Search

Your search keyword '"Kolle, O"' showing total 232 results
Start Over Author "Kolle, O"
232 results on '"Kolle, O"'

1. Towards long-Term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems: A review

Author

Franz, D, Acosta, M, Altimir, N, Arriga, N, Arrouays, D, Aubinet, M, Aurela, M, Ayres, E, López-Ballesteros, A, Barbaste, M, Berveiller, D, Biraud, S, Boukir, H, Brown, T, Brömmer, C, Buchmann, N, Burba, G, Carrara, A, Cescatti, A, Ceschia, E, Clement, R, Cremonese, E, Crill, P, Darenova, E, Dengel, S, D'Odorico, P, Filippa, G, Fleck, S, Fratini, G, Fuß, R, Gielen, B, Gogo, S, Grace, J, Graf, A, Grelle, A, Gross, P, Grönwald, T, Haapanala, S, Hehn, M, Heinesch, B, Heiskanen, J, Herbst, M, Herschlein, C, Hörtnagl, L, Hufkens, K, Ibrom, A, Jolivet, C, Joly, L, Jones, M, Kiese, R, Klemedtsson, L, Kljun, N, Klumpp, K, Kolari, P, Kolle, O, Kowalski, A, Kutsch, W, Laurila, T, De Ligne, A, Linder, S, Lindroth, A, Lohila, A, Longdoz, B, Mammarella, I, Manise, T, Jiménez, SM, Matteucci, G, Mauder, M, Meier, P, Merbold, L, Mereu, S, Metzger, S, Migliavacca, M, Mölder, M, Montagnani, L, Moureaux, C, Nelson, D, Nemitz, E, Nicolini, G, Nilsson, MB, De Beeck, MOM, Osborne, B, Löfvenius, MO, Pavelka, M, Peichl, M, Peltola, O, Pihlatie, M, Pitacco, A, Pokorný, R, Pumpanen, J, Ratié, C, Rebmann, C, Roland, M, Sabbatini, S, Saby, NPA, Saunders, M, Schmid, HP, Schrumpf, M, Sedlák, P, and Ortiz, PS

Subjects
ICOS, GHG exchange, carbon cycle, standardised monitoring, observational network, Agronomy & Agriculture
Abstract

Research infrastructures play a key role in launching a new generation of integrated long-Term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-Access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

Published
2018

3. Plant diversity stabilizes soil temperature

Author

Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Dong, H., Eichenberg, D., Gleixner, G., Hildebrandt, Anke, Lange, M., Roscher, Christiane, Schielzeth, H., Schmid, B., Weigelt, A., Weisser, W.W., Shadaydeh, M., Denzler, J., Ebeling, A., Eisenhauer, N., Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Dong, H., Eichenberg, D., Gleixner, G., Hildebrandt, Anke, Lange, M., Roscher, Christiane, Schielzeth, H., Schmid, B., Weigelt, A., Weisser, W.W., Shadaydeh, M., Denzler, J., Ebeling, A., and Eisenhauer, N.

Abstract

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate impacts of climate change by increasing plant productivity and ecosystem stability1,2. Although soil temperature and its stability are key determinants of essential ecosystem processes related to water and nutrient uptake3 as well as soil respiration and microbial activity4, no study has yet investigated whether plant diversity can buffer soil temperature fluctuations. Using 18 years of a continuous dataset with a resolution of 1 minute (∼795,312,000 individual measurements) from a large-scale grassland biodiversity experiment, we show that plant diversity buffers soil temperature throughout the year. Plant diversity helped to prevent soil heating in hot weather, and cooling in cold weather. Moreover, this effect of plant diversity increased over the 18-year observation period with the aging of experimental communities and was even stronger under extreme conditions, i.e., on hot days or in dry years. Using structural equation modelling, we found that plant diversity stabilized soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, by increasing the plant leaf area index. We suggest that the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon release, thus slow global warming.

Published
2023

4. Data and R code used in: Enhanced stability of grassland soil temperature by plant diversity

Author

Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Gleixner, G., Lange, M., Roscher, Christiane, Schmid, B., Weigelt, A., Ebeling, A., Eisenhauer, N., Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Gleixner, G., Lange, M., Roscher, Christiane, Schmid, B., Weigelt, A., Ebeling, A., and Eisenhauer, N.

Abstract

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate the impacts of climate change by increasing plant productivity and ecosystem stability. Although soil temperature and its stability are key determinants of essential ecosystem processes, no study has yet investigated whether plant diversity buffers soil temperature fluctuations over long-term community development. Here we have conducted a comprehensive analysis of a continuous 18-year dataset from a grassland biodiversity experiment with high spatial and temporal resolutions. Our findings reveal that plant diversity acts as a natural buffer, preventing soil heating in hot weather and cooling in cold weather. This diversity effect persists year-round, intensifying with the aging of experimental communities and being even stronger under extreme climate conditions, such as hot days or dry years. Using structural equation modelling, we found that plant diversity stabilizes soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, plant leaf area index. Our results suggest that, in lowland grasslands, the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon decomposition, thus slowing global warming.

Published
2023

5. Enhanced stability of grassland soil temperature by plant diversity

Author

Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Dong, H., Eichenberg, D., Gleixner, G., Hildebrandt, Anke, Lange, M., Roscher, Christiane, Schielzeth, H., Schmid, B., Weigelt, A., Weisser, W.W., Shadaydeh, M., Denzler, J., Ebeling, A., Eisenhauer, N., Huang, Y., Stein, G., Kolle, O., Kübler, K., Schulze, E.-D., Dong, H., Eichenberg, D., Gleixner, G., Hildebrandt, Anke, Lange, M., Roscher, Christiane, Schielzeth, H., Schmid, B., Weigelt, A., Weisser, W.W., Shadaydeh, M., Denzler, J., Ebeling, A., and Eisenhauer, N.

Abstract

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate the impacts of climate change by increasing plant productivity and ecosystem stability. Although soil temperature and its stability are key determinants of essential ecosystem processes, no study has yet investigated whether plant diversity buffers soil temperature fluctuations over long-term community development. Here we have conducted a comprehensive analysis of a continuous 18-year dataset from a grassland biodiversity experiment with high spatial and temporal resolutions. Our findings reveal that plant diversity acts as a natural buffer, preventing soil heating in hot weather and cooling in cold weather. This diversity effect persists year-round, intensifying with the aging of experimental communities and being even stronger under extreme climate conditions, such as hot days or dry years. Using structural equation modelling, we found that plant diversity stabilizes soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, plant leaf area index. Our results suggest that, in lowland grasslands, the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon decomposition, thus slowing global warming.

Published
2023

7. Effects of Reversal of Water Flow in an Arctic Floodplain River on Fluvial Emissions of CO 2 and CH 4

Author

Castro‐Morales, K., Canning, Anna, Körtzinger, Arne, Göckede, M., Küsel, K., Overholt, W. A., Wichard, T., Redlich, S., Arzberger, S., Kolle, O., Zimov, N., Castro‐Morales, K., Canning, Anna, Körtzinger, Arne, Göckede, M., Küsel, K., Overholt, W. A., Wichard, T., Redlich, S., Arzberger, S., Kolle, O., and Zimov, N.

Abstract

When organic matter from thawed permafrost is released, the sources and sinks of greenhouse gases (GHGs), like carbon dioxide (CO2) and methane (CH4) in Arctic rivers will be influenced in the future. However, the temporal variation, environmental controls, and magnitude of the Arctic riverine GHGs are largely unknown. We measured in situ high temporal resolution concentrations of CO2, CH4, and oxygen (O2) in the Ambolikha River in northeast Siberia between late June and early August 2019. During this period, the largely supersaturated riverine CO2 and CH4 concentrations decreased steadily by 90% and 78%, respectively, while the O2 concentrations increased by 22% and were driven by the decreasing water temperature. Estimated gas fluxes indicate that during late June 2019, significant emissions of CO2 and CH4 were sustained, possibly by external terrestrial sources during flooding, or due to lateral exchange with gas-rich downstream-flowing water. In July and early August, the river reversed its flow constantly and limited the water exchange at the site. The composition of dissolved organic matter and microbial communities analyzed in discrete samples also revealed a temporal shift. Furthermore, the cumulative total riverine CO2 emissions (36.8 gC-CO2 m−2) were nearly five times lower than the CO2 uptake at the adjacent floodplain. Emissions of riverine CH4 (0.21 gC-CH4 m−2) were 16 times lower than the floodplain CH4 emissions. Our study revealed that the hydraulic connectivity with the land in the late freshet, and reversing flow directions in Arctic streams in summer, regulate riverine carbon replenishment and emissions.

Published
2022
Full Text
View/download PDF

8. Resolving seasonal and diel dynamics of non-rainfall water inputs in a Mediterranean ecosystem using lysimeters

Author

Paulus, S.J., El-Madany, T.S., Orth, R., Hildebrandt, Anke, Wutzler, T., Carrara, A., Moreno, G., Perez-Priego, O., Kolle, O., Reichstein, M., Migliavacca, M., Paulus, S.J., El-Madany, T.S., Orth, R., Hildebrandt, Anke, Wutzler, T., Carrara, A., Moreno, G., Perez-Priego, O., Kolle, O., Reichstein, M., and Migliavacca, M.

Abstract

The input of liquid water to terrestrial ecosystems is composed of rain and non-rainfall water (NRW). The latter comprises dew, fog, and the adsorption of atmospheric vapor on soil particle surfaces. Although NRW inputs can be relevant to support ecosystem functioning in seasonally dry ecosystems, they are understudied, being relatively small, and therefore hard to measure. In this study, we apply a partitioning routine focusing on NRW inputs over 1 year of data from large, high-precision weighing lysimeters at a semi-arid Mediterranean site. NRW inputs occur for at least 3 h on 297 d (81 % of the year), with a mean diel duration of 6 h. They reflect a pronounced seasonality as modulated by environmental conditions (i.e., temperature and net radiation). During the wet season, both dew and fog dominate NRW, while during the dry season it is mostly the soil adsorption of atmospheric water vapor. Although NRW contributes only 7.4 % to the annual water input, NRW is the only water input to the ecosystem during 15 weeks, mainly in the dry season. Benefitting from the comprehensive set of measurements at our experimental site, we show that our findings are in line with (i) independent measurements and (ii) independent model simulations forced with (near-) surface energy and moisture measurements. Furthermore, we discuss the simultaneous occurrence of soil vapor adsorption and negative eddy-covariance-derived latent heat fluxes. This study shows that NRW inputs can be reliably detected through high-resolution weighing lysimeters and a few additional measurements. Their main occurrence during nighttime underlines the necessity to consider ecosystem water fluxes at a high temporal resolution and with 24 h coverage.

Published
2022

12. Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

Author

Pacheco-Labrador, J, Perez-Priego, O, El-Madany, T, Julitta, T, Rossini, M, Guan, J, Moreno, G, Carvalhais, N, Martin, M, Gonzalez-Cascon, R, Kolle, O, Reischtein, M, van der Tol, C, Carrara, A, Martini, D, Hammer, T, Moossen, H, Migliavacca, M, Pacheco-Labrador J., Perez-Priego O., El-Madany T. S., Julitta T., Rossini M., Guan J., Moreno G., Carvalhais N., Martin M. P., Gonzalez-Cascon R., Kolle O., Reischtein M., van der Tol C., Carrara A., Martini D., Hammer T. W., Moossen H., Migliavacca M., Pacheco-Labrador, J, Perez-Priego, O, El-Madany, T, Julitta, T, Rossini, M, Guan, J, Moreno, G, Carvalhais, N, Martin, M, Gonzalez-Cascon, R, Kolle, O, Reischtein, M, van der Tol, C, Carrara, A, Martini, D, Hammer, T, Moossen, H, Migliavacca, M, Pacheco-Labrador J., Perez-Priego O., El-Madany T. S., Julitta T., Rossini M., Guan J., Moreno G., Carvalhais N., Martin M. P., Gonzalez-Cascon R., Kolle O., Reischtein M., van der Tol C., Carrara A., Martini D., Hammer T. W., Moossen H., and Migliavacca M.

Abstract

The most recent efforts to provide remote sensing (RS) estimates of plant function rely on the combination of Radiative Transfer Models (RTM) and Soil-Vegetation-Atmosphere Transfer (SVAT) models, such as the Soil-Canopy Observation Photosynthesis and Energy fluxes (SCOPE) model. In this work we used ground spectroradiometric and chamber-based CO2 flux measurements in a nutrient manipulated Mediterranean grassland in order to: 1) develop a multiple-constraint inversion approach of SCOPE able to retrieve vegetation biochemical, structural as well as key functional traits, such as chlorophyll concentration (Cab), leaf area index (LAI), maximum carboxylation rate (Vcmax) and the Ball-Berry sensitivity parameter (m); and 2) compare the potential of the of gross primary production (GPP) and sun-induced fluorescence (SIF), together with up-welling Thermal Infrared (TIR) radiance and optical reflectance factors (RF), to estimate such parameters. The performance of the proposed inversion method as well as of the different sets of constraints was assessed with contemporary measurements of water and heat fluxes and leaf nitrogen content, using pattern-oriented model evaluation. The multiple-constraint inversion approach proposed together with the combination of optical RF and diel GPP and TIR data provided reliable estimates of parameters, and improved predicted water and heat fluxes. The addition of SIF to this scheme slightly improved the estimation of m. Parameter estimates were coherent with the variability imposed by the fertilization and the seasonality of the grassland. Results revealed that fertilization had an impact on Vcmax, while no significant differences were found for m. The combination of RF, SIF and diel TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated Cab in the dry period. These problems might be related to the presence of high fractions of senescent leaves in the grassland. The pr

Published
2019

13. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (vol 7, 225, 2020)

Author

Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D

Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

Published
2021

14. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D

Abstract

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions.

Published
2021

17. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D

Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Published
2020

18. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), Papale, D. (Dario), Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), and Papale, D. (Dario)

Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Published
2020

19. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author

Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D, Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, and Papale D

Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Published
2020

20. Effects of Reversal of Water Flow in an Arctic Floodplain River on Fluvial Emissions of CO2 and CH4.

Author

Castro‐Morales, K., Canning, A., Körtzinger, A., Göckede, M., Küsel, K., Overholt, W. A., Wichard, T., Redlich, S., Arzberger, S., Kolle, O., and Zimov, N.

Subjects
HYDRAULICS, FLUVIAL geomorphology, CARBON dioxide, EMISSIONS (Air pollution), ORGANIC compounds
Abstract

When organic matter from thawed permafrost is released, the sources and sinks of greenhouse gases (GHGs), like carbon dioxide (CO2) and methane (CH4) in Arctic rivers will be influenced in the future. However, the temporal variation, environmental controls, and magnitude of the Arctic riverine GHGs are largely unknown. We measured in situ high temporal resolution concentrations of CO2, CH4, and oxygen (O2) in the Ambolikha River in northeast Siberia between late June and early August 2019. During this period, the largely supersaturated riverine CO2 and CH4 concentrations decreased steadily by 90% and 78%, respectively, while the O2 concentrations increased by 22% and were driven by the decreasing water temperature. Estimated gas fluxes indicate that during late June 2019, significant emissions of CO2 and CH4 were sustained, possibly by external terrestrial sources during flooding, or due to lateral exchange with gas‐rich downstream‐flowing water. In July and early August, the river reversed its flow constantly and limited the water exchange at the site. The composition of dissolved organic matter and microbial communities analyzed in discrete samples also revealed a temporal shift. Furthermore, the cumulative total riverine CO2 emissions (36.8 gC‐CO2 m−2) were nearly five times lower than the CO2 uptake at the adjacent floodplain. Emissions of riverine CH4 (0.21 gC‐CH4 m−2) were 16 times lower than the floodplain CH4 emissions. Our study revealed that the hydraulic connectivity with the land in the late freshet, and reversing flow directions in Arctic streams in summer, regulate riverine carbon replenishment and emissions. Plain Language Summary: When the snow and ice melt in the Arctic, then organic matter, carbon dioxide (CO2), and methane (CH4) can be transported from land into rivers. Bacteria or sunlight transform river organic matter, releasing more of those gases. However, little is known about how CO2 and CH4 levels in Arctic rivers change over time or how environmental factors affect them. We measured CO2, CH4, and oxygen in the Ambolikha River in northeast Siberia, from late June to early August 2019. Riverine CO2 and CH4 concentrations decreased over time but remained high enough to be emitted into the atmosphere. Riverine CO2 emissions were five times lower than floodplain terrestrial plant CO2 uptake. Riverine CH4 emissions were 16 times lower than floodplain emissions. Upstream fluvial contributions and lateral influences from the floodplain, must have maintained high riverine gas concentrations during flooding. The direction of the river's flow reversed repeatedly in July and early August, limiting water and gas exchange. Changes in river flow patterns and permafrost thaw must be considered to better quantify temporal and spatial variations in Arctic riverine CO2 and CH4 emissions. This will help us understand the role of Arctic aquatic ecosystems in regional and global carbon budgets. Key Points: Elevated concentration and fluxes of carbon dioxide and methane in Ambolikha River decrease from the late freshet to summerTotal floodplain methane emissions were higher than the methane emitted from Ambolikha RiverHydraulic connectivity and river flow reversals in Arctic streams can affect C replenishment and emissions [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

21. Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO2 and COS Flux Measurements

Author

Spielmann, F. M., Wohlfahrt, G., Hammerle, A., Kitz, F., Migliavacca, M., Alberti, G., Ibrom, Andreas, El‐Madany, T. S., Gerdel, K., Moreno, G., Kolle, O., Karl, T., Peressotti, A., and Delle Vedove, G.

Subjects
flux partitioning, LRU, Atmospheric Composition and Structure, Biogeochemistry, Biogeosciences, Hydrology and Land Surface Studies, Research Letters, ERU, GPP, OCS, Biogeochemical Kinetics and Reaction Modeling, Oceanography: Biological and Chemical, Paleoceanography, Research Letter, Global Change, Biosphere/Atmosphere Interactions, Cryosphere, Biogeochemical Cycles, Processes, and Modeling, SDG 15 - Life on Land
Abstract

Gross primary productivity (GPP), the gross uptake of carbon dioxide (CO2) by plant photosynthesis, is the primary driver of the land carbon sink, which presently removes around one quarter of the anthropogenic CO2 emissions each year. GPP, however, cannot be measured directly and the resulting uncertainty undermines our ability to project the magnitude of the future land carbon sink. Carbonyl sulfide (COS) has been proposed as an independent proxy for GPP as it diffuses into leaves in a fashion very similar to CO2, but in contrast to the latter is generally not emitted. Here we use concurrent ecosystem‐scale flux measurements of CO2 and COS at four European biomes for a joint constraint on CO2 flux partitioning. The resulting GPP estimates generally agree with classical approaches relying exclusively on CO2 fluxes but indicate a systematic underestimation under low light conditions, demonstrating the importance of using multiple approaches for constraining present‐day GPP., Key Points Traditionally gross primary productivity is inferred from ecosystem‐scale CO2 flux measurementsThe proposed joint assimilation of CO2 and COS flux measurements avoids the need to specify the leaf relative uptake rate of COS a prioriThe additional information content of ecosystem‐scale COS flux measurements increases inferred gross primary productivity estimates

Published
2019
Full Text
View/download PDF

22. Drought impact on carbon and water cycling in a Mediterranean Quercus suber L. woodland during the extreme drought event in 2012

Author

Piayda, A, Dubbert, M, Rebmann, C, Kolle, O, Costa e Silva, F, Correia, A, Pereira, J S, Werner, C, Cuntz, Matthias, Department Computational Hydrosystems [UFZ Leipzig], Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), University of Bayreuth, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, and Universidade Técnica de Lisboa

Subjects
lcsh:Geology, lcsh:QH501-531, tree species, lcsh:QH540-549.5, Physiological, [SDV]Life Sciences [q-bio], lcsh:QE1-996.5, lcsh:Life, lcsh:Ecology, ecosystems
Abstract

Savannah-type ecosystems account for 26–30% of global gross primary productivity GPP, with water being one of the major driving factors. In Europe, savannah-type woodlands cover an area of about 1.5 million ha. Here, the recent past has shown a significant decrease in precipitation P in winter and spring as well as a decrease in total annual precipitation. Strong effects on local water balance and carbon sink strength have thus been reported due to changes in precipitation regime. The objective of this study is to quantify the impact of the extreme drought event in 2012 on the water balance, gross primary productivity and carbon sink strength of a typical Portuguese cork-oak woodland (montado) compared to the wet year of 2011. Physiological responses of the dominant tree species Quercus suber (L.) are disentangled employing combined photosynthesis and stomatal conductance modelling. Precipitation effectiveness ET/P increased from 86% in 2011 to 122% in the 2012 dry year due to deep soil or groundwater access of the Q. suber trees leaving no water for groundwater replenishment. Understorey and overstorey GPP were strongly reduced, by 53 and 28%, respectively, in 2012 compared to 2011, due to the late onset of the autumn rains in 2011 and an additional severe winter/spring drought. However, the ecosystem was still a carbon sink in both years, but with a 38% reduced sink strength under extreme drought in 2012 compared to 2011. The combined photosynthesis–stomatal conductance model yielded the best results if it was allowed to adjust photosynthetic and stomatal parameters simultaneously. If stomatal response was modelled with the Leuning approach, which allows for a different sensitivity to vapour pressure deficit, the stomatal model parameters were highly coupled. A change in either of the parameters needed to be compensated by the other to guarantee a stable sensitivity of stomatal conductance to assimilation, independent of variations in vapour pressure deficit. The Q. suber trees showed a 37% reduced stomatal conductance during the drought period of 2012 compared to 2011, due to water supply limitations. In response to reduced leaf-internal CO2 availability, the trees strongly reduced the apparent maximum carboxylation rate by 43% in 2012 compared to 2011. Unexpectedly, the optimum temperature Topt of the maximum electron transport rate decreased during the drought period, enhancing the susceptibility of the trees to high temperature stress during the summer. Our results suggest that, if the trend of decreasing annual precipitation and changed precipitation patterns on the Iberian Peninsula continues, sustained effects on local groundwater reservoirs, understorey species composition and tree mortality have to be expected in the long term. To model the effect of drought on the montado ecosystem successfully, variable apparent maximum carboxylation rate Vc,max, stomatal conductance parameter m and vapour pressure deficit sensitivity parameter D0 need to be incorporated into photosynthesis–stomatal conductance modelling.

Published
2018
Full Text
View/download PDF

23. CO2 exchange and carbon balance in two grassland sites on eutrophic drained peat soils

Author

Veenendaal, E. M., Kolle, O., Leffelaar, P. A., Schrier-Uijl, A. P., Van Huissteden, J., Van Walsem, J., Möller, F., Berendse, F., Nature Conservation and Plant Ecology group, Nature Conservation and Plant Ecology Group, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Department of Plant Production Systems, Wageningen University and Research [Wageningen] (WUR), Department of Hydrology and Geo-Environmental Sciences [Amsterdam], Vrije Universiteit Amsterdam [Amsterdam] (VU), EGU, Publication, and Hydrology and Geo-environmental sciences

Subjects
interannual variability, methane emissions, water-vapor, lcsh:Life, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Plant Ecology and Nature Conservation, netherlands, netto ecosysteem koolstofbalans, flux measurements, net carbon, [SDU.ASTR] Sciences of the Universe [physics]/Astrophysics [astro-ph], nederland, ecosystem-atmosphere exchange, [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], lcsh:QH540-549.5, TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY, SDG 13 - Climate Action, eddy covariance, melkveehouderijsystemen, net ecosystem carbon balance, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, peatlands, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, eddy-covariantie, [SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph], [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:QE1-996.5, grasslands, wet grasslands, carbon dioxide, dioxide exchange, PE&RC, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, graslanden, lcsh:Geology, lcsh:QH501-531, kooldioxide, Plant Production Systems, [PHYS.ASTR.CO] Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Plantaardige Productiesystemen, [SDU.STU] Sciences of the Universe [physics]/Earth Sciences, Plantenecologie en Natuurbeheer, spatial variability, lcsh:Ecology, seasonal-variation, dairy farming systems, veengebieden
Abstract

In this study we investigated the role of intensive and extensive dairy farm practices on CO2 exchange and the carbon balance of peatlands by means of eddy covariance (EC) measurements. Year long EC measurements were made in two adjacent farm sites on peat soil in the western part of the Netherlands. One site (Stein) is a new meadow bird reserve and is managed predominantly by mowing in June and August. The second site (Oukoop) is an intensive dairy farm.In this study we investigated the role of intensive and extensive dairy farm practices on CO2 exchange and the carbon balance of peatlands by means of eddy covariance (EC) measurements. Year long EC measurements were made in two adjacent farm sites on peat soil in the western part of the Netherlands. One site (Stein) is a new meadow bird reserve and is managed predominantly by mowing in June and August. The second site (Oukoop) is an intensive dairy farm. Maximum photosynthetic uptake of the grass sward (range 2 to 34 mu mol CO2 m(-2) s(-1)) showed a close and similar linear relationship with Leaf Area Index (LAI; range 1 to 5) except in maturing hay meadows, where maximum photosynthetic uptake did not increase further. Apparent quantum yield varied between 0.02 and 0.08 (mean 0.045) mu mol CO2 mu mol(-1) photons at both sites and was significantly correlated with LAI during the growth season. Ecosystem Respiration at 10 degrees C (R-10) calculated from the year round data set was 3.35 mu mol CO2 m(-2) s(-1) at Stein and 3.69 mu mol CO2 m(-2) s(-1) at Oukoop. Both sites were a source of carbon in winter and a sink during summer with net ecosystem exchange varying between 50 to 100 mmol CO2 m(-2) d(-1) in winter to below -400 mmol CO2 m(-2) d(-1) in summer. Periodically, both sites became a source after mowing. Net annual ecosystem exchange (NEE) for Stein was -5.7 g C m(-2) a(-1) and for Oukoop 133.9 g C m(-2) a(-1). When biomass removal, manure applications and estimates of methane emissions ware taken into account, both eutrophic peat meadows are a strong source for C around 420 g C m(-2) a(-1).

Published
2018
Full Text
View/download PDF

24. Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO 2 and COS Flux Measurements

Author

Spielmann, F. M., primary, Wohlfahrt, G., additional, Hammerle, A., additional, Kitz, F., additional, Migliavacca, M., additional, Alberti, G., additional, Ibrom, A., additional, El‐Madany, T. S., additional, Gerdel, K., additional, Moreno, G., additional, Kolle, O., additional, Karl, T., additional, Peressotti, A., additional, and Delle Vedove, G., additional

Published
2019
Full Text
View/download PDF

25. Shifted energy fluxes, increased Bowen ratios, and reduced thaw depths linked with drainage-induced changes in permafrost ecosystem structure

Author

Göckede, M., Kittler, F., Kwon, M., Burjack, I., Heimann, M., Kolle, O., Zimov, N., Zimov, S., Department of Physics, and INAR Physics

Subjects
ARCTIC TUNDRA, CLIMATE-CHANGE, NORTHERN SIBERIA, WATER-BALANCE, HIGH-LATITUDE WETLANDS, SNOW-SHRUB INTERACTIONS, TUSSOCK TUNDRA, POLYGONAL TUNDRA SITE, SOIL TEMPERATURES, 114 Physical sciences, CARBON DYNAMICS
Abstract

Hydrologic conditions are a key factor in Arctic ecosystems, with strong influences on ecosystem structure and related effects on biogeophysical and biogeochemical processes. With systematic changes in water availability expected for large parts of the Northern high latitude region in the coming centuries, knowledge on shifts in ecosystem functionality triggered by altered water levels is crucial for reducing uncertainties in climate change predictions. Here, we present findings from paired ecosystem observations in Northeast Siberia that comprise a drained and a control site. At the former, the water table has been artificially lowered by up to 30 cm in summer for more than a decade. This sustained primary disturbance in hydrologic conditions has triggered a suite of secondary shifts in ecosystem properties, including vegetation community structure, snow cover dynamics, and radiation budget, all of which influence the net drainage effects. Reduced heat conductivity in dry organic soils was identified as the dominating drainage effect on energy budget and soil thermal regime. Through this effect, reduced heat transfer into deeper soil layers leads to shallower thaw depths, initially leading to a stabilization of organic permafrost soils, while the long-term effects on permafrost temperature trends still need to be assessed. At the same time, more energy is transferred back into the atmosphere in the drained area, with the largest fraction attributed to the sensible heat flux. Accordingly, this increase in vertical heat transfer will act as a positive feedback to permafrost degradation triggered by the warming of the lower atmospheric surface layer.

Published
2017

26. Long-Term Drainage Reduces CO2 Uptake and CH4 Emissions in a Siberian Permafrost Ecosystem

Author

Kittler, F., Heimann, M., Kolle, O., Zimov, N., Zimov, S., Göckede, M., and Department of Physics

Subjects
ARCTIC TUNDRA, POLYGONAL TUNDRA, COLD SEASON, FLUX MEASUREMENTS, TUSSOCK TUNDRA, 114 Physical sciences, CARBON-DIOXIDE, climate change, Arctic, TEMPERATURE-DEPENDENCE, GROWING-SEASON, METHANE EMISSIONS, eddy-covariance, carbon fluxes, ATMOSPHERE EXCHANGE, permafrost
Abstract

Permafrost landscapes in northern high latitudes with their massive organic carbon stocks are an important, poorly known, component of the global carbon cycle. However, in light of future Arctic warming, the sustainability of these carbon pools is uncertain. To a large part, this is due to a limited understanding of the carbon cycle processes because of sparse observations in Arctic permafrost ecosystems. Here we present an eddy covariance data set covering more than 3 years of continuous CO2 and CH4 flux observations within a moist tussock tundra ecosystem near Chersky in north-eastern Siberia. Through parallel observations of a disturbed (drained) area and a control area nearby, we aim to evaluate the long-term effects of a persistently lowered water table on the net vertical carbon exchange budgets and the dominating biogeochemical mechanisms. Persistently drier soils trigger systematic shifts in the tundra ecosystem carbon cycle patterns. Both, uptake rates of CO2 and emissions of CH4 decreased. Year-round measurements emphasize the importance of the non-growing seasonin particular the zero-curtain period in the fallto the annual budget. Approximately 60% of the CO2 uptake in the growing season is lost during the cold seasons, while CH4 emissions during the non-growing season account for 30% of the annual budget. Year-to-year variability in temperature conditions during the late growing season was identified as the primary control of the interannual variability observed in the CO2 and CH4 fluxes.

Published
2017

28. ICOS eddy covariance flux-station site setup: a review

Author

Rebmann, Corinna, Aubinet, M., Schmid, H.P., Arriga, N., Aurela, M., Burba, G., Clement, R., de Ligne, A., Fratini, G., Gielen, B., Grace, J., Graf, A., Gross, P., Haapanala, S., Herbst, M., Hörtnagl, L., Ibrom, A., Joly, L., Kljun, N., Kolle, O., Kowalski, A., Lindroth, A., Loustau, D., Mammarella, I., Mauder, M., Merbold, L., Metzger, S., Mölder, M., Montagnani, L., Papale, D., Pavelka, M., Peichl, M., Roland, M., Serrano-Ortiz, P., Siebicke, L., Steinbrecher, R., Tuovinen, J.-P., Vesala, T., Wohlfahrt, G., Franz, D., Rebmann, Corinna, Aubinet, M., Schmid, H.P., Arriga, N., Aurela, M., Burba, G., Clement, R., de Ligne, A., Fratini, G., Gielen, B., Grace, J., Graf, A., Gross, P., Haapanala, S., Herbst, M., Hörtnagl, L., Ibrom, A., Joly, L., Kljun, N., Kolle, O., Kowalski, A., Lindroth, A., Loustau, D., Mammarella, I., Mauder, M., Merbold, L., Metzger, S., Mölder, M., Montagnani, L., Papale, D., Pavelka, M., Peichl, M., Roland, M., Serrano-Ortiz, P., Siebicke, L., Steinbrecher, R., Tuovinen, J.-P., Vesala, T., Wohlfahrt, G., and Franz, D.

Abstract

The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features.

Published
2018

29. ICOS eddy covariance flux-station site setup: a review

Author

Rebmann, C., Aubinet, M., Scmid, HaPe, Arriga, N., Aurela, M., Burba, G., Clement, R., De Ligne, A., Fratini, G., Gielen, B., Grace, J., Graf, A., Gross, P., Haapanala, S., Herbst, M., Hörtnagl, L., Ibrom, Andreas, Joly, L., Kljun, N., Kolle, O, Kowalski, A., Lindroth, A., Loustau, D., Mammarella, I., Mauder, M., Merbold, L., Metzger, S., Mölder, M., Montagnani, L., Papale, D., Pavelka, M., Peichl, M., Roland, M., Serrano-Ortiz, P., Siebicke, L., Steinbrecher, R., Tuovinen, J., Vesala, T., Wohlfahrt, G., Franz, D., Rebmann, C., Aubinet, M., Scmid, HaPe, Arriga, N., Aurela, M., Burba, G., Clement, R., De Ligne, A., Fratini, G., Gielen, B., Grace, J., Graf, A., Gross, P., Haapanala, S., Herbst, M., Hörtnagl, L., Ibrom, Andreas, Joly, L., Kljun, N., Kolle, O, Kowalski, A., Lindroth, A., Loustau, D., Mammarella, I., Mauder, M., Merbold, L., Metzger, S., Mölder, M., Montagnani, L., Papale, D., Pavelka, M., Peichl, M., Roland, M., Serrano-Ortiz, P., Siebicke, L., Steinbrecher, R., Tuovinen, J., Vesala, T., Wohlfahrt, G., and Franz, D.

Abstract

The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features.

Published
2018

30. Continuous low-maintenance CO2/CH4/H2O measurements at the Zotino Tall Tower Observatory (ZOTTO) in Central Siberia

Author

Winderlich, J., Chen, H., Gerbig, C., Seifert, T., Kolle, O., Lavrič, J., Kaiser, C., Höfer, A., Heimann, M., Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:TA715-787, lcsh:Earthwork. Foundations, lcsh:TA170-171, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Environmental engineering
Abstract

To monitor the continental carbon cycle, a fully automated low maintenance measurement system is installed at the Zotino Tall Tower Observatory in Central Siberia (ZOTTO, 60 degrees 48'N, 89 degrees 21') since April 2009. A cavity ring-down spectroscopy (CRDS) analyzer continuously measures carbon dioxide (CO2) and methane (CH4) from six heights up to 301 m a.g.l. Buffer volumes in each air line remove short term CO2 and CH4 mixing ratio fluctuations associated with turbulence, and allow continuous, near-concurrent measurements from all tower levels. Instead of drying the air sample, the simultaneously measured water vapor is used to correct the dilution and pressure-broadening effects for the accurate determination of dry air CO2 and CH4 mixing ratios. The stability of the water vapor correction was demonstrated by repeated laboratory and field tests. The effect of molecular adsorption in the wet air lines was shown to be negligible. The low consumption of four calibration tanks that need recalibration only on decadal timescale further reduces maintenance. The measurement precision (accuracy) of 0.04 ppm (0.09 ppm) for CO2 and 0.3 ppb (1.5 ppb) for CH4 is compliant with the WMO recommendations. The data collected so far (until April 2010) reveals a seasonal cycle amplitude for CO2 of 30.4 ppm at the 301 m level.

Published
2010
Full Text
View/download PDF

31. Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO2 and COS Flux Measurements.

Author

Spielmann, F. M., Wohlfahrt, G., Hammerle, A., Kitz, F., Migliavacca, M., Alberti, G., Ibrom, A., El‐Madany, T. S., Gerdel, K., Moreno, G., Kolle, O., Karl, T., Peressotti, A., and Delle Vedove, G.

Subjects
ECOSYSTEMS, CARBON dioxide, PHOTOSYNTHESIS, ATMOSPHERE, HYDROGEN sulfide
Abstract

Gross primary productivity (GPP), the gross uptake of carbon dioxide (CO2) by plant photosynthesis, is the primary driver of the land carbon sink, which presently removes around one quarter of the anthropogenic CO2 emissions each year. GPP, however, cannot be measured directly and the resulting uncertainty undermines our ability to project the magnitude of the future land carbon sink. Carbonyl sulfide (COS) has been proposed as an independent proxy for GPP as it diffuses into leaves in a fashion very similar to CO2, but in contrast to the latter is generally not emitted. Here we use concurrent ecosystem‐scale flux measurements of CO2 and COS at four European biomes for a joint constraint on CO2 flux partitioning. The resulting GPP estimates generally agree with classical approaches relying exclusively on CO2 fluxes but indicate a systematic underestimation under low light conditions, demonstrating the importance of using multiple approaches for constraining present‐day GPP. Plain Language Summary: Plants are Earth's biggest contributor for cleaning the atmosphere of carbon dioxide and remove around one quarter of the carbon dioxide emitted by humans each year. However, this contribution cannot be measured directly and has to be inferred or modelled on the basis of related parameters. This introduces large uncertainties, which in turn undermine our ability to accurately create future climate scenarios. Recent research revealed that the trace gas carbonyl sulfide is taken up by plants in a very similar way as carbon dioxide and offers us an additional way of quantifying the carbon dioxide uptake by photosynthesis. Here we use joint measurements of the carbon dioxide and carbonyl sulfide exchange to infer plant carbon dioxide uptake, demonstrating the advantage of using multiple approaches. We apply our method at four major European ecosystems and show that previous approaches, based solely on carbon dioxide, may have underestimated the plant carbon dioxide uptake. Key Points: Traditionally gross primary productivity is inferred from ecosystem‐scale CO2 flux measurementsThe proposed joint assimilation of CO2 and COS flux measurements avoids the need to specify the leaf relative uptake rate of COS a prioriThe additional information content of ecosystem‐scale COS flux measurements increases inferred gross primary productivity estimates [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

32. Empfehlung zur Einrichtung eines nationalen Observatorien-Netzes für die terrestrische Ökosystemforschung : Abschlussbericht der Arbeitsgruppe „Infrastrukturen in der terrestrischen Forschung“ der Allianz der Wissenschaftsorganisationen

Author

Kögel-Knabner, I., Teutsch, Georg, Adrian, R., von Blanckenburg, F., Flügge, U.-I., Kolle, O., Kleinn, C., Küsel, K., Lischeid, G., Löw, A., Schäfers, C., Schmid, P., Simmer, C., Vereecken, H., Walz, R., Haase, P., Lütkemeier, E., Weymann, D., Brüchmann, C., Schmitz-Möller, P., Weber, U., Kögel-Knabner, I., Teutsch, Georg, Adrian, R., von Blanckenburg, F., Flügge, U.-I., Kolle, O., Kleinn, C., Küsel, K., Lischeid, G., Löw, A., Schäfers, C., Schmid, P., Simmer, C., Vereecken, H., Walz, R., Haase, P., Lütkemeier, E., Weymann, D., Brüchmann, C., Schmitz-Möller, P., and Weber, U.

Abstract

Im Jahr 2017 hat die Arbeitsgruppe der DFG-Senatskommission  „Infrastrukturen in der terrestrischen Forschung“ der Allianz der Wissenschaftsorganisationen ihren Abschluss-Bericht „Infrastrukturen in der terrestrischen Forschung – Empfehlung zur Einrichtung eines nationalen Observatorien-Netzes“ verfasst, der als Diskussionsgrundlage für die wissenschaftliche Community, Observatorien-Betreiber und Förderorganisationen dient.Im Abschlussbericht empfiehlt die Allianz-Arbeitsgruppe die Einrichtung eines Observatorien-Netzes für die terrestrische Ökosystemforschung. Ein solches Netzwerk kann den Kern eines national abgestimmten Langzeit-Konzepts bilden, und dazu beitragen, die noch weitgehend fragmentierte Langzeitforschung in Deutschland zu integrieren. Zugleich eignet es sich als Nukleus für den Aufbau einer national abgestimmten Koordinationsstruktur der terrestrischen Umweltbeobachtung und ihres Datenmanagements. Die Allianz-Arbeitsgruppe empfiehlt, dass die Aufnahme von Observatorien in das Netzwerk über ein Ausschreibungs- und Bewerbungsverfahren entschieden werden soll, um das Potenzial der bestehenden Observatorien so umfassend wie möglich zu berücksichtigen. ihren Abschluss-Bericht „Infrastrukturen in der terrestrischen Forschung – Empfehlung zur Einrichtung eines nationalen Observatorien-Netzes“ verfasst, der als Diskussionsgrundlage für die wissenschaftliche Community, Observatorien-Betreiber und Förderorganisationen dient.

Published
2017

33. Plant functional traits and canopy structure control the relationship between photosynthetic CO2 uptake and far-red sun-induced fluorescence in a Mediterranean grassland under different nutrient availability

Author

Migliavacca, M, Perez Priego, O, Rossini, M, El Madany, T, Moreno, G, van der Tol, C, Rascher, U, Berninger, A, Bessenbacher, V, Burkart, A, Carrara, A, Fava, F, Guan, J, Hammer, T, Henkel, K, Juarez Alcalde, E, Julitta, T, Kolle, O, Martín, M, Musavi, T, Pacheco Labrador, J, Pérez Burgueño, A, Wutzler, T, Zaehle, S, Reichstein, M, Reichstein, M., ROSSINI, MICOL, Migliavacca, M, Perez Priego, O, Rossini, M, El Madany, T, Moreno, G, van der Tol, C, Rascher, U, Berninger, A, Bessenbacher, V, Burkart, A, Carrara, A, Fava, F, Guan, J, Hammer, T, Henkel, K, Juarez Alcalde, E, Julitta, T, Kolle, O, Martín, M, Musavi, T, Pacheco Labrador, J, Pérez Burgueño, A, Wutzler, T, Zaehle, S, Reichstein, M, Reichstein, M., and ROSSINI, MICOL

Abstract

Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary production (GPP). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F760) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen–phosphorous (NP). Using the soil–canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration (Cab) and maximum carboxylation capacity (Vcmax)) affected the observed linear relationship between F760 and GPP. We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F760. Changes in canopy structure mainly control the GPP–F760 relationship, with a secondary effect of Cab and Vcmax. In order to exploit F760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered.

Published
2017

34. Complementarity among four highly productive grassland species depends on resource availability

Author

Roscher, Christiane, Schmid, B., Kolle, O., Schulze, E.-D., Roscher, Christiane, Schmid, B., Kolle, O., and Schulze, E.-D.

Abstract

Positive species richness–productivity relationships are common in biodiversity experiments, but how resource availability modifies biodiversity effects in grass–legume mixtures composed of highly productive species is yet to be explicitly tested. We addressed this question by choosing two grasses (Arrhenatherum elatius and Dactylis glomerata) and two legumes (Medicago × varia and Onobrychis viciifolia) which are highly productive in monocultures and dominant in mixtures (the Jena Experiment). We established monocultures, all possible two- and three-species mixtures, and the four-species mixture under three different resource supply conditions (control, fertilization, and shading). Compared to the control, community biomass production decreased under shading (−56 %) and increased under fertilization (+12 %). Net diversity effects (i.e., mixture minus mean monoculture biomass) were positive in the control and under shading (on average +15 and +72 %, respectively) and negative under fertilization (−10 %). Positive complementarity effects in the control suggested resource partitioning and facilitation of growth through symbiotic N2 fixation by legumes. Positive complementarity effects under shading indicated that resource partitioning is also possible when growth is carbon-limited. Negative complementarity effects under fertilization suggested that external nutrient supply depressed facilitative grass–legume interactions due to increased competition for light. Selection effects, which quantify the dominance of species with particularly high monoculture biomasses in the mixture, were generally small compared to complementarity effects, and indicated that these species had comparable competitive strengths in the mixture. Our study shows that resource availability has a strong impact on the occurrence of positive diversity effects among tall and highly productive grass and legume species.

Published
2016

36. Drought impact on carbon and water cycling in a Mediterranean Quercus suber L. woodland during the extreme drought event in 2012

Author

Dubbert, M, Rebmann, C, Kolle, O, Costa e Silva, F, Correia, A, Pereira, J S, Werner, C, Cuntz, Matthias, and Piayda, A

Subjects
ecosystems, tree species, Physiological
Abstract

Savannah-type ecosystems account for 26–30 % of global gross primary productivity GPP, with water being one of the major driving factors. In Europe, savannah-type woodlands cover an area of about 1.5 million ha. Here, the recent past has shown a significant decrease in precipitation P in winter and spring as well as a decrease in total annual precipitation. Strong effects on local water balance and car- bon sink strength have thus been reported due to changes in precipitation regime. The objective of this study is to quantify the impact of the extreme drought event in 2012 on the water balance, gross primary productivity and carbon sink strength of a typ- ical Portuguese cork-oak woodland (montado) compared to the wet year of 2011. Physiological responses of the dom- inant tree species Quercus suber (L.) are disentangled em- ploying combined photosynthesis and stomatal conductance modelling. Precipitation effectiveness ET/P increased from 86 % in 2011 to 122% in the 2012 dry year due to deep soil or groundwater access of the Q. suber trees leaving no water for groundwater replenishment. Understorey and overstorey GPP were strongly reduced, by 53 and 28%, respectively, in 2012 compared to 2011, due to the late onset of the au- tumn rains in 2011 and an additional severe winter/spring drought. However, the ecosystem was still a carbon sink in both years, but with a 38 % reduced sink strength under ex- treme drought in 2012 compared to 2011. The combined photosynthesis–stomatal conductance model yielded the best results if it was allowed to adjust photosynthetic and stomatal parameters simultaneously. If stomatal response was mod- elled with the Leuning approach, which allows for a differ- ent sensitivity to vapour pressure deficit, the stomatal model parameters were highly coupled. A change in either of the parameters needed to be compensated by the other to guar- antee a stable sensitivity of stomatal conductance to assim- ilation, independent of variations in vapour pressure deficit. The Q. suber trees showed a 37 % reduced stomatal conduc- tance during the drought period of 2012 compared to 2011, due to water supply limitations. In response to reduced leaf- internal CO2 availability, the trees strongly reduced the ap- parent maximum carboxylation rate by 43 % in 2012 com- pared to 2011. Unexpectedly, the optimum temperature Topt of the maximum electron transport rate decreased during the drought period, enhancing the susceptibility of the trees to high temperature stress during the summer. Our results suggest that, if the trend of decreasing an- nual precipitation and changed precipitation patterns on the Iberian Peninsula continues, sustained effects on lo- cal groundwater reservoirs, understorey species composition and tree mortality have to be expected in the long term. To model the effect of drought on the montado ecosystem successfully, variable apparent maximum carboxylation rate Vc,max, stomatal conductance parameter m and vapour pres- sure deficit sensitivity parameter D0 need to be incorporated into photosynthesis–stomatal conductance modelling.

Published
2014

37. Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO2and COS Flux Measurements

Author

Spielmann, F. M., Wohlfahrt, G., Hammerle, A., Kitz, F., Migliavacca, M., Alberti, G., Ibrom, A., El‐Madany, T. S., Gerdel, K., Moreno, G., Kolle, O., Karl, T., Peressotti, A., and Delle Vedove, G.

Abstract

Gross primary productivity (GPP), the gross uptake of carbon dioxide (CO2) by plant photosynthesis, is the primary driver of the land carbon sink, which presently removes around one quarter of the anthropogenic CO2emissions each year. GPP, however, cannot be measured directly and the resulting uncertainty undermines our ability to project the magnitude of the future land carbon sink. Carbonyl sulfide (COS) has been proposed as an independent proxy for GPP as it diffuses into leaves in a fashion very similar to CO2, but in contrast to the latter is generally not emitted. Here we use concurrent ecosystem‐scale flux measurements of CO2and COS at four European biomes for a joint constraint on CO2flux partitioning. The resulting GPP estimates generally agree with classical approaches relying exclusively on CO2fluxes but indicate a systematic underestimation under low light conditions, demonstrating the importance of using multiple approaches for constraining present‐day GPP. Plants are Earth's biggest contributor for cleaning the atmosphere of carbon dioxide and remove around one quarter of the carbon dioxide emitted by humans each year. However, this contribution cannot be measured directly and has to be inferred or modelled on the basis of related parameters. This introduces large uncertainties, which in turn undermine our ability to accurately create future climate scenarios. Recent research revealed that the trace gas carbonyl sulfide is taken up by plants in a very similar way as carbon dioxide and offers us an additional way of quantifying the carbon dioxide uptake by photosynthesis. Here we use joint measurements of the carbon dioxide and carbonyl sulfide exchange to infer plant carbon dioxide uptake, demonstrating the advantage of using multiple approaches. We apply our method at four major European ecosystems and show that previous approaches, based solely on carbon dioxide, may have underestimated the plant carbon dioxide uptake. Traditionally gross primary productivity is inferred from ecosystem‐scale CO2flux measurementsThe proposed joint assimilation of CO2and COS flux measurements avoids the need to specify the leaf relative uptake rate of COS a prioriThe additional information content of ecosystem‐scale COS flux measurements increases inferred gross primary productivity estimates

Published
2019
Full Text
View/download PDF

39. Calibration of column-averaged CH4 over European TCCON FTS sites with airborne in-situ measurements

Author

Geibel, M., Messerschmidt, J., Gerbig, C., Blumenstock, T., Chen, H., Hase, F., Kolle, O., Lavrič, J. V., Notholt, J., Palm, M., Rettinger, M., Schmidt, M., Sussmann, R., Warneke, T., Feist, D. G., Isotope Research, Molecular Pharmacology, Groningen Research Institute for Asthma and COPD (GRIAC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-RAMCES (ICOS-RAMCES), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
lcsh:Chemistry, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Earth sciences, lcsh:QD1-999, OBSERVING NETWORK, ddc:550, SPECTRA, CO2, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Physics, lcsh:QC1-999, SYSTEM, GREENHOUSE GASES
Abstract

In September/October 2009, six European ground-based Fourier Transform Spectrometers (FTS) of the Total Carbon Column Observation Network (TCCON) were calibrated for the first time using aircraft measurements. The campaign was part of the Infrastructure for Measurement of the European Carbon Cycle (IMECC) project. During this campaign, altitude profiles of several trace gases and meteorological parameters were taken close to the FTS sites (typically within 1–2 km distance for flight altitudes below 5000 m). Profiles of CO2, CH4, CO and H2O were measured continuously. N2O, H2, and SF6 were later derived from flask measurements. The aircraft data had a vertical coverage ranging from approximately 300 to 13 000 m, corresponding to ~80% of the total atmospheric column seen by the FTS. This study summarizes the calibration results for CH4. The resulting calibration factor of 0.978 ± 0.002 (±1 σ) from the IMECC campaign agreed very well with the results that Wunch et al. (2010) had derived for TCCON instruments in North America, Australia, New Zealand, and Japan using similar methods. By combining our results with the data of Wunch et al. (2010), the uncertainty of the calibration factor could be reduced by a factor of three (compared to using only IMECC or only Wunch et al. (2010) data). A careful analysis of the calibration method used by Wunch et al. (2010) revealed that the incomplete vertical coverage of the aircraft profiles can lead to a bias in the calibration factor. This bias can be compensated with a new iterative approach that we developed. Using this improved method, we derived a significantly lower calibration factor of 0.974 ± 0.002 (±1 σ). This corresponds to a correction of all TCCON CH4 measurements by roughly −7 ppb.

Published
2012
Full Text
View/download PDF

40. Methane airborne measurements and comparison to global models during BARCA

Author

Beck, V., Chen, H., Gerbig, C, Bergamaschi, P., Bruhwiler, L., Houweling, S., Röckmann, T., Kolle, O., Steinbach, J., Koch, T., Sapart, C.J., van der Veen, C., Frankenberg, C., Andreae, M.O., Artaxo, P., Longo, K.M., Wofsy, S.C., Marine and Atmospheric Research, Dep Natuurkunde, and Sub Atmospheric physics and chemistry

Abstract

Tropical regions, especially the Amazon region, account for large emissions of methane (CH4). Here, we present CH4 observations from two airborne campaigns conducted within the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) project in the Amazon basin in November 2008 (end of the dry season) and May 2009 (end of the wet season). We performed continuous measurements of CH4 onboard an aircraft for the first time in the Amazon region, covering the whole Amazon basin with over 150 vertical profiles between altitudes of 500 m and 4000 m. The observations support the finding of previous ground-based, airborne, and satellite measurements that the Amazon basin is a large source of atmospheric CH4. Isotope analysis verified that the majority of emissions can be attributed to CH4 emissions from wetlands, while urban CH4 emissions could be also traced back to biogenic origin. A comparison of five TM5 based global CH4 inversions with the observations clearly indicates that the inversions using SCIAMACHY observations represent the BARCA observations best. The calculated CH4 flux estimate obtained from the mismatch between observations and TM5-modeled CH4 fields ranges from 36 to 43 mg m−2 d−1 for the Amazon lowland region.

Published
2012

41. Calibration of TCCON column-averaged CO2: the first aircraft campaign over European TCCON sites

Author

Messerschmidt, J., Geibel, M., Blumenstock, T., Chen, H., Deutscher, N., Engel, A., Feist, D., Gerbig, C., Gisi, M., Hase, F., Katrynski, K., Kolle, O., Lavrič, J., Notholt, J., Palm, M., Ramonet, M., Rettinger, M., Schmidt, M., Sussmann, R., Toon, G., Truong, F., Warneke, T., Wennberg, P., Wunch, D., Xueref-Remy, Irène, Isotope Research, Molecular Pharmacology, Groningen Research Institute for Asthma and COPD (GRIAC), Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Karlsruhe Institute of Technology (KIT), Institute for Atmospheric and Environmental Sciences [Frankfurt/Main] (IAU), Goethe-University Frankfurt am Main, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-RAMCES (ICOS-RAMCES), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Chimie Atmosphérique Expérimentale (CAE), California Institute of Technology (CALTECH), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, PROFILES, FOURIER-TRANSFORM SPECTROMETRY, lcsh:QC1-999, TRANSPORT, TROPOSPHERE, lcsh:Chemistry, LOWERMOST STRATOSPHERE, CARBON-DIOXIDE, lcsh:QD1-999, OBSERVING NETWORK, ddc:550, SPECTRA, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Physics, SYSTEM, GREENHOUSE GASES
Abstract

The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25% (1-σ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.1% ± 0.2% low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellites.

Published
2011
Full Text
View/download PDF

42. Sun-induced chlorophyll fluorescence and photochemical reflectance index improve remote-sensing gross primary production estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Author

Perez Priego, O, Guan, J, Rossini, M, Fava, F, Wutzler, T, Moreno, G, Carvalhais, N, Carrara, A, Kolle, O, Julitta, T, Schrumpf, M, Reichstein, M, Migliavacca, M, Migliavacca, M., ROSSINI, MICOL, FAVA, FRANCESCO PIETRO, JULITTA, TOMMASO, Perez Priego, O, Guan, J, Rossini, M, Fava, F, Wutzler, T, Moreno, G, Carvalhais, N, Carrara, A, Kolle, O, Julitta, T, Schrumpf, M, Reichstein, M, Migliavacca, M, Migliavacca, M., ROSSINI, MICOL, FAVA, FRANCESCO PIETRO, and JULITTA, TOMMASO

Abstract

This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different nitrogen (N) and phosphorous (P) availability. Sun-induced chlorophyll fluorescence yield computed at 760 nm (Fy760), scaled photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy chambers on the same locations sampled by the spectrometers. We tested whether light-use efficiency (LUE) models driven by remote-sensing quantities (RSMs) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed higher GPP in the N-fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was closely related to the mean of plant N content across treatments (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments, but it is affected by N availability. Results from a cross-validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv =140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However, residua

Published
2015

43. Interpreting canopy development and physiology using a European phenology camera network at flux sites

Author

Wingate, L., Ogee, J., Cremonese, E., Filippa, G., Mizunuma, T., Migliavacca, M., Moisy, C., Wilkinson, M., Moureaux, C., Wohlfahrt, G., Hammerle, A., Hoertnagl, L., Gimeno, C., Porcar-Castell, A., Galvagno, M., Nakaji, T., Morison, J., Kolle, O., Knohl, A., Kutsch, W., Kolari, P., Nikinmaa, E., Ibrom, A., Gielen, B., Eugster, W., Balzarolo, M., Papale, D., Klumpp, K., Koestner, B., Gruenwald, T., Joffre, R., Ourcival, J. -M., Hellstrom, M., Lindroth, A., George, C., Longdoz, B., Genty, B., Levula, J., Heinesch, B., Sprintsin, M., Yakir, D., Manise, T., Guyon, D., Ahrends, H., Plaza-Aguilar, A., Guan, J. H., Grace, J., Wingate, L., Ogee, J., Cremonese, E., Filippa, G., Mizunuma, T., Migliavacca, M., Moisy, C., Wilkinson, M., Moureaux, C., Wohlfahrt, G., Hammerle, A., Hoertnagl, L., Gimeno, C., Porcar-Castell, A., Galvagno, M., Nakaji, T., Morison, J., Kolle, O., Knohl, A., Kutsch, W., Kolari, P., Nikinmaa, E., Ibrom, A., Gielen, B., Eugster, W., Balzarolo, M., Papale, D., Klumpp, K., Koestner, B., Gruenwald, T., Joffre, R., Ourcival, J. -M., Hellstrom, M., Lindroth, A., George, C., Longdoz, B., Genty, B., Levula, J., Heinesch, B., Sprintsin, M., Yakir, D., Manise, T., Guyon, D., Ahrends, H., Plaza-Aguilar, A., Guan, J. H., and Grace, J.

Abstract

Plant phenological development is orchestrated through subtle changes in photoperiod, temperature, soil moisture and nutrient availability. Presently, the exact timing of plant development stages and their response to climate and management practices are crudely represented in land surface models. As visual observations of phenology are laborious, there is a need to supplement long-term observations with automated techniques such as those provided by digital repeat photography at high temporal and spatial resolution. We present the first synthesis from a growing observational network of digital cameras installed on towers across Europe above deciduous and evergreen forests, grasslands and croplands, where vegetation and atmosphere CO2 fluxes are measured continuously. Using colour indices from digital images and using piecewise regression analysis of time series, we explored whether key changes in canopy phenology could be detected automatically across different land use types in the network. The piecewise regression approach could capture the start and end of the growing season, in addition to identifying striking changes in colour signals caused by flowering and management practices such as mowing. Exploring the dates of green-up and senescence of deciduous forests extracted by the piecewise regression approach against dates estimated from visual observations, we found that these phenological events could be detected adequately (RMSE < 8 and 11 days for leaf out and leaf fall, respectively). We also investigated whether the seasonal patterns of red, green and blue colour fractions derived from digital images could be modelled mechanistically using the PROSAIL model parameterised with information of seasonal changes in canopy leaf area and leaf chlorophyll and carotenoid concentrations. From a model sensitivity analysis we found that variations in colour fractions, and in particular the late spring 'green hump' observed repeatedly in deciduous broadleaf canopies ac

Published
2015

44. Sun-induced chlorophyll fluorescence and photochemical reflectance index improve remote-sensing gross primary production estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Author

Perez-Priego, O., primary, Guan, J., additional, Rossini, M., additional, Fava, F., additional, Wutzler, T., additional, Moreno, G., additional, Carvalhais, N., additional, Carrara, A., additional, Kolle, O., additional, Julitta, T., additional, Schrumpf, M., additional, Reichstein, M., additional, and Migliavacca, M., additional

Published
2015
Full Text
View/download PDF

45. Interpreting canopy development and physiology using a European phenology camera network at flux sites

Author

Wingate, L., primary, Ogée, J., additional, Cremonese, E., additional, Filippa, G., additional, Mizunuma, T., additional, Migliavacca, M., additional, Moisy, C., additional, Wilkinson, M., additional, Moureaux, C., additional, Wohlfahrt, G., additional, Hammerle, A., additional, Hörtnagl, L., additional, Gimeno, C., additional, Porcar-Castell, A., additional, Galvagno, M., additional, Nakaji, T., additional, Morison, J., additional, Kolle, O., additional, Knohl, A., additional, Kutsch, W., additional, Kolari, P., additional, Nikinmaa, E., additional, Ibrom, A., additional, Gielen, B., additional, Eugster, W., additional, Balzarolo, M., additional, Papale, D., additional, Klumpp, K., additional, Köstner, B., additional, Grünwald, T., additional, Joffre, R., additional, Ourcival, J.-M., additional, Hellstrom, M., additional, Lindroth, A., additional, George, C., additional, Longdoz, B., additional, Genty, B., additional, Levula, J., additional, Heinesch, B., additional, Sprintsin, M., additional, Yakir, D., additional, Manise, T., additional, Guyon, D., additional, Ahrends, H., additional, Plaza-Aguilar, A., additional, Guan, J. H., additional, and Grace, J., additional

Published
2015
Full Text
View/download PDF

46. Retrieval and validation of carbon dioxide, methane and water vapor for the Canary Islands IR-laser occultation experiment

Author

Proschek, V., primary, Kirchengast, G., additional, Schweitzer, S., additional, Brooke, J. S. A., additional, Bernath, P. F., additional, Thomas, C. B., additional, Wang, J.-G., additional, Tereszchuk, K. A., additional, González Abad, G., additional, Hargreaves, R. J., additional, Beale, C. A., additional, Harrison, J. J., additional, Martin, P. A., additional, Kasyutich, V. L., additional, Gerbig, C., additional, Kolle, O., additional, and Loescher, A., additional

Published
2015
Full Text
View/download PDF

47. Sun-induced Chlorophyll fluorescence and PRI improve remote sensing GPP estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Author

Perez-Priego, O., primary, Guan, J., additional, Rossini, M., additional, Fava, F., additional, Wutzler, T., additional, Moreno, G., additional, Carvalhais, N., additional, Carrara, A., additional, Kolle, O., additional, Julitta, T., additional, Schrumpf, M., additional, Reichstein, M., additional, and Migliavacca, M., additional

Published
2015
Full Text
View/download PDF

48. Interpreting canopy development and physiology using the EUROPhen camera network at flux sites

Author

Wingate, L., primary, Ogée, J., additional, Cremonese, E., additional, Filippa, G., additional, Mizunuma, T., additional, Migliavacca, M., additional, Moisy, C., additional, Wilkinson, M., additional, Moureaux, C., additional, Wohlfahrt, G., additional, Hammerle, A., additional, Hörtnagl, L., additional, Gimeno, C., additional, Porcar-Castell, A., additional, Galvagno, M., additional, Nakaji, T., additional, Morison, J., additional, Kolle, O., additional, Knohl, A., additional, Kutsch, W., additional, Kolari, P., additional, Nikinmaa, E., additional, Ibrom, A., additional, Gielen, B., additional, Eugster, W., additional, Balzarolo, M., additional, Papale, D., additional, Klumpp, K., additional, Köstner, B., additional, Grünwald, T., additional, Joffre, R., additional, Ourcival, J.-M., additional, Hellstrom, M., additional, Lindroth, A., additional, Charles, G., additional, Longdoz, B., additional, Genty, B., additional, Levula, J., additional, Heinesch, B., additional, Sprintsin, M., additional, Yakir, D., additional, Manise, T., additional, Guyon, D., additional, Ahrends, H., additional, Plaza-Aguilar, A., additional, Guan, J. H., additional, and Grace, J., additional

Published
2015
Full Text
View/download PDF

49. Supplementary material to "Interpreting canopy development and physiology using the EUROPhen camera network at flux sites"

Author

Wingate, L., primary, Ogée, J., additional, Cremonese, E., additional, Filippa, G., additional, Mizunuma, T., additional, Migliavacca, M., additional, Moisy, C., additional, Wilkinson, M., additional, Moureaux, C., additional, Wohlfahrt, G., additional, Hammerle, A., additional, Hörtnagl, L., additional, Gimeno, C., additional, Porcar-Castell, A., additional, Galvagno, M., additional, Nakaji, T., additional, Morison, J., additional, Kolle, O., additional, Knohl, A., additional, Kutsch, W., additional, Kolari, P., additional, Nikinmaa, E., additional, Ibrom, A., additional, Gielen, B., additional, Eugster, W., additional, Balzarolo, M., additional, Papale, D., additional, Klumpp, K., additional, Köstner, B., additional, Grünwald, T., additional, Joffre, R., additional, Ourcival, J.-M., additional, Hellstrom, M., additional, Lindroth, A., additional, Charles, G., additional, Longdoz, B., additional, Genty, B., additional, Levula, J., additional, Heinesch, B., additional, Sprintsin, M., additional, Yakir, D., additional, Manise, T., additional, Guyon, D., additional, Ahrends, H., additional, Plaza-Aguilar, A., additional, Guan, J. H., additional, and Grace, J., additional

Published
2015
Full Text
View/download PDF

50. Impact of Manaus City on the Amazon Green Ocean atmosphere: ozone production, precursor sensitivity and aerosol load

Author

Kuhn, U., Ganzeveld, L., Thielmann, A., Dindorf, T., Schebeske, G., Welling, M., Sciare, J., Roberts, G., Meixner, F., Kesselmeier, J., Lelieveld, J., Kolle, O., Ciccioli, P., Lloyd, J., Trentmann, J., Artaxo, P., Andreae, M., Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Chimie Atmosphérique Expérimentale (CAE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 010504 meteorology & atmospheric sciences, 15. Life on land, 010501 environmental sciences, 01 natural sciences, lcsh:QC1-999, lcsh:Chemistry, lcsh:QD1-999, 13. Climate action, 11. Sustainability, ddc:550, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Physics, 0105 earth and related environmental sciences
Abstract

As a contribution to the Large-Scale Biosphere-Atmosphere Experiment in Amazonia – Cooperative LBA Airborne Regional Experiment (LBA-CLAIRE-2001) field campaign in the heart of the Amazon Basin, we analyzed the temporal and spatial dynamics of the urban plume of Manaus City during the wet-to-dry season transition period in July 2001. During the flights, we performed vertical stacks of crosswind transects in the urban outflow downwind of Manaus City, measuring a comprehensive set of trace constituents including O3, NO, NO2, CO, VOC, CO2, and H2O. Aerosol loads were characterized by concentrations of total aerosol number (CN) and cloud condensation nuclei (CCN), and by light scattering properties. Measurements over pristine rainforest areas during the campaign showed low levels of pollution from biomass burning or industrial emissions, representative of wet season background conditions. The urban plume of Manaus City was found to be joined by plumes from power plants south of the city, all showing evidence of very strong photochemical ozone formation. One episode is discussed in detail, where a threefold increase in ozone mixing ratios within the atmospheric boundary layer occurred within a 100 km travel distance downwind of Manaus. Observation-based estimates of the ozone production rates in the plume reached 15 ppb h−1. Within the plume core, aerosol concentrations were strongly enhanced, with ΔCN/ΔCO ratios about one order of magnitude higher than observed in Amazon biomass burning plumes. ΔCN/ΔCO ratios tended to decrease with increasing transport time, indicative of a significant reduction in particle number by coagulation, and without substantial new particle nucleation occurring within the time/space observed. While in the background atmosphere a large fraction of the total particle number served as CCN (about 60–80% at 0.6% supersaturation), the CCN/CN ratios within the plume indicated that only a small fraction (16±12%) of the plume particles were CCN. The fresh plume aerosols showed relatively weak light scattering efficiency. The CO-normalized CCN concentrations and light scattering coefficients increased with plume age in most cases, suggesting particle growth by condensation of soluble organic or inorganic species. We used a Single Column Chemistry and Transport Model (SCM) to infer the urban pollution emission fluxes of Manaus City, implying observed mixing ratios of CO, NOx and VOC. The model can reproduce the temporal/spatial distribution of ozone enhancements in the Manaus plume, both with and without accounting for the distinct (high NOx) contribution by the power plants; this way examining the sensitivity of ozone production to changes in the emission rates of NOx. The VOC reactivity in the Manaus region was dominated by a high burden of biogenic isoprene from the background rainforest atmosphere, and therefore NOx control is assumed to be the most effective ozone abatement strategy. Both observations and models show that the agglomeration of NOx emission sources, like power plants, in a well-arranged area can decrease the ozone production efficiency in the near field of the urban populated cores. But on the other hand remote areas downwind of the city then bear the brunt, being exposed to increased ozone production and N-deposition. The simulated maximum stomatal ozone uptake fluxes were 4 nmol m−2 s−1 close to Manaus, and decreased only to about 2 nmol m−2 s−1 within a travel distance >1500 km downwind from Manaus, clearly exceeding the critical threshold level for broadleaf trees. Likewise, the simulated N deposition close to Manaus was ~70 kg N ha−1 a−1 decreasing only to about 30 kg N ha−1 a−1 after three days of simulation.

Published
2010
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results