Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests
<p>CO<span class="inline-formula"><sub>2</sub></span> storage (<span class="inline-formula"><i>F</i><sub>s</sub></span>) is the cumulation or depletion in CO<span class="inline-formula"><sub>2...
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Copernicus Publications
2024-09-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/17/5581/2024/amt-17-5581-2024.pdf |
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| author | D. Teng D. Teng J. Zhu J. Zhu J. Zhu T. Gao T. Gao T. Gao F. Yu F. Yu Y. Zhu Y. Zhu X. Zhou X. Zhou B. Yang |
| author_facet | D. Teng D. Teng J. Zhu J. Zhu J. Zhu T. Gao T. Gao T. Gao F. Yu F. Yu Y. Zhu Y. Zhu X. Zhou X. Zhou B. Yang |
| author_sort | D. Teng |
| collection | DOAJ |
| description | <p>CO<span class="inline-formula"><sub>2</sub></span> storage (<span class="inline-formula"><i>F</i><sub>s</sub></span>) is the cumulation or depletion in CO<span class="inline-formula"><sub>2</sub></span> amount over a period in an ecosystem. Along with the eddy covariance flux and wind-stream advection of CO<span class="inline-formula"><sub>2</sub></span>, it is a major term in the net ecosystem CO<span class="inline-formula"><sub>2</sub></span> exchange (NEE) equation. The CO<span class="inline-formula"><sub>2</sub></span> storage dominates the NEE equation under a stable atmospheric stratification when the equation is used for forest ecosystems over complex terrains. However, estimating <span class="inline-formula"><i>F</i><sub>s</sub></span> remains challenging due to the frequent gusts and random fluctuations in boundary-layer flows that lead to tremendous difficulties in capturing the true trend of CO<span class="inline-formula"><sub>2</sub></span> changes for use in storage estimation from eddy covariance along with atmospheric profile techniques. Using measurements from Qingyuan Ker Towers equipped with NEE instrument systems separately covering mixed broad-leaved, oak, and larch forest towers in a mountain watershed, this study investigates gust periods and CO<span class="inline-formula"><sub>2</sub></span> fluctuation magnitudes and examines their impact on <span class="inline-formula"><i>F</i><sub>s</sub></span> estimation in relation to the terrain complexity index (TCI). The gusts induce CO<span class="inline-formula"><sub>2</sub></span> fluctuations for numerous periods of 1 to 10 min over 2 h. Diurnal, seasonal, and spatial differences (<span class="inline-formula"><i>P</i></span> <span class="inline-formula"><</span> 0.01) in the maximum amplitude of CO<span class="inline-formula"><sub>2</sub></span> fluctuations (<span class="inline-formula"><i>A</i><sub>m</sub></span>) range from 1.6 to 136.7 ppm, and these differences range from 140 to 170 s in a period (<span class="inline-formula"><i>P</i><sub>m</sub></span>) at the same significance level. <span class="inline-formula"><i>A</i><sub>m</sub></span> and <span class="inline-formula"><i>P</i><sub>m</sub></span> are significantly correlated to the magnitude of and random error in <span class="inline-formula"><i>F</i><sub>s</sub></span> with diurnal and seasonal differences. These correlations decrease as CO<span class="inline-formula"><sub>2</sub></span> averaging time windows become longer. To minimize the uncertainties in <span class="inline-formula"><i>F</i><sub>s</sub></span>, a constant [CO<span class="inline-formula"><sub>2</sub></span>] averaging time window for the <span class="inline-formula"><i>F</i><sub>s</sub></span> estimates is not ideal. Dynamic averaging time windows and a decision-level fusion model can reduce the potential underestimation of <span class="inline-formula"><i>F</i><sub>s</sub></span> by 29 %–33 % for temperate forests in complex terrain. In our study, the relative contribution of <span class="inline-formula"><i>F</i><sub>s</sub></span> to the 30 min NEE observations ranged from 17 % to 82 % depending on turbulent mixing and the TCI. The study's approach is notable as it incorporates the TCI and utilizes three flux towers for replication, making the findings relevant to similar regions with a single tower.</p> |
| format | Article |
| id | doaj-art-d67d4b4dadfd4f32b08c9a80cce0b7f6 |
| institution | OA Journals |
| issn | 1867-1381 1867-8548 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj-art-d67d4b4dadfd4f32b08c9a80cce0b7f62025-08-20T01:55:10ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482024-09-01175581559910.5194/amt-17-5581-2024Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forestsD. Teng0D. Teng1J. Zhu2J. Zhu3J. Zhu4T. Gao5T. Gao6T. Gao7F. Yu8F. Yu9Y. Zhu10Y. Zhu11X. Zhou12X. Zhou13B. Yang14CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110000, ChinaQingyuan Forest CERN, National Observation and Research Station, Liaoning Province, Shenyang 110016, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110000, ChinaQingyuan Forest CERN, National Observation and Research Station, Liaoning Province, Shenyang 110016, ChinaCAS–CSI Joint Laboratory of Research and Development for Monitoring Forest Fluxes of Trace Gases and Isotope Elements, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110000, ChinaQingyuan Forest CERN, National Observation and Research Station, Liaoning Province, Shenyang 110016, ChinaCAS–CSI Joint Laboratory of Research and Development for Monitoring Forest Fluxes of Trace Gases and Isotope Elements, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110000, ChinaQingyuan Forest CERN, National Observation and Research Station, Liaoning Province, Shenyang 110016, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110000, ChinaQingyuan Forest CERN, National Observation and Research Station, Liaoning Province, Shenyang 110016, ChinaCAS–CSI Joint Laboratory of Research and Development for Monitoring Forest Fluxes of Trace Gases and Isotope Elements, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, ChinaCampbell Scientific, Inc., Logan, Utah 84321, USACampbell Scientific, Inc., Logan, Utah 84321, USA<p>CO<span class="inline-formula"><sub>2</sub></span> storage (<span class="inline-formula"><i>F</i><sub>s</sub></span>) is the cumulation or depletion in CO<span class="inline-formula"><sub>2</sub></span> amount over a period in an ecosystem. Along with the eddy covariance flux and wind-stream advection of CO<span class="inline-formula"><sub>2</sub></span>, it is a major term in the net ecosystem CO<span class="inline-formula"><sub>2</sub></span> exchange (NEE) equation. The CO<span class="inline-formula"><sub>2</sub></span> storage dominates the NEE equation under a stable atmospheric stratification when the equation is used for forest ecosystems over complex terrains. However, estimating <span class="inline-formula"><i>F</i><sub>s</sub></span> remains challenging due to the frequent gusts and random fluctuations in boundary-layer flows that lead to tremendous difficulties in capturing the true trend of CO<span class="inline-formula"><sub>2</sub></span> changes for use in storage estimation from eddy covariance along with atmospheric profile techniques. Using measurements from Qingyuan Ker Towers equipped with NEE instrument systems separately covering mixed broad-leaved, oak, and larch forest towers in a mountain watershed, this study investigates gust periods and CO<span class="inline-formula"><sub>2</sub></span> fluctuation magnitudes and examines their impact on <span class="inline-formula"><i>F</i><sub>s</sub></span> estimation in relation to the terrain complexity index (TCI). The gusts induce CO<span class="inline-formula"><sub>2</sub></span> fluctuations for numerous periods of 1 to 10 min over 2 h. Diurnal, seasonal, and spatial differences (<span class="inline-formula"><i>P</i></span> <span class="inline-formula"><</span> 0.01) in the maximum amplitude of CO<span class="inline-formula"><sub>2</sub></span> fluctuations (<span class="inline-formula"><i>A</i><sub>m</sub></span>) range from 1.6 to 136.7 ppm, and these differences range from 140 to 170 s in a period (<span class="inline-formula"><i>P</i><sub>m</sub></span>) at the same significance level. <span class="inline-formula"><i>A</i><sub>m</sub></span> and <span class="inline-formula"><i>P</i><sub>m</sub></span> are significantly correlated to the magnitude of and random error in <span class="inline-formula"><i>F</i><sub>s</sub></span> with diurnal and seasonal differences. These correlations decrease as CO<span class="inline-formula"><sub>2</sub></span> averaging time windows become longer. To minimize the uncertainties in <span class="inline-formula"><i>F</i><sub>s</sub></span>, a constant [CO<span class="inline-formula"><sub>2</sub></span>] averaging time window for the <span class="inline-formula"><i>F</i><sub>s</sub></span> estimates is not ideal. Dynamic averaging time windows and a decision-level fusion model can reduce the potential underestimation of <span class="inline-formula"><i>F</i><sub>s</sub></span> by 29 %–33 % for temperate forests in complex terrain. In our study, the relative contribution of <span class="inline-formula"><i>F</i><sub>s</sub></span> to the 30 min NEE observations ranged from 17 % to 82 % depending on turbulent mixing and the TCI. The study's approach is notable as it incorporates the TCI and utilizes three flux towers for replication, making the findings relevant to similar regions with a single tower.</p>https://amt.copernicus.org/articles/17/5581/2024/amt-17-5581-2024.pdf |
| spellingShingle | D. Teng D. Teng J. Zhu J. Zhu J. Zhu T. Gao T. Gao T. Gao F. Yu F. Yu Y. Zhu Y. Zhu X. Zhou X. Zhou B. Yang Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests Atmospheric Measurement Techniques |
| title | Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| title_full | Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| title_fullStr | Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| title_full_unstemmed | Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| title_short | Field assessments on the impact of CO<sub>2</sub> concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| title_sort | field assessments on the impact of co sub 2 sub concentration fluctuations along with complex terrain flows on the estimation of the net ecosystem exchange of temperate forests |
| url | https://amt.copernicus.org/articles/17/5581/2024/amt-17-5581-2024.pdf |
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