Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling : A review
Balsamo, Gianpaolo ; Agusti-Panareda, Anna ; Albergel, Clement ; Arduini, Gabriele ; Beljaars, Anton ; Bidlot, Jean ; Blyth, Eleanor ; Bousserez, Nicolas ; Boussetta, Souhail ; Brown, Andy ; Buizza, Roberto ; Buontempo, Carlo ; Chevallier, Frederic ; Choulga, Margarita ; Cloke, Hannah ; Cronin, Meghan F. ; Dahoui, Mohamed ; Rosnay, Patricia De ; Dirmeyer, Paul A. ; Drusch, Matthias ; Dutra, Emanuel ; Ek, Michael B. ; Gentine, Pierre ; Hewitt, Helene ; Keeley, Sarah P.E. ; Kerr, Yann ; Kumar, Sujay ; Lupu, Cristina ; Mahfouf, Jean Francois ; McNorton, Joe ; Mecklenburg, Susanne ; Mogensen, Kristian ; Muñoz-Sabater, Joaquín ; Orth, Rene ; Rabier, Florence ; Reichle, Rolf ; Ruston, Ben ; Pappenberger, Florian ; Sandu, Irina ; Seneviratne, Sonia I. ; Tietsche, Steffen ; Trigo, Isabel F. ; Uijlenhoet, Remko ; Wedi, Nils ; Woolway, R.I. ; Zeng, Xubin - \ 2019
Remote Sensing 11 (2019)8. - ISSN 2072-4292
Direct and inverse methods - Earth system modelling - Earth-observations

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Global carbon budget 2019
Friedlingstein, Pierre ; Jones, Matthew W. ; O'Sullivan, Michael ; Andrew, Robbie M. ; Hauck, Judith ; Peters, Glen P. ; Peters, Wouter ; Pongratz, Julia ; Sitch, Stephen ; Quéré, Corinne Le; Bakker, Dorothee C.E. ; Canadell1, Josep G. ; Ciais1, Philippe ; Jackson, Robert B. ; Anthoni, Peter ; Barbero, Leticia ; Bastos, Ana ; Bastrikov, Vladislav ; Becker, Meike ; Bopp, Laurent ; Buitenhuis, Erik ; Chandra, Naveen ; Chevallier, Frédéric ; Chini, Louise P. ; Currie, Kim I. ; Feely, Richard A. ; Gehlen, Marion ; Gilfillan, Dennis ; Gkritzalis, Thanos ; Goll, Daniel S. ; Gruber, Nicolas ; Gutekunst, Sören ; Harris, Ian ; Haverd, Vanessa ; Houghton, Richard A. ; Hurtt, George ; Ilyina, Tatiana ; Jain, Atul K. ; Joetzjer, Emilie ; Kaplan, Jed O. ; Kato, Etsushi ; Goldewijk, Kees Klein ; Korsbakken, Jan Ivar ; Landschützer, Peter ; Lauvset, Siv K. ; Lefèvre, Nathalie ; Lenton, Andrew ; Lienert, Sebastian ; Lombardozzi, Danica ; Marland, Gregg ; McGuire, Patrick C. ; Melton, Joe R. ; Metzl, Nicolas ; Munro, David R. ; Nabel, Julia E.M.S. ; Nakaoka, Shin Ichiro ; Neill, Craig ; Omar, Abdirahman M. ; Ono, Tsuneo ; Peregon, Anna ; Pierrot, Denis ; Poulter, Benjamin ; Rehder, Gregor ; Resplandy, Laure ; Robertson, Eddy ; Rödenbeck, Christian ; Séférian, Roland ; Schwinger, Jörg ; Smith, Naomi ; Tans, Pieter P. ; Tian, Hanqin ; Tilbrook, Bronte ; Tubiello, Francesco N. ; Werf, Guido R. Van Der; Wiltshire, Andrew J. ; Zaehle, Sönke - \ 2019
Earth System Science Data 11 (2019)4. - ISSN 1866-3508 - p. 1783 - 1838.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere-the "global carbon budget"-is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2009-2018), EFF was 9:5±0:5 GtC yr-1, ELUC 1:5±0:7 GtC yr-1, GATM 4:9±0:02 GtC yr-1 (2:3±0:01 ppm yr-1), SOCEAN 2:5±0:6 GtC yr-1, and SLAND 3:2±0:6 GtC yr-1, with a budget imbalance BIM of 0.4 GtC yr-1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1% and fossil emissions increased to 10:0±0:5 GtC yr-1, reaching 10 GtC yr-1 for the first time in history, ELUC was 1:5±0:7 GtC yr-1, for total anthropogenic CO2 emissions of 11:5±0:9 GtC yr-1 (42:5±3:3 GtCO2). Also for 2018, GATM was 5:1±0:2 GtC yr-1 (2:4±0:1 ppm yr-1), SOCEAN was 2:6±0:6 GtC yr-1, and SLAND was 3:5±0:7 GtC yr-1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407:38±0:1 ppm averaged over 2018. For 2019, preliminary data for the first 6-10 months indicate a reduced growth in EFF of C0:6% (range of.0:2% to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959-2018, but discrepancies of up to 1 GtC yr-1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

Population recovery changes population composition at a major southern Caribbean juvenile developmental habitat for the green turtle, Chelonia mydas
Zee, Jurjan P. van der; Christianen, Marjolijn J.A. ; Nava, Mabel ; Velez-Zuazo, Ximena ; Hao, Wensi ; Bérubé, Martine ; Lavieren, Hanneke van; Hiwat, Michael ; Berzins, Rachel ; Chevalier, Johan ; Chevallier, Damien ; Lankester, Marie Clélia ; Bjorndal, Karen A. ; Bolten, Alan B. ; Becking, L.E. ; Palsbøll, Per J. - \ 2019
Scientific Reports 9 (2019)1. - ISSN 2045-2322

Understanding the population composition and dynamics of migratory megafauna at key developmental habitats is critical for conservation and management. The present study investigated whether differential recovery of Caribbean green turtle (Chelonia mydas) rookeries influenced population composition at a major juvenile feeding ground in the southern Caribbean (Lac Bay, Bonaire, Caribbean Netherlands) using genetic and demographic analyses. Genetic divergence indicated a strong temporal shift in population composition between 2006–2007 and 2015–2016 (ϕST = 0.101, P < 0.001). Juvenile recruitment (<75.0 cm straight carapace length; SCL) from the north-western Caribbean increased from 12% to 38% while recruitment from the eastern Caribbean region decreased from 46% to 20% between 2006–2007 and 2015–2016. Furthermore, the product of the population growth rate and adult female abundance was a significant predictor for population composition in 2015–2016. Our results may reflect early warning signals of declining reproductive output at eastern Caribbean rookeries, potential displacement effects of smaller rookeries by larger rookeries, and advocate for genetic monitoring as a useful method for monitoring trends in juvenile megafauna. Furthermore, these findings underline the need for adequate conservation of juvenile developmental habitats and a deeper understanding of the interactions between megafaunal population dynamics in different habitats.

Global atmospheric CO2 inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate
Gaubert, Benjamin ; Stephens, Britton B. ; Basu, Sourish ; Chevallier, Frédéric ; Deng, Feng ; Kort, Eric A. ; Patra, Prabir K. ; Peters, Wouter ; Rödenbeck, Christian ; Saeki, Tazu ; Schimel, David ; Laan-Luijkx, Ingrid van der; Wofsy, Steven ; Yin, Yi - \ 2019
Biogeosciences 16 (2019)1. - ISSN 1726-4170 - p. 117 - 134.

We have compared a suite of recent global CO2 atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO2 concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-To-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009-2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80% since TransCom 3 and 70% since RECCAP. Most modeled CO2 fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009- 2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004-2014, 2001-2004, 1992-1996) and reevaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean-land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean-land partitioning from the model ensemble.

Satellite and in situ observations for advancing global earth surface modelling : A review
Balsamo, Gianpaolo ; Agusti-Panareda, Anna ; Albergel, Clement ; Arduini, Gabriele ; Beljaars, Anton ; Bidlot, Jean ; Blyth, Eleanor ; Bousserez, Nicolas ; Boussetta, Souhail ; Brown, Andy ; Buizza, Roberto ; Buontempo, Carlo ; Chevallier, Frederic ; Choulga, Margarita ; Cloke, Hannah ; Cronin, Meghan F. ; Dahoui, Mohamed ; Rosnay, Patricia De ; Dirmeyer, Paul A. ; Drusch, Matthias ; Dutra, Emanuel ; Ek, Michael B. ; Gentine, Pierre ; Hewitt, Helene ; Keeley, Sarah P.E. ; Kerr, Yann ; Kumar, Sujay ; Lupu, Cristina ; Mahfouf, Jean Francois ; McNorton, Joe ; Mecklenburg, Susanne ; Mogensen, Kristian ; Muñoz-Sabater, Joaquín ; Orth, Rene ; Rabier, Florence ; Reichle, Rolf ; Ruston, Ben ; Pappenberger, Florian ; Sandu, Irina ; Seneviratne, Sonia I. ; Tietsche, Steffen ; Trigo, Isabel F. ; Uijlenhoet, Remko ; Wedi, Nils ; Woolway, R.I. ; Zeng, Xubin - \ 2018
Remote Sensing 10 (2018)12. - ISSN 2072-4292
Direct and inverse methods - Earth system modelling - Earth-observations

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Tropical land carbon cycle responses to 2015/16 El Niño as recorded by atmospheric greenhouse gas and remote sensing data
Gloor, Emanuel ; Wilson, Chris ; Chipperfield, Martyn P. ; Chevallier, Frederic ; Buermann, Wolfgang ; Boesch, Hartmut ; Parker, Robert ; Somkuti, Peter ; Gatti, Luciana V. ; Correia, Caio ; Domingues, Lucas G. ; Peters, Wouter ; Miller, John ; Deeter, Merritt N. ; Sullivan, Martin J.P. - \ 2018
Philosophical Transactions of the Royal Society B. Biological sciences 373 (2018)1760. - ISSN 0962-8436 - 12 p.
carbon cycle - fire - global warming - tropical forests

The outstanding tropical land climate characteristic over the past decades is rapid warming, with no significant large-scale precipitation trends. This warming is expected to continue but the effects on tropical vegetation are unknown. El Niño-related heat peaks may provide a test bed for a future hotter world. Here we analyse tropical land carbon cycle responses to the 2015/16 El Niño heat and drought anomalies using an atmospheric transport inversion. Based on the global atmospheric CO2 and fossil fuel emission records, we find no obvious signs of anomalously large carbon release compared with earlier El Niño events, suggesting resilience of tropical vegetation. We find roughly equal net carbon release anomalies from Amazonia and tropical Africa, approximately 0.5 PgC each, and smaller carbon release anomalies from tropical East Asia and southern Africa. Atmospheric CO anomalies reveal substantial fire carbon release from tropical East Asia peaking in October 2015 while fires contribute only a minor amount to the Amazonian carbon flux anomaly. Anomalously large Amazonian carbon flux release is consistent with downregulation of primary productivity during peak negative near-surface water anomaly (October 2015 to March 2016) as diagnosed by solar-induced fluorescence. Finally, we find an unexpected anomalous positive flux to the atmosphere from tropical Africa early in 2016, coincident with substantial CO release.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Age of air as a diagnostic for transport timescales in global models
Krol, Maarten ; Bruine, Marco de; Killaars, Lars ; Ouwersloot, Huug ; Pozzer, Andrea ; Yin, Yi ; Chevallier, Frederic ; Bousquet, Philippe ; Patra, Prabir ; Belikov, Dmitry ; Maksyutov, Shamil ; Dhomse, Sandip ; Feng, Wuhu ; Chipperfield, Martyn P. - \ 2018
Geoscientific Model Development 11 (2018)8. - ISSN 1991-959X - p. 3109 - 3130.

This paper presents the first results of an age-of-air (AoA) inter-comparison of six global transport models. Following a protocol, three global circulation models and three chemistry transport models simulated five tracers with boundary conditions that grow linearly in time. This allows for an evaluation of the AoA and transport times associated with inter-hemispheric transport, vertical mixing in the troposphere, transport to and in the stratosphere, and transport of air masses between land and ocean. Since AoA is not a directly measurable quantity in the atmosphere, simulations of 222Rn and SF6 were also performed. We focus this first analysis on averages over the period 2000-2010, taken from longer simulations covering the period 1988-2014. We find that two models, NIES and TOMCAT, show substantially slower vertical mixing in the troposphere compared to other models (LMDZ, TM5, EMAC, and ACTM). However, while the TOMCAT model, as used here, has slow transport between the hemispheres and between the atmosphere over land and ocean, the NIES model shows efficient horizontal mixing and a smaller latitudinal gradient in SF6 compared to the other models and observations. We find consistent differences between models concerning vertical mixing of the troposphere, expressed as AoA differences and modelled 222Rn gradients between 950 and 500 hPa. All models agree, however, on an interesting asymmetry in inter-hemispheric mixing, with faster transport from the Northern Hemisphere surface to the Southern Hemisphere than vice versa. This is attributed to a rectifier effect caused by a stronger seasonal cycle in boundary layer venting over Northern Hemispheric land masses, and possibly to a related asymmetric position of the intertropical convergence zone. The calculated AoA in the mid-upper stratosphere varies considerably among the models (4-7 years). Finally, we find that the inter-model differences are generally larger than differences in AoA that result from using the same model with a different resolution or convective parameterisation. Taken together, the AoA model inter-comparison provides a useful addition to traditional approaches to evaluate transport timescales. Results highlight that inter-model differences associated with resolved transport (advection, reanalysis data, nudging) and parameterised transport (convection, boundary layer mixing) are still large and require further analysis. For this purpose, all model output and analysis software are available.

Global Carbon Budget 2017
Quéré, Corinne Le; Andrew, Robbie M. ; Friedlingstein, Pierre ; Sitch, Stephen ; Pongratz, Julia ; Manning, Andrew C. ; Ivar Korsbakken, Jan ; Peters, Glen P. ; Canadell, Josep G. ; Jackson, Robert B. ; Boden, Thomas A. ; Tans, Pieter P. ; Andrews, Oliver D. ; Arora, Vivek K. ; Bakker, Dorothee C.E. ; Barbero, Leticia ; Becker, Meike ; Betts, Richard A. ; Bopp, Laurent ; Chevallier, Frédéric ; Chini, Louise P. ; Ciais, Philippe ; Cosca, Catherine E. ; Cross, Jessica ; Currie, Kim ; Gasser, Thomas ; Harris, Ian ; Hauck, Judith ; Haverd, Vanessa ; Houghton, Richard A. ; Hunt, Christopher W. ; Hurtt, George ; Ilyina, Tatiana ; Jain, Atul K. ; Kato, Etsushi ; Kautz, Markus ; Keeling, Ralph F. ; Klein Goldewijk, Kees ; Körtzinger, Arne ; Landschützer, Peter ; Lefèvre, Nathalie ; Lenton, Andrew ; Lienert, Sebastian ; Lima, Ivan ; Lombardozzi, Danica ; Metzl, Nicolas ; Millero, Frank ; Monteiro, Pedro M.S. ; Munro, David R. ; Nabel, Julia E.M.S. ; Nakaoka, Shin Ichiro ; Nojiri, Yukihiro ; Padin, X.A. ; Peregon, Anna ; Pfeil, Benjamin ; Pierrot, Denis ; Poulter, Benjamin ; Rehder, Gregor ; Reimer, Janet ; Rödenbeck, Christian ; Schwinger, Jörg ; Séférian, Roland ; Skjelvan, Ingunn ; Stocker, Benjamin D. ; Tian, Hanqin ; Tilbrook, Bronte ; Tubiello, Francesco N. ; Laan-Luijkx, Ingrid T. van der; Werf, Guido R. van der; Heuven, Steven Van; Viovy, Nicolas ; Vuichard, Nicolas ; Walker, Anthony P. ; Watson, Andrew J. ; Wiltshire, Andrew J. ; Zaehle, Sönke ; Zhu, Dan - \ 2018
Earth System Science Data 10 (2018)1. - ISSN 1866-3508 - p. 405 - 448.
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere-the "global carbon budget"-is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1δ. For the last decade available (2007-2016), EFF was 9.4±0.5 GtC yr-1, ELUC 1.3±0.7 GtC yr-1, GATM 4.7±0.1 GtC yr-1, SOCEAN 2.4±0.5 GtC yr-1, and SLAND 3.0±0.8 GtC yr-1, with a budget imbalance BIM of 0.6 GtC yr-1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9±0.5 GtC yr-1. Also for 2016, ELUC was 1.3±0.7 GtC yr-1, GATM was 6.1±0.2 GtC yr-1, SOCEAN was 2.6±0.5 GtC yr-1, and SLAND was 2.7±1.0 GtC yr-1, with a small BIM of-0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007-2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ninõ conditions. The global atmospheric CO2 concentration reached 402.8±0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6-9 months indicate a renewed growth in EFF of C2.0% (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).
Atmospheric deposition, CO2, and change in the land carbon sink
Fernández-Martínez, M. ; Vicca, S. ; Janssens, I.A. ; Ciais, P. ; Obersteiner, M. ; Bartrons, M. ; Sardans, Jordi ; Verger, Aleixandre ; Canadell, J.G. ; Chevallier, F. ; Wang, X. ; Bernhofer, C. ; Curtis, P.S. ; Gianelle, D. ; Grünwald, T. ; Heinesch, B. ; Ibrom, A. ; Knohl, A. ; Laurila, T. ; Law, Beverly E. ; Limousin, J.M. ; Longdoz, B. ; Loustau, D. ; Mammarella, I. ; Matteucci, G. ; Monson, R.K. ; Montagnani, L. ; Moors, E.J. ; Munger, J.W. ; Papale, D. ; Piao, S.L. ; Peñuelas, J. - \ 2017
Scientific Reports 7 (2017). - ISSN 2045-2322 - 13 p.

Concentrations of atmospheric carbon dioxide (CO2) have continued to increase whereas atmospheric deposition of sulphur and nitrogen has declined in Europe and the USA during recent decades. Using time series of flux observations from 23 forests distributed throughout Europe and the USA, and generalised mixed models, we found that forest-level net ecosystem production and gross primary production have increased by 1% annually from 1995 to 2011. Statistical models indicated that increasing atmospheric CO2 was the most important factor driving the increasing strength of carbon sinks in these forests. We also found that the reduction of sulphur deposition in Europe and the USA lead to higher recovery in ecosystem respiration than in gross primary production, thus limiting the increase of carbon sequestration. By contrast, trends in climate and nitrogen deposition did not significantly contribute to changing carbon fluxes during the studied period. Our findings support the hypothesis of a general CO2-fertilization effect on vegetation growth and suggest that, so far unknown, sulphur deposition plays a significant role in the carbon balance of forests in industrialized regions. Our results show the need to include the effects of changing atmospheric composition, beyond CO2, to assess future dynamics of carbon-climate feedbacks not currently considered in earth system/climate modelling.

Global inverse modeling of CH4 sources and sinks : An overview of methods
Houweling, Sander ; Bergamaschi, Peter ; Chevallier, Frederic ; Heimann, Martin ; Kaminski, Thomas ; Krol, Maarten ; Michalak, Anna M. ; Patra, Prabir - \ 2017
Atmospheric Chemistry and Physics 17 (2017)1. - ISSN 1680-7316 - p. 235 - 256.

The aim of this paper is to present an overview of inverse modeling methods that have been developed over the years for estimating the global sources and sinks of CH4. It provides insight into how techniques and estimates have evolved over time and what the remaining shortcomings are. As such, it serves a didactical purpose of introducing apprentices to the field, but it also takes stock of developments so far and reflects on promising new directions. The main focus is on methodological aspects that are particularly relevant for CH4, such as its atmospheric oxidation, the use of methane isotopologues, and specific challenges in atmospheric transport modeling of CH4. The use of satellite retrievals receives special attention as it is an active field of methodological development, with special requirements on the sampling of the model and the treatment of data uncertainty. Regional scale flux estimation and attribution is still a grand challenge, which calls for new methods capable of combining information from multiple data streams of different measured parameters. A process model representation of sources and sinks in atmospheric transport inversion schemes allows the integrated use of such data. These new developments are needed not only to improve our understanding of the main processes driving the observed global trend but also to support international efforts to reduce greenhouse gas emissions.

Global Carbon Budget 2016
Quéré, C. Le; Andrew, R.M. ; Canadell, J.G. ; Sitch, Stephen ; Korsbakken, Jan Ivar ; Peters, Glen P. ; Manning, Andrew C. ; Boden, Thomas A. ; Tans, Pieter P. ; Houghton, Richard A. ; Keeling, Ralph F. ; Alin, Simone ; Andrews, Oliver D. ; Anthoni, Peter ; Barbero, Leticia ; Bopp, Laurent ; Chevallier, Frédéric ; Chini, Louise P. ; Ciais, Philippe ; Currie, Kim ; Delire, Christine ; Doney, Scott C. ; Friedlingstein, Pierre ; Gkritzalis, Thanos ; Harris, Ian ; Hauck, Judith ; Haverd, Vanessa ; Hoppema, Mario ; Klein Goldewijk, Kees ; Jain, Atul K. ; Kato, Etsushi ; Körtzinger, Arne ; Landschützer, Peter ; Lefèvre, Nathalie ; Lenton, Andrew ; Lienert, Sebastian ; Lombardozzi, Danica ; Melton, Joe R. ; Metzl, Nicolas ; Millero, Frank ; Monteiro, Pedro M.S. ; Munro, David R. ; Nabel, Julia E.M.S. ; Nakaoka, Shin-Ichiro ; O'Brien, Kevin ; Olsen, Are ; Omar, Abdirahman M. ; Ono, Tsuneo ; Pierrot, Denis ; Poulter, Benjamin ; Rödenbeck, Christian ; Salisbury, Joe ; Schuster, Ute ; Séférian, Roland ; Skjelvan, Ingunn ; Stocker, Benjamin D. ; Sutton, Adrienne J. ; Takahashi, Taro ; Tian, Hanqin ; Tilbrook, Bronte ; Laan-Luijkx, I.T. van der; Werf, Guido R. Van Der; Viovy, Nicolas ; Walker, Anthony P. ; Wiltshire, Andrew J. ; Zaehle, Sönke - \ 2016
Global Carbon Budget 2016
Quéré, Corinne Le; Andrew, Robbie M. ; Canadell, Josep G. ; Sitch, Stephen ; Korsbakken, Jan Ivar ; Peters, Glen P. ; Manning, Andrew C. ; Boden, Thomas A. ; Tans, Pieter P. ; Houghton, Richard A. ; Keeling, Ralph F. ; Alin, Simone ; Andrews, Oliver D. ; Anthoni, Peter ; Barbero, Leticia ; Bopp, Laurent ; Chevallier, Frédéric ; Chini, Louise P. ; Ciais, Philippe ; Currie, Kim ; Delire, Christine ; Doney, Scott C. ; Friedlingstein, Pierre ; Gkritzalis, Thanos ; Harris, Ian ; Hauck, Judith ; Haverd, Vanessa ; Hoppema, Mario ; Klein Goldewijk, Kees ; Jain, Atul K. ; Kato, Etsushi ; Körtzinger, Arne ; Landschützer, Peter ; Lefèvre, Nathalie ; Lenton, Andrew ; Lienert, Sebastian ; Lombardozzi, Danica ; Melton, Joe R. ; Metzl, Nicolas ; Millero, Frank ; Monteiro, Pedro M.S. ; Munro, David R. ; Nabel, Julia E.M.S. ; Nakaoka, S. ; O'Brien, Kevin ; Olsen, Are ; Omar, Abdirahman M. ; Ono, Tsuneo ; Pierrot, Denis ; Poulter, Benjamin ; Rödenbeck, Christian ; Salisbury, Joe ; Schuster, Ute ; Schwinger, Jörg ; Séférian, Roland ; Skjelvan, Ingunn ; Stocker, Benjamin D. ; Sutton, Adrienne J. ; Takahashi, Taro ; Tian, Hanqin ; Tilbrook, Bronte ; Laan-Luijkx, Ingrid T. van der; Werf, Guido R. van der; Viovy, Nicolas ; Walker, Anthony P. ; Wiltshire, Andrew J. ; Zaehle, Sönke - \ 2016
Earth System Science Data 8 (2016)2. - ISSN 1866-3508 - p. 605 - 649.
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center.
Inverse modeling of GOSAT-retrieved ratios of total column CH4 and CO2 for 2009 and 2010
Pandey, Sudhanshu ; Houweling, Sander ; Krol, Maarten ; Aben, Ilse ; Chevallier, Frédéric ; Dlugokencky, Edward J. ; Gatti, Luciana V. ; Gloor, Emanuel ; Miller, John B. ; Detmers, Rob ; Machida, Toshinobu ; Röckmann, Thomas - \ 2016
Atmospheric Chemistry and Physics 16 (2016)8. - ISSN 1680-7316 - p. 5043 - 5062.

This study investigates the constraint provided by greenhouse gas measurements from space on surface fluxes. Imperfect knowledge of the light path through the atmosphere, arising from scattering by clouds and aerosols, can create biases in column measurements retrieved from space. To minimize the impact of such biases, ratios of total column retrieved CH4 and CO2 (Xratio) have been used. We apply the ratio inversion method described in Pandey et al. (2015) to retrievals from the Greenhouse Gases Observing SATellite (GOSAT). The ratio inversion method uses the measured Xratio as a weak constraint on CO2 fluxes. In contrast, the more common approach of inverting proxy CH4 retrievals (Frankenberg et al., 2005) prescribes atmospheric CO2 fields and optimizes only CH4 fluxes. The TM5-4DVAR (Tracer Transport Model version 5-variational data assimilation system) inverse modeling system is used to simultaneously optimize the fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy inversions using model-derived CO2 mixing ratios (XCO2model) from CarbonTracker and the Monitoring Atmospheric Composition and Climate (MACC) Reanalysis CO2 product. The performance of the inverse models is evaluated using measurements from three aircraft measurement projects. Xratio and XCO2model are compared with TCCON retrievals to quantify the relative importance of errors in these components of the proxy XCH4 retrieval (XCH4proxy). We find that the retrieval errors in Xratio (mean Combining double low line 0.61%) are generally larger than the errors in XCO2model (mean Combining double low line 0.24 and 0.01% for CarbonTracker and MACC, respectively). On the annual timescale, the CH4 fluxes from the different satellite inversions are generally in agreement with each other, suggesting that errors in XCO2model do not limit the overall accuracy of the CH4 flux estimates. On the seasonal timescale, however, larger differences are found due to uncertainties in XCO2model, particularly over Australia and in the tropics. The ratio method stays closer to the a priori CH4 flux in these regions, because it is capable of simultaneously adjusting the CO2 fluxes. Over tropical South America, comparison to independent measurements shows that CO2 fields derived from the ratio method are less realistic than those used in the proxy method. However, the CH4 fluxes are more realistic, because the impact of unaccounted systematic uncertainties is more evenly distributed between CO2 and CH4. The ratio inversion estimates an enhanced CO2 release from tropical South America during the dry season of 2010, which is in accordance with the findings of Gatti et al. (2014) and Van der Laan et al. (2015). The performance of the ratio method is encouraging, because despite the added nonlinearity due to the assimilation of Xratio and the significant increase in the degree of freedom by optimizing CO2 fluxes, still consistent results are obtained with respect to other CH4 inversions.

Top-down assessment of the Asian carbon budget since the mid 1990s
Thompson, R.L. ; Patra, P.K. ; Chevallier, F. ; Maksyutov, S. ; Law, R.M. ; Ziehn, T. ; Laan-Luijkx, I.T. Van Der; Peters, W. ; Ganshin, A. ; Zhuravlev, R. ; Maki, T. ; Nakamura, T. ; Shirai, T. ; Ishizawa, M. ; Saeki, T. ; Machida, T. ; Poulter, B. ; Canadell, J.G. ; Ciais, P. - \ 2016
Nature Communications 7 (2016). - ISSN 2041-1723

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world's 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of -0.46 (-0.70-0.24) PgC per year (median and range) for 1996-2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996-2001 and 2008-2012 by 0.56 (0.30-0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change.

Global Carbon Budget 2015
Quéré, C. Le; Moriarty, R. ; Andrew, R.M. ; Canadell, J.G. ; Sitch, S. ; Korsbakken, J.I. ; Friedlingstein, P. ; Peters, G.P. ; Andres, R.J. ; Houghton, R.A. ; House, J.I. ; Keeling, R.F. ; Tans, P.P. ; Arneth, A. ; Bakker, D. ; Barbero, L. ; Bopp, L. ; Chang, J. ; Chevallier, F. ; Chini, L.P. ; Ciais, P. ; Feely, R.A. ; Gkritzalis, T. ; Harris, I. ; Hauck, J. ; Ilyina, T. ; Jain, A.K. ; Kato, E. ; Kitidis, V. ; Klein-Goldewijk, K. ; Koven, C. ; Landschützer, Peter ; Lauvset, S.K. ; Lefèvre, N. ; Metzl, N. ; Millero, F. ; Munro, D.R. ; Murata, A. ; Nabel, Julia E.M.S. ; Nakaoka, S. ; Nojiri, Y. ; O'Brien, Kate ; Olson, A. ; Ono, T. ; Pérez, N. ; Pfeil, B. ; Pierrot, D. ; Poulter, B. ; Rehder, G. ; Rödenbeck, C. ; Saito, S. ; Schuster, U. ; Schwinger, J. ; Séférian, R. ; Steinhoff, T. ; Stocker, B.D. ; Sutton, A.J. ; Takahashi, T. ; Tilbrook, B. ; Laan-Luijkx, I.T. van der; Werf, G.R. van de; Heuven, S. Van; Vandemark, D. ; Viovy, N. ; Wiltshire, A. ; Zaehle, S. ; Zeng, N. - \ 2015
Global Carbon Budget 2014
Quéré, C. Le; Moriarty, R. ; Andrew, R.M. ; Peters, G.P. ; Ciais, P. ; Friedlingstein, P. ; Jones, S.D. ; Sitch, S. ; Tans, P.P. ; Arneth, A. ; Boden, T.A. ; Bopp, L. ; Bozec, Y. ; Canadell, J.G. ; Chevallier, F. ; Cosca, C.E. ; Harris, I. ; Hoppema, Mario ; Houghton, R.A. ; House, J.I. ; Jain, A.K. ; Johannessen, T. ; Kato, E. ; Keeling, R.F. ; Kitidis, V. ; Klein Goldewijk, Kees ; Koven, C. ; Landa, C.S. ; Landschützer, P. ; Lenton, A. ; Lima, I.D. ; Marland, G. ; Mathis, J.T. ; Metzl, N. ; Nojiri, Y. ; Olson, A. ; Ono, T. ; Peters, Wouter ; Pfeil, B. ; Poulter, Benjamin ; Raupach, M.R. ; Regnier, P. ; Rödenbeck, C. ; Saito, S. ; Sailsbury, J.E. ; Schuster, U. ; Schwinger, J. ; Séférian, R. ; Segschneider, J. ; Steinhoff, T. ; Stocker, B.D. ; Sutton, A.J. ; Takahashi, T. ; Tilbrook, B. ; Werf, G.R. van der; Viovy, N. ; Wang, Y.P. ; Wanninkhof, R. ; Wiltshire, A. ; Zeng, N. - \ 2015
CDIAC
Global Carbon Budget 2015
Quéré, C. Le; Moriarty, R. ; Andrew, R.M. ; Canadell, J.G. ; Sitch, S. ; Korsbakken, J.I. ; Friedlingstein, P. ; Peters, G.P. ; Andres, R.J. ; Boden, T.A. ; Houghton, R.A. ; House, J.I. ; Keeling, R.F. ; Tans, P. ; Arneth, A. ; Bakker, D.C.E. ; Barbero, L. ; Bopp, L. ; Chang, J. ; Chevallier, F. ; Chini, L.P. ; Ciais, P. ; Fader, M. ; Feely, R.A. ; Gkritzalis, T. ; Harris, I. ; Hauck, J. ; Ilyina, T. ; Jain, A.K. ; Kato, E. ; Kitidis, V. ; Klein Goldewijk, K. ; Koven, C. ; Landschützer, P. ; Lauvset, S.K. ; Lefèvre, N. ; Lenton, A. ; Lima, I.D. ; Metzl, N. ; Millero, F. ; Munro, D.R. ; Murata, A. ; Nabel, J.E.M.S. ; Nakaoka, S. ; Nojiri, Y. ; O'Brien, K. ; Olsen, A. ; Ono, T. ; Pérez, F.F. ; Pfeil, B. ; Pierrot, D. ; Poulter, B. ; Rehder, G. ; Rödenbeck, C. ; Saito, S. ; Schuster, U. ; Schwinger, J. ; Séférian, R. ; Steinhoff, T. ; Stocker, B.D. ; Sutton, A.J. ; Takahashi, T. ; Tilbrook, B. ; Laan-Luijkx, I.T. Van Der; Werf, G.R. Van Der; Heuven, S. Van; Vandemark, D. ; Viovy, N. ; Wiltshire, A. ; Zaehle, S. ; Zeng, N. - \ 2015
Earth System Science Data 7 (2015)2. - ISSN 1866-3508 - p. 349 - 396.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005-2014), EFF was 9.0 ± 0.5 GtC yrg'1, ELUC was 0.9 ± 0.5 GtC yrg'1, GATM was 4.4 ± 0.1 GtC yrg'1, SOCEAN was 2.6 ± 0.5 GtC yrg'1, and SLAND was 3.0 ± 0.8 GtC yrg'1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yrg'1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yrg'1 that took place during 2005-2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yrg'1, GATM was 3.9 ± 0.2 GtC yrg'1, SOCEAN was 2.9 ± 0.5 GtC yrg'1, and SLAND was 4.1 ± 0.9 GtC yrg'1. GATM was lower in 2014 compared to the past decade (2005-2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of g'0.6 [range of g'1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870-2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2015).

River flow regime and snow cover of the Pamir Alay (Central Asia) in a changing climate
Chevallier, P. ; Pouyaud, B. ; Mojaisky, M. ; Bolgov, M. ; Olsson, O. ; Bauer, M. ; Froebrich, J. - \ 2014
Hydrological Sciences Journal 59 (2014)8. - ISSN 0262-6667 - p. 1491 - 1506.
remote-sensing data - northern tien-shan - hydrological regime - water availability - glacier retreat - historical data - stereo imagery - aster imagery - mass balances - runoff
The Vakhsh and Pyandj rivers, main tributaries of the Amu Darya River in the mountainous region of the Pamir Alay, play an important role in the water resources of the Aral Sea basin (Central Asia). In this region, the glaciers and snow cover significantly influence the water cycle and flow regime, which could be strongly modified by climate change. The present study, part of a project funded by the European Commission, analyses the hydrological situation in six benchmark basins covering areas of between 1800 and 8400km(2), essentially located in Tajikistan, with a variety of topographical situations, precipitation amounts and glacierized areas. Four types of parameter are discussed: temperature, glaciation, snow cover and river flows. The study is based mainly on a long-time series that ended in the 1990s (with the collapse of the Soviet Union) and on field observations and data collection. In addition, a short, more recent period (May 2000 to May 2002) was examined to better understand the role of snow cover, using scarce monitored data and satellite information. The results confirm the overall homogeneous trend of temperature increase in the mountain range and its impacts on the surface water regime. Concerning the snow cover, significant differences are noted in the location, elevation, orientation and morphology of snow cover in the respective basins. The changes in the river flow regime are regulated by the combination of the snow cover dynamics and the increasing trend of the air temperature.
On the variation of regional CO2 exchange over temperate and boreal North America
Zhang, X. ; Gurney, K.R. ; Peylin, P. ; Chevallier, F. ; Law, R.M. ; Patra, P.K. ; Rayner, P.J. ; Roedenbeck, C. ; Krol, M.C. - \ 2013
Global Biogeochemical Cycles 27 (2013)4. - ISSN 0886-6236 - p. 991 - 1000.
atmospheric carbon-dioxide - terrestrial ecosystems - united-states - interannual variability - climate - forest - trends - drought - fluxes - land
Inverse-estimated net carbon exchange time series spanning two decades for six North American regions are analyzed to examine long-term trends and relationships to temperature and precipitation variations. Results reveal intensification of carbon uptake in eastern boreal North America (0.1 PgC/decade) and the Midwest United States (0.08 PgC/decade). Seasonal cross-correlation analysis shows a significant relationship between net carbon exchange and temperature/precipitation anomalies during the western United States growing season with warmer, dryer conditions leading reduced carbon uptake. This relationship is consistent with global change-type drought dynamics which drive increased vegetation mortality, increases in dry woody material, and increased wildfire occurrence. This finding supports the contention that future climate change may increase carbon loss in this region. Similarly, higher temperatures and reduced precipitation are accompanied by decreased net carbon uptake in the Midwestern United States toward the end of the growing season. Additionally, intensified net carbon uptake during the eastern boreal North America growing season is led by increased precipitation anomalies in the previous year, suggesting the influence of climate memory carried by regional snowmelt water. The two regions of boreal North America exhibit opposing seasonal carbon-temperature relationships with the eastern half experiencing a net carbon loss with near coincident increases in temperature and the western half showing increased net carbon uptake. The carbon response in the boreal west region lags the temperature anomalies by roughly 6months. This opposing carbon-temperature relationship in boreal North America may be a combination of different dominant vegetation types, the amount and timing of snowfall, and temperature anomaly differences across boreal North America.
Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling
Locatelli, R. ; Bousquet, P. ; Chevallier, F. ; Fortems-Cheney, A. ; Szopa, S. ; Saunois, M. ; Agusti-Panareda, A. ; Bergmann, D. ; Bian, H. ; Cameron-Smith, P. ; Chipperfield, M.P. ; Gloor, E. ; Houweling, S. ; Kawa, S.R. ; Krol, M.C. ; Patra, P.K. ; Prinn, R.G. ; Rigby, M. ; Saito, R. ; Wilson, C. - \ 2013
Atmospheric Chemistry and Physics 13 (2013)19. - ISSN 1680-7316 - p. 9917 - 9937.
general-circulation model - atmospheric transport - tracer transport - co2 inversions - boundary-layer - vertical profiles - data assimilation - climate-change - growth-rate - part i
A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Meteorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System) inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure) is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr(-1) at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr(-1) in North America to 7 Tg yr(-1) in Boreal Eurasia (from 23 to 48 %, respectively). At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly question the consistency of transport model errors in current inverse systems. Future inversions should include more accurately prescribed observation covariances matrices in order to limit the impact of transport model errors on estimated methane fluxes.
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