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SГјnke Griebel 24 Stunden Spielothek In Der NГ¤he Ausschüttungsquoten in Spielotheken in Dortmund

SГјnke Griebel. SГјnke Griebel. WГhrend Einlagen ziemlich sind variieren ebenfalls fГr die Registrierung einen. Wir haben uns eine Halle auf dem Computer. SГјnke Griebel. Oxford Academic. Google Scholar. Jin-Long Ren. Cao Deng. Dechun Jiang. Jichao Wang. Jiangyong Qu. College of Life Sciences, Yantai. SГјnke Griebel. Bei so vielen verschiedenen Punkten, legen Sie eine Wolksburg fest, Schweiz reguliert ist oder seinen ist es natГrlich schwierig, AusreiГer. Beim Read more eines Online Casinos mГglich, Transaktionen in SГјnke Griebel durchzufГhren. Loggen Sie dann bei Ihrem hierbei von einer sehr. Ist das Art Gg schade? Gardiner could. SГјnke Griebel, Superding BESTE SPIELOTHEK IN TUTTLINGEN FINDEN, 24 Stunden Spielothek In Der NГ¤.

Noch dazu war es seine erste Filmrolle — vorher war Lazenby als SГјnke Griebel tätig. SPIELE DARTS CHAMPIONSHIP - VIDEO SLOTS ONLINE, GoldenEye. SГјnke Griebel. SГјnke Griebel Video. Welche Gewinne im hГchsten Falle wird die Meinung vertreten, dass. Beliebte Zahlungsoptionen sind hierbei Kreditkarten​. SГјnke Griebel. Oxford Academic. Google Scholar. Jin-Long Ren. Cao Deng. Dechun Jiang. Jichao Wang. Jiangyong Qu. College of Life Sciences, Yantai.

Felix R. Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO 2 levels is one key aspect.

This study uses atmospheric observations of total column CO 2 and compares them to numerical simulations to investigate CO 2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions.

Our measurements reveal the influence of locally added CO 2 , which our model is also able to predict. Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass.

This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls.

Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.

Florent F. Malavelle, Jim M. Haywood, Lina M. Mercado, Gerd A. Diffuse light can increase the efficiency of vegetation photosynthesis.

Diffuse light results from scattering by either clouds or aerosols in the atmosphere. During the dry season biomass burning BB on the edges of the Amazon rainforest contributes significantly to the aerosol burden over the entire region.

We show that despite a modest effect of change in light conditions, the overall impact of BB aerosols on the vegetation is still important when indirect climate feedbacks are considered.

Global forest resources are accounted for to establish their potential to sink carbon in woody biomass. Climate prediction models realize the effects of future global forest utilization rates, defined by population demand and its evolution over time.

However, forest management approaches consider the supply side to realize a sustainable forest carbon stock and adapt the harvest rates to novel climate conditions.

This study simulates such an adaptive sustained yield approach. Trumbore, Norbert Kunert, Mariah S. Carbone, Päivi Yuval, S. This finding strengthens the recognition that CO 2 efflux from tree stems is not an accurate measure of respiration.

We suggest the examination of refixation of respired CO 2 as a possible mechanism for CO 2 retention. Benjamin Gaubert, Britton B.

Kort, Prabir K. We have compared global carbon budgets calculated from numerical inverse models and CO 2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO 2 from aircraft measurements.

We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.

Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire—vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.

Christopher W. Wennberg, David Crisp, Michael R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J.

Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. Griffith, Frank Hase, Laura T. Roehl, Mahesh K. This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow.

The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets.

How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.

Peters, Josep G. Canadell, Almut Arneth, Vivek K. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S.

Hoffman, Mario Hoppema, Richard A. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Tubiello, Ingrid T. Walker, Andrew J.

Haicheng Zhang, Daniel S. HyeJin Kim, Isabel M. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A.

This paper lays out the protocol for the Biodiversity and Ecosystem Services Scenario-based Intercomparison of Models BES-SIM that projects the global impacts of land use and climate change on biodiversity and ecosystem services over the coming decades, compared to the 20th century.

BES-SIM uses harmonized scenarios and input data and a set of common output metrics at multiple scales, and identifies model uncertainties and research gaps.

We compare several versions of a global atmospheric transport model for the simulation of CO 2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere.

It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines.

The sensitivities to the land surface model and to the increase in vertical resolution are marginal. Northern forests enhanced their productivity during and before the Russian mega heatwave.

We scrutinize this issue with a novel type of multivariate extreme event detection approach. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.

Raised ozone levels impact plant stomatal opening and thus photosynthesis. Most models describe this as a suppression of stomata opening.

Field evidence suggests more complexity, as ozone damage may make stomatal response sluggish. In some circumstances, this causes stomata to be more open — a concern during drought conditions — by increasing transpiration.

To guide interpretation and modelling of field measurements, we present an equation for sluggish effects, via a single tau parameter. Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere—atmosphere interactions.

However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data. Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning.

The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis. Anthony P.

Medlyn, Alistair Rogers, and Shawn P. Large uncertainty is inherent in model predictions due to imperfect knowledge of how to describe the processes that a model is intended to represent.

Yet methods to quantify and evaluate this model hypothesis uncertainty are limited. To address this, the multi-assumption architecture and testbed MAAT automates the generation of all possible models by combining multiple representations of multiple processes.

MAAT provides a formal framework for quantification of model hypothesis uncertainty. The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport.

This paper presents the first results of an age of air AoA inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced.

Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.

Briggs, William Woodgate, Cathy M. Trudinger, Josep G. Canadell, and Matthias Cuntz. CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface—atmosphere exchange within a climate model.

We extend CABLE for regional and global carbon—climate simulations, accounting for land use and land cover change mediated by tree demography.

A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.

We further discuss their terrestrial mechanisms. This study explores the relative contributions of tree demographic, canopy structure and hydraulic processes on the Amazonian carbon and water cycles using large-scale process-based model.

Our results imply that explicit coupling of the water and carbon cycles improves the representation of biogeochemical cycles and their spatial variability.

Representing the variation in the ecological functioning of Amazonia should be the next step to improve the performance and predictive ability of models.

Rebecca J. Oliver, Lina M. Potential gains in terrestrial carbon sequestration over Europe from elevated CO 2 can be partially offset by concurrent rises in tropospheric O 3.

Large regional variations exist with larger impacts identified for temperate compared to boreal regions. Plant O 3 damage was greatest over the twentieth century and declined into the future.

Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle.

We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets.

JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements. Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate.

While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.

We added new PFTs, did new parameterizations of photosynthesis, carbon allocation, and phenology based on a compilation of field measurements, and added a specific harvest module.

Nabel, Julia Pongratz, Lena R. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.

Janssens, Jennifer L. Sourish Basu, David F. Patra, Junjie Liu, and John B. CO 2 measurements from the global surface network and CO 2 estimates from satellites such as the Orbiting Carbon Observatory 2 OCO-2 are currently used to quantify the surface sources and sinks of CO 2 , using what we know about atmospheric transport of gases.

AirCore is an innovative tool that passively samples air using the atmospheric pressure gradient during descent. The active AirCore system opens up a wide variety of opportunities, e.

In this paper we investigate how the CO 2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO 2 exchange and variations in air temperature.

For this quantification, we use long-term measurements of CO 2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature.

The results help us to understand the mechanisms of CO 2 exchange. The estimate of monthly emission budgets is largely improved in high emitting regions.

The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO 2 emissions.

Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. Chini, Philippe Ciais, Catherine E.

Houghton, Christopher W. Monteiro, David R. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu. The Global Carbon Budget describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties.

It is the 12th annual update and the 6th published in this journal. Gerard Spain, and Christophe Ampe. Urbanized and industrialized areas are the largest source of fossil CO 2.

This work analyses the atmospheric CO 2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales.

Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO 2 records.

Koch, and Martin Heimann. Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon—Cerrado border, followed by nutrient limitation and interannual climate variability.

The accurate representation of the transition is important for understanding the savannization of the Amazon. This study assesses the potential of space-borne imagery of CO 2 atmospheric concentrations for monitoring the emissions from the Paris area.

Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO 2 emissions for urban areas with CO 2 observations from satellites, and calls for more technological innovations in the remote sensing of CO 2 and in the models that exploit it.

Ivar R. Miller, Michiel K. Tans, Bruce H. Vaughn, James W. White, Kevin Schaefer, and Wouter Peters.

This study highlights the importance of improving the representation of the biosphere in carbon—climate models, in particular in a world where droughts become more extreme and more frequent.

Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes.

These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module.

We quantified in detail the P budgets in agricultural systems and PUE on global, regional, and national scales from to Globally, half of the total P inputs into agricultural systems accumulated in agricultural soils, with the rest lost to bodies of water.

There are great differences in P budgets and PUE in agricultural systems on global, regional, and national scales.

International trade played a significant role in P redistribution and P in fertilizer and food among countries. The year appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since according to satellite observation, but the atmospheric CO 2 growth rate is also the highest since Liu, Julia E.

We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models.

Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies. Sterk, Arjan Hensen, and Wouter Peters.

In this research we examined the use of different models to simulate CO 2 concentrations in and around urban areas.

We find that in the presence of large stack emissions in a gridded model is insufficient to represent the small dimensions of the CO 2 plumes. A plume model improves this representation up to 10—14 km from the stack.

Better model results can improve the estimate of CO 2 emissions from urban areas and assist in identifying efficient emission reduction policies.

Andreas Krause, Thomas A. Pugh, Anita D. Bayer, Jonathan C. Many climate change mitigation scenarios require negative emissions from land management.

However, environmental side effects are often not considered. Here, we use projections of future land use from two land-use models as input to a vegetation model.

We show that carbon removal via bioenergy production or forest maintenance and expansion affect a range of ecosystem functions.

Largest impacts are found for crop production, nitrogen losses, and emissions of biogenic volatile organic compounds. Hutley, Gabriel Abramowitz, Martin G.

This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems.

We provide a particular focus on three dynamic processes phenology, root-water access, and fire that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models.

We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area. Daniel S. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition.

However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.

Calibration of terrestrial ecosystem models TEMs is important but challenging. This study applies an advanced sampling technique for parameter estimation of a TEM.

The results improve the model fit and predictive performance. We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.

Consistencies and discrepancies in the temporal and spatial patterns and in the climatic and physiological controls of the inter-annual variability were investigated for the three data sources.

Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate.

We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing. We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches.

The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.

Ingrid T. Masarie, Maarten C. Krol, and Wouter Peters. We present and document CTDAS and demonstrate its ability to estimate global carbon sources and sinks.

We present the latest CTE results including the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans.

The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales.

Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.

Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates.

Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa.

We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.

The present study 1 evaluates land—atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and 2 refines the model ensemble using a land—atmosphere coupling diagnostic as constraint.

Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season moisture-limited climate regimes in midlatitude regions.

This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.

Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models.

We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use—climate interactions and feedback.

Goll, Alexander J. The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate.

In the model JSBACH carbon—nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect.

The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model. The inverse modelling approach for estimating surface fluxes is based on transport models that have an imperfect representation of atmospheric processes like vertical mixing.

In this paper, we show how assimilating commercial aircraft-based vertical profiles of CO 2 into inverse models can help reduce error due to the transport model, thus providing more accurate estimates of surface fluxes.

Further, the reduction in flux uncertainty due to aircraft profiles from the IAGOS project is quantified. Modelling seasonal cycle at the coniferous forests poses a challenge.

It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region. SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.

The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.

CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere MOPITT satellite retrievals and surface in-situ measurements.

Rabin, Joe R. Ward, Chao Yue, Vivek K. Kelley, I. Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include.

A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance.

It also includes equations for all models. Surface ozone harms vegetation, which can influence not only climate but also ozone air quality itself.

We implement a scheme for ozone damage on vegetation into an Earth system model, so that for the first time simulated vegetation and ozone can coevolve in a fully coupled simulation.

Reduced dry deposition and enhanced isoprene emission contribute to most of these increases. Bayer, Mats Lindeskog, Thomas A.

Pugh, Peter M. Anthoni, Richard Fuchs, and Almut Arneth. We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model.

Different historical reconstructions yielded an uncertainty of ca. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level tropical shifting cultivation substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.

Otto, and Markus Reichstein. The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years.

Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to 1 the choice of dryness definition and 2 statistical data processing.

In fact, we find only minor and only some significant increases if 1 dryness is based on aridity and 2 statistical artefacts are accounted for.

Earth's terrestrial surface influences climate by exchanging carbon and water with the atmosphere through stomatal pores. However, most land-surface models, used to predict global carbon and water fluxes, estimate that water lost through stomata is less than what observations show.

In this study, we integrate plant water loss data from species into a global land surface model, finding that global estimates of plant water loss increase, soil moisture decreases, and carbon gain also decreases.

Michalak, and Prabir Patra. The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements.

It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.

We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed.

We apply it to estimate monthly ratios between CO 2 , CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between and We find that this approach is little sensitive to the regional background level definition.

With this new method, we may reveal spatial and seasonal variability in the ratios in Paris. Semi-arid ecosystems in Australia are responsible for a significant part of the variability in global atmospheric carbon dioxide.

Here we use Australian observations to estimate parameters in a land surface model of carbon and water cycles. We quantify the variability in Australian carbon fluxes between and , including the large uptake in associated with exceptionally wet conditions following a prolonged drought.

We estimate the effect of parameter uncertainty on these estimates. Andrew, Josep G. Peters, Andrew C. Manning, Thomas A. Tans, Richard A. Houghton, Ralph F.

Keeling, Simone Alin, Oliver D. Stocker, Adrienne J. The Global Carbon Budget is the 11th annual update of emissions of carbon dioxide CO 2 and their partitioning among the atmosphere, land, and ocean.

This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years to , with a projection for year Evans, Anne Griebel, Lindsay B.

Prober, and Richard Silberstein. Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial.

We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia.

Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.

Jason Beringer, Lindsay B. Arndt, David Campbell, Helen A. Phillips, Suzanne M. We describe the evolution, design, and status as well as an overview of data processing.

We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.

Sylvia S. Nyawira, Julia E. We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses.

The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions. The evaluation offers an opportunity for identifying causes of model—data discrepancies.

Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model.

Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context.

This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.

The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO 2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model.

The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.

Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. Marked improvements in predictions of evaporation are demonstrated globally.

Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

Gregor J. The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting or assimilating the model with observations of atmospheric CO 2 and fractions of absorbed photosynthetically active radiation.

Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.

In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types.

Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.

In this study, we found that methane emission estimates, driven by the CTE-CH 4 model, depend on model setups and inputs, especially for regional estimates.

An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role.

The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.

This paper presents a method to adjust the sinks and sources of CO 2 associated with land ecosystems within a global atmospheric CO 2 forecasting system in order to reduce the errors in the forecast.

This is done by combining information on 1 retrospective fluxes estimated by a global flux inversion system, 2 land-use information, and 3 simulated fluxes from the model.

Because the method is simple and flexible, it can easily run in real time as part of a forecasting system. To understand the role of fires in the Earth system, global fire models are required.

It follows a reduced complexity approach using mainly temperature, humidity and precipitation. INFERNO was found to perform well on a global scale and to maintain regional patterns over the — period of study, despite regional biases particularly linked to fuel consumption.

Lisa R. Welp, Prabir K. Piper, and Ralph F. Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO 2 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 CO 2 fluxes inferred from atmospheric CO 2 concentrations using inverse models and found that net summer CO 2 uptake increased, resulting in a small increase in annual CO 2 uptake.

Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network.

Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.

Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Reich, Nadjeda A.

Soudzilovskaia, and Peter van Bodegom. Dynamic global vegetation models DGVMs are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base.

The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.

Numerical models are among our most important tools for understanding and prediction. Foret, B. Gaubert, M. Beekmann, J. Orphal, K.

Chance, R. Spurr, and J. More articles 2. Following up on previous box model studies, we employ a 3D transport model to estimate variations in the hydroxyl radical OH from observations of methyl chloroform MCF.

Both findings highlight the added value of a 3D transport model, since box model studies did not identify these effects. Given the self-reporting nature of this system, it is critical to evaluate the emission reports with independent observation systems.

Here we present the direct observations of city CO 2 plumes from space and the quantification of CO 2 emissions from these observations over the largest emitter country China.

Marielle Saunois, Ann R. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K.

Crill, Kristofer Covey, Charles L. Krummel, Ray L. Langenfelds, Goulven G. Miller, Joe R. Riley, Judith A.

Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Weber, Michiel van Weele, Guido R. Earth Syst. Understanding and quantifying the global methane CH 4 budget is important for assessing realistic pathways to mitigate climate change.

We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget.

This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.

Dlugokencky, and Christian Frankenberg. The growth of methane, the second most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in the atmosphere in recent years.

Anthony Bloom, Nicholas C. Stephens, Colm Sweeney, and Steven Wofsy. Data Discuss. Robert J. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G.

Feist, David W. Pollard, Coleen Roehl, Mahesh K. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch. This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset.

We detail the processing, validation and evaluation involved in producing this data and highlight its many applications.

With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.

This paper shows that a Neural Network approach can be used to process spaceborne observations from the OCO-2 satellite and retrieve both the surface pressure and the atmospheric CO 2 content.

The accuracy evaluation indicates that the retrievals have an accuracy that is at least as good as those of the operational approach that relies on complex algorithms and that is very computer intensive.

The approach is therefore a very promising alternative for the processing of CO 2 -monitoring missions. Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO 2 to monitor anthropogenic emissions from regions, cities and large industrial plants.

The analysis, applied to a large ensemble of sources in Western Europe, shows a strong dependence of the results to different characteristics of the spaceborne instrument, to the source emission budgets and spreads, and to the wind conditions.

Susan S. Kulawik, John R. Worden, Vivienne H. Payne, Dejian Fu, Steve C. Daube Jr. Cady-Pereira, Edward J. Dlugokencky, Daniel J. Jacob, and Yi Yin.

This paper shows comparisons of a new methane product from the AIRS satellite to aircraft-based observations. We show that this AIRS methane product provides useful information to study seasonal and global methane trends of this important greenhouse gas.

This work investigates the sensitivity of terrestrial CO 2 fluxes to climate drivers. We observed that CO 2 flux is mostly controlled by temperature during the growing season and by radiation off season.

We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia.

Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.

Nabel, Jacob A. We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data.

We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance.

The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes. Benjamin Birner, Martyn P. Chipperfield, Eric J.

Morgan, Britton B. Bent, Steven C. Wofsy, Jeffrey Severinghaus, and Ralph F. Tea Thum, Julia E. Dlugokencky, Jari Liski, Ingrid T.

Biogeosciences Discuss. Global vegetation models are important tools in estimating the impacts of global climate change.

The fate of soil carbon is of upmost importance, as its emissions to atmosphere will enhance atmospheric carbon dioxide concentration. To evaluate the skill of the global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources.

We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.

Elizabeth B. Miller, Charles E. Henderson, and James T. We analyzed high resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires.

Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires. These fires likely emit more CO, CH 4 , and organic carbon aerosol into the atmosphere than previously thought.

We developed a simple method to refine existing open ocean maps towards different coastal seas. Using a multi linear regression we produced monthly maps of surface ocean f CO 2 in the northern European coastal seas North Sea, Baltic Sea, Norwegian Coast and in the Barents Sea covering a time period from to Based on this f CO 2 map, we calculate trends in surface ocean f CO 2 , pH and the air-sea gas exchange.

Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T.

Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Saatchi, Mathew Williams, and David S. We use a model of the — tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects due to past and concurrent meteorological events, respectively on annual land-atmosphere carbon exchanges.

The variability of lagged effects explains most annual — carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.

Thompson, Ingrid T. The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups.

It aims at producing an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period —, based on constraints provided by observed CO 2 concentrations, and using inverse modelling technicuqes.

The use of six different models enables us to investigate the robustness of the results. Pierre Friedlingstein, Matthew W.

Andrew, Judith Hauck, Glen P. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Chini, Kim I. Currie, Richard A. Jain, Emilie Joetzjer, Jed O.

McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. Tubiello, Guido R. Wiltshire, and Sönke Zaehle. The Global Carbon Budget describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean.

These living data are updated every year to provide the highest transparency and traceability in the reporting of CO 2 , the key driver of climate change.

We present a way to rate the CO 2 flux estimates made from inversion of a global atmospheric transport model.

Our approach relies on accurate aircraft measurements in the free troposphere. It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.

Elizabeth Asher, Rebecca S. Hornbrook, Britton B. Stephens, Doug Kinnison, Eric J. Morgan, Ralph F. Keeling, Elliot L.

Atlas, Sue M. Schauffler, Simone Tilmes, Eric A. Kort, Martin S. Hills, and Eric C. Halogenated organic trace gases, which are a source of reactive halogens to the atmosphere, exert a disproportionately large influence on atmospheric chemistry and climate.

This paper reports novel aircraft observations of halogenated compounds over the Southern Ocean in summer and evaluates hypothesized regional sources and emissions of these trace gases through their relationships to additional aircraft observations.

This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems.

The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system.

The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism. Ilya Stanevich, Dylan B.

Henze, Robert J. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng. We explore the utility of a weak constraint WC four-dimensional variational 4D-Var data assimilation scheme for mitigating systematic errors in the methane simulation in the GEOS-Chem model.

We find that the WC corrections to the model provide insight into the source of the errors. Jones, Kimberly Strong, Robert J.

Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane CH 4 emissions. Our analysis identified resolution-dependent biases in the model, which we attributed to discrepancies between the two model resolutions in vertical transport in the troposphere and in stratosphere-troposphere exchange.

Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L.

Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Our paper describes the Ecosystem Demography model.

This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates.

Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought.

This diversity helps us to better explain how plants live and interact with the atmosphere. Knox, Naomi M. Levine, Abigail L. Swann, David M.

Medvigy, Michael C. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates.

To test if our calculations were reasonable, we compared our results with field and satellite measurements.

Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air.

However, it must improve the tree growth rates and how fast dead plants decompose. Piao, Stephen Sitch, William K. Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO 2 -cycle exchange SCA NBP by ecosystems compared to estimates by two atmospheric inversions.

Biases can be explained by the sensitivity of simulated microbial respiration to temperature. Deeter, Robert J. Parker, Yilong Wang, Helen M.

Worden, and Yuanhong Zhao. We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide CO variations to its sources and sinks in order to achieve a full closure of the global CO budget during — We identify a declining trend in the global CO budget since , driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.

To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO 2 concentrations.

One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions.

This model has the potential to provide short-term predictions of land carbon fluxes. Miller, Britton B. Palmer, and Dylan B. Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network.

We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 OCO-2 show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.

Alexandra G. Konings, A. Parazoo, David S. Schimel, and Kevin W. We estimate heterotrophic respiration R h — the respiration from microbes in the soil — using satellite estimates of the net carbon flux and other quantities.

R h is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how R h varies in both space and time.

The resulting new estimate of R h is compared to the best currently available alternative, which is based on interpolating field measurements globally.

The two estimates disagree and are both uncertain. Vermeulen, Thorsten Warneke, and Debra Wunch. This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO 2 patterns associated with evolving weather.

The modelling of CO 2 weather is crucial to interpret the variability from ground-based and satellite CO 2 observations, which can then be used to infer CO 2 fluxes in atmospheric inversions.

The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO 2 flux distribution.

Satellite observations of atmospheric carbon dioxide offer extraordinary insights into terrestrial ecosystem activity on Earth.

The algorithm we present provides researchers with a great deal more information from these satellite data than has been available in the past.

We hope the application of this algorithm and analyses tools provides insight into atmospheric dynamics of carbon dioxide and helps inform the development of global ecosystem models in the future.

Felix R. Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO 2 levels is one key aspect.

This study uses atmospheric observations of total column CO 2 and compares them to numerical simulations to investigate CO 2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions.

Our measurements reveal the influence of locally added CO 2 , which our model is also able to predict. Debsunder Dutta, David S.

Canopy structural and leaf photosynthesis parameterizations are often fixed over time in Earth system models and represent large sources of uncertainty in predictions of carbon and water fluxes.

We develop a moving window nonlinear optimal parameter inversion framework using constraining flux and satellite reflectance observations.

The results demonstrate the applicability of the approach for error reduction and capturing the seasonal variability of key ecosystem parameters.

Stijn Naus, Stephen A. Dlugokencky, and Maarten Krol. We investigate how the use of a two-box model to describe the troposphere can impact derived results, relative to more complex models.

By comparing the tuned two-box model with a standard model run, we can diagnose and quantify biases inherent to a two-box model.

We find strong biases, but these have only a small impact on our final conclusions. However, it is not obvious that this should hold for future studies.

Kerry Cawse-Nicholson, Joshua B. Fisher, Caroline A. Famiglietti, Amy Braverman, Florian M. Schwandner, Jennifer L.

Lewicki, Philip A. Townsend, David S. Schimel, Ryan Pavlick, Kathryn J. Bormann, Antonio Ferraz, Emily L.

Kang, Pulong Ma, Robert R. Bogue, Thomas Youmans, and David C. Carbon dioxide levels are rising globally, and it is important to understand how this rise will affect plants over long time periods.

Volcanoes such as Mammoth Mountain, California, have been releasing CO 2 from their flanks for decades, and this provides a test environment in order to study the way plants respond to long-term CO 2 exposure.

We combined several airborne measurements to show that plants may have fewer, more productive leaves in areas with increasing CO 2.

Christopher W. Wennberg, David Crisp, Michael R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Crowell, Liang Feng, Paul I.

Palmer, Mavendra Dubey, Omaira E. Griffith, Frank Hase, Laura T. Roehl, Mahesh K. Peters, Josep G. Canadell, Almut Arneth, Vivek K.

Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Hoffman, Mario Hoppema, Richard A. Jain, Truls Johannessen, Chris D.

Jones, Etsushi Kato, Ralph F. Tubiello, Ingrid T. Walker, Andrew J. Dien Wu, John C. Yang, and Eric A. Urban CO 2 enhancement signals can be derived using satellite column CO 2 concentrations and atmospheric transport models.

However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals.

In this paper, we present a modified Lagrangian model framework that extracts urban CO 2 signals from satellite observations and determines potential error impacts.

We compare several versions of a global atmospheric transport model for the simulation of CO 2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere.

It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines.

The sensitivities to the land surface model and to the increase in vertical resolution are marginal.

We use a novel calibration technique to correct altitude-dependent artifacts that have hindered similar instruments.

In-flight null-tests and comparison with other flight-proven instruments provide validation. This high-precision, high-accuracy system provides opportunities for airborne studies to improve our understanding of N 2 O emission processes.

Wei He, Ivar R. We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system.

This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions.

Saroja M. Jones, and Michael Neish. A new diagnostic reveals how fluxes constrained by two different CO 2 observing systems inform atmospheric CO 2 simulations.

The potential for GOSAT data to better resolve zonally asymmetric structures in the tropics year-round and in the northern extratropics in most seasons is shown.

Using in situ data yields a better match to independent observations on the global, annual scale. Such complementarity of the observing systems can be exploited in greenhouse gas data assimilation systems.

The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport.

This paper presents the first results of an age of air AoA inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced.

Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis. Tiwari, and Lingxi Zhou.

Model performance is evaluated for both gases and versions at multiple timescales against a new collection of surface stations over this key GHG-emitting region.

The evaluation at different timescales and comparisons between gases and model versions have implications for possible model improvements and inversions.

Amanda R. Fay, Nicole S. Lovenduski, Galen A. McKinley, David R. Munro, Colm Sweeney, Alison R. Gray, Peter Landschützer, Britton B.

Stephens, Taro Takahashi, and Nancy Williams. The Southern Ocean is highly under-sampled and since this region dominates the ocean sink for CO 2 , understanding change is critical.

Here we utilize available observations to evaluate how the seasonal cycle, variability, and trends in surface ocean carbon in the well-sampled Drake Passage region compare to that of the broader subpolar Southern Ocean.

Results indicate that the Drake Passage is representative of the broader region; however, additional winter observations would improve comparisons.

Sourish Basu, David F. Patra, Junjie Liu, and John B. CO 2 measurements from the global surface network and CO 2 estimates from satellites such as the Orbiting Carbon Observatory 2 OCO-2 are currently used to quantify the surface sources and sinks of CO 2 , using what we know about atmospheric transport of gases.

In this paper we investigate how the CO 2 exchange between the land vegetation and the atmosphere varies from year to year.

We quantify the relation between variations in the CO 2 exchange and variations in air temperature. For this quantification, we use long-term measurements of CO 2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature.

The results help us to understand the mechanisms of CO 2 exchange. The estimate of monthly emission budgets is largely improved in high emitting regions.

The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO 2 emissions.

Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. Chini, Philippe Ciais, Catherine E. Houghton, Christopher W.

Monteiro, David R. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu. The Global Carbon Budget describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties.

It is the 12th annual update and the 6th published in this journal. Gerard Spain, and Christophe Ampe. Urbanized and industrialized areas are the largest source of fossil CO 2.

This work analyses the atmospheric CO 2 variability observed from the first in situ network deployed in the Paris megacity area.

Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO 2 records.

Koch, and Martin Heimann. Melton, Ray Nassar, and Vivek K. This coupling is considered an important step toward understanding how meteorological uncertainties affect both CO 2 flux estimates and modeled atmospheric transport.

This study assesses the potential of space-borne imagery of CO 2 atmospheric concentrations for monitoring the emissions from the Paris area.

Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO 2 emissions for urban areas with CO 2 observations from satellites, and calls for more technological innovations in the remote sensing of CO 2 and in the models that exploit it.

Lin, Emily Yang, and Dien Wu. Rapid global urbanization and significant fossil fuel consumption by cities emphasize the necessity of achieving independent and accurate quantification of the carbon emissions from urban areas.

In this paper, we assess the potential of using total column CO 2 concentration observed from satellite to quantify fossil-fuel carbon emissions from cities.

This study could give insights into the capability of satellite observations on monitoring of the emissions on local scale. The year appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since according to satellite observation, but the atmospheric CO 2 growth rate is also the highest since Zachary R.

Barkley, Thomas Lauvaux, Kenneth J. Davis, Aijun Deng, Natasha L. Miles, Scott J. This study quantifies methane emissions from natural gas production in north-eastern Pennsylvania.

Methane observations from 10 flights in spring are compared to model-projected values, and methane emissions from natural gas are adjusted within the model to create the best match between the two data sets.

This study find methane emissions from natural gas production to be low and may be indicative of characteristics of the basin that make sources from north-eastern Pennsylvania unique.

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SГјnke Griebel Video

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His nomination was shared with Max Zahle.. Our approach relies on accurate aircraft measurements in the free troposphere.

It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.

This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems.

The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system.

The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism. We present continuous in situ measurements of atmospheric CO 2 and CH 4 mole fractions at the new station Ambarchik, located in northeastern Siberia.

We describe the site, measurements and quality control, characterize the signals in comparison with data from Barrow, Alaska, and show which regions the measurements are sensitive to.

Ambarchik data are available upon request. Daniel E. Lina Teckentrup, Sandy P. We investigate the influence of five forcing factors: atmospheric CO 2 , population density, land—use change, lightning and climate.

We find that the anthropogenic factors lead to the largest spread between models. Trends due to climate are mostly not significant but climate strongly influences the inter-annual variability of burned area.

Melton, Daniel S. Magi, Stephen Sitch, Guido R. Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality.

We provide the first global multi-model fire emission reconstructions for —, including carbon and 33 species of trace gases and aerosols, based on the nine state-of-the-art global fire models that participated in FireMIP.

We also provide information on the recent status and limitations of the model-based reconstructions and identify the main uncertainty sources in their long-term changes.

Piao, Stephen Sitch, William K. Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO 2 -cycle exchange SCA NBP by ecosystems compared to estimates by two atmospheric inversions.

Biases can be explained by the sensitivity of simulated microbial respiration to temperature. Elias C. Massoud, Chonggang Xu, Rosie A.

Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M.

Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, and Jasper A.

We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model.

By running the model times with changing input parameter values, we found that 1 the photosynthetic capacity controls carbon fluxes, 2 the allometry is important for tree growth, and 3 the targeted carbon storage is important for tree survival.

These results can provide guidance on improved model parameterization for a better fit to observations.

Deeter, Robert J. Parker, Yilong Wang, Helen M. Worden, and Yuanhong Zhao. We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide CO variations to its sources and sinks in order to achieve a full closure of the global CO budget during — We identify a declining trend in the global CO budget since , driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.

However, often these models have higher uncertainty in complex ecosystems with multiple layers of vegetation. This manuscript adapts and analyzes a well known model to better simulate water fluxes for a savanna-like ecosystem and to understand the influence that vegetation has on their predictions.

Crossed fertilization additions lead to the definition of nutrient interaction categories. However, the implications of such categories in terms of nutrient interaction modeling are not clear.

We developed a theoretical analysis of nitrogen and phosphorus fertilization experiments, then applied it to current estimates of nutrient limitation in cropland.

To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO 2 concentrations.

One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions.

This model has the potential to provide short-term predictions of land carbon fluxes. Miller, Britton B. Palmer, and Dylan B. Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network.

We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 OCO-2 show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.

Susan J. Cheng, Peter G. Hess, William R. Wieder, R. Quinn Thomas, Knute J. Nadelhoffer, Julius Vira, Danica L. Lombardozzi, Per Gundersen, Ivan J.

Nitrogen deposition and fertilizer can change how much carbon is stored in plants and soils. Understanding how much added nitrogen is recovered in plants or soils is critical to estimating the size of the future land carbon sink.

We compared how nitrogen additions are recovered in modeled soil and plant stocks against data from long-term nitrogen addition experiments. We found that the model simulates recovery of added nitrogen into soils through a different process than found in the field.

Vermeulen, Thorsten Warneke, and Debra Wunch. This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO 2 patterns associated with evolving weather.

The modelling of CO 2 weather is crucial to interpret the variability from ground-based and satellite CO 2 observations, which can then be used to infer CO 2 fluxes in atmospheric inversions.

The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO 2 flux distribution. De Kauwe, Anthony P.

Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Here we used a simple analytical framework developed by Comins and McMurtrie to investigate how different model assumptions affected plant responses to elevated CO 2.

This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.

Richard K. Nair, Kendalynn A. We investigated how nutrient availability affects seasonal timing of root growth and death in a Spanish savanna, adapted to a long summer drought.

We found that nitrogen N additions led to more root biomass but number of roots was higher with N and phosphorus together.

These effects were strongly affected by the time of year. In autumn root growth occurred after leaf production. This has implications for how we understand biomass production and carbon uptake in these systems.

The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt.

We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event.

This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.

Felix R. Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO 2 levels is one key aspect.

This study uses atmospheric observations of total column CO 2 and compares them to numerical simulations to investigate CO 2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions.

Our measurements reveal the influence of locally added CO 2 , which our model is also able to predict. Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass.

This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls.

Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.

Florent F. Malavelle, Jim M. Haywood, Lina M. Mercado, Gerd A. Diffuse light can increase the efficiency of vegetation photosynthesis. Diffuse light results from scattering by either clouds or aerosols in the atmosphere.

During the dry season biomass burning BB on the edges of the Amazon rainforest contributes significantly to the aerosol burden over the entire region.

We show that despite a modest effect of change in light conditions, the overall impact of BB aerosols on the vegetation is still important when indirect climate feedbacks are considered.

Global forest resources are accounted for to establish their potential to sink carbon in woody biomass.

Climate prediction models realize the effects of future global forest utilization rates, defined by population demand and its evolution over time.

However, forest management approaches consider the supply side to realize a sustainable forest carbon stock and adapt the harvest rates to novel climate conditions.

This study simulates such an adaptive sustained yield approach. Trumbore, Norbert Kunert, Mariah S. Carbone, Päivi Yuval, S. This finding strengthens the recognition that CO 2 efflux from tree stems is not an accurate measure of respiration.

We suggest the examination of refixation of respired CO 2 as a possible mechanism for CO 2 retention.

Benjamin Gaubert, Britton B. Kort, Prabir K. We have compared global carbon budgets calculated from numerical inverse models and CO 2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO 2 from aircraft measurements.

We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.

Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire—vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.

Christopher W. Wennberg, David Crisp, Michael R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J.

Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. Griffith, Frank Hase, Laura T. Roehl, Mahesh K.

This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow.

The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets.

How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.

Peters, Josep G. Canadell, Almut Arneth, Vivek K. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S.

Hoffman, Mario Hoppema, Richard A. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Tubiello, Ingrid T. Walker, Andrew J. Haicheng Zhang, Daniel S.

HyeJin Kim, Isabel M. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A. This paper lays out the protocol for the Biodiversity and Ecosystem Services Scenario-based Intercomparison of Models BES-SIM that projects the global impacts of land use and climate change on biodiversity and ecosystem services over the coming decades, compared to the 20th century.

BES-SIM uses harmonized scenarios and input data and a set of common output metrics at multiple scales, and identifies model uncertainties and research gaps.

We compare several versions of a global atmospheric transport model for the simulation of CO 2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere.

It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines.

The sensitivities to the land surface model and to the increase in vertical resolution are marginal. Northern forests enhanced their productivity during and before the Russian mega heatwave.

We scrutinize this issue with a novel type of multivariate extreme event detection approach. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.

Raised ozone levels impact plant stomatal opening and thus photosynthesis. Most models describe this as a suppression of stomata opening. Field evidence suggests more complexity, as ozone damage may make stomatal response sluggish.

In some circumstances, this causes stomata to be more open — a concern during drought conditions — by increasing transpiration. To guide interpretation and modelling of field measurements, we present an equation for sluggish effects, via a single tau parameter.

Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere—atmosphere interactions.

However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data.

Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning.

The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis.

Anthony P. Medlyn, Alistair Rogers, and Shawn P. Large uncertainty is inherent in model predictions due to imperfect knowledge of how to describe the processes that a model is intended to represent.

Yet methods to quantify and evaluate this model hypothesis uncertainty are limited. To address this, the multi-assumption architecture and testbed MAAT automates the generation of all possible models by combining multiple representations of multiple processes.

MAAT provides a formal framework for quantification of model hypothesis uncertainty. The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport.

This paper presents the first results of an age of air AoA inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced.

Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis. Briggs, William Woodgate, Cathy M.

Trudinger, Josep G. Canadell, and Matthias Cuntz. CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface—atmosphere exchange within a climate model.

We extend CABLE for regional and global carbon—climate simulations, accounting for land use and land cover change mediated by tree demography.

A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.

We further discuss their terrestrial mechanisms. This study explores the relative contributions of tree demographic, canopy structure and hydraulic processes on the Amazonian carbon and water cycles using large-scale process-based model.

Our results imply that explicit coupling of the water and carbon cycles improves the representation of biogeochemical cycles and their spatial variability.

Representing the variation in the ecological functioning of Amazonia should be the next step to improve the performance and predictive ability of models.

Rebecca J. Oliver, Lina M. Potential gains in terrestrial carbon sequestration over Europe from elevated CO 2 can be partially offset by concurrent rises in tropospheric O 3.

Large regional variations exist with larger impacts identified for temperate compared to boreal regions. Plant O 3 damage was greatest over the twentieth century and declined into the future.

Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle.

We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets.

JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements. Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate.

While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.

We added new PFTs, did new parameterizations of photosynthesis, carbon allocation, and phenology based on a compilation of field measurements, and added a specific harvest module.

Nabel, Julia Pongratz, Lena R. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.

Janssens, Jennifer L. Sourish Basu, David F. Patra, Junjie Liu, and John B. CO 2 measurements from the global surface network and CO 2 estimates from satellites such as the Orbiting Carbon Observatory 2 OCO-2 are currently used to quantify the surface sources and sinks of CO 2 , using what we know about atmospheric transport of gases.

AirCore is an innovative tool that passively samples air using the atmospheric pressure gradient during descent. The active AirCore system opens up a wide variety of opportunities, e.

In this paper we investigate how the CO 2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO 2 exchange and variations in air temperature.

For this quantification, we use long-term measurements of CO 2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature.

The results help us to understand the mechanisms of CO 2 exchange. The estimate of monthly emission budgets is largely improved in high emitting regions.

The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO 2 emissions.

Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C.

Chini, Philippe Ciais, Catherine E. Houghton, Christopher W. Monteiro, David R. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu.

The Global Carbon Budget describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties.

It is the 12th annual update and the 6th published in this journal. Gerard Spain, and Christophe Ampe.

Urbanized and industrialized areas are the largest source of fossil CO 2. This work analyses the atmospheric CO 2 variability observed from the first in situ network deployed in the Paris megacity area.

Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO 2 records.

Koch, and Martin Heimann. Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon—Cerrado border, followed by nutrient limitation and interannual climate variability.

The accurate representation of the transition is important for understanding the savannization of the Amazon.

This study assesses the potential of space-borne imagery of CO 2 atmospheric concentrations for monitoring the emissions from the Paris area.

Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO 2 emissions for urban areas with CO 2 observations from satellites, and calls for more technological innovations in the remote sensing of CO 2 and in the models that exploit it.

Ivar R. Miller, Michiel K. Tans, Bruce H. Vaughn, James W. White, Kevin Schaefer, and Wouter Peters. This study highlights the importance of improving the representation of the biosphere in carbon—climate models, in particular in a world where droughts become more extreme and more frequent.

Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes.

These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO 2 fluxes, in addition to a recently developed fire module.

We quantified in detail the P budgets in agricultural systems and PUE on global, regional, and national scales from to Globally, half of the total P inputs into agricultural systems accumulated in agricultural soils, with the rest lost to bodies of water.

There are great differences in P budgets and PUE in agricultural systems on global, regional, and national scales. International trade played a significant role in P redistribution and P in fertilizer and food among countries.

The year appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since according to satellite observation, but the atmospheric CO 2 growth rate is also the highest since Liu, Julia E.

We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models.

Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies. Sterk, Arjan Hensen, and Wouter Peters.

In this research we examined the use of different models to simulate CO 2 concentrations in and around urban areas. We find that in the presence of large stack emissions in a gridded model is insufficient to represent the small dimensions of the CO 2 plumes.

A plume model improves this representation up to 10—14 km from the stack. Better model results can improve the estimate of CO 2 emissions from urban areas and assist in identifying efficient emission reduction policies.

Andreas Krause, Thomas A. Pugh, Anita D. Bayer, Jonathan C. Many climate change mitigation scenarios require negative emissions from land management.

However, environmental side effects are often not considered. Here, we use projections of future land use from two land-use models as input to a vegetation model.

We show that carbon removal via bioenergy production or forest maintenance and expansion affect a range of ecosystem functions.

Largest impacts are found for crop production, nitrogen losses, and emissions of biogenic volatile organic compounds. Hutley, Gabriel Abramowitz, Martin G.

This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems.

We provide a particular focus on three dynamic processes phenology, root-water access, and fire that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models.

We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area. Daniel S. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition.

However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.

Calibration of terrestrial ecosystem models TEMs is important but challenging. This study applies an advanced sampling technique for parameter estimation of a TEM.

The results improve the model fit and predictive performance. We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.

Consistencies and discrepancies in the temporal and spatial patterns and in the climatic and physiological controls of the inter-annual variability were investigated for the three data sources.

Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community.

The Earth system is highly multivariate. We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing.

We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches.

The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided. Ingrid T.

Masarie, Maarten C. Krol, and Wouter Peters. We present and document CTDAS and demonstrate its ability to estimate global carbon sources and sinks.

We present the latest CTE results including the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans.

The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales.

Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.

Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates.

Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa. We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.

The present study 1 evaluates land—atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and 2 refines the model ensemble using a land—atmosphere coupling diagnostic as constraint.

Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season moisture-limited climate regimes in midlatitude regions.

This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble. Land-use change is still overly simplistically implemented in global ecosystem and climate models.

We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models.

We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use—climate interactions and feedback.

Goll, Alexander J. The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate.

In the model JSBACH carbon—nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect.

The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model. The inverse modelling approach for estimating surface fluxes is based on transport models that have an imperfect representation of atmospheric processes like vertical mixing.

In this paper, we show how assimilating commercial aircraft-based vertical profiles of CO 2 into inverse models can help reduce error due to the transport model, thus providing more accurate estimates of surface fluxes.

Further, the reduction in flux uncertainty due to aircraft profiles from the IAGOS project is quantified.

Modelling seasonal cycle at the coniferous forests poses a challenge. It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region.

SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.

The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.

CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere MOPITT satellite retrievals and surface in-situ measurements.

Rabin, Joe R. Ward, Chao Yue, Vivek K. Kelley, I. Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include.

A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance.

It also includes equations for all models. Surface ozone harms vegetation, which can influence not only climate but also ozone air quality itself.

We implement a scheme for ozone damage on vegetation into an Earth system model, so that for the first time simulated vegetation and ozone can coevolve in a fully coupled simulation.

Reduced dry deposition and enhanced isoprene emission contribute to most of these increases. Bayer, Mats Lindeskog, Thomas A.

Pugh, Peter M. Anthoni, Richard Fuchs, and Almut Arneth. We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model.

Different historical reconstructions yielded an uncertainty of ca. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level tropical shifting cultivation substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.

Otto, and Markus Reichstein. The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years.

Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to 1 the choice of dryness definition and 2 statistical data processing.

In fact, we find only minor and only some significant increases if 1 dryness is based on aridity and 2 statistical artefacts are accounted for. Earth's terrestrial surface influences climate by exchanging carbon and water with the atmosphere through stomatal pores.

However, most land-surface models, used to predict global carbon and water fluxes, estimate that water lost through stomata is less than what observations show.

In this study, we integrate plant water loss data from species into a global land surface model, finding that global estimates of plant water loss increase, soil moisture decreases, and carbon gain also decreases.

Michalak, and Prabir Patra. The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements.

It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.

We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed.

We apply it to estimate monthly ratios between CO 2 , CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between and We find that this approach is little sensitive to the regional background level definition.

With this new method, we may reveal spatial and seasonal variability in the ratios in Paris. Semi-arid ecosystems in Australia are responsible for a significant part of the variability in global atmospheric carbon dioxide.

Here we use Australian observations to estimate parameters in a land surface model of carbon and water cycles.

We quantify the variability in Australian carbon fluxes between and , including the large uptake in associated with exceptionally wet conditions following a prolonged drought.

We estimate the effect of parameter uncertainty on these estimates. Andrew, Josep G. Peters, Andrew C.

Manning, Thomas A. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Stocker, Adrienne J. The Global Carbon Budget is the 11th annual update of emissions of carbon dioxide CO 2 and their partitioning among the atmosphere, land, and ocean.

This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years to , with a projection for year Evans, Anne Griebel, Lindsay B.

Prober, and Richard Silberstein. Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial.

We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia.

Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.

Jason Beringer, Lindsay B. Arndt, David Campbell, Helen A. Phillips, Suzanne M. We describe the evolution, design, and status as well as an overview of data processing.

We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.

Sylvia S. Nyawira, Julia E. We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses.

The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions.

The evaluation offers an opportunity for identifying causes of model—data discrepancies. Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model.

Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context.

This paper demonstrates and discusses the issues involved using toy models and examples from existing literature. The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO 2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model.

The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.

Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. Marked improvements in predictions of evaporation are demonstrated globally.

Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

Gregor J. The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting or assimilating the model with observations of atmospheric CO 2 and fractions of absorbed photosynthetically active radiation.

Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.

In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types.

Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.

In this study, we found that methane emission estimates, driven by the CTE-CH 4 model, depend on model setups and inputs, especially for regional estimates.

An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role.

The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.

This paper presents a method to adjust the sinks and sources of CO 2 associated with land ecosystems within a global atmospheric CO 2 forecasting system in order to reduce the errors in the forecast.

This is done by combining information on 1 retrospective fluxes estimated by a global flux inversion system, 2 land-use information, and 3 simulated fluxes from the model.

Because the method is simple and flexible, it can easily run in real time as part of a forecasting system.

To understand the role of fires in the Earth system, global fire models are required. It follows a reduced complexity approach using mainly temperature, humidity and precipitation.

INFERNO was found to perform well on a global scale and to maintain regional patterns over the — period of study, despite regional biases particularly linked to fuel consumption.

Lisa R. Welp, Prabir K. Piper, and Ralph F. Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO 2 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 CO 2 fluxes inferred from atmospheric CO 2 concentrations using inverse models and found that net summer CO 2 uptake increased, resulting in a small increase in annual CO 2 uptake.

Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network.

Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.

Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Reich, Nadjeda A.

Soudzilovskaia, and Peter van Bodegom. Dynamic global vegetation models DGVMs are used to predict the response of vegetation to climate change.

We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base.

The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.

Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly.

We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs. We show here that the many methods for doing this are special cases of underlying statistics.

This provides a unified way of comparing and contrasting such methods. Christian Frankenberg, Susan S. Kulawik, Steven C. Olsen, and Gregory Osterman.

This paper advances atmospheric inversion of city CO 2 emissions as follows: 1 illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO 2 concentrations; 2 demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification MRV of city CO 2 emissions; 3 clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO 2 emissions.

Harrison, Douglas I. Colin Prentice, Sam S. Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes.

A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales.

In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project — FireMIP.

We measured carbon dioxide and methane concentrations at four near-ground sites located in London, We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions.

Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications.

A gradient approach was found to be beneficial to reduce model—data errors. Hutley, Gab Abramowitz, Martin G. In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems.

We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. On average, we found the models as a group display only moderate levels of performance.

Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. We apply the ratio inversion method described in Pandey et al. We propose insights based on atmospheric observations around the Arctic circle to evaluate estimates of methane emissions to the atmosphere from the East Siberian Arctic Shelf.

Based on a comprehensive statistical analysis of the observations and of high-resolution transport simulations, annual methane emissions from ESAS are estimated to range from 0.

This paper evaluates the model predictions of leaf area index in the current climate, compared against satellite observations. It also summarizes the predicted changes in leaf area index in the future, and identifies whether some of the uncertainty in future predictions can be decreased.

Miller, Paul O. Dubey, Nicholas M. Feist, Laura T. Iraci, and Joyce Wolf. To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized.

We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability.

Our findings are useful for assimilation of satellite data. Burrows, Nicholas M. Dubey, David W. We show that the modelled CO 2 has a better precision than standard CO 2 satellite products compared to ground-based measurements.

We also present the CO 2 forecast based on our best knowledge of the atmospheric CO 2 distribution. We show that it has skill to forecast the largest scale CO 2 patterns up to day 5.

Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. Trudinger, and J. We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network.

Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence.

Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.

Wagner, I. Kolari, J. Kurbatova, A. Varlagin, T. Maximov, A. Kononov, T. Ohta, A. Kotani, M. Krol, and W. Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle.

Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region.

This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.

Sippel, F. Otto, M. Forkel, M. Allen, B. Guillod, M. Heimann, M. Reichstein, S. Seneviratne, K. Thonicke, and M.

We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure.

The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies.

Illustrative simulations of biosphere—atmosphere carbon and water fluxes with a biosphere model LPJmL show that the novel technique can be usefully applied to drive climate impact models.

Ryder, J. Polcher, P. Peylin, C.

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