A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes

被引:364
作者
Richardson, AD
Hollinger, DY
Burba, GG
Davis, KJ
Flanagan, LB
Katul, GG
Munger, JW
Ricciuto, DM
Stoy, PC
Suyker, AE
Verma, SB
Wofsy, SC
机构
[1] Univ New Hampshire, Complex Syst Res Ctr, Durham, NH 03824 USA
[2] US Forest Serv, USDA, NE Res Stn, Durham, NH 03824 USA
[3] LI COR Biosci Inc, Lincoln, NE 68504 USA
[4] Penn State Univ, Dept Meteorol, University Pk, PA 16802 USA
[5] Univ Lethbridge, Dept Biol Sci, Lethbridge, AB T1K 3M4, Canada
[6] Duke Univ, Nicholas Sch Environm & Earth Sci, Durham, NC 27708 USA
[7] Harvard Univ, Dept Earth & Planetary Sci, Div Engn & Appl Sci, Cambridge, MA 02138 USA
[8] Univ Nebraska, Sch Nat Resources, Lincoln, NE 68583 USA
基金
加拿大自然科学与工程研究理事会;
关键词
AmeriFlux; carbon; data assimilation; eddy covariance; flux; measurement error; random error; uncertainty;
D O I
10.1016/j.agrformet.2006.01.007
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the "true" flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include "tall tower" instrumentation), one grassland site, and one agricultural site, to conduct a cross-site analysis of random flux error. Quantification of this uncertainty is a prerequisite to model-data synthesis (data assimilation) and for defining confidence intervals on annual sums of net ecosystem exchange or making statistically valid comparisons between measurements and model predictions. We differenced paired observations (separated by exactly 24 h, under similar environmental conditions) to infer the characteristics of the random error in measured fluxes. Random flux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian), distribution, and increase as a linear function of the magnitude of the flux for all three scalar fluxes. Across sites, variation in the random error follows consistent and robust patterns in relation to environmental variables. For example, seasonal differences in the random error for H are small, in contrast to both LE and FCO2, for which the random errors are roughly three-fold larger at the peak of the growing season compared to the dormant season. Random errors also generally scale with R-n (H and LE) and PPFD (FCO2). For FCO2 (but not H or LE), the random error decreases with increasing wind speed. Data from two sites suggest that FCO2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used. (c) 2006 Elsevier B.V. All rights reserved.
引用
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页码:1 / 18
页数:18
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