Browsing by Subject "SPATIAL VARIABILITY"

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  • Niemi, Tero J.; Warsta, Lassi; Taka, Maija; Hickman, Brandon; Pulkkinen, Seppo; Krebs, Gerald; Moisseev, Dmitri N.; Koivusalo, Harri; Kokkonen, Teemu (2017)
    Rainfall-runoff simulations in urban environments require meteorological input data with high temporal and spatial resolutions. The availability of precipitation data is constantly increasing due to the shift towards more open data sharing. However, the applicability of such data for urban runoff assessments is often unknown. Here, the feasibility of Finnish Meteorological Institute's open rain gauge and open weather radar data as input sources was studied by conducting Storm Water Management Model simulations at a very small (33.5 ha) urban catchment in Helsinki, Finland. In addition to the open data sources, data were also available from two research gauges, one of them located on-site, and from a research radar. The results confirmed the importance of local precipitation measurements for urban rainfall-runoff simulations, implying the suitability of open gauge data to be largely dictated by the gauge's distance from the catchment. Performance of open radar data with 5 min and 1 km' resolution was acceptable in terms of runoff reproduction, albeit peak flows were constantly and flow volumes often underestimated. Gauge adjustment and advection interpolation were found to improve the quality of the radar data, and at least gauge adjustment should be performed when open radar data are used. Finally, utilizing dual-polarization capabilities of radars has a potential to improve rainfall estimates for high intensity storms although more research is still needed. (C) 2017 Elsevier B.V. All rights reserved.
  • Stoy, P. C.; Richardson, A. D.; Baldocchi, D. D.; Katul, G. G.; Stanovick, J.; Mahecha, M. D.; Reichstein, M.; Detto, M.; Law, B. E.; Wohlfahrt, G.; Arriga, N.; Campos, J.; McCaughey, J. H.; Montagnani, L.; U, K. T. Paw; Sevanto, S.; Williams, M. (2009)
  • Hussein, Tareq; Saleh, Shatha Suleiman Ali; dos Santos, Vanessa N.; Abdullah, Huthaifah; Boor, Brandon E. (2019)
    There is a paucity of comprehensive air quality data from urban areas in the Middle East. In this study, portable instrumentation was used to measure size-fractioned aerosol number, mass, and black carbon concentrations in Amman and Zarqa, Jordan. Submicron particle number concentrations at stationary urban background sites in Amman and Zarqa exhibited a characteristic diurnal pattern, with the highest concentrations during traffic rush hours (2-5 x 10(4) cm(-3) in Amman and 2-7 x 10(4) cm(-3) in Zarqa). Super-micron particle number concentrations varied considerably in Amman (1-10 cm(-3)). Mobile measurements identified spatial variations and local hotspots in aerosol levels within both cities. Walking paths around the University of Jordan campus showed increasing concentrations with proximity to main roads with mean values of 8 x 10(4) cm(-3), 87 mu g/m(3), 62 mu g/m(3), and 7.7 mu g/m(3) for submicron, PM10, PM2.5, and black carbon (BC), respectively. Walking paths in the Amman city center showed moderately high concentrations (mean 10(5) cm(-3), 120 mu g/m(3), 85 mu g/m(3), and 8.1 mu g/m(3) for submicron aerosols, PM10, PM2.5, and black carbon, respectively). Similar levels were found along walking paths in the Zarqa city center. On-road measurements showed high submicron concentrations (>10(5) cm(-3)). The lowest submicron concentration (
  • Yi, Chuixiang; Ricciuto, Daniel; Li, Runze; Wolbeck, John; Xu, Xiyan; Nilsson, Mats; Aires, Luis; Albertson, John D.; Ammann, Christof; Arain, M. Altaf; de Araujo, Alessandro C.; Aubinet, Marc; Aurela, Mika; Barcza, Zoltan; Barr, Alan; Berbigier, Paul; Beringer, Jason; Bernhofer, Christian; Black, Andrew T.; Bolstad, Paul V.; Bosveld, Fred C.; Broadmeadow, Mark S. J.; Buchmann, Nina; Burns, Sean P.; Cellier, Pierre; Chen, Jiquan; Ciais, Philippe; Clement, Robert; Cook, Bruce D.; Curtis, Peter S.; Dail, D. Bryan; Dellwik, Ebba; Delpierre, Nicolas; Desai, Ankur R.; Dore, Sabina; Dragoni, Danilo; Drake, Bert G.; Dufrene, Eric; Dunn, Allison; Elbers, Jan; Eugster, Werner; Falk, Matthias; Feigenwinter, Christian; Flanagan, Lawrence B.; Foken, Thomas; Frank, John; Fuhrer, Juerg; Gianelle, Damiano; Goldstein, Allen; Goulden, Mike; Granier, Andre; Gruenwald, Thomas; Gu, Lianhong; Guo, Haiqiang; Hammerle, Albin; Han, Shijie; Hanan, Niall P.; Haszpra, Laszlo; Heinesch, Bernard; Helfter, Carole; Hendriks, Dimmie; Hutley, Lindsay B.; Ibrom, Andreas; Jacobs, Cor; Johansson, Torbjoern; Jongen, Marjan; Katul, Gabriel; Kiely, Gerard; Klumpp, Katja; Knohl, Alexander; Kolb, Thomas; Kutsch, Werner L.; Lafleur, Peter; Laurila, Tuomas; Leuning, Ray; Lindroth, Anders; Liu, Heping; Loubet, Benjamin; Manca, Giovanni; Marek, Michal; Margolis, Hank A.; Martin, Timothy A.; Massman, William J.; Matamala, Roser; Matteucci, Giorgio; McCaughey, Harry; Merbold, Lutz; Meyers, Tilden; Migliavacca, Mirco; Miglietta, Franco; Misson, Laurent; Moelder, Meelis; Moncrieff, John; Monson, Russell K.; Montagnani, Leonardo; Montes-Helu, Mario; Moors, Eddy; Moureaux, Christine; Mukelabai, Mukufute M.; Munger, J. William; Myklebust, May; Nagy, Zoltan; Noormets, Asko; Oechel, Walter; Oren, Ram; Pallardy, Stephen G.; Kyaw, Tha Paw U.; Pereira, Joao S.; Pilegaard, Kim; Pinter, Krisztina; Pio, Casimiro; Pita, Gabriel; Powell, Thomas L.; Rambal, Serge; Randerson, James T.; von Randow, Celso; Rebmann, Corinna; Rinne, Janne; Rossi, Federica; Roulet, Nigel; Ryel, Ronald J.; Sagerfors, Jorgen; Saigusa, Nobuko; Sanz, Maria Jose; Mugnozza, Giuseppe-Scarascia; Schmid, Hans Peter; Seufert, Guenther; Siqueira, Mario; Soussana, Jean-Francois; Starr, Gregory; Sutton, Mark A.; Tenhunen, John; Tuba, Zoltan; Tuovinen, Juha-Pekka; Valentini, Riccardo; Vogel, Christoph S.; Wang, Shaoqiang; Wang, Weiguo; Welp, Lisa R.; Wen, Xuefa; Wharton, Sonia; Wilkinson, Matthew; Williams, Christopher A.; Wohlfahrt, Georg; Yamamoto, Susumu; Yu, Guirui; Zampedri, Roberto; Zhao, Bin; Zhao, Xinquan (2010)
  • Wang, Kai; Zheng, Xunhua; Pihlatie, Mari; Vesala, Timo; Liu, Chunyan; Haapanala, Sami; Mammarella, Ivan; Rannik, Ullar; Liu, Huizhi (2013)
    Nitrous oxide (N2O) fluxes from a cotton field in northern China were measured for a year using the static chamber method based on a gas chromatograph (GC) and the eddy covariance (EC) technique based on a tunable diode laser (TDL). The aims were to compare the N2O fluxes obtained from both techniques, assess the uncertainties in the fluxes and evaluate the annual direct emission factors (EFds, i.e. the loss rate of fertilizer nitrogen via N2O emission) using the year-round datasets. During the experimental period, the hourly and daily mean chamber fluxes ranged from 0.6 to 781.8 and from 1.2 to 468.8 g N m−2 h−1, respectively. The simultaneously measured daily mean EC fluxes varied between −10.8 and 912.0 g N m−2 h−1. The EC measurements only provided trustworthy 30-min fluxes during high-emission period (a 20-day period immediately after the irrigation that followed the nitrogen fertilization event). A reliable comparison was confined to the high-emission period and showed that the chamber fluxes were 17–20% lower than the EC fluxes. This difference may implicate the magnitude of systematic underestimation in the fluxes from chamber measurements. The annual emission from the fertilized cotton field was estimated at 1.43 kg N ha−1 yr−1 by the chamber observations and 3.15 kg N ha−1 yr−1 by the EC measurements. The EFds calculated from the chamber and EC data were 1.04% and 1.65%, respectively. The chamber-based estimate was very close to the default value (1.0%) recommended by the Intergovernmental Panel on Climate Change. However, the difference in the EFds based on the two measurement techniques may vary greatly with changing environmental conditions and management practices. Further comparison studies are still needed to elucidate this issue.
  • Saunders, Matthew; Dengel, Sigrid; Kolari, Pasi; Moureaux, Christine; Montagnani, Leonardo; Ceschia, Eric; Altimir, Nuria; Lopez-Ballesteros, Ana; Maranon-Jimenez, Sara; Acosta, Manuel; Klumpp, Katja; Gielen, Bert; Op de Beeck, Maarten; Hortnagl, Lukas; Merbold, Lutz; Osborne, Bruce; Grunwald, Thomas; Arrouays, Dominique; Boukir, Hakima; Saby, Nicolas; Nicolini, Giacomo; Papale, Dario; Jones, Michael (2018)
    There are many factors that influence ecosystem scale carbon, nitrogen and greenhouse gas dynamics, including the inherent heterogeneity of soils and vegetation, anthropogenic management interventions, and biotic and abiotic disturbance events. It is important therefore, to document the characteristics of the soils and vegetation and to accurately report all management activities, and disturbance events to aid the interpretation of collected data, and to determine whether the ecosystem either amplifies or mitigates climate change. This paper outlines the importance of assessing both the spatial and temporal variability of soils and vegetation and to report all management events, the import or export of C or N from the ecosystem, and the occurrence of biotic/abiotic disturbances at ecosystem stations of the Integrated Carbon Observation System, a pan-European research infrastructure.
  • Peltola, Olli; Vesala, Timo; Gao, Yao; Raty, Olle; Alekseychik, Pavel; Aurela, Mika; Chojnicki, Bogdan; Desai, Ankur R.; Dolman, Albertus J.; Euskirchen, Eugenie S.; Friborg, Thomas; Goeckede, Mathias; Helbig, Manuel; Humphreys, Elyn; Jackson, Robert B.; Jocher, Georg; Joos, Fortunat; Klatt, Janina; Knox, Sara H.; Kowalska, Natalia; Kutzbach, Lars; Lienert, Sebastian; Lohila, Annalea; Mammarella, Ivan; Nadeau, Daniel F.; Nilsson, Mats B.; Oechel, Walter C.; Peichl, Matthias; Pypker, Thomas; Quinton, William; Rinne, Janne; Sachs, Torsten; Samson, Mateusz; Schmid, Hans Peter; Sonnentag, Oliver; Wille, Christian; Zona, Donatella; Aalto, Tuula (2019)
    Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45 degrees N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency = 0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95% confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr(-1). To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163.
  • Pihlatie, Mari; Rinne, Janne; Ambus, P; Pilegaard, K; Dorsey, J. R; Rannik, Ullar; Markkanen, T; Launiainen, Samuli; Vesala, Timo (2005)
  • Pavelka, Marian; Acosta, Manuel; Kiese, Ralf; Altimir, Nuria; Bruemmer, Christian; Crill, Patrick; Darenova, Eva; Fuss, Roland; Gielen, Bert; Graf, Alexander; Klemedtsson, Leif; Lohila, Annalea; Longdoz, Bernhard; Lindroth, Anders; Nilsson, Mats; Jimenez, Sara Maranon; Merbold, Lutz; Montagnani, Leonardo; Peichl, Matthias; Pihlatie, Mari; Pumpanen, Jukka; Ortiz, Penelope Serrano; Silvennoinen, Hanna; Skiba, Ute; Vestin, Patrik; Weslien, Per; Janous, Dalibor; Kutsch, Werner (2018)
    Chamber measurements of trace gas fluxes between the land surface and the atmosphere have been conducted for almost a century. Different chamber techniques, including static and dynamic, have been used with varying degrees of success in estimating greenhouse gases (CO2, CH4, N2O) fluxes. However, all of these have certain disadvantages which have either prevented them from providing an adequate estimate of greenhouse gas exchange or restricted them to be used under limited conditions. Generally, chamber methods are relatively low in cost and simple to operate. In combination with the appropriate sample allocations, chamber methods are adaptable for a wide variety of studies from local to global spatial scales, and they are particularly well suited for in situ and laboratory-based studies. Consequently, chamber measurements will play an important role in the portfolio of the Pan-European long-term research infrastructure Integrated Carbon Observation System. The respective working group of the Integrated Carbon Observation System Ecosystem Monitoring Station Assembly has decided to ascertain standards and quality checks for automated and manual chamber systems instead of defining one or several standard systems provided by commercial manufacturers in order to define minimum requirements for chamber measurements. The defined requirements and recommendations related to chamber measurements are described here.
  • Nemitz, Eiko; Mammarella, Ivan; Ibrom, Andreas; Aurela, Mika; Burba, George G.; Dengel, Sigrid; Gielen, Bert; Grelle, Achim; Heinesch, Bernard; Herbst, Mathias; Hörtnagl, Lukas; Klemedtsson, Leif; Lindroth, Anders; Lohila, Annalea; McDermitt, Dayle K.; Meier, Philip; Merbold, Lutz; Nelson, David; Nicolini, Giacomo; Nilsson, Mats B.; Peltola, Olli; Rinne, Janne; Zahniser, Mark (2018)
    Commercially available fast-response analysers for methane (CH4) and nitrous oxide (N2O) have recently become more sensitive, more robust and easier to operate. This has made their application for long-term flux measurements with the eddycovariance method more feasible. Unlike for carbon dioxide (CO2) and water vapour (H2O), there have so far been no guidelines on how to optimise and standardise the measurements. This paper reviews the state-of-the-art of the various steps of the measurements and discusses aspects such as instrument selection, setup and maintenance, data processing as well as the additional measurements needed to aid interpretation and gap-filling. It presents the methodological protocol for eddy covariance measurements of CH4 and N2O fluxes as agreed for the ecosystem station network of the pan-European Research Infrastructure Integrated Carbon Observation System and provides a first international standard that is suggested to be adopted more widely. Fluxes can be episodic and the processes controlling the fluxes are complex, preventing simple mechanistic gap-filling strategies. Fluxes are often near or below the detection limit, requiring additional care during data processing. The protocol sets out the best practice for these conditions to avoid biasing the results and long-term budgets. It summarises the current approach to gap-filling.
  • Park, Sung-Bin; Knohl, Alexander; Migliavacca, Mirco; Thum, Tea; Vesala, Timo; Peltola, Olli; Mammarella, Ivan; Prokushkin, Anatoly; Kolle, Olaf; Lavric, Jost; Park, Sang Seo; Heimann, Martin (2021)
    Climate change impacts the characteristics of the vegetation carbon-uptake process in the northern Eurasian terrestrial ecosystem. However, the currently available direct CO2 flux measurement datasets, particularly for central Siberia, are insufficient for understanding the current condition in the northern Eurasian carbon cycle. Here, we report daily and seasonal interannual variations in CO2 fluxes and associated abiotic factors measured using eddy covariance in a coniferous forest and a bog near Zotino, Krasnoyarsk Krai, Russia, for April to early June, 2013-2017. Despite the snow not being completely melted, both ecosystems became weak net CO2 sinks if the air temperature was warm enough for photosynthesis. The forest became a net CO2 sink 7-16 days earlier than the bog. After the surface soil temperature exceeded similar to 1 degrees C, the ecosystems became persistent net CO2 sinks. Net ecosystem productivity was highest in 2015 for both ecosystems because of the anomalously high air temperature in May compared with other years. Our findings demonstrate that long-term monitoring of flux measurements at the site level, particularly during winter and its transition to spring, is essential for understanding the responses of the northern Eurasian ecosystem to spring warming.