NWIPB OpenIR
Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales
Wu, Xiaocui1,2; Ju, Weimin1,2; Zhou, Yanlian3,4; He, Mingzhu5; Law, Beverly E.6; Black, T. Andrew7; Margolis, Hank A.8; Cescatti, Alessandro9; Gu, Lianhong10; Montagnani, Leonardo11,12; Noormets, Asko13; Griffis, Timothy J.14; Pilegaard, Kim15; Varlagin, Andrej16; Valentini, Riccardo17; Blanken, Peter D.18; Wang, Shaoqiang19; Wang, Huimin19; Han, Shijie20; Yan, Junhua21; Li, Yingnian22; Zhou, Bingbing3,4; Liu, Yibo23
2015
Source PublicationREMOTE SENSING
Volume7Issue:3Pages:2238-2278
SubtypeArticle
AbstractThe reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.; The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.
WOS HeadingsScience & Technology ; Technology
WOS KeywordGROSS PRIMARY PRODUCTION ; NET ECOSYSTEM EXCHANGE ; CARBON-DIOXIDE EXCHANGE ; WATER-VAPOR EXCHANGE ; RADIATION-USE EFFICIENCY ; IN-SITU MEASUREMENTS ; PINE MIXED FOREST ; PRIMARY PRODUCTIVITY ; INTERANNUAL VARIABILITY ; FLUX MEASUREMENTS
Indexed BySCI
Language英语
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000353685200001
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://210.75.249.4/handle/363003/5574
Collection中国科学院西北高原生物研究所
Affiliation1.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China
2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
3.Nanjing Univ, Sch Geog, Nanjing 210023, Jiangsu, Peoples R China
4.Nanjing Univ, Sch Oceanog Sci, Nanjing 210023, Jiangsu, Peoples R China
5.Univ Montana, Numer Terradynam Simulat Grp, Missoula, MT 59812 USA
6.Oregon State Univ, Coll Forestry, Corvallis, OR 97331 USA
7.Univ British Columbia, Fac Land & Food Syst, Vancouver, BC V6T 1Z4, Canada
8.Univ Laval, Ctr Etud Foret, Quebec City, PQ G1V 0A6, Canada
9.Commiss European Communities, Inst Environm & Sustainabil, Joint Res Ctr, I-20127 Ispra, Italy
10.Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA
11.Autonomous Prov Bolzano, Forest Serv, I-39100 Bolzano, Italy
12.Free Univ Bolzano, Fac Sci & Technol, I-39100 Bolzano, Italy
13.N Carolina State Univ, Dept Forestry & Environm Resources, Raleigh, NC 27695 USA
14.Univ Minnesota, Dept Soil Water & Climate, St Paul, MN 55108 USA
15.Tech Univ Denmark, Dept Chem & Biochem Engn, DK-2800 Lyngby, Denmark
16.Russian Acad Sci, AN Severtsov Inst Ecol & Evolut, Moscow 119071, Russia
17.Univ Tuscia, Dept Innovat Biol Arofood & Forest Syst, I-01100 Viterbo, Italy
18.Univ Colorado, Dept Geog, Boulder, CO 80309 USA
19.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
20.Chinese Acad Sci, Inst Appl Ecol, State Key Lab Forest & Soil Ecol, Shenyang 110016, Peoples R China
21.Chinese Acad Sci, South China Bot Garden, Guangzhou 510650, Guangdong, Peoples R China
22.Chinese Acad Sci, Northwest Inst Plateau Biol, Xining 810008, Peoples R China
23.Nanjing Univ Informat Sci & Technol, Coll Appl Meteorol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Wu, Xiaocui,Ju, Weimin,Zhou, Yanlian,et al. Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales[J]. REMOTE SENSING,2015,7(3):2238-2278.
APA Wu, Xiaocui.,Ju, Weimin.,Zhou, Yanlian.,He, Mingzhu.,Law, Beverly E..,...&Liu, Yibo.(2015).Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales.REMOTE SENSING,7(3),2238-2278.
MLA Wu, Xiaocui,et al."Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales".REMOTE SENSING 7.3(2015):2238-2278.
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