUCTS;
TERRESTRIAL GROSS;
EDDY COVARIANCE;
BALANCE CLOSURE;
EXCHANGE;
VEGETATION;
FORESTS;
CLIMATE;
CO2;
D O I:
10.1016/j.agrformet.2013.03.010
中图分类号:
S3 [农学(农艺学)];
学科分类号:
0901 ;
摘要:
Site carbon, water and energy fluxes, such as those measured by eddy covariance, only provide point source information about the earth's surface. A major challenge is scaling these fluxes to regional and global level to forge a unified understanding of both ecophysiology and flux exchange across all spatial scales. Furthermore, the ability of site fluxes to represent global vegetation and climate remains unquantified. The present study examines these questions using a process-based Land-Surface Model (LSM) containing state-of-the-art formulations of biophysical processes such as canopy light interception. The LSM is calibrated, forced and validated using a large and diverse range of established (e.g. FLUXNET) and novel (e.g. soil respiration, global river discharge and Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index and reflectance) observational datasets spanning different spatial scales. Multiple calibration datasets are expected to provide tighter model constraints, better global coverage and reduced observational bias. Uncertainties, estimated using a Monte-Carlo analysis, are quite large in the global simulation. Nevertheless, the present study reveals an inconsistency in measured carbon and water fluxes at site level compared to regional/global level. The model, once tuned at site-level, predicts a carbon sink of 20 +/- 14 Gt yr(-1) for the tropics which is inconsistent with atmospheric CO2 inversion and carbon inventory. Furthermore, evapotranspiration recorded at FLUXNET sites would have to be reduced by 30% to agree with measured global river discharge. Future modelling would benefit from complementary flux measurements in currently underrepresented global vegetation classes (tropical broadleaf forest and C4 grassland) and climate zones (tundra). (C) 2013 Elsevier B.V. All rights reserved.
机构:
Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Changjiang Inst Survey Planning Design & Res, Wuhan 430010, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Zeng, Sidong
Xia, Jun
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Xia, Jun
Chen, Xiangdong
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机构:
China Water Exchange, Beijing 100053, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Chen, Xiangdong
Zou, Lei
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Zou, Lei
Du, Hong
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机构:
South Cent Univ Nationalities, Coll Resources & Environm Sci, Wuhan 430074, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
Du, Hong
She, Dunxian
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机构:
Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R ChinaChinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
机构:
Seoul Natl Univ, Res Inst Agr & Life Sci, Seoul, South KoreaSeoul Natl Univ, Res Inst Agr & Life Sci, Seoul, South Korea
Jiang, Chongya
Ryu, Youngryel
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机构:
Seoul Natl Univ, Res Inst Agr & Life Sci, Seoul, South Korea
Seoul Natl Univ, Dept Landscape Architecture & Rural Syst Engn, Seoul, South KoreaSeoul Natl Univ, Res Inst Agr & Life Sci, Seoul, South Korea
Ryu, Youngryel
[J].
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS),
2016,
: 5217
-
5220
机构:
Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Univ Chinese Acad Sci, Coll Resources & Environm, 19A Yuquan Rd, Beijing 100049, Peoples R ChinaChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Li, Sinan
Zhang, Li
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机构:
Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R ChinaChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Zhang, Li
Xiao, Jingfeng
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机构:
Univ New Hampshire, Inst Study Earth Oceans & Space, Earth Syst Res Ctr, Durham, NH 03824 USAChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Xiao, Jingfeng
Ma, Rui
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机构:
University, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R ChinaChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Ma, Rui
Tian, Xiangjun
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机构:
Chinese Acad Sci, Inst Atmospher Phys, Int Ctr Climate & Environm Sci ICCES, Beijing 100029, Peoples R ChinaChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Tian, Xiangjun
Yan, Min
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机构:
Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China
Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R ChinaChinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China