Articles | Volume 13, issue 21
https://doi.org/10.5194/acp-13-10555-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-10555-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Nov 2013
Research article |
| 01 Nov 2013
Quantifying the constraint of biospheric process parameters by CO2 concentration and flux measurement networks through a carbon cycle data assimilation system
E. N. Koffi
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR8212, Ormes des merisiers, 91191 Gif-sur-Yvette, France
now at: the European Commission Joint Research Centre, Institute for Environment and Sustainability, 21027 Ispra (Va), Italy
P. J. Rayner
School of Earth Sciences, University of Melbourne, Melbourne, Australia
M. Scholze
School of Earth Sciences, University of Bristol, Queen's Road, Bristol BS8 1RJ, UK
F. Chevallier
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR8212, Ormes des merisiers, 91191 Gif-sur-Yvette, France
T. Kaminski
FastOpt, Lerchenstraße 28a, 22767 Hamburg, Germany
Related subject area
Subject: Biosphere Interactions | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Impact of atmospheric transport on CO2 flux estimates derived from the atmospheric tracer inversions
Net ecosystem exchange (NEE) estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system
Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models
Distinguishing the impacts of natural and anthropogenic aerosols on global gross primary productivity through diffuse fertilization effect
Was Australia a sink or source of CO2 in 2015? Data assimilation using OCO-2 satellite measurements
CO2-equivalence metrics for surface albedo change based on the radiative forcing concept: a critical review
Effects of aerosol dynamics and gas–particle conversion on dry deposition of inorganic reactive nitrogen in a temperate forest
Ozone–vegetation feedback through dry deposition and isoprene emissions in a global chemistry–carbon–climate model
Pathway dependence of ecosystem responses in China to 1.5 °C global warming
A model-based analysis of foliar NOx deposition
Quantifying the UK's carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network
Prediction of photosynthesis in Scots pine ecosystems across Europe by a needle-level theory
Technical note: How are NH3 dry deposition estimates affected by combining the LOTOS-EUROS model with IASI-NH3 satellite observations?
Isoprene and monoterpene emissions in south-east Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric observations
Particulate matter air pollution may offset ozone damage to global crop production
Sensitivity of stomatal conductance to soil moisture: implications for tropospheric ozone
The influence of idealized surface heterogeneity on virtual turbulent flux measurements
Technical Note: Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: methodology and system evaluation
Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: quantification of the European terrestrial CO2 fluxes
Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks
Future inhibition of ecosystem productivity by increasing wildfire pollution over boreal North America
Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook
Modeling soil organic carbon dynamics and their driving factors in the main global cereal cropping systems
A wedge strategy for mitigation of urban warming in future climate scenarios
The boundary condition for vertical velocity and its interdependence with surface gas exchange
Pan-Eurasian Experiment (PEEX): towards a holistic understanding of the feedbacks and interactions in the land–atmosphere–ocean–society continuum in the northern Eurasian region
Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO2
Increasing summer net CO2 uptake in high northern ecosystems inferred from atmospheric inversions and comparisons to remote-sensing NDVI
A study of the influence of forest gaps on fire–atmosphere interactions
Stratospheric sulfate geoengineering could enhance the terrestrial photosynthesis rate
Distinguishing the drivers of trends in land carbon fluxes and plant volatile emissions over the past 3 decades
Granger causality from changes in level of atmospheric CO2 to global surface temperature and the El Niño–Southern Oscillation, and a candidate mechanism in global photosynthesis
MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
Stably stratified canopy flow in complex terrain
Fire emission heights in the climate system – Part 1: Global plume height patterns simulated by ECHAM6-HAM2
Fire emission heights in the climate system – Part 2: Impact on transport, black carbon concentrations and radiation
Reliable, robust and realistic: the three R's of next-generation land-surface modelling
Biases in atmospheric CO2 estimates from correlated meteorology modeling errors
Carbon balance of China constrained by CONTRAIL aircraft CO2 measurements
Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case
Sensitivity analysis of an updated bidirectional air–surface exchange model for elemental mercury vapor
Nitrous oxide emissions 1999 to 2009 from a global atmospheric inversion
Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model
Present and future nitrogen deposition to national parks in the United States: critical load exceedances
Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions
Scorched Earth: how will changes in the strength of the vegetation sink to ozone deposition affect human health and ecosystems?
The effect of climate and climate change on ammonia emissions in Europe
Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design
CO2 flux estimation errors associated with moist atmospheric processes
DO3SE modelling of soil moisture to determine ozone flux to forest trees
Saqr Munassar, Guillaume Monteil, Marko Scholze, Ute Karstens, Christian Rödenbeck, Frank-Thomas Koch, Kai Uwe Totsche, and Christoph Gerbig
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-510, https://doi.org/10.5194/acp-2022-510, 2022
Revised manuscript accepted for ACP
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Using different transport models results in large errors in optimized fluxes in the inversion frameworks. Boundary conditions and inversion system configurations lead to a smaller, but non-negligible impact. The findings highlight the importance to validate transport models for further developments, but also to properly account for such errors in inverse modelling. This will help narrow the convergence of GHG estimates reported in the scientific literature from different inversion frameworks.
Saqr Munassar, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, https://doi.org/10.5194/acp-22-7875-2022, 2022
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The results obtained from ensembles of inversions over 13 years show the largest spread in the a posteriori fluxes over the station set ensemble. Using different prior fluxes in the inversions led to a smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as seen in net ecosystem exchange estimates. Our study highlights the importance of expanding the atmospheric site network across Europe to better constrain CO2 fluxes in inverse modelling.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
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This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Hao Zhou, Xu Yue, Yadong Lei, Chenguang Tian, Jun Zhu, Yimian Ma, Yang Cao, Xixi Yin, and Zhiding Zhang
Atmos. Chem. Phys., 22, 693–709, https://doi.org/10.5194/acp-22-693-2022, https://doi.org/10.5194/acp-22-693-2022, 2022
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Aerosols enhance plant photosynthesis by increasing diffuse radiation. In this study, we found that the aerosol impacts are quite different for varied species. Scattering aerosols such as sulfate and organic carbon promote photosynthesis while absorbing aerosols such as black carbon have negative impacts. Earth system models should consider the impacts of cloud and aerosol species on terrestrial ecosystems so as to better predict carbon cycles under different emission scenarios.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
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Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Ryan M. Bright and Marianne T. Lund
Atmos. Chem. Phys., 21, 9887–9907, https://doi.org/10.5194/acp-21-9887-2021, https://doi.org/10.5194/acp-21-9887-2021, 2021
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Humans affect the reflective properties (albedo) of Earth's surface and the amount of solar energy that it absorbs, in turn affecting climate. In recent years, a variety of climate metrics have been applied to characterize albedo perturbations in terms of their
CO2-equivalenteffects, despite the lack of scientific consensus surrounding the methods behind them. We review these metrics, evaluate their (de)merits, provide guidance for future application, and suggest avenues for future research.
Genki Katata, Kazuhide Matsuda, Atsuyuki Sorimachi, Mizuo Kajino, and Kentaro Takagi
Atmos. Chem. Phys., 20, 4933–4949, https://doi.org/10.5194/acp-20-4933-2020, https://doi.org/10.5194/acp-20-4933-2020, 2020
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This work quantified the role of aerosol dynamics and gas–particle conversion processes in the dry deposition of inorganic reactive nitrogen using a new multilayer land surface model. It also revealed a potential impact of the above processes on improving the predictive accuracy of chemical transport models.
Cheng Gong, Yadong Lei, Yimian Ma, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 20, 3841–3857, https://doi.org/10.5194/acp-20-3841-2020, https://doi.org/10.5194/acp-20-3841-2020, 2020
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We evaluate ozone–vegetation feedback using a fully coupled chemistry–carbon–climate global model (ModelE2-YIBs). Ozone damage to photosynthesis, stomatal conductance, and isoprene emissions parameterized by different schemes and sensitivities is jointly considered. In general, surface ozone concentrations are increased due to ozone–vegetation interactions, especially over the regions with a high ambient ozone level such as the eastern US, eastern China, and western Europe.
Xu Yue, Hong Liao, Huijun Wang, Tianyi Zhang, Nadine Unger, Stephen Sitch, Zhaozhong Feng, and Jia Yang
Atmos. Chem. Phys., 20, 2353–2366, https://doi.org/10.5194/acp-20-2353-2020, https://doi.org/10.5194/acp-20-2353-2020, 2020
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We explore ecosystem responses in China to 1.5 °C global warming under stabilized versus transient pathways. Remarkably, GPP shows 30 % higher enhancement in the stabilized than the transient pathway because of the lower ozone (smaller damages to photosynthesis) and fewer aerosols (higher light availability) in the former pathway. Our analyses suggest that an associated reduction of CO2 and pollution emissions brings more benefits to ecosystems in China via 1.5 °C global warming.
Erin R. Delaria and Ronald C. Cohen
Atmos. Chem. Phys., 20, 2123–2141, https://doi.org/10.5194/acp-20-2123-2020, https://doi.org/10.5194/acp-20-2123-2020, 2020
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Uptake of nitrogen dioxide (NO2) through pores in the surfaces of leaves has been identified as a significant, but inadequately understood, loss process of atmospheric nitrogen oxides. We have constructed a simple model for examining the impact of NO2 foliar uptake on the atmospheric chemistry of nitrogen oxides. We show that an accurate representation in atmospheric models of the effects of weather and soil conditions on leaf NO2 uptake may be important for accurately predicting NO2 deposition.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
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Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Pertti Hari, Steffen Noe, Sigrid Dengel, Jan Elbers, Bert Gielen, Veli-Matti Kerminen, Bart Kruijt, Liisa Kulmala, Anders Lindroth, Ivan Mammarella, Tuukka Petäjä, Guy Schurgers, Anni Vanhatalo, Markku Kulmala, and Jaana Bäck
Atmos. Chem. Phys., 18, 13321–13328, https://doi.org/10.5194/acp-18-13321-2018, https://doi.org/10.5194/acp-18-13321-2018, 2018
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The development of eddy-covariance measurements of ecosystem CO2 fluxes began a new era in the field studies of photosynthesis. The interpretation of the very variable CO2 fluxes in evergreen forests has been problematic especially in seasonal transition times. We apply two theoretical needle-level equations and show they can predict photosynthetic CO2 flux between the atmosphere and Scots pine forests. This has strong implications for the interpretation of the global change and boreal forests.
Shelley C. van der Graaf, Enrico Dammers, Martijn Schaap, and Jan Willem Erisman
Atmos. Chem. Phys., 18, 13173–13196, https://doi.org/10.5194/acp-18-13173-2018, https://doi.org/10.5194/acp-18-13173-2018, 2018
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A combination of NH3 satellite observations from IASI and the LOTOS-EUROS model is used to derive NH3 surface concentrations and dry deposition fluxes over Europe. The results were evaluated using surface measurements (EMEP, LML, MAN) and a sensitivity study. This is a first step in further integration of surface measurements, satellite observations and an atmospheric transport model to derive accurate NH3 surface concentrations and dry deposition fluxes on a large scale.
Kathryn M. Emmerson, Martin E. Cope, Ian E. Galbally, Sunhee Lee, and Peter F. Nelson
Atmos. Chem. Phys., 18, 7539–7556, https://doi.org/10.5194/acp-18-7539-2018, https://doi.org/10.5194/acp-18-7539-2018, 2018
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We compare the CSIRO in-house biogenic emissions model (ABCGEM) with the Model of Emissions of Gases and Aerosols from Nature (MEGAN), for eucalypt-rich south-east Australia. Differences in emissions are not only due to the emission factors, but also how these emission factors are processed. ABCGEM assumes monoterpenes are not light dependent, whilst MEGAN does. Comparison with observations suggests that Australian monoterpenes may not be as light dependent as other vegetation globally.
Luke D. Schiferl and Colette L. Heald
Atmos. Chem. Phys., 18, 5953–5966, https://doi.org/10.5194/acp-18-5953-2018, https://doi.org/10.5194/acp-18-5953-2018, 2018
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Global population growth and industrialization have contributed to poor air quality worldwide, and increasing population will put pressure on global food production. We therefore assess how air pollution may impact crop growth. Ozone has previously been shown to damage crops. We demonstrate that the impact of particles associated with enhanced light scattering promotes growth, offsetting much, if not all, ozone damage. This has implications for air quality management and global food security.
Alessandro Anav, Chiara Proietti, Laurent Menut, Stefano Carnicelli, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 18, 5747–5763, https://doi.org/10.5194/acp-18-5747-2018, https://doi.org/10.5194/acp-18-5747-2018, 2018
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Soil moisture and water stress play a pivotal role in regulating stomatal behaviour of plants; however, the role of water availability is often neglected in atmospheric chemistry modelling studies.
We show how dry deposition significantly declines when soil moisture is used to regulate the stomatal opening, mainly in semi-arid environments. Despite the fact that dry deposition occurs from the top of canopy to ground level, it affects the concentration of gases remaining in the lower atmosphere.
Frederik De Roo and Matthias Mauder
Atmos. Chem. Phys., 18, 5059–5074, https://doi.org/10.5194/acp-18-5059-2018, https://doi.org/10.5194/acp-18-5059-2018, 2018
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We investigate the mismatch between incoming energy and the turbulent flux of sensible heat at the Earth's surface and how surface heterogeneity affects this imbalance. To resolve the turbulent fluxes we employ large-eddy simulations. We study terrain with different heterogeneity lengths and quantify the contributions of advection by the mean flow and horizontal flux-divergence in the surface energy budget. We find that the latter contributions depend on the scale of the heterogeneity length.
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas Frank Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3027–3045, https://doi.org/10.5194/acp-18-3027-2018, https://doi.org/10.5194/acp-18-3027-2018, 2018
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas F. Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3047–3064, https://doi.org/10.5194/acp-18-3047-2018, https://doi.org/10.5194/acp-18-3047-2018, 2018
Sara C. Pryor, Ryan C. Sullivan, and Justin T. Schoof
Atmos. Chem. Phys., 17, 14457–14471, https://doi.org/10.5194/acp-17-14457-2017, https://doi.org/10.5194/acp-17-14457-2017, 2017
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The air temperature and water vapor content are increasing globally due to the increased concentration of "heat-trapping" (greenhouse) gases. But not all regions are warming at the same rate. This analysis is designed to improve understanding of the causes of recent trends and year-to-year variability in summertime heat indices over the eastern US and to present a new model that can be used to make projections of future events that may cause loss of life and/or decreased human well-being.
Xu Yue, Susanna Strada, Nadine Unger, and Aihui Wang
Atmos. Chem. Phys., 17, 13699–13719, https://doi.org/10.5194/acp-17-13699-2017, https://doi.org/10.5194/acp-17-13699-2017, 2017
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Climate change will significantly increase wildfire emissions in boreal North America by the midcentury, leading to increased surface ozone and atmospheric aerosols. These air pollutants can affect vegetation photosynthesis through stomatal uptake (for ozone) and radiative and climatic perturbations (for aerosols). Using a carbon–chemistry–climate model, we estimate trivial ozone vegetation damages but significant aerosol-induced reduction in ecosystem productivity by the 2050s.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
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This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
Guocheng Wang, Wen Zhang, Wenjuan Sun, Tingting Li, and Pengfei Han
Atmos. Chem. Phys., 17, 11849–11859, https://doi.org/10.5194/acp-17-11849-2017, https://doi.org/10.5194/acp-17-11849-2017, 2017
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Cropland soil carbon sequestration contribute to not only climate change mitigation but also to sustainable agricultural production. This paper investigates soil carbon dynamics across the global main cereal cropping systems at a fine spatial resolution, using a modeling approach based on state-of-the-art databases of soil and climate. The key environmental controls on soil carbon changes were also identified.
Lei Zhao, Xuhui Lee, and Natalie M. Schultz
Atmos. Chem. Phys., 17, 9067–9080, https://doi.org/10.5194/acp-17-9067-2017, https://doi.org/10.5194/acp-17-9067-2017, 2017
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Heat stress associated with climate change is one of most severe threats to human society. The problem is further compounded in urban areas by urban heat islands (UHIs). We use an urban climate model to evaluate the cooling benefits of active urban heat mitigation strategies both individually and collectively. We show that by forming UHI mitigation wedges, these strategies have the potential to significantly reduce the UHI effect plus warming induced by greenhouse gases.
Andrew S. Kowalski
Atmos. Chem. Phys., 17, 8177–8187, https://doi.org/10.5194/acp-17-8177-2017, https://doi.org/10.5194/acp-17-8177-2017, 2017
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An analysis based on physical conservation law demonstrates that surface–atmosphere exchanges include a non-diffusive component. This implies the need to revise flux gradient relationships including eddy diffusivities in micrometeorology and stomatal conductances in plant physiology.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Saroja M. Polavarapu, Michael Neish, Monique Tanguay, Claude Girard, Jean de Grandpré, Kirill Semeniuk, Sylvie Gravel, Shuzhan Ren, Sébastien Roche, Douglas Chan, and Kimberly Strong
Atmos. Chem. Phys., 16, 12005–12038, https://doi.org/10.5194/acp-16-12005-2016, https://doi.org/10.5194/acp-16-12005-2016, 2016
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CO2 predictions are used to compute model–data mismatches when estimating surfaces fluxes using atmospheric observations together with an atmospheric transport model. By isolating the component of transport error which is due to uncertain meteorological analyses, it is demonstrated that CO2 can only be defined on large spatial scales. Thus, there is a spatial scale below which we cannot infer fluxes simply due to the fact that meteorological analyes are imperfect.
Lisa R. Welp, Prabir K. Patra, Christian Rödenbeck, Rama Nemani, Jian Bi, Stephen C. Piper, and Ralph F. Keeling
Atmos. Chem. Phys., 16, 9047–9066, https://doi.org/10.5194/acp-16-9047-2016, https://doi.org/10.5194/acp-16-9047-2016, 2016
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Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO2 over the last decades. It is not clear if these ecosystems are sequestering more carbon or possibly becoming sources. This is an important feedback of the carbon cycle to global warming. We studied monthly biological land CO2 fluxes inferred from atmospheric CO2 concentrations using inverse models and found that net summer CO2 uptake increased, resulting in a small increase in annual CO2 uptake.
Michael T. Kiefer, Warren E. Heilman, Shiyuan Zhong, Joseph J. Charney, and Xindi Bian
Atmos. Chem. Phys., 16, 8499–8509, https://doi.org/10.5194/acp-16-8499-2016, https://doi.org/10.5194/acp-16-8499-2016, 2016
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Studies of fire–atmosphere interactions in horizontally heterogeneous forests are limited in number. This study considers the sensitivity of fire-perturbed variables (e.g., vertical velocity, turbulent kinetic energy) to gaps in forest cover using ARPS-CANOPY, an atmospheric numerical model with a canopy sub-model. Results show that the atmosphere is most sensitive to the fire when the gap is centered on the fire and least sensitive when the gap is upstream of the fire.
L. Xia, A. Robock, S. Tilmes, and R. R. Neely III
Atmos. Chem. Phys., 16, 1479–1489, https://doi.org/10.5194/acp-16-1479-2016, https://doi.org/10.5194/acp-16-1479-2016, 2016
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Climate model simulations show that stratospheric sulfate geoengineering could impact the terrestrial carbon cycle by enhancing the carbon sink. Enhanced downward diffuse radiation, combined with cooling, could stimulate plants to grow more and absorb more carbon dioxide. This beneficial impact of stratospheric sulfate geoengineering would need to be balanced by a large number of potential risks in any future decisions about implementation of geoengineering.
X. Yue, N. Unger, and Y. Zheng
Atmos. Chem. Phys., 15, 11931–11948, https://doi.org/10.5194/acp-15-11931-2015, https://doi.org/10.5194/acp-15-11931-2015, 2015
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We estimate decadal trends in land carbon fluxes and emissions of biogenic volatile organic compounds (BVOCs) during 1982-2011, with a focus on the feedback from biosphere (such as tree growth and phenology). Increases of LAI at peak season accounts for ~25% of the trends in GPP and isoprene emissions at the northern lands. However, phenological change alone does not promote regional carbon uptake and BVOC emissions.
L. M. W. Leggett and D. A. Ball
Atmos. Chem. Phys., 15, 11571–11592, https://doi.org/10.5194/acp-15-11571-2015, https://doi.org/10.5194/acp-15-11571-2015, 2015
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The previously expected linear relationship between atmospheric CO2 and climate variables including temperature is showing an increasing mismatch. This paper nonetheless provides fresh and possibly definitive support for a major relationship between CO2 and climate. Granger causality analysis provides evidence that change in level not level of CO2 primarily influences both global temperature and the El Niño–Southern Oscillation. The results may contribute to the prediction of future climate.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
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The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
X. Xu, C. Yi, and E. Kutter
Atmos. Chem. Phys., 15, 7457–7470, https://doi.org/10.5194/acp-15-7457-2015, https://doi.org/10.5194/acp-15-7457-2015, 2015
A. Veira, S. Kloster, S. Wilkenskjeld, and S. Remy
Atmos. Chem. Phys., 15, 7155–7171, https://doi.org/10.5194/acp-15-7155-2015, https://doi.org/10.5194/acp-15-7155-2015, 2015
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We discuss the representation of wildfire emission heights in global climate models. Our implementation of a simple, semi-empirical plume height parametrization in the aerosol-climate model ECHAM6-HAM2 shows reasonable agreement with observations and with a more complex plume rise model. In contrast, prescribed emission heights, which do not consider the intensity of individual fires, fail to adequately simulate global plume height patterns. Diurnal and seasonal cycles are of minor importance.
A. Veira, S. Kloster, N. A. J. Schutgens, and J. W. Kaiser
Atmos. Chem. Phys., 15, 7173–7193, https://doi.org/10.5194/acp-15-7173-2015, https://doi.org/10.5194/acp-15-7173-2015, 2015
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Global aerosol-climate models usually prescribe wildfire emission injections at fixed atmospheric levels. Here, we quantify the impact of prescribed and parametrized emission heights on aerosol long-range transport and radiation. For global emission height changes of 1.5-3.5km, we find a top-of-atmosphere radiative forcing of 0.05-0.1Wm-2. Replacing prescribed emission heights by a simple plume height parametrization only marginally improves the model performance in aerosol optical thickness.
I. C. Prentice, X. Liang, B. E. Medlyn, and Y.-P. Wang
Atmos. Chem. Phys., 15, 5987–6005, https://doi.org/10.5194/acp-15-5987-2015, https://doi.org/10.5194/acp-15-5987-2015, 2015
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Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
S. M. Miller, M. N. Hayek, A. E. Andrews, I. Fung, and J. Liu
Atmos. Chem. Phys., 15, 2903–2914, https://doi.org/10.5194/acp-15-2903-2015, https://doi.org/10.5194/acp-15-2903-2015, 2015
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
T. Ziehn, A. Nickless, P. J. Rayner, R. M. Law, G. Roff, and P. Fraser
Atmos. Chem. Phys., 14, 9363–9378, https://doi.org/10.5194/acp-14-9363-2014, https://doi.org/10.5194/acp-14-9363-2014, 2014
X. Wang, C.-J. Lin, and X. Feng
Atmos. Chem. Phys., 14, 6273–6287, https://doi.org/10.5194/acp-14-6273-2014, https://doi.org/10.5194/acp-14-6273-2014, 2014
R. L. Thompson, F. Chevallier, A. M. Crotwell, G. Dutton, R. L. Langenfelds, R. G. Prinn, R. F. Weiss, Y. Tohjima, T. Nakazawa, P. B. Krummel, L. P. Steele, P. Fraser, S. O'Doherty, K. Ishijima, and S. Aoki
Atmos. Chem. Phys., 14, 1801–1817, https://doi.org/10.5194/acp-14-1801-2014, https://doi.org/10.5194/acp-14-1801-2014, 2014
N. Unger, K. Harper, Y. Zheng, N. Y. Kiang, I. Aleinov, A. Arneth, G. Schurgers, C. Amelynck, A. Goldstein, A. Guenther, B. Heinesch, C. N. Hewitt, T. Karl, Q. Laffineur, B. Langford, K. A. McKinney, P. Misztal, M. Potosnak, J. Rinne, S. Pressley, N. Schoon, and D. Serça
Atmos. Chem. Phys., 13, 10243–10269, https://doi.org/10.5194/acp-13-10243-2013, https://doi.org/10.5194/acp-13-10243-2013, 2013
R. A. Ellis, D. J. Jacob, M. P. Sulprizio, L. Zhang, C. D. Holmes, B. A. Schichtel, T. Blett, E. Porter, L. H. Pardo, and J. A. Lynch
Atmos. Chem. Phys., 13, 9083–9095, https://doi.org/10.5194/acp-13-9083-2013, https://doi.org/10.5194/acp-13-9083-2013, 2013
M. Sofiev, R. Vankevich, T. Ermakova, and J. Hakkarainen
Atmos. Chem. Phys., 13, 7039–7052, https://doi.org/10.5194/acp-13-7039-2013, https://doi.org/10.5194/acp-13-7039-2013, 2013
L. D. Emberson, N. Kitwiroon, S. Beevers, P. Büker, and S. Cinderby
Atmos. Chem. Phys., 13, 6741–6755, https://doi.org/10.5194/acp-13-6741-2013, https://doi.org/10.5194/acp-13-6741-2013, 2013
C. A. Skjøth and C. Geels
Atmos. Chem. Phys., 13, 117–128, https://doi.org/10.5194/acp-13-117-2013, https://doi.org/10.5194/acp-13-117-2013, 2013
T. Kaminski, P. J. Rayner, M. Voßbeck, M. Scholze, and E. Koffi
Atmos. Chem. Phys., 12, 7867–7879, https://doi.org/10.5194/acp-12-7867-2012, https://doi.org/10.5194/acp-12-7867-2012, 2012
N. C. Parazoo, A. S. Denning, S. R. Kawa, S. Pawson, and R. Lokupitiya
Atmos. Chem. Phys., 12, 6405–6416, https://doi.org/10.5194/acp-12-6405-2012, https://doi.org/10.5194/acp-12-6405-2012, 2012
P. Büker, T. Morrissey, A. Briolat, R. Falk, D. Simpson, J.-P. Tuovinen, R. Alonso, S. Barth, M. Baumgarten, N. Grulke, P. E. Karlsson, J. King, F. Lagergren, R. Matyssek, A. Nunn, R. Ogaya, J. Peñuelas, L. Rhea, M. Schaub, J. Uddling, W. Werner, and L. D. Emberson
Atmos. Chem. Phys., 12, 5537–5562, https://doi.org/10.5194/acp-12-5537-2012, https://doi.org/10.5194/acp-12-5537-2012, 2012
Cited articles
Aubinet, M., Grelle, A., Ibrom, A., Rannik, U, Moncrieff, J., T. Foken, T., Kowalski, A. S., Martin, P. H., Berbigier, P., Bernhofer, Ch., Clement, R., Elbers, J., Granier, A., Grünwald, T., Morgenstern, K., Pilegaard, K., Rebmann, C., Snijders, W., Valentini, R., and Vesala, T.: Estimates of the annual net carbon and water exchange of forest: the EUROFLUX methodology, Adv. Ecol. Res., 30, 114–173, 2000.
Baldocchi, D. D.: Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future, Glob. Change Biol., 9, 479–492, 2003.
Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P., Denning, A. S., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fung, I. Y., Heimann, M., John, J., Maki, T., Maksyutov, S., Masarie, K., Prather, M., Pak, B., Taguchi, S., and Zhu, Z.: TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003, Global Biogeochem. Cy., 20, GB1002, https://doi.org/10.1029/2004GB002439, 2006.
Carouge, C., Bousquet, P., Peylin, P., Rayner, P. J., and Ciais, P.: What can we learn from European continuous atmospheric CO2 measurements to quantify regional fluxes – Part 1: Potential of the 2001 network, Atmos. Chem. Phys., 10, 3107–3117, https://doi.org/10.5194/acp-10-3107-2010, 2010a.
Carouge, C., Rayner, P. J., Peylin, P., Bousquet, P., Chevallier, F., and Ciais, P.: What can we learn from European continuous atmospheric CO2 measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup, Atmos. Chem. Phys., 10, 3119–3129, https://doi.org/10.5194/acp-10-3119-2010, 2010b.
Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P., Bréon, F.-M., Chédin, A., and Ciais, P: Inferring CO2 sources and sinks from satellite observations: method and application to TOVS data, J. Geophys. Res., 110, D24309, https://doi.org/10.1029/2005JD006390, 2005.
Chevallier, F., Bréon, F.-M., and Rayner, P. J.: The contribution of the Orbiting Carbon Observatory to the estimation of CO2 sources and sinks: Theoretical study in a variational data assimilation framework, J. Geophys. Res., 112, D09307, https://doi.org/10.1029/2006JD007375, 2007.
Chevallier, F., Ciais, P., Conway, T. J., Aalto, T., Anderson, B. E., Bousquet, P., Brunke, E. G., Ciattaglia, L., Esaki, Y., Fröhlich, M., Gomez, A. J., Gomez-Pelaez, A. J., Haszpra, L., Krummel, P., Langenfelds, R., Leuenberger, M., Machida, T., Maignan, F., Matsueda, H., Morguí, J. A., Mukai, H., Nakazawa, T., Peylin, P., Ramonet, M., Rivier, L., Sawa, Y., Schmidt, M., Steele, P., Vay, S. A., Vermeulen, A. T., Wofsy, S., and Worthy, D.: CO2 surface fluxes at grid point scale estimated from a global 21-year reanalysis of atmospheric measurements, J. Geophys. Res., 115, D21307, https://doi.org/10.1029/2010JD013887, 2010.
Chevallier, F., Wang, T., Ciais, P., Maignan, F., Bocquet, M., Arain, A., Cescatti, A., Chen, J.-Q., Dolman, H., Law, B. E., Margolis, H. A., Montagni, L., and Moors, E. J.: What eddy-covariance flux measurements tell us about prior errors in CO2-flux inversion schemes, Global Biogeochem. Cy., 26, GB1021, https://doi.org/10.1029/2010GB003974, 2012.
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogee, J., Allard, V., Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F., De Noblet, N., Friend, A. D., Friedlingstein, P., Grunwald, T., Heinesch, B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci, G., Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S., Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala, T., and Valentini, R.: Europe-wide reduction in primary productivity caused by the heat and drought in 2003, Nature, 437, 529–533, 2005.
Collatz G. J., Ribas-Carbo, M., and Berry, J. A.: Coupled photosynthesis-stomatal conductance model 5 of leaves for C4 plants, Aust. J. Plant Physiol., 19, 519–538, 1992.
Enting, I. G.: Inverse Problems in Atmospheric Constituent Transport, Cambridge University Press, 392 pp., 2002.
Farquhar, G. D., Cammerer, S. V., and Berry, J. A.: A biochemical model of photosynthesis in leaves of C4 species, Planta, 149, 78–90, 1980.
Foken, T. and Wichura, B.: Tools for quality assessment of surface-based flux measurements, Agr. Forest Meteorol., 78, 83–105, 1996.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Giering, R. and Kaminski, T: Recipes for adjoint code construction, ACM Transactions on Mathematical Software, 24, 437–474, 1998.
GLOBALVIEW-CO2: Cooperative Atmospheric Data Integration Project – Carbondioxide [CD-ROM],Global Monit. Div. Earth Syst. Res. Lab., NOAA, Boulder, Colorado (available at ftp://ftp.cmdl.noaa.gov/ccg/co2/GLOBALVIEW), 2004.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D.,. Bousquet, P. Bruhwiler, L., Chen, Y. H, Ciais, P., Fan, S. M., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Kowalczyk, E., Maki, T., Maksyutov, S., Peylin, P., Prather, M., Pak, B. C., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C. W.: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models, Nature, 415, 626–630, 2002.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y. H., Ciais, P., Fan, S. M., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Kowalczyk, E., Maki, T., Maksyutov, S., Peylin, P., Prather, M., Pak, B. C., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C. W.: TransCom 3 CO2 inversion intercomparison: 30 1. Annual mean control results and sensitivity to transport and prior fluxes, Tellus B, 55, 555–579, https://doi.org/10.1034/j.1600-0889.2003.00049.x, 2003.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, J. P., Pak, B. C., Baker, D., Bousquet, P., Bruhwiler, L., . Chen, Y. H., Ciais, P., Fung, I. Y., Heimann, M., John, J., Maki, T., Maksyutov, S., Peylin, P., Prather, M., and Taguchi, S.: Transcom 3 inversion intercomparison: Model mean results for the estimation of seasonal carbon sources and sinks, Global Biogeochem. Cy., 18, GB1010, https://doi.org/10.1029/2003GB002111, 2004.
Hagen, S. C., Braswell, B. H., Linder, E., Frolking, S., Richardson, A. D., and Hollinger, D. Y.: Statistical uncertainty of eddy flux – based estimates of gross ecosystem carbon exchange at Howland Forest, Maine, J. Geophys. Res., 111, D08S03, https://doi.org/10.1029/2005JD006154, 2006.
Hardt, M. and Scherbaum, F.: The design of optimum networks for aftershock recordings, Geophysical Journal International, 117, 716–726, https://doi.org/10.1111/j.1365-246X.1994.tb02464.x, 1994.
Heimann, M. and Körner, S.:The global atmospheric tracer model TM3, in: Max-Planck-Institut für Biogeochemie, Technical Report. Vol. 5, Max-Planck-Institut für Biogeochemie, Jena 131 pp. 131 [BGC0601; ECO140/036+5], 2003.
Hourdin, F., Musat, I., Bony, S., Braconnot, P., Codron, F., Dufresne, J. L., Fairhead, L., Filiberti, M., Friedlingstein, P., Grandpeix, J., Krinner, G., LeVan, P., Zhao-Xin, L., and Lott, F.: The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection, Climate Dynam., 27, 787–813, 2006.
Kaminski, T. and Rayner, P. J.: Assimilation and network design, in: Observing the continental scale Greenhouse Gas Balance of Europe, edited by: Dolman, H., Freibauer, A., and Valentini, R., Ecological Studies, chapter 3, 33–52, Springer-Verlag, New York, 2008.
Kaminski, T., Heimann, M., and Giering, R.: A coarse grid three-dimensional global inverse model of the atmospheric transport, 2, Inversion of the transport of CO2 in the 1980s, J. Geophys. Res., 104, 18555–18581, 1999.
Kaminski, T., Knorr, W., Rayner, P., and Heimann, M: Assimilating atmospheric data into a terrestrial biosphere model: A case study of the seasonal cycle, Global Biogeochem. Cy., 16, 1066, https://doi.org/10.1029/2001GB001463, 2002.
Kaminski, T., Giering, R., Scholze, M., Rayner, P., and Knorr, W.: An example of an automatic differentiation-based modelling system, in: Computational Science – ICCSA 2003, edited by: Kumar, V., Gavrilova, L., Tan, C. J. K., and L'Ecuyer, P., International Conference Montreal, Canada, May 2003, Proceedings, Part II, volume 2668 of Lecture Notes in Computer Science, 95–104, Berlin, Springer, 2003.
Kaminski, T., Scholze, M., and Houweling, S.: Quantifying the Benefit of A-SCOPE Data for Reducing Uncertainties in Terrestrial Carbon Fluxes in CCDAS, Tellus B, 62, 784–796, 2010.
Kaminski, T., Knorr, W., Scholze, M., Gobron, N., Pinty, B., Giering, R., and Mathieu, P.-P.: Consistent assimilation of MERIS FAPAR and atmospheric CO2 into a terrestrial vegetation model and interactive mission benefit analysis, Biogeosciences, 9, 3173–3184, https://doi.org/10.5194/bg-9-3173-2012, 2012a.
Kaminski, T., Rayner, P. J., Voßbeck, M., Scholze, M., and Koffi, E.: Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design, Atmos. Chem. Phys., 12, 7867–7879, https://doi.org/10.5194/acp-12-7867-2012, 2012b.
Kato, T., Knorr, W., Scholze, M., Veenendaal, E., Kaminski, T., Kattge, J., and Gobron, N.: Simultaneous assimilation of satellite and eddy covariance data for improving terrestrial water and carbon simulations at a semi-arid woodland site in Botswana, Biogeosciences, 10, 789–802, https://doi.org/10.5194/bg-10-789-2013, 2013.
Knorr, W.: Annual and interannual CO2 exchanges of the terrestrial biosphere: process-based simulations and uncertainties, Global Ecology and Biogeography, 9, 225–252, 2000.
Knorr, W. and Kattge, J.: Inversion of terrestrial ecosystem model parameter values against eddy covariance measurements by Monte Carlo sampling, Glob. Change Biol., 11, 1333–1351, 2005.
Knorr, W., Kaminski, T., Scholze, M., Gobron, N., Pinty, B., Giering, R., and Mathieu, P.-P.: 20 Carbon cycle data assimilation with a generic phenology model, J. Geophys. Res., 115, G04017, https://doi.org/10.1029/2009JG001119, 2010.
Koffi, E. N., Rayner, P., Scholze, M., and Beer, C.: Atmospheric constraints on gross primary productivity and net ecosystem productivity: Results from a carbon-cycle data assimilation system, Global Biogeochem. Cy., 26, GB1024, https://doi.org/10.1029/2010GB003900, 2012.
Kuppel, S., Peylin, P., Chevallier, F., Bacour, C., Maignan, F., and Richardson, A. D.: Constraining a global ecosystem model with multi-site eddy-covariance data, Biogeosciences, 9, 3757–3776, https://doi.org/10.5194/bg-9-3757-2012, 2012.
Lauvaux, T., Pannekoucke, O., Sarrat, C., Chevallier, F., Ciais, P., Noilhan, J., and Rayner, P. J.: Structure of the transport uncertainty in mesoscale inversions of CO2 sources and sinks using ensemble model simulations, Biogeosciences, 6, 1089–1102, https://doi.org/10.5194/bg-6-1089-2009, 2009a.
Lauvaux T., Gioli, B., Sarrat, C., Rayner, P. J., Ciais, P., Chevallier, F., Noilhan, J., Miglietta, F., Brunet, Y., Ceschia, E., Holman, H., Elbers, J. A., Gerbig, C., Hutjes, R., Jarosz,N., Legain, D., and Uliasz, M.: Bridging the gap between atmospheric concentrations and local ecosystem measurements, Geophys. Res. Lett., 36, L19809, https://doi.org/10.1029/2009GL039574, 2009b.
Law, R. M., Yu-Chan, C., Gurney, K. R., Rayner, P., Denning, A. S., and TransCom3 modelers:TransCom 3 CO2 inversion intercomparison: 2. Sensitivity of annual mean results to data choices, Tellus, 55B, 580–595, https://doi.org/10.1034/j.1600-0889.2003.00053.x, 2003.
Lasslop, G., Reichstein, M., Kattge, J., and Papale, D.: Influences of observation errors in eddy flux data on inverse model parameter estimation, Biogeosciences, 5, 1311–1324, https://doi.org/10.5194/bg-5-1311-2008, 2008.
Lasslop, G., Reichstein, M., Papale, D., Richardson, A., Arneth, A., Barr, A., Stoy, P., and Wohlfahrt, G.: Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation, Glob. Change Biol., 16, 187–208, 2010.
Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., and Moorcroft, P. R.: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2, J. Geophys. Res., 114, G01002, https://doi.org/10.1029/2008JG000812, 2009.
Moore, D. J. P., Hu, J., Sacks, W. J., Schimel, D. S., and Monson, R. K.: Estimating transpiration and the sensitivity of carbon uptake to water water availability in a subalpine forest using a simple ecosystem process model informed by measured net CO2 and H2O fluxes, Agr. Forest Meteorol., 148, 1467–1477, https://doi.org/10.1016/j.agrformet.2008.04.013, 2008.
Nijssen, B., Schnur, R., and Lettenmaier, D.: Retrospective estimation of soil moisture using the VIC land surface model, 1980–1993, J. Climate, 14, 1790–1808, 2001.
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J., Masarie, K., Miller, J. B., Bruhwiler, L. M. P.,P\textasciiacute etron, G., Hirsch, A. I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O., Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104, 18925–18930, 2007.
Peters, W., Krol, M. C., Werf van der, G. R., Houweling, S., Jones, C. D., Hughes, J., Schaefer, K., Masarie, K. A., Jacobson, A. R., Miller, J. B., Cho, C. H., Ramonet, M., Schmidt, M. , Ciattaglia, L., Apadula, F., Heltai, D., Meinhardt, F., Sarra, A. G., di Piacentino, S., Sferlazzo, D., Aalto, T., Hatakka, J., Ström, J., Haszpra, L., Meijer, H. A. J., Laan, S., van der Neubert, R. E. M., Jordan, A., Rodó, X., Morguí, J.-A., Vermeulen, A. T., Popa, E., Rozanski, K., Zimnoch, M., Manning, A. C., Leuenberger, M., Uglietti, C., Dolman, H., Ciais, P., Heimann, M., and Tans, P. P.: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations, Glob. Change Biol., 16, 1317–1337, https://doi.org/10.1111/j.1365-2486.2009.02078.x, 2010.
Peylin, P., Bousquet, P., Le Quere, C., Sitch, S., Friedlingstein, P., McKinley, G., Gruber, N., Rayner, P., and Ciais, P.: Multiple constraints on regional CO2 flux variations over land and oceans, Global Biogeochem. Cy., 19, GB1011, https://doi.org/10.1029/2003GB002214, 2005.
Piao, S. L., Ciais, P., Friedlingstein, P., Peylin, P., Reichstein, M., Luyssaert, S., Margolis, H., Fang, J. Y., Barr, A., Chen, A. P., Grelle, A., Hollinger, D. Y., Laurila, T., Lindroth, A., Richardson, A. D., and Vesala, T.: Net carbon dioxide losses of northern ecosystems in response to autumn warming, Nature, 451, 49–U43, 2008.
Rayner, P. J.: The current state of carbon-cycle data assimilation, Current Opinion in Environmental Sustainability, 2, 289–296, https://doi.org/10.1016/j.cosust.2010.05.005, 2010.
Rayner, P., Scholze, M., Knorr, W., Kaminski, T., Giering, R., and Widmann, H.: Two decades of terrestrial Carbon fluxes from a Carbon Cycle Data Assimilation System (CCDAS), Global Biogeochem. Cy., 19, GB2026, https://doi.org/10.1029/2004GB002254, 2005.
Rayner, P. J., Law, R. M., Allison, C. E., Francey, R. J., Trudinger, C. M., and Pickett-Heaps, C.: Interannual variability of the global carbon cycle (1992–2005) inferred by inversion of atmospheric CO2 and $\delta $13CO2 measurements, Global Biogeochem. Cy., 22, GB3008, https://doi.org/10.1029/2007GB003068, 2008.
Rebmann, C., Göckede, M., Foken, T., Aubinet, M., Aurela, M., Berbigier, P., Bernhofer, C., Buchmann, N., Carrara, A., Cescatti, A., Ceulemans, R., Clement, R., Granier, J. A., Grünwald, T., Guyon, D., Havránková, K., Heinesch, B., Knohl, A., Laurila, T. Longdoz, B., Marcolla, B., Markkanen, T., Miglietta, F., Moncrieff, J., Montagnani, L., Moors, E., Nardino, M., Ourcival, J.-M., Rambal, S., Rannik, U., Rotenberg, E., Sedlak, P., Unterhuber, G., Vesala, T., and Yakir, D.: Quality analysis applied on eddy covariance measurements at complex forest sites using footprint modelling, Theor. Appl. Climatol., 80, 121–141, 2005.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Glob. Change Biol., 11, 1424–1439, 2005.
Richardson, A. D. and Hollinger, D. Y.: Statistical modeling of ecosystem respiration using eddy covariance data: Maximum likelihood parameter estimation, and Monte Carlo simulation of model and parameter uncertainty, applied to three simple models, Agr. Forest Meteorol., 131, 191–208, 2005.
Richardson, A. D., Mahecha, M. D., Falge, E., Kattge, J., Moffat, A. M., Papale, D., Reichstein, M., Stauch, V. J., Braswell, B. H., Churkina, G., Kruijt, B., and Hollinger, D. Y.: Statistical properties of random CO2 flux measurement uncertainty inferred from model residuals, Agr. Forest Meteorol., 148, 38–50, 2008.
Richardson, A. D., Williams, M., Hollinger, D. Y., Moore, D. J. P., Bryan, P. D. B., Davidson, E. A., Scott, N. A., Evans, R. S., Hughes, H., Lee, J. T., Rodrigues, C., and Savage, K: Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints, Oecologia, 164, 25–40, 2010.
Rödenbeck, C., Houweling, S., Gloor, M., and Heimann, M.: CO2 flux history 1982–2001 inferred from atmospheric data using a global inversion of atmospheric transport, Atmos. Chem. Phys., 3, 1919–1964, https://doi.org/10.5194/acp-3-1919-2003, 2003.
Scholze, M., Kaminski, T., Rayner, P., Knorr, W., and Giering, R.: Propagating uncertainty through prognostic CCDAS simulations, J. Geophys. Res., 112, D17305, https://doi.org/10.1029/2007JD008642, 2007.
Tarantola, A: Inverse Problem Theory: Methods for Data Fitting and Parameter Estimation, Elsevier, Amsterdam, 1987.
Tarantola, A.: Inverse problem theory and methods for model parameters estimation. Society for Industrial and Applied Mathematics, Philadelphia, ISBN 0-89871-572-5, 2005.
Wang, Y. P., Leuning, R., Cleugh, H., and Coppin, P. A.: Parameter estimation in surface exchange models using non-linear inversion: How many parameters can we estimate and which measurements are most useful?, Glob. Change Biol., 7, 495–510, 2001.
Williams, M., Richardson, A. D., Reichstein, M., Stoy, P. C., Peylin, P., Verbeeck, H., Carvalhais, N., Jung, M., Hollinger, D. Y., Kattge, J., Leuning, R., Luo, Y., Tomelleri, E., Trudinger, C. M., and Wang, Y. -P.: Improving land surface models with FLUXNET data, Biogeosciences, 6, 1341–1359, https://doi.org/10.5194/bg-6-1341-2009, 2009.
Ziehn, T., Kattge, J., Knorr, W., and Scholze, M.: Improving the predictability of global CO2 assimilation rates under climate change, Geophys. Res. Lett., 38, L10404, https://doi.org/10.1029/2011GL047182, 2011.
Zobitz, J. M., Moore, D. J. P., Sacks, W. J., Monson, R. K., Bowling, D. R., and Schimel, D. S.: Integration of process-based soil respiration models with whole-ecosystem CO2 measurements, Ecosystems, 11, 250–269, https://doi.org/10.1007/s10021-007-9120-1, 2008.
Zupanski, D., Denning, A. S., Uliasz, M., Zupanski, M., Schuh, A. E., Rayner, P. J., Peters, W., and Corbin, K. D.: Carbon flux bias esimation employing Maximum Likelihood Ensemble Filter (MLEF), J. Geophys. Res., 112, D17107, https://doi.org/10.1029/2006JD008371, 2007.
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