Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation
Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the pr...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Blomquist, Byron W. [verfasserIn] Huebert, Barry J. [verfasserIn] Fairall, Christopher W. [verfasserIn] Bariteau, Ludovic [verfasserIn] Edson, James B. [verfasserIn] Hare, Jeffrey E. [verfasserIn] McGillis, Wade R. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Boundary layer meteorology - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970, 152(2014), 3 vom: 12. Apr., Seite 245-276 |
|---|---|
| Übergeordnetes Werk: |
volume:152 ; year:2014 ; number:3 ; day:12 ; month:04 ; pages:245-276 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10546-014-9926-2 |
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| Katalog-ID: |
SPR011042753 |
|---|
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| 520 | |a Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. | ||
| 650 | 4 | |a Air–sea gas exchange |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Carbon dioxide |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Cavity ring-down spectrometer |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Eddy correlation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Flux measurement |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Infrared gas analyzer |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Huebert, Barry J. |e verfasserin |4 aut | |
| 700 | 1 | |a Fairall, Christopher W. |e verfasserin |4 aut | |
| 700 | 1 | |a Bariteau, Ludovic |e verfasserin |4 aut | |
| 700 | 1 | |a Edson, James B. |e verfasserin |4 aut | |
| 700 | 1 | |a Hare, Jeffrey E. |e verfasserin |4 aut | |
| 700 | 1 | |a McGillis, Wade R. |e verfasserin |4 aut | |
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10.1007/s10546-014-9926-2 doi (DE-627)SPR011042753 (SPR)s10546-014-9926-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Blomquist, Byron W. verfasserin aut Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 Huebert, Barry J. verfasserin aut Fairall, Christopher W. verfasserin aut Bariteau, Ludovic verfasserin aut Edson, James B. verfasserin aut Hare, Jeffrey E. verfasserin aut McGillis, Wade R. verfasserin aut Enthalten in Boundary layer meteorology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 152(2014), 3 vom: 12. Apr., Seite 245-276 (DE-627)270429395 (DE-600)1477639-X 1573-1472 nnns volume:152 year:2014 number:3 day:12 month:04 pages:245-276 https://dx.doi.org/10.1007/s10546-014-9926-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 152 2014 3 12 04 245-276 |
| spelling |
10.1007/s10546-014-9926-2 doi (DE-627)SPR011042753 (SPR)s10546-014-9926-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Blomquist, Byron W. verfasserin aut Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 Huebert, Barry J. verfasserin aut Fairall, Christopher W. verfasserin aut Bariteau, Ludovic verfasserin aut Edson, James B. verfasserin aut Hare, Jeffrey E. verfasserin aut McGillis, Wade R. verfasserin aut Enthalten in Boundary layer meteorology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 152(2014), 3 vom: 12. Apr., Seite 245-276 (DE-627)270429395 (DE-600)1477639-X 1573-1472 nnns volume:152 year:2014 number:3 day:12 month:04 pages:245-276 https://dx.doi.org/10.1007/s10546-014-9926-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 152 2014 3 12 04 245-276 |
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10.1007/s10546-014-9926-2 doi (DE-627)SPR011042753 (SPR)s10546-014-9926-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Blomquist, Byron W. verfasserin aut Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 Huebert, Barry J. verfasserin aut Fairall, Christopher W. verfasserin aut Bariteau, Ludovic verfasserin aut Edson, James B. verfasserin aut Hare, Jeffrey E. verfasserin aut McGillis, Wade R. verfasserin aut Enthalten in Boundary layer meteorology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 152(2014), 3 vom: 12. Apr., Seite 245-276 (DE-627)270429395 (DE-600)1477639-X 1573-1472 nnns volume:152 year:2014 number:3 day:12 month:04 pages:245-276 https://dx.doi.org/10.1007/s10546-014-9926-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 152 2014 3 12 04 245-276 |
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10.1007/s10546-014-9926-2 doi (DE-627)SPR011042753 (SPR)s10546-014-9926-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Blomquist, Byron W. verfasserin aut Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 Huebert, Barry J. verfasserin aut Fairall, Christopher W. verfasserin aut Bariteau, Ludovic verfasserin aut Edson, James B. verfasserin aut Hare, Jeffrey E. verfasserin aut McGillis, Wade R. verfasserin aut Enthalten in Boundary layer meteorology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 152(2014), 3 vom: 12. Apr., Seite 245-276 (DE-627)270429395 (DE-600)1477639-X 1573-1472 nnns volume:152 year:2014 number:3 day:12 month:04 pages:245-276 https://dx.doi.org/10.1007/s10546-014-9926-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 152 2014 3 12 04 245-276 |
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10.1007/s10546-014-9926-2 doi (DE-627)SPR011042753 (SPR)s10546-014-9926-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Blomquist, Byron W. verfasserin aut Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 Huebert, Barry J. verfasserin aut Fairall, Christopher W. verfasserin aut Bariteau, Ludovic verfasserin aut Edson, James B. verfasserin aut Hare, Jeffrey E. verfasserin aut McGillis, Wade R. verfasserin aut Enthalten in Boundary layer meteorology Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 152(2014), 3 vom: 12. Apr., Seite 245-276 (DE-627)270429395 (DE-600)1477639-X 1573-1472 nnns volume:152 year:2014 number:3 day:12 month:04 pages:245-276 https://dx.doi.org/10.1007/s10546-014-9926-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 152 2014 3 12 04 245-276 |
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Enthalten in Boundary layer meteorology 152(2014), 3 vom: 12. Apr., Seite 245-276 volume:152 year:2014 number:3 day:12 month:04 pages:245-276 |
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Enthalten in Boundary layer meteorology 152(2014), 3 vom: 12. Apr., Seite 245-276 volume:152 year:2014 number:3 day:12 month:04 pages:245-276 |
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Air–sea gas exchange Carbon dioxide Cavity ring-down spectrometer Eddy correlation Flux measurement Infrared gas analyzer |
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Blomquist, Byron W. @@aut@@ Huebert, Barry J. @@aut@@ Fairall, Christopher W. @@aut@@ Bariteau, Ludovic @@aut@@ Edson, James B. @@aut@@ Hare, Jeffrey E. @@aut@@ McGillis, Wade R. @@aut@@ |
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Blomquist, Byron W. |
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Blomquist, Byron W. ddc 550 bkl 38.81 misc Air–sea gas exchange misc Carbon dioxide misc Cavity ring-down spectrometer misc Eddy correlation misc Flux measurement misc Infrared gas analyzer Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation |
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550 ASE 38.81 bkl Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation Air–sea gas exchange (dpeaa)DE-He213 Carbon dioxide (dpeaa)DE-He213 Cavity ring-down spectrometer (dpeaa)DE-He213 Eddy correlation (dpeaa)DE-He213 Flux measurement (dpeaa)DE-He213 Infrared gas analyzer (dpeaa)DE-He213 |
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ddc 550 bkl 38.81 misc Air–sea gas exchange misc Carbon dioxide misc Cavity ring-down spectrometer misc Eddy correlation misc Flux measurement misc Infrared gas analyzer |
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ddc 550 bkl 38.81 misc Air–sea gas exchange misc Carbon dioxide misc Cavity ring-down spectrometer misc Eddy correlation misc Flux measurement misc Infrared gas analyzer |
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ddc 550 bkl 38.81 misc Air–sea gas exchange misc Carbon dioxide misc Cavity ring-down spectrometer misc Eddy correlation misc Flux measurement misc Infrared gas analyzer |
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Elektronische Aufsätze Aufsätze Elektronische Ressource |
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Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation |
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Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation |
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Blomquist, Byron W. |
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Blomquist, Byron W. Huebert, Barry J. Fairall, Christopher W. Bariteau, Ludovic Edson, James B. Hare, Jeffrey E. McGillis, Wade R. |
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Elektronische Aufsätze |
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Blomquist, Byron W. |
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10.1007/s10546-014-9926-2 |
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advances in air–sea %$\hbox {co}_2%$ flux measurement by eddy correlation |
| title_auth |
Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation |
| abstract |
Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. |
| abstractGer |
Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. |
| abstract_unstemmed |
Abstract Eddy-correlation measurements of the oceanic %$\hbox {CO}_2%$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for %$\hbox {CO}_2%$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured %$\hbox {CO}_2%$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be %$<%$5 % for a cavity ring-down analyzer (CRDS) and dryer with a 60-m inlet line. The estimated flux detection limit for the CRDS analyzer and dryer is a factor of ten better than for IRGAs sampling moist air. While ship-motion interference is apparent with all analyzers tested in this study, decorrelation or regression methods are effective in removing most of this bias from IRGA measurements and may also be applicable to the CRDS. |
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Advances in Air–Sea %$\hbox {CO}_2%$ Flux Measurement by Eddy Correlation |
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Huebert, Barry J. Fairall, Christopher W. Bariteau, Ludovic Edson, James B. Hare, Jeffrey E. McGillis, Wade R. |
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| score |
7.4008074 |